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A Higher-Order Energy Expansion to Two-Dimensional Singularly Neumann Problems
Of concern is the
following singularly perturbed semilinear elliptic problem
\begin{equation*}
\left\{ \begin{array}{c}
\mbox{ in }\\
\mbox{ in and on },
\end{array}
\right.
\end{equation*}
where is a bounded domain in with smooth
boundary , is a small constant and
. Associated with the
above problem is the energy functional defined by
\begin{equation*}
J_{\epsilon}[u]:=\int_{\Omega}\left(\frac{\epsilon^2}{2}{|\nabla
u|}^2 +\frac{1}{2}u^2 -F(u)\right)dx
\end{equation*}
for , where .
Ni and Takagi (\cite{nt1}, \cite{nt2}) proved that for a single
boundary spike solution , the following asymptotic
expansion holds:
\begin{equation*}
(1) \ \ \ \ \ \ \ \ J_{\epsilon}[u_{\epsilon}]=\epsilon^{N}
\left[\frac{1}{2}I[w]-c_1 \epsilon
H(P_{\epsilon})+o(\epsilon)\right],
\end{equation*}
where is the energy of the ground state, is a
generic constant, is the unique local maximum point
of and is the boundary mean
curvature function at . Later,
Wei and Winter (\cite{ww3}, \cite{ww4}) improved the result and
obtained a higher-order expansion of :
\begin{equation*}
(2) \ \ \ \ \ \ J_{\epsilon}[u_{\epsilon}]=\epsilon^{N}
\left[\frac{1}{2}I[\omega]-c_{1} \epsilon
H(P_{\epsilon})+\epsilon^2 [c_2(H(P_\epsilon))^2 +c_{3}
R(P_\epsilon)]+o(\epsilon^2)\right],
\end{equation*}
where and are generic constants and
is the scalar curvature at . However, if , the
scalar curvature is always zero. The expansion (2) is no longer sufficient to distinguish spike locations with same mean curvature.
In this paper, we consider
this case and assume that . Without loss of generality, we may assume that the
boundary near P\in\partial\Om is represented by the graph . Then we have the following higher order expansion of
\begin{equation*}
(3) \ \ \ \ \ J_\epsilon [u_\epsilon]
=\epsilon^N \left[\frac{1}{2}I[w]-c_1
\epsilon H({P_\epsilon})+c_2 \epsilon^2(H({P_\epsilon}))^2 ]
+\epsilon^3
[P(H({P_\epsilon}))+c_3S({P_\epsilon})]+o(\epsilon^3)\right],
\end{equation*}
where H(P_\ep)= \rho_{P_\ep}^{''} (0) is the curvature, is a polynomial,
, , and , , are generic real
constants and S(P_\epsilon)= \rho_{P_\ep}^{(4)} (0). In
particular . Some applications of this expansion are given
Profile control charts based on nonparametric -1 regression methods
Classical statistical process control often relies on univariate
characteristics. In many contemporary applications, however, the quality of
products must be characterized by some functional relation between a response
variable and its explanatory variables. Monitoring such functional profiles has
been a rapidly growing field due to increasing demands. This paper develops a
novel nonparametric -1 location-scale model to screen the shapes of
profiles. The model is built on three basic elements: location shifts, local
shape distortions, and overall shape deviations, which are quantified by three
individual metrics. The proposed approach is applied to the previously analyzed
vertical density profile data, leading to some interesting insights.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS501 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Stability of spikes in the shadow Gierer-Meinhardt system with Robin boundary conditions
We consider the shadow system of the Gierer-Meinhardt system in a smooth bounded domain RN,At=2A−A+,x, t>0, ||t=−||+Ardx, t>0 with the Robin boundary condition +aAA=0, x, where aA>0, the reaction rates (p,q,r,s) satisfy 1<p<()+, q>0, r>0, s0, 1<<+, the diffusion constant is chosen such that 1, and the time relaxation constant is such that 0. We rigorously prove the following results on the stability of one-spike solutions: (i) If r=2 and 1<p<1+4/N or if r=p+1 and 1<p<, then for aA>1 and sufficiently small the interior spike is stable. (ii) For N=1 if r=2 and 1<p3 or if r=p+1 and 1<p<, then for 0<aA<1 the near-boundary spike is stable. (iii) For N=1 if 3<p<5 and r=2, then there exist a0(0,1) and µ0>1 such that for a(a0,1) and µ=2q/(s+1)(p−1)(1,µ0) the near-boundary spike solution is unstable. This instability is not present for the Neumann boundary condition but only arises for the Robin boundary condition. Furthermore, we show that the corresponding eigenvalue is of order O(1) as 0. ©2007 American Institute of Physic
Stability of cluster solutions in a cooperative consumer chain model
This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ Springer-Verlag Berlin Heidelberg 2012.We study a cooperative consumer chain model which consists of one producer and two consumers. It is an extension of the Schnakenberg model suggested in Gierer and Meinhardt [Kybernetik (Berlin), 12:30-39, 1972] and Schnakenberg (J Theor Biol, 81:389-400, 1979) for which there is only one producer and one consumer. In this consumer chain model there is a middle component which plays a hybrid role: it acts both as consumer and as producer. It is assumed that the producer diffuses much faster than the first consumer and the first consumer much faster than the second consumer. The system also serves as a model for a sequence of irreversible autocatalytic reactions in a container which is in contact with a well-stirred reservoir. In the small diffusion limit we construct cluster solutions in an interval which have the following properties: The spatial profile of the third component is a spike. The profile for the middle component is that of two partial spikes connected by a thin transition layer. The first component in leading order is given by a Green's function. In this profile multiple scales are involved: The spikes for the middle component are on the small scale, the spike for the third on the very small scale, the width of the transition layer for the middle component is between the small and the very