Some transformations acting on radially symmetric solutions to the following class of non-homogeneous reaction-diffusion equations | x | σ 1 ∂ t u = ∆ u m + | x | σ 2 u p , ( x , t ) ∈ R N × ( 0 , ∞ ) , which has been proposed in a number of previous mathematical works as well as in several physical models, are introduced. We consider here m≥1, p≥1, N≥1 and σ 1 , σ 2 real exponents. We apply these transformations in connection to previous results on the one hand to deduce general qualitative properties of radially symmetric solutions and on the other hand to construct self-similar solutions which are expected to be patterns for the dynamics of the equations, strongly improving the existing theory. We also introduce mappings between solutions which work in the semilinear case m=1.

Formulas to calculate multivector exponentials in a basis-free representation and orthonormal basis are presented for an arbitrary Clifford geometric algebra , . The formulas are based on the analysis of roots of characteristic polynomial of a multivector. Elaborate examples how to use the formulas in practice are presented. The results are generalised to arbitrary functions of multivector and may be useful in the quantum circuits or in the problems of analysis of evolution of the entangled quantum states.

We show that the gradient of a strongly differentiable function at a point is the limit of a single coordinate-free Clifford quotient between a multi-difference pseudo-vector and a pseudo-scalar, or of a sum of Clifford quotients between scalars (as numerators) and vectors (as denominators), both evaluated at the vertices of a same non-degenerate simplex contracting to that point. Such result allows to fix a issue with a defective definition of pseudo-scalar field in Sobczyck’s Simplicial Calculus. Then, we provide some consequences and conjectures implied by the foregoing results.

This work is concerned with the global existence of large solutions to the three-dimensional dissipative fluid-dynamical model, which is a strongly coupled nonlinear nonlocal system characterized by the incompressible Navier–Stokes–Poisson–Nernst–Planck equations. Making full use of the algebraic structure of the system, we obtain the global existence of solutions without smallness assumptions imposed on the third component of the initial velocity field and the summation of initial densities of charged species. More precisely, we prove that there exist two positive constants c 0 , C 0 such that if the initial data satisfies ( ∥ u 0 h ∥ B _ p , 1 − 1 + 3 p + ∥ N 0 − P 0 ∥ B _ q , 1 − 2 + 3 q ) exp { C 0 ( ∥ u 0 3 ∥ B _ p , 1 − 1 + 3 p 2 + ( ∥ N 0 + P 0 ∥ B _ r , 1 − 2 + 3 r + 1 ) exp { C 0 ∥ u 0 3 ∥ B _ p , 1 − 1 + 3 p } + 1 ) } ≤ c 0 , then the incompressible Navier–Stokes–Poisson–Nernst–Planck equations admits a unique global solution.

A Coronavirus Disease 2019 (COVID-19) epidemiological model incorporating a boosted infection-acquired immunity and heterogeneity in infection-acquired immunity among recovered individuals is designed. The model is used to investigate whether incorporating these two processes can induce new epidemiological insights. Analytical findings reveal co-existence of multiple endemic equilibria on either regions divided by the fundamental threshold (control reproduction number). Numerical findings conducted to validate analytical results show that heterogeneity in infection-acquired immunity among recovered individuals can induce various bifurcation structures such as reversed backward bifurcation, forward bifurcation, backward bifurcation and reversed hysteresis effect. Moreover, numerical results show that reversed backward bifurcation is annihilated or switches to the usual forward bifurcation if infection-acquired immunity among recovered individuals with strong immunity is assumed to be everlasting. However, this is only possible if primary infection is more likely than reinfection. In case reinfection is more likely to occur than primary infection, reversed backward bifurcation structure switches to a backward bifurcation phenomenon. Further, longer duration of infection-acquired immunity does lead to COVID-19 decline over time but does not lead to flattening of the COVID-19 peak.

We present a framework to model and provide numerical evidence for compartmentalization in the yeast endoplasmic reticulum. Measurement data is collected and an optimal control problem is formulated as a regularized inverse problem. To our knowledge, this is the first attempt in the literature to introduce a PDE-constrained optimization formulation to study the kinetics of fluorescently labeled molecules in budding yeast. Optimality conditions are derived and a gradient descent algorithm allows accurate estimation of unknown key parameters in different cellular compartments. For the first time, the numerical results support the barrier index theory suggesting the presence of a physical diffusion barrier that compartmentalizes the endoplasmic reticulum by limiting protein exchange between the mother and its growing bud. We report several numerical experiments on real data and geometry, with the aim of illustrating the accuracy and efficiency of the method. Furthermore, a relationship between the size ratio of mother and bud compartments and the barrier index ratio is provided.

This paper is concerned with a diffusive predator-prey model with prey-taxis and prey-structure under the homogeneous Neumann boundary condition. The stability of the unique positive constant equilibrium of the predator-prey model is derived. Hopf bifurcation and steady state bifurcation are also concluded.

The Boussinesq equations with partial or fractional dissipation not only naturally generalize the classical Boussinesq equations, but also are physically relevant and mathematically important. Unfortunately, it is not often well understood for many ranges of fractional powers. This paper focuses on a system of the 3D Boussinesq equations with fractional horizontal ( − ∆ h ) α u and ( − ∆ h ) β θ dissipation and proves that if an initial data ( u 0 , θ 0 ) in the Sobolev space H 3 ( R 3 ) close enough to the hydrostatic balance state, respectively, the equations with α , β ∈ ( 1 2 , 1 ] then always lead to a steady solution.

A document by Jorge Herrera de la Cruz. Click on the document to view its contents.

