In this article, we propose a Bayesian Adaptive bridge regression for ordinal model. We developed a new hierarchical model for ordinal regression in the Bayesian adaptive bridge. We consider a fully Bayesian approach that yields a new algorithm with tractable full conditional posteriors. All of the results in real data and simulation application indicate that our method is effective and performs very good compared to other methods. We can also observe that the estimator parameters in our proposed method, compared with other methods, are very close to the true parameter values.
The main objective of this paper is to introduce and study the generality differential operator involving the q-Mittag-Leffler function on certain subclasses of analytic functions. Also, we investigate the inclusion properties of these classes, by using the concept of subordination between analytic functions.
After Zadeh introduced the concept of z-number scientists in various fields have shown keen interest in applying this concept in various applications. In applications of z-numbers, to compare two z-numbers, a ranking procedure is essential. While a few ranking functions have been already proposed in the literature there is a need to evolve some more good ranking functions. In this paper, a novel ranking function for z-numbers is proposed- "the Momentum Ranking Function"(MRF). Also, game theoretic problems where the payoff matrix elements are z-numbers are considered and the application of the momentum ranking function in such problems is demonstrated.
Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use
... Show MoreUnderstanding energy metabolism and intracellular energy transmission requires knowledge of the function and structure of the mitochondria. Issues with mitochondrial morphology, structure, and function are the most prevalent symptoms. They can damage organs such as the heart, brain, and muscle due to a variety of factors, such as oxidative damage, incorrect metabolism of energy, or genetic conditions. The control of cell metabolism and physiology depends on functional connections between mitochondrial and biological surroundings. Therefore, it is essential to research mitochondria in situ or in vivo without isolating them from their surrounding biological environment. Finding and spotting abnormal alterations in mitochondria is the
... Show MoreCluster analysis (clustering) is mainly concerned with dividing a number of data elements into clusters. The paper applies this method to create a gathering of symmetrical government agencies with the aim to classify them and understand how far they are close to each other in terms of administrative and financial corruption by means of five variables representing the prevalent administrative and financial corruption in the state institutions. Cluster analysis has been applied to each of these variables to understand the extent to which these agencies are close to other in each of the cases related to the administrative and financial corruption.
Copper is a cheaper alternative to various noble metals with a range of potential applications in the field of nanoscience and nanotechnology. However, copper nanoparticles have major limitations, which include rapid oxidation on exposure to air. Therefore, alternative pathways have been developed to synthesize metal nanoparticles in the presence of polymers and surfactants as stabilizers, and to form coatings on the surface of nanoparticles. These surfactants and polymeric ligands are made from petrochemicals which are non- renewable. As fossil resources are limited, finding renewable and biodegradable alternative is promising.The study aimed at preparing, characterizing and evaluating the antibacterial properties of copper nanoparticle
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