small scale. The first component acts on the large scale. To the best of our knowledge, this type of spiky pattern has never before been studied rigorously. It is shown that, if the feedrates are small enough, there exist two such patterns which differ by their amplitudes.We also study the stability properties of these cluster solutions. We use a rigorous analysis to investigate the linearized operator around cluster solutions which is based on nonlocal eigenvalue problems and rigorous asymptotic analysis. The following result is established: If the time-relaxation constants are small enough, one cluster solution is stable and the other one is unstable. The instability arises through large eigenvalues of order O(1). Further, there are small eigenvalues of order o(1) which do not cause any instabilities. Our approach requires some new ideas: (i) The analysis of the large eigenvalues of order O(1) leads to a novel system of nonlocal eigenvalue problems with inhomogeneous Robin boundary conditions whose stability properties have been investigated rigorously. (ii) The analysis of the small eigenvalues of order o(1) needs a careful study of the interaction of two small length scales and is based on a suitable inner/outer expansion with rigorous error analysis. It is found that the order of these small eigenvalues is given by the smallest diffusion constant ε22.RGC of Hong Kon
Effect of carbon nanotube doping on critical current density of MgB2 superconductor
The effect of doping MgB2 with carbon nanotubes on transition temperature,
lattice parameters, critical current density and flux pinning was studied for
MgB2-xCx with x = 0, 0.05, 0.1, 0.2 and 0.3. The carbon substitution for B was
found to enhance Jc in magnetic fields but depress Tc. The depression of Tc,
which is caused by the carbon substitution for B, increases with increasing
doping level, sintering temperature and duration. By controlling the extent of
the substitution and addition of carbon nanotubes we can achieve the optimal
improvement on critical current density and flux pinning in magnetic fields
while maintaining the minimum reduction in Tc. Under these conditions, Jc was
enhanced by two orders of magnitude at 8T and 5K and 7T and 10K. Jc was more
than 10,000A/cm2 at 20K and 4T and 5K and 8.5T, respectively
Performance Analysis of a Dual-Hop Cooperative Relay Network with Co-Channel Interference
This paper analyzes the performance of a dual-hop amplify-and-forward (AF) cooperative relay network in the presence of direct link between the source and destination and multiple co-channel interferences (CCIs) at the relay. Specifically, we derive the new analytical expressions for the moment generating function (MGF) of the output signal-to-interference-plus-noise ratio (SINR) and the average symbol error rate (ASER) of the relay network. Computer simulations are given to confirm the validity of the analytical results and show the effects of direct link and interference on the considered AF relay network
Towards Identification of Relevant Variables in the observed Aerosol Optical Depth Bias between MODIS and AERONET observations
Measurements made by satellite remote sensing, Moderate Resolution Imaging
Spectroradiometer (MODIS), and globally distributed Aerosol Robotic Network
(AERONET) are compared. Comparison of the two datasets measurements for aerosol
optical depth values show that there are biases between the two data products.
In this paper, we present a general framework towards identifying relevant set
of variables responsible for the observed bias. We present a general framework
to identify the possible factors influencing the bias, which might be
associated with the measurement conditions such as the solar and sensor zenith
angles, the solar and sensor azimuth, scattering angles, and surface
reflectivity at the various measured wavelengths, etc. Specifically, we
performed analysis for remote sensing Aqua-Land data set, and used machine
learning technique, neural network in this case, to perform multivariate
regression between the ground-truth and the training data sets. Finally, we
used mutual information between the observed and the predicted values as the
measure of similarity to identify the most relevant set of variables. The
search is brute force method as we have to consider all possible combinations.
The computations involves a huge number crunching exercise, and we implemented
it by writing a job-parallel program
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Filtering for nonlinear genetic regulatory networks with stochastic disturbances
In this paper, the filtering problem is investigated for nonlinear genetic regulatory networks with stochastic disturbances and time delays, where the nonlinear function describing the feedback regulation is assumed to satisfy the sector condition, the stochastic perturbation is in the form of a scalar Brownian motion, and the time delays exist in both the translation process and the feedback regulation process. The purpose of the addressed filtering problem is to estimate the true concentrations of the mRNA and protein. Specifically, we are interested in designing a linear filter such that, in the presence of time delays, stochastic disturbances as well as sector nonlinearities, the filtering dynamics of state estimation for the stochastic genetic regulatory network is exponentially mean square stable with a prescribed decay rate lower bound beta. By using the linear matrix inequality (LMI) technique, sufficient conditions are first derived for ensuring the desired filtering performance for the gene regulatory model, and the filter gain is then characterized in terms of the solution to an LMI, which can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures
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