Parametric Study of Fuel Distribution Effects on a Kerosene-Based Scramjet Combustor by Jun Yang, Xian-yu Wu, Zhen-guo Wang

“…The fuel equivalence ratio for each injection port was taken as the design variables. And the combustion efficiency, the total pressure recovery coefficient, and the drag coefficient were chosen as the objective functions. …”
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Analisis Kualitas Website Balai Besar Taman Nasional Gunung Gede Pangranggo (BBTNGGP) menggunakan Metode Webqual 4.0 by Muhammad Syahid Qadhafi, Atit Pertiwi

“…The results of the analysis of the quality of this website concluded that the variable usability and information quality had a good value compared to the variable service interaction quality. …”
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Simultaneous single-sample determination of NMNAT isozyme activities in mouse tissues. by Giuseppe Orsomando, Lucia Cialabrini, Adolfo Amici, Francesca Mazzola, Silverio Ruggieri, Laura Conforti, Lucie Janeckova, Michael P Coleman, Giulio Magni

“…Final assay validation was achieved in a tissue extract by comparing the activity and expression levels of individual isozymes, considering their distinctive catalytic efficiencies. Furthermore, considering the key role played by NMNAT activity in preserving axon integrity and physiological function, this assay procedure was applied to both liver and brain extracts from wild-type and Wallerian degeneration slow (Wld(S)) mouse. …”
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Fuzzy System for the Quality Assessment of Educational Multimedia Edition Design by Vsevolod Senkivskyy, Liubomyr Sikora, Nataliia Lysa, Alona Kudriashova, Iryna Pikh

“…A multilevel model of fuzzy logical inference is constructed, representing the dependency between quality factors. Membership functions for linguistic variables are formed and their weight coefficients are determined using pairwise comparison matrices. …”
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Multiple mechanisms contribute to leakiness of a frameshift mutation in canine cone-rod dystrophy. by Keiko Miyadera, Ian Brierley, Jesús Aguirre-Hernández, Cathryn S Mellersh, David R Sargan

“…Variable polyA(n) length was confirmed in DNA from different RPGRIP1(-/-) dogs, yet polyA(n) variability did not correspond with the clinical phenotypes and no individual was found that carried a polyA(n) tract capable of encoding an in-frame variant. …”
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An improved robust variance inflation factor: Reducing the negative effects of good leverage points by Osman Ufuk Ekiz

“…It is defined as the function of the coefficient of determination between the explanatory variables, and it is based on the maximum likelihood estimator of the regression coefficients. …”
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Exploring restoration efforts from a social lens: statistical models reveal relationships between salmon habitat restoration efforts and ecological and social characteristics of th... by Brittany D King, Robert Fonner

“…We specified statistical models to explain the variation in the number of restoration worksites undertaken in subwatersheds as a function of environmental and social variables. Using a common set of explanatory variables, we fit four models to examine the distribution of worksites associated with particular types of restoration actions (instream, riparian, land acquisition, and fish passage) and a fifth model to examine the distribution of all aquatic-based restoration worksites across action types. …”
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Sparse Learning of the Disease Severity Score for High-Dimensional Data by Ivan Stojkovic, Zoran Obradovic

“…This problem is solved by addressing a dual formulation which is smooth and allows an efficient optimization. The proposed approach might be used as an effective and reliable tool for both scoring function learning and biomarker discovery, as demonstrated by identifying a stable set of genes related to influenza symptoms’ severity, which are enriched in immune-related processes.…”
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Bifurcations of Spatially Inhomogeneous Solutions of a Boundary Value Problem for the Generalized Kuramoto–Syvashinsky Equation by Alina V. Sekatskaya

“…In this paper, a differential partial equation with an unknown function of three variables time and two spatial variables – is considered. …”
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Faktor-Faktor Yang Mempengaruhi Pertumbuhan Ekonomi Di Jawa Timur Dengan Pendekatan Spatial Regression by Rendra Erdkhadifa

“…The research results show that the weighting function used is fixed gaussian, and the spatial model has a coefficient of determination of 92.97%. …”
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Non-destructive textural quality assessment of peaches and nectarines using near-infrared spectroscopy integration time by Eva Cristina Correa, Paola Baltazar, Pilar Barreiro, Natalia Hernández-Sánchez, Lourdes Lleó, Ángela Melado-Herreros, Belén Diezma

“…A principal component analysis (PCA) was used to analyze textural variability, and discriminant function analysis (DFA) and artificial neural networks (ANNs) were applied to classify fruit firmness levels.PCA effectively defined a new variable, PC1, that captured the variance in fruit texture, correlating positively with juiciness and negatively with firmness. …”
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Modeling of Ozone Interactions with Various Air Pollutants and Meteorological Factors Using Jaya and Teaching-Learning Based Optimization (TLBO) Algorithms by Nurcan Öztürk

“…In conclusion, it is shown that Jaya and TLBO algorithms can be used in the optimization of the regression function coefficients in modelling some air pollutants interactions and the best-fit equation for each parameter is obtained from the quadratic function.…”
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An Analysis of Influential Factors in the Use of Public Bicycles in Tehran by Ehsan Faghihi, Mojtaba Rafieian

“…So far, many researches have been conducted on the components affecting the functional stability of the shared bicycles system, for example Si et al. in 2020 found that factors of efficiency, economic benefits, environmental awareness, and infrastructure incentives influence the willingness to use the shared bicycle system. …”
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Dimensions-Reduced Volterra Digital Pre-Distortion Based On Orthogonal Basis for Band-Limited Nonlinear Opto-Electronic Components by Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

“…However, naive implementation of the Volterra polynomial model usually introduces significant complexity due to the large number of model coefficients. Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. …”
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Contribution of entropy analysis on three-dimensional Prandtl model under Hall and ion slip effects with generalized mass and heat fluxes via OHAM by Sana Akbar, Muhammad Sohail, Syed Tehseen Abbas, Abha Singh

“…This article also examined the combined impacts of thermal conductivity change together with variable mass diffusion co-efficient within the heat and mass transport in the occurrence of Prandtl fluid. …”
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Spatial dependencies between large-scale brain networks. by Robert Leech, Gregory Scott, Robin Carhart-Harris, Federico Turkheimer, Simon D Taylor-Robinson, David J Sharp

“…Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. …”
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Weather Phenomena Monitoring: Optimizing Solar Irradiance Forecasting With Temporal Fusion Transformer by Xinyang Hu

“…The proposed model decomposes the raw solar irradiance sequence into intrinsic mode functions using VMD and optimizes the TFT using the variable screening network and GRU-based encoder-decoder. …”
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Optimizing Constrained Engineering Optimization Problems Using Improved Mountain Gazelle Optimizer by Vu Hong Son Pham, Nghiep Trinh Nguyen Dang, Van Nam Nguyen

“…These enhancements underscore the significant potential of iMGO in real-world applications across aerospace engineering, structural design optimization, energy system planning, and other fields, thereby contributing to more efficient and sustainable engineering solutions.…”
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Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure by GUO Xiaojing, ZHAO Xiaoyuan, ZOU Songlin

“…Higher identification precision and efficiency serve as reference indices for evaluating the model. …”
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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…The mean squared error is assumed as the loss function which stipulates several restrictions: deviatoric character of internal variables, compliance with the flow rule, the differentiation of elastic and plastic steps and the associativity of the flow rule. …”
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