48 research outputs found

    Error estimates for interpolation of rough data using the scattered shifts of a radial basis function

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    The error between appropriately smooth functions and their radial basis function interpolants, as the interpolation points fill out a bounded domain in R^d, is a well studied artifact. In all of these cases, the analysis takes place in a natural function space dictated by the choice of radial basis function -- the native space. The native space contains functions possessing a certain amount of smoothness. This paper establishes error estimates when the function being interpolated is conspicuously rough.Comment: 12 page

    Interpolation by piecewise-linear radial basis functions, I

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    AbstractIn the two-dimensional plane, a set of points x1, x2, …, xn (called “nodes”) is given. It is desired to interpolate arbitrary data given on the nodes by continuous functions having piecewise-linear (“PL”) structure. For this purpose, one can employ the space of all PL-functions on a rectangular grid generated by the nodes. We study this space first. Next, we investigate the special PL-functions that are linear combinations of functions hi(x) = ∥x − xi∥1, in which the l1-norm on R2 is employed. The “dual” case, involving the two-dimensional l∞-norm, is included in our results, as are certain general interpolating functions of the form (s, t) ↦ F(s − si) + G(t − ti)

    Potential medicinal value of some South African seaweeds

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    Eleven macroalgae were collected from the KwaZulu-Natal coast and nineteen species from the cooler Western Cape coast in March and April 2000. Ethanolic and aqueous extracts were made and tested for biological activity in the Cox-1 anti-inflammatory assay, in a nematode mortality bioassay for anthelminthic activity, an IC50 anticancer assay and a MIC antimicrobial assay. The ethanolic extracts were very active in the Cox-1 anti-inflammatory assay for almost all of the species tested. The aqueous extracts were not active. No anthelminthic mortality was detected in extracts from any of the species tested. Many of the extracts had cytotoxic activity against three cancer cell lines tested, with those from representative species of the Chlorophyta and Rhodophyta being the most effective. The extracts had much lower cytotoxic activity when tested on normal mouse fibroblasts (NIH3T3). Extracts from only a few species had antimicrobial activity with those of the Chlorophyta tested being the most effective against both the Gram-positive and Gram-negative bacteria

    Reproducing Kernels of Generalized Sobolev Spaces via a Green Function Approach with Distributional Operators

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    In this paper we introduce a generalized Sobolev space by defining a semi-inner product formulated in terms of a vector distributional operator P\mathbf{P} consisting of finitely or countably many distributional operators PnP_n, which are defined on the dual space of the Schwartz space. The types of operators we consider include not only differential operators, but also more general distributional operators such as pseudo-differential operators. We deduce that a certain appropriate full-space Green function GG with respect to L:=PTPL:=\mathbf{P}^{\ast T}\mathbf{P} now becomes a conditionally positive definite function. In order to support this claim we ensure that the distributional adjoint operator P\mathbf{P}^{\ast} of P\mathbf{P} is well-defined in the distributional sense. Under sufficient conditions, the native space (reproducing-kernel Hilbert space) associated with the Green function GG can be isometrically embedded into or even be isometrically equivalent to a generalized Sobolev space. As an application, we take linear combinations of translates of the Green function with possibly added polynomial terms and construct a multivariate minimum-norm interpolant sf,Xs_{f,X} to data values sampled from an unknown generalized Sobolev function ff at data sites located in some set XRdX \subset \mathbb{R}^d. We provide several examples, such as Mat\'ern kernels or Gaussian kernels, that illustrate how many reproducing-kernel Hilbert spaces of well-known reproducing kernels are isometrically equivalent to a generalized Sobolev space. These examples further illustrate how we can rescale the Sobolev spaces by the vector distributional operator P\mathbf{P}. Introducing the notion of scale as part of the definition of a generalized Sobolev space may help us to choose the "best" kernel function for kernel-based approximation methods.Comment: Update version of the publish at Num. Math. closed to Qi Ye's Ph.D. thesis (\url{http://mypages.iit.edu/~qye3/PhdThesis-2012-AMS-QiYe-IIT.pdf}

    SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

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    BACKGROUND: Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. METHODS: In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FINDINGS: Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. INTERPRETATION: The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. FUNDING: This study has been supported by ISARIC4C and PHOSP-COVID consortia. ISARIC4C is supported by grants from the National Institute for Health and Care Research and the Medical Research Council. Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research. The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research. The funders were not involved in the study design, interpretation of data or the writing of this manuscript

    An Introduction to Abstract Analysis

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    Mapping with numbers

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