As the COVID-19 continues to mutate, the number of infected people is increasing dramatically, and the vaccine is not enough to fight the mutated strain. In this paper, a SEIR-type fractional model with reinfection and vaccine inefficacy is proposed, which can successfully capture the mutated COVID-19 pandemic. The existence, uniqueness, boundedness and nonnegativeness of the fractional model are derived. Based on the basic reproduction number R 0 , locally stability and globally stability are analyzed. The sensitivity analysis evaluate the influence of each parameter on the R 0 and rank key epidemiological parameters. Finally, the necessary conditions for implementing fractional optimal control are obtained by Pontryagin's Maximum Principle, and the corresponding optimal solutions are derived for mitigation COVID-19 transmission. The numerical results show that humans will coexist with COVID-19 for a long time under the current control strategy. Furthermore, it is particularly important to develop new vaccines with higher protection rates.

This paper is devoted to solve the backward problem for radially symmetric time-fractional diffusion-wave equation under Robin boundary condition. This problem is ill-posed and we apply an iterative regularization method to solve it. The error estimates are obtained under the a priori and a posteriori parameter choice rules. Numerical results show that the proposed method is efficient and stable.

We consider the coupled propagation of an optical field and its second harmonic in a quadratic nonlinear medium governed by a coupled system of Schrodinger equations. We prove the existence of ring-profiled optical vortex solitons appearing as solutions to a constrained minimization problem and as solutions to a min-max problem. In the case of the constrained minimization problem solutions are shown to be positive but the wave propagation constants undetermined, but in the min-max approach the wave propagation constants can be prescribed. The quadratic nonlinearity introduces some interesting properties not commonly observed in other coupled systems in the context of nonlinear optics, such as the system not accepting any semi-trivial solutions, meaning, that optical solitons cannot be observed when, say, one of the beams are off. Additionally, the second harmonic always remains positive.

This paper is concerned with the spreading or vanishing of an epidemic disease which is characterized by a nonlocal diffusion SIR model with nonlocal incidence rate and double free boundaries. We prove that the disease will vanish if the basic reproduction number R 0 < 1 , or the initial area h 0 , the initial datum S 0 , and the expanding ability µ are sufficiently small even that R 0 > 1 , and the disease will spread to the whole area if R 0 > 1 , when h 0 is suitably large or h 0 is small but µ is large enough. Moreover, we also show that the long-time asymptotic limit of the solution when vanishing happens.

This paper is concerned with the global smooth solution of the 3D generalized magneto-micropolar equations. When the velocity dissipation is logarithmically hyperdissipative and the magnetic diffusion is fractional Laplacian, based on some new observations on the nonlinear structure for the magneto-micropolar equations, it is examined the system has a unique global smooth solution ( u , w , b ) ∈ C ( [ 0 , T ] ; H s ( R 3 ) ) . AMS Subject Classification 2010: 35Q35; 35B65; 76A10; 76B03.

Precision in measurement of glucose level in artificial pancreas is a challenging task and mandatory requirement for the proper functioning of artificial pancreas. A suitable machine learning technique for the measurement of glucose level in artificial pancreas may play crucial role in the management of diabetes. Therefore in the present work, a comparison has been made among few machine learning (ML) techniques for measurement of glucose levels in artificial pancreas because the machine learning is an astounding technology of artificial intelligence, and widely applicable in various fields such as medical science, robotics, environmental science, etc. The models namely decision tree (DT), random forest (RF), support vector machine (SVM), and K-nearest neighbours (KNN), based on supervised learning, are proposed for the dataset of Pima Indian to predict and classify the diabetes mellitus. Ensuring the predictions and accuracy up to the level of DMT2, the comparative behavior of all four models has been discussed. The machine learning models developed here stratifies and predicts whether an individual is diabetic or not based on the features available in the data set. Dataset passes through pre-processing and machine learning algorithms are fitted to train the dataset, and then the performance of the test results has been discussed. Error matrix (EM) has been generated to measure the accuracy score of the models. The accuracies in prediction and classification of DMT2 models are 71%, 77%, 78%, and 80% for DT, SVM, RF and KNN algorithms respectively. The KNN model has shown a more precise result in comparison to other models. The proposed methods have shown astounding behaviour in terms of accuracy in the prediction of diabetes mellitus as compared to previously developed methods.

In this work we propose the construction of discrete-time systems with two time scales in which infectious diseases dynamics are involved. We deal with two general situations. In the first, we consider that individuals affected by the disease move between generalized sites on a faster time scale than the dynamics of the disease itself. The second situation includes the dynamics of the disease acting faster together with another slower general process. Once the models have been built, conditions are established so that the analysis of the asymptotic behavior of their solutions can be carried out through reduced models. This is done using known reduction results for discrete-time systems with two time scales. These results are applied in the analysis of two new models. The first of them illustrates the first proposed situation, being the local dynamics of the SIS-type disease. Conditions are found for the eradication or global endemicity of the disease. In the second model, a case of co-infection with a primary disease and an opportunistic disease is treated, the latter acting faster than the former. Conditions for eradication and endemicity of co-infection are proposed.

In this paper, we consider switched systems that allow discontinuous jumps in the state when switching occurs. In particular we analyze the case where these jumps are dictated by a state reset rule. We show that it is possible to study the state trajectories of a switched system with state reset by means of some switched systems without state resets, i.e., with continuous state trajectories. We establish some sufficient conditions for stability of switched systems with state reset using the associated systems without reset. The obtained results are used in numerical examples to show the effectiveness of the proposed approach.

We consider the system of linear equations arisen from the finite element discretization of the distributed optimal control problem with time-periodic parabolic equations. A block alternating splitting iteration (BASI) method is presented for solving the obtained system. We prove that the BASI method is unconditionally convergent. We derive the BASI preconditioner and present an estimation formula for the parameter of the BASI preconditioner. Numerical results are presented to verify the efficiency of both the BASI method and the BASI preconditioner. Comparison with some existing methods are also given.