COVID-19 Epidemic Prediction Based on Deep Learning

In this paper, a multi-layer gated recurrent unit neural network (multi-head GRU) model is proposed to predict the confirmed cases of the new crown epidemic (COVID-19). We extract the time series relationship in the data, and the rolling prediction method is adopted to ensure the simple structure of the model and achieve higher precision and interpretability. The prediction results of this model are compared with the LSTM model, the Transformer model and the infectious disease model (SIR). The results show that the proposed model has higher prediction accuracy. The mean absolute error (MAE) of epidemic prediction in most countries (the United States, Brazil, India, the United Kingdom and Russia) is respectively 197.52, 68.02, 200.67, 24.78 and 123.50, which is much smaller than the prediction error of the SIR model, LSTM model and Transformer model. For the spread of the COVID-19 epidemic, traditional infectious disease models and machine learning models cannot achieve more accurate predictions. In this paper, we use a GRU model to predict the real-time spread of COVID-19, which has fewer parameters and reduces the risk of overfitting to train faster. Meanwhile, it can make up for the shortcoming of the transformer model to capture local features.     

United States and South Korean citizens’ interpretation and assessment of COVID-19 quantitative data

We investigate United States and South Korean citizens’ mathematical schemes and how these schemes supported or hindered their attempts to assess the severity of COVID-19. We selected web and media-based COVID-19 data representations that we hypothesized citizens would interpret differently depending on their mathematical schemes. We included items that we conjectured would be easier or more difficult to interpret with schemes that prior research had reported were more or less productive, respectively. We used the representations during clinical interviews with 25 United States and seven South Korean citizens. We illustrate that citizens’ mathematical schemes (as well as their beliefs) impacted how they assessed the severity of COVID-19. We present vignettes of citizens’ schemes that inhibited interpreting representations of COVID-19 in ways compatible with the displayed quantitative data, schemes that aided them in assessing the severity of COVID-19, and beliefs about the reliability of scientific data that overrode their mathematical conclusions.     

GAMMA-MINIMAX ESTIMATORS FOR THE MEAN VECTOR OF A MULTIVARIATE NORMAL DISTRIBUTION

Γ-minimax estimators are determined for the mean vector of a multivariate normaldistribution under arbitrary squared error loss.Thereby the set Γ consists of all priorswhose vector of first moments and matrix of second moments satisfy some given restric-tions.Necessary and sufficient conditions are derived which ensure a prior being leastfavourable in Γ and the unique Bayes estimator with respect to this prior being Γ-minimax.By applying these results the Γ-minimax estimator is explicitly found in some special casesor can be computed by solving a system of non-linear equations or by minimizing a quad-ratic form on a compact and convex set.     

Adaptive-Additive Multilevel Methods for Hypersingular Integral Equation

In this article we present the combined adaptive-additive multilevel methods for the Galerkin approximation of hypersingular integral equation on the interval o = ( m 1,1). We also derive an efficient and reliable a posteriori error estimate for the error between the exact solution u and the approximated multilevel solution $ \tilde u_ {\cal M} $ , measuring locally the quality of $ \tilde u_ {\cal M} $ . The algorithm is carefully designed to obtain minimal complexity. A limitation of our analysis approach is that the meshes must be assumed to be quasi-uniform.     

Positive Ground State Solutions for Schrödinger-Poisson System with General Nonlinearity and Critical Exponent

In this paper, we consider the following Schrödinger-Poisson system \begin{equation*}\begin{cases} -\Delta u + \eta\phi u = f(x,u) + u^5,& x\in\Omega,\\ -\Delta\phi=u^2,& x\in\Omega,\\u = \phi =0,& x\in \partial\Omega, \end{cases}\end{equation*} where $\Omega$ is a smooth bounded domain in $R^3$, $\eta=\pm1$ and the continuous function $f$ satisfies some suitable conditions. Based on the Mountain pass theorem, we prove the existence of positive ground state solutions.     

Uniformly Accurate Multiscale Time Integrators for Highly Oscillatory Second Order Differential Equations

In this paper, two multiscale time integrators (MTIs), motivated from two types of multiscale decomposition by either frequency or frequency and amplitude, are proposed and analyzed for solving highly oscillatory second order differential equations with a dimensionless parameter $0 < \varepsilon≤ 1.$ In fact, the solution to this equation propagates waves with wavelength at $O(\varepsilon^2)$ when $0<\varepsilon≪1,$ which brings significantly numerical burdens in practical computation. We rigorously establish two independent error bounds for the two MTIs at $O(\tau^2/\varepsilon^2)$ and $O(\varepsilon^2)$ for $\varepsilon ∈ (0,1]$ with $\tau > 0$ as step size, which imply that the two MTIs converge uniformly with linear convergence rate at $O(\tau)$ for $ε ∈ (0,1]$ and optimally with quadratic convergence rate at $O(\tau^2)$ in the regimes when either $ε=O(1)$ or $0<ε≤\tau.$ Thus the meshing strategy requirement (or $ε$-scalability) of the two MTIs is $\tau =O(1)$ for $0<ε≪1,$ which is significantly improved from $\tau =O(ε^3)$ and $\tau =O(ε^2)$ requested by finite difference methods and exponential wave integrators to the equation, respectively. Extensive numerical tests and comparisons with those classical numerical integrators are reported, which gear towards better understanding on the convergence and resolution properties of the two MTIs. In addition, numerical results support the two error bounds very well.     

