Computational and Mathematical Methods最新文献

Glycans are one of the most widely investigated biomolecules, due to their roles in numerous vital biological processes. However, few system-independent, LC-MS/MS (liquid chromatography tandem mass spectrometry) based studies have been developed with this particular goal. Standard approaches generally rely on normalized retention times as well as m/z-mass to charge ratios of ion values. Due to these limitations, there is need for quantitative characterization methods which can be used independently of m/z values, thus utilizing only normalized retention times. As such, the primary goal of this article is to construct an LC-MS/MS based classification of the glycans derived from standard glycoproteins and human blood serum using a glucose unit index as the reference frame in the space of compound parameters. For the reference frame, we develop a closed-form analytic formula via the Green's function of a relevant convection-diffusion-absorption equation used to model composite material transport. The aforementioned equation is derived from an Einstein–Brownian motion paradigm, which provides a physical interpretation of the time-dependence at the point of observation for molecular transport in the experiment. The necessary coefficients are determined via a data-driven learning procedure. The methodology is presented in an abstractly and validated via comparison with experimental mass spectrometer data.

This study is focused to discuss the applications of non-Newtonian fluid in engineering problems. In this article magneto-hydrodynamics Casson fluid have taken with ramped temperature along an infinite plate with oscillations. In addition, in the present study we have considered the effect of porous media, chemical reaction, and radiation. Mostly, non-Newtonian fluids uses for the lubrication purposes such as, engine oil, grease, and so forth. In the present study engine oil EO is selected as base fluid due to enormous applications in engineering. To enhance the rate of heat transfer two nanoparticles molybdenum disulfide (MoS₂) and graphene oxide (GO) dispersed in EO. To transform the classical model into time fractional model Caputo–Fabrizio derivative have been used. To obtain the exact solutions for the proposed problem the Laplace transform is used. The solutions are depicted through graphs for various parameters to show the influence on fluid flow. Finally, we have compared the rate of heat transfer using different nanoparticles. It is worth noting that by using (MoS₂) nanoparticle the heat transfer of engine oil can be enhanced up to 6.35% and by adding GO in regular engine oil the heat transfer can be enhanced up to 5.49%.

The restricted three-body problem, where the primaries are magnetic dipoles, is discussed. In the predefined interval, the effect of the varying values of mass parameter $��\mu �$ and the angular velocity $��\omega �$ on the parametric variation of locations of the equilibrium points are illustrated. Indeed, the influence of the values of the ratio $��\lambda �$ of the magnetic moments in the presence of angular velocity $��\omega �$ on the topology of the basins of convergence is discussed. The bivariate version of the well-known Newton–Raphson scheme is used to illustrate the basins of convergence on the configuration (x, y) plane. In addition, the correlations betwixt the basins of convergence associated to the equilibrium points and the linked number of iterations required to assure the preassumed precision are discussed. In this study, a rigorous and structured numerical investigation are illustrated by exhibiting how the values of $��\lambda �$ and $��\omega �$ have significant influence on the shape, the topology and also the degree of fractality of the domain of basins of convergence. The results and outcomes of present study strongly indicate that the parameters $��\omega �,�\mu �$, and $��\lambda �$ have significant influence in the electromagnetic binary system.

New C¹ cubic Hermite interpolation methods based on algebraic trigonometric (AT) spline functions are proposed. In the first one, values of a function and its first derivatives are interpolated. In the second one, a C¹ AT-spline of low degree which preserves the monotonicity of the given data is defined by adding additional knots. Numerical examples are provided to show the good performance of both interpolation schemes.

In Debnath et al. (2019), a tritrophic food chain model subject to a Allee effect on the prey growth and Crowley–Martin senses functional response between intermediate predator and top predator, with a top predator of sexually reproductive type is considered. It is claimed that under certain restrictions on the parameter space, the model has bounded solutions for all positive initial conditions, and is dissipative. We show that this is not true. In particular, solutions to the model can blow-up in finite time, even under the restrictions derived in Debnath et al. (2019), for sufficiently chosen initial data. We derive a new extinction boundary for the system. We also conjecture on the effect of the Allee threshold on the blow-up dynamics in the model. All of our results are validated via numerical simulations.

In this article, we present the general expressions for the variance of the ruin time of the classic two-player gambler's ruin problem with successive and nonoverlapping trials. The rationale of this game plan is motivated by its exhibition in the game of tennis, where a player is required to win two consecutive serves to win the point after achieving deuce. This strategy (i.e., decision is based on successive and nonoverlapping trials) is in favor of the player, who plays with a better skill set and reduces the chances of decision based only on luck. We explicitly derive the general expressions of variance up to m successive and non-overlapping trials for the case of symmetric and asymmetric games. It is proved that the expressions given in literature for the symmetric and asymmetric cases are the sub cases of our proposed expressions. Finally, some special games (i.e., m = 2) are simulated and the results are verified with the proposed formulas.

The identification of outstanding behaviors is a matter of essential importance in sports analytics. However, analyzing how human experts select each match's most valuable player (MVP) according to objective and subjective factors is a great challenge. This article proposes a data-driven approach for sports team performance based on the weighted aggregation of statistical indicators. The proposal is divided into two approaches: The first conducts a principal component analysis to examine the relationship between each game's statistical indicators. The other addresses a meta-heuristic analysis to weight the attributes and choose the MVPs optimally. Finally, we apply the proposed approach to the 2018 European Men's Handball Championship and take the “Player of the Match” of each game as an example to illustrate its usefulness and efficacy. We perform multiple analyses, including a comparison with a fuzzy multi-criteria decision-making method that show that the data-driven approach can predict the “Player of the Match” in most matches. It also allows us to estimate and quantify the expert evaluations, which are often difficult to obtain in a disaggregated form.

In this article, we introduce a new general family of skewed distributions obtained through the use of a weighted skewed technique. This technique has the feature to unify two classical skewness techniques. Also, it is based on a clear stochastic representation involving a tuning weight function. General moments results are given. Subsequently, we focus our attention on a special case called asymmetric bimodal normal distribution. We investigate the maximum likelihood estimation of the parameters for this new distribution, with a complete numerical study. The developed model and method of inference are applied to some daily closing prices of some popular stocks.