###### Generalized canonical correlation analysis for functional data

## Summary

There is a growing need to analyze data sets characterized by several sets of variables observed on the same set of individuals. Such complex data structures are known as multiblock (or multiple-set) data sets. Multi-block data sets are encountered in diverse fields including bioinformatics, chemometrics, food analysis, etc. Generalized Canonical Correlation Analysis (GCCA) is a very powerful method to study this kind of relationships between blocks. It can also be viewed as a method for the integration of information from *K >* 2 distinct sources (Takane and Oshima-Takane 2002). In this paper, GCCA is considered in the context of multivariate functional data. Such data are treated as realizations of multivariate random processes. GCCA is a technique that allows the joint analysis of several sets of data through dimensionality reduction. The central problem of GCCA is to construct a series of components aiming to maximize the association among the multiple variable sets. This method will be presented for multivariate functional data. Finally, a practical example will be discussed.

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Improvement of the Fast Clustering Algorithm Improved by *K*-Means in the Big Data

## Abstract

Clustering as a fundamental unsupervised learning is considered an important method of data analysis, and *K*-means is demonstrably the most popular clustering algorithm. In this paper, we consider clustering on feature space to solve the low efficiency caused in the Big Data clustering by *K*-means. Different from the traditional methods, the algorithm guaranteed the consistency of the clustering accuracy before and after descending dimension, accelerated *K*-means when the clustering centeres and distance functions satisfy certain conditions, completely matched in the preprocessing step and clustering step, and improved the efficiency and accuracy. Experimental results have demonstrated the effectiveness of the proposed algorithm.

###### A Mathematical Model to describe the herd behaviour considering group defense

## Abstract

A model for predator-prey interactions with herd behaviour is proposed. Novelty includes a smooth transition from individual behaviour (low number of prey) to herd behaviour (large number of prey). The model is analysed using standard stability and bifurcations techniques. We prove that the system undergoes a Hopf bifurcation as we vary the parameter that represents the efficiency of predators (dependent on the predation rate, for instance), giving rise to sustained oscillations in the system. The proposed model appears to possess more realistic features than the previous approaches while being also relatively easier to analyse and understand.

###### Phase transitions of biological phenotypes by means of a prototypical PDE model

## Abstract

The basic investigation is the existence and the (numerical) observability of propagating fronts in the framework of the so-called Epithelial-to-Mesenchymal Transition and its reverse Mesenchymal-to-Epithelial Transition, which are known to play a crucial role in tumor development. To this aim, we propose a simplified one-dimensional hyperbolic-parabolic PDE model composed of two equations, one for the representative of the epithelial phenotype, and the second describing the mesenchymal phenotype. The system involves two positive constants, the *relaxation time* and a measure of *invasiveness*, moreover an essential feature is the presence of a nonlinear reaction function, typically assumed to be *S*-shaped. An identity characterizing the speed of propagation of the fronts is proven, together with numerical evidence of the existence of traveling waves. The latter is obtained by discretizing the system by means of an implicit-explicit finite difference scheme, then the algorithm is validated by checking the capability of the so-called *LeVeque–Yee formula* to reproduce the value of the speed furnished by the above cited identity. Once such justification has been achieved, we concentrate on numerical experiments relative to Riemann initial data connecting two stable stationary states of the underlying ODE model. In particular, we detect an explicit transition threshold separating regression regimes from invasive ones, which depends on critical values of the invasiveness parameter. Finally, we perform an extensive sensitivity analysis with respect to the system parameters, exhibiting a subtle dependence for those close to the threshold values, and we postulate some conjectures on the propagating fronts.

###### Subsampled Nonmonotone Spectral Gradient Methods

## Abstract

This paper deals with subsampled spectral gradient methods for minimizing finite sums. Subsample function and gradient approximations are employed in order to reduce the overall computational cost of the classical spectral gradient methods. The global convergence is enforced by a nonmonotone line search procedure. Global convergence is proved provided that functions and gradients are approximated with increasing accuracy. R-linear convergence and worst-case iteration complexity is investigated in case of strongly convex objective function. Numerical results on well known binary classification problems are given to show the effectiveness of this framework and analyze the effect of different spectral coefficient approximations arising from the variable sample nature of this procedure.

###### Entropy Generation in Couette Flow Through a Deformable Porous Channel

## Abstract

The present study examines the entropy generation on Couette flow of a viscous fluid in parallel plates filled with deformable porous medium. The fluid is injected into the porous channel perpendicular to the lower wall with a constant velocity and is sucked out of the upper wall with same velocity .The coupled phenomenon of the fluid flow and solid deformation in the porous medium is taken in to consideration. The exact expressions for the velocity of fluid, solid displacement and temperature distribution are found analytically. The effect of pertinent parameters on the fluid velocity, solid displacement and temperature profiles are discussed in detail. In the deformable porous layer, it is noticed that the velocity of fluid, solid displacement and temperature distribution are decreases with increasing the suction/injection velocity parameter. The results obtained for the present flow characteristic reveal several interesting behaviors that warrant further study on the deformable porous media. Furthermore, the significance of drag and the volume fraction on entropy generation number and Bejan number are discussed with the help of graphs.

###### Mathematical analysis of a B-cell chronic lymphocytic leukemia model with immune response

## Abstract

A B-cell chronic lymphocytic leukemia has been modeled via a highly nonlinear system of ordinary differential equations. We consider the rather important theoretical question of the equilibria existence. Under suitable assumptions all model populations are shown to coexist.

###### New iterative schemes for solving variational inequality and fixed points problems involving demicontractive and quasi-nonexpansive mappings in Banach spaces

## Abstract

In this paper, we suggest and analyze a new iterative method for finding a common element of the set of fixed points of a quasi-nonexpansive mapping and the set of fixed points of a demicontractive mapping which is the unique solution of some variational inequality problems involving accretive operators in a Banach space. We prove the strong convergence of the proposed iterative scheme without imposing any compactness condition on the mapping or the space. Finally, applications of our theorems to some constrained convex minimization problems are given.

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Note On Jakimovski-Leviatan Operators Preserving *e*
^{–x
}

## Abstract

In the present article, a modification of Jakimovski-Leviatan operators is presented which reproduce constant and *e*
^{–x} functions. We prove uniform convergence order of a quantitative estimate for the modified operators. We also give a quantitative Voronovskya type theorem.

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Optical solitons to the fractional Schr*ö*dinger-Hirota equation

## Abstract

This study reaches the dark, bright, mixed dark-bright, and singular optical solitons to the fractional Schr*ö*dinger-Hirota equation with a truncated *M*-fractional derivative via the extended sinh-Gordon equation expansion method. Dark soliton describes the solitary waves with lower intensity than the background, bright soliton describes the solitary waves whose peak intensity is larger than the background, and the singular soliton solutions is a solitary wave with discontinuous derivatives; examples of such solitary waves include compactions, which have finite (compact) support, and peakons, whose peaks have a discontinuous first derivative. The constraint conditions for the existence of valid solutions are given. We use some suitable values of the parameters in plotting 3-dimensional surfaces to some of the reported solutions.