The Geometry of the Phase Diffusion Equation

$ \tau(|{{\vec k}}|) \mbox{\bf $\Theta$}_T = -\nabla\cdot (B(|{{\vec k}}|)\cdot {{\vec k}}), \,\, {{\vec k}} = \nabla \mbox{\bf $\Theta$},$ and its regularization describes natural patterns and defects far from onset in large aspect ratio systems with rotational symmetry. In this paper we construct explicit solutions of the unregularized equation and suggest candidates for its weak solutions. We confirm these ideas by examining a fourth-order regularized equation in the limit of infinite aspect ratio. The stationary solutions of this equation include the minimizers of a free energy, and we show these minimizers are remarkably well-approximated by a second-order ``self-dual' equation. Moreover, the self-dual solutions give upper bounds for the free energy which imply the existence of weak limits for the asymptotic minimizers. In certain cases, some recent results of Jin and Kohn [28] combined with these upper bounds enable us to demonstrate that the energy of the asymptotic minimizers converges to that of the self-dual solutions in a viscosity limit. Received on October 30, 1998; final revision received July 6, 1999     

人口迁入与新增确诊数的趋势关系及因果量化分析

目前,很多地区新冠肺炎疫情已得到缓解,复工、复产已被多地政府部门提上日程.2月10日前后,全国各地返城复工人数增多,2月14日开始,广东、河南等地新增病例数出现了明显反弹,人口跨地区迁徙使疫情防控更加困难.目前全国返工、返校需求还远未得到满足,需要通过数据分析,对"返城复工"的风险进行评估.通过观察数据可以发现人口迁徙与新增确诊病例数有很强的正相关性,因此由"格兰杰因果检验"确定了人口迁徙与新增确诊病例数有显著的因果关系.     

Classification of Solutions to a Critically Nonlinear System of Elliptic Equations on Euclidean Half-Space

For $N\geq 3$ and non-negative real numbers $a_{ij}$ and $b_{ij}$ ($i,j= 1, \cdots, m$), the semi-linear elliptic system\begin{equation*} \begin{cases}\Delta u_i+\prod\limits_{j=1}^m u_j^{a_{ij}}=0,\text{in}\mathbb{R}_+^N,\\dfrac{\partial u_i}{\partial y_N}=c_i\prod\limits_{j=1}^m u_j^{b_{ij}},\text{on} \partial\mathbb{R}_+^N,\end{cases}\qquad i=1,\cdots,m,\end{equation*} % is considered, where $\mathbb{R}_+^N$ is the upper half of $N$-dimensional Euclidean space. Under suitable assumptions on the exponents $a_{ij}$ and $b_{ij}$, a classification theorem for the positive $C^2(\mathbb{R}_+^N)\cap C^1(\overline{R_+^N})$-solutions of this system is proven.     

Weak solvability and well-posedness of a coupled Schrödinger-Korteweg de Vries equation for capillary-gravity wave interactions

An interaction equation of the capillary-gravity wave is considered. We show that the Cauchy problem of the coupled Schrödinger-KdV equation,

is locally well-posed for weak initial data . We apply the analogous method for estimating the nonlinear coupling terms developed by Bourgain and refined by Kenig, Ponce, and Vega.

     

关于有限域上一类方程解的个数

Let Fq be a finite field with q = pf elements,where p is an odd prime.Let N(a1x12 + ···+anxn2 = bx1 ···xs) denote the number of solutions(x1,...,xn) of the equation a1x12 +···+ anxn2 = bx1 ···xs in Fnq,where n 5,s n,and ai ∈ F*q,b ∈ F*q.In this paper,we solve the problem which the present authors mentioned in an earlier paper,and obtain a reduction formula for the number of solutions of equation a1x21 + ··· + anxn2 = bx1 ···xs,where n 5,3 ≤ s n,under a certain restriction on coefficients.We also obtain an explicit formula for the number of solutions of equation a1x21 + ··· + anxn2 = bx1 ···xn-1 in Fqn under a restriction on n and q.     

N维多重非齐次调和方程及其边界积分方程

对n维多重非齐次调和方程△~((k))u=f(x),x∈R~n,给出了基本解的递推公式以及多重调和函数的积分关系式.在非齐次项f(x)为m次调和的情形下将域上的积分转化为沿边界的积分,进而应用直接法给出了基本边界积分方程.对f(x)为一般光滑函数的情形,给出了用泰勒多项式逼近时相应的误差估计并证明了含误差项的积分是收敛的.     

