The central trajectory of a linear program consists of the set of optimal solutions x(Mu) and (y(t), s(j)) to the logarithmic barrier problems: (P,(d)): min{cT x + --p(x) : Ax = b, x > 0), (D,(d)): maxb T y /p(s) : ATy + s = c,s > 0), where p(ul) -= ln(u), is the logarithmic barrier function, d = (A, b, c) is a data instance in the space of all data D = {(A, b, c) : A C Wmn, b E Rm, c E fn), an...

Asthma is the most frequently encountered allergic respiratory disease, and one that has a potentially serious impact on patients' functioning and well-being. From a public health perspective, it is important to collect data on the prevalence, burden and management of asthma in order to improve understanding of the pathogenesis of asthma and to ensure that national healthcare policies are adapt...

Fourth-order Schrödinger equations have been introduced by Karpman and Shagalov to take into account the role of small fourth-order dispersion terms in the propagation of intense laser beams in a bulk medium with Kerr nonlinearity. In this paper we investigate the cubic defocusing fourth order Schrödinger equation i∂tu +∆ 2 u + |u|u = 0 in arbitrary space dimension R for arbitrary initial data....

We consider the linear inverse problem of reconstructing an unknown finite measure μ from a noisy observation of a generalized moment of μ defined as the integral of a continuous and bounded operator Φ with respect to μ. Motivated by various applications, we focus on the case where the operator Φ is unknown; instead, only an approximation Φm to it is available. An approximate maximum entropy so...

An emerging body of evidence suggests that our penchant for entertaining thoughts that are unrelated to ongoing activities might be a detriment to our emotional wellbeing. In light of this evidence, researchers have posited that mindwandering is a cause rather than a manifestation of discontent. We review the evidence in support of this viewpoint. We then consider this evidence in a broader con...

In this paper, we study the statistical properties of method of regularization with radial basis functions in the context of linear inverse problems. Radial basis function regularization is widely used in machine learning because of its demonstrated effectiveness in numerous applications and computational advantages. From a statistical viewpoint, one of the main advantages of radial basis funct...

In this paper, we consider the Cauchy problem for Klein-Gordon equation with a cubic convolution nonlinearity in R. Making use of Bourgain’s method in conjunction with precise Strichartz estimates of S.Klainerman and D.Tataru, we establish the Hs-global well-posedness with s < 1 of the Cauchy problem for the cubic convolution defocusing Klein-Gordon-Hartree equation, inspired by I. Gallagher an...

We investigate, in a systematic fashion, coherent structures, or defects, which serve as interfaces between wave trains with possibly different wavenumbers in reaction-diffusion systems. We propose a classification of defects into four different defect classes which have all been observed experimentally. The characteristic distinguishing these classes is the sign of the group velocities of the ...

The Hermite Radial Basis Functions (HRBF) Implicits reconstruct an implicit function which interpolates or approximates scattered multivariate Hermite data (i.e., unstructured points and their corresponding normals). Experiments suggest that HRBF Implicits allow the reconstruction of surfaces rich in details and behave better than previous related methods under coarse and/or nonuniform sampling...

The Thermal Infrared Sensor (TIRS) for the Landsat 8 platform was designed and built at NASA Goddard Space Flight Center (GSFC). TIRS data will extend the data record for thermal observations from the heritage Landsat sensors, dating back to the launch of Landsat 4 in 1982. The two-band (10.9 and 12.0 μm) pushbroom sensor with a 185 km-wide swath uses a staggered arrangement of quantum well inf...