Optimal Transportation for Generalized Lagrangian

This paper deals with the optimal transportation for generalized Lagrangian L = L(x, u, t), and considers the following cost function: c(x, y) = inf x(0)=x x(1)=y u∈U∫_0~1 L(x(s), u(x(s), s), s)ds, where U is a control set, and x satisfies the ordinary equation x(s) = f(x(s), u(x(s), s)).It is proved that under the condition that the initial measure μ0 is absolutely continuous w.r.t. the Lebesgue measure, the Monge problem has a solution, and the optimal transport map just walks along the characteristic curves of the corresponding Hamilton-Jacobi equation:V_t(t, x) + sup u∈UV_x(t, x), f(x, u(x(t), t), t)-L(x(t), u(x(t), t), t) = 0,V(0, x) = Φ0(x).     

Mean growth of Koenigs eigenfunctions

In 1884, G. Koenigs solved Schroeder's functional equation

in the following context: is a given holomorphic function mapping the open unit disk into itself and fixing a point , is holomorphic on , and is a complex scalar. Koenigs showed that if , then Schroeder's equation for has a unique holomorphic solution satisfying

moreover, he showed that the only other solutions are the obvious ones given by constant multiples of powers of . We call the Koenigs eigenfunction of . Motivated by fundamental issues in operator theory and function theory, we seek to understand the growth of integral means of Koenigs eigenfunctions. For , we prove a sufficient condition for the Koenigs eigenfunction of to belong to the Hardy space and show that the condition is necessary when is analytic on the closed disk. For many mappings the condition may be expressed as a relationship between and derivatives of at points on that are fixed by some iterate of . Our work depends upon a formula we establish for the essential spectral radius of any composition operator on the Hardy space .

     

LIMIT CYCLES OF THE GENERALIZED POLYNOMIAL LINARD DIFFERENTIAL SYSTEMS

Using the averaging theory of first and second order we study the maximum number of limit cycles of generalized Linard differential systems{x = y + εh_l~1(x) + ε~2h_l~2(x),y=-x- ε(f_n~1(x)y~(2p+1) + g_m~1(x)) + ∈~2(f_n~2(x)y~(2p+1) + g_m~2(x)),which bifurcate from the periodic orbits of the linear center x = y,y=-x,where ε is a small parameter.The polynomials h_l~1 and h_l~2 have degree l;f_n~1and f_n~2 have degree n;and g_m~1,g_m~2 have degree m.p ∈ N and[·]denotes the integer part function.     

Existence and uniqueness for a degenerate parabolic equation with -data

In this paper we study existence and uniqueness of solutions for the boundary-value problem, with initial datum in ,

where a is a Carathéodory function satisfying the classical Leray-Lions hypothesis, is the Neumann boundary operator associated to , the gradient of and is a maximal monotone graph in with .

     

(Semi-)Nonrelativisitic Limit of the Nonlinear Dirac Equations

We consider the nonlinear Dirac equation (NLD) with time dependent external electro-magnetic potentials, involving a dimensionless parameter $ε\in(0,1]$ which is inversely proportional to the speed of light. In the nonrelativistic limit regime $ε\ll1$ (speed of light tends to infinity), we decompose the solution into the eigenspaces associated with the 'free Dirac operator' and construct an approximation to the NLD with $O(ε^2)$ error. The NLD converges (with a phase factor) to a coupled nonlinear Schrödinger system (NLS) with external electric potential in the nonrelativistic limit as $ε\to0^+$, and the error of the NLS approximation is first order $O(ε)$. The constructed $O(ε^2)$ approximation is well-suited for numerical purposes.     

PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming

Suppose we wish to recover a signal \input amssym $\font\abc=cmmib10\def\bi#1{\hbox{\abc#1}} {\bi x} \in {\Bbb C}^n$ from m intensity measurements of the form $\font\abc=cmmib10\def\bi#1{\hbox{\abc#1}} |\langle \bi x,\bi z_i \rangle|^2$ , $i = 1, 2, \ldots, m$ ; that is, from data in which phase information is missing. We prove that if the vectors $\font\abc=cmmib10\def\bi#1{\hbox{\abc#1}}{\bi z}_i$ are sampled independently and uniformly at random on the unit sphere, then the signal x can be recovered exactly (up to a global phase factor) by solving a convenient semidefinite program–‐a trace‐norm minimization problem; this holds with large probability provided that m is on the order of $n {\log n}$ , and without any assumption about the signal whatsoever. This novel result demonstrates that in some instances, the combinatorial phase retrieval problem can be solved by convex programming techniques. Finally, we also prove that our methodology is robust vis‐à‐vis additive noise. © 2012 Wiley Periodicals, Inc.