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Porcine prion protein amyloid Per Hammarstr€om and Sofie Nystr€om*
, 2015
"... ABSTRACT. Mammalian prions are composed of misfolded aggregated prion protein (PrP) with amyloidlike features. Prions are zoonotic disease agents that infect a wide variety of mammalian species including humans. Mammals and byproducts thereof which are frequently encountered in daily life are most ..."
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ABSTRACT. Mammalian prions are composed of misfolded aggregated prion protein (PrP) with amyloidlike features. Prions are zoonotic disease agents that infect a wide variety of mammalian species including humans. Mammals and byproducts thereof which are frequently encountered in daily life are most important for human health. It is established that bovine prions (BSE) can infect humans while there is no such evidence for any other prion susceptible species in the human food chain (sheep, goat, elk, deer) and largely prion resistant species (pig) or susceptible and resistant pets (cat and dogs, respectively). PrPs from these species have been characterized using biochemistry, biophysics and neurobiology. Recently we studied PrPs from several mammals in vitro and found evidence for generic amyloidogenicity as well as crossseeding fibril formation activity of all PrPs on the human PrP sequence regardless if the original species was resistant or susceptible to prion disease. Porcine PrP amyloidogenicity was among the studied. Experimentally inoculated pigs as well as transgenic mouse lines overexpressing porcine PrP have, in the past, been used to investigate the possibility of prion transmission in pigs. The pig is a species with extraordinarily wide use within human daily life with over a billion pigs harvested for human consumption each year. Here we discuss the possibility that the largely prion disease resistant pig can be a clinically silent carrier of replicating prions.
Order of Accuracy of Functional Fitting
"... In this paper we introduce functional fitting RungeKuttaNystr\"om method which integrates some set of functions exactly. The method proposed here is a generalization of exponentially or trigonometrically fitting RungeKuttaNystr\"om methods. ..."
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In this paper we introduce functional fitting RungeKuttaNystr\"om method which integrates some set of functions exactly. The method proposed here is a generalization of exponentially or trigonometrically fitting RungeKuttaNystr\"om methods.
$r_{\mathrm{b}\mathrm{i}\mathrm{m}}\mathrm{g}_{\mathrm{o}\mathrm{n}\mathrm{o}}\mathrm{e}\mathrm{t}\mathrm{r}\mathrm{i}_{\mathrm{C}}\mathrm{R}\mathrm{u}\mathrm{n}\mathrm{g}\mathrm{e}$KuttaNystr\"om Method for Solving Periodic lnitial Value Problems
"... A number of numerical methods for the solution of periodic initial value problems have been developed (see e.g. [1], [5], [7], and [8]). Only few of them, however, take advantage of special properties of the solution that may be known in advance. If the frequency of the solution, or a reasonable est ..."
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A number of numerical methods for the solution of periodic initial value problems have been developed (see e.g. [1], [5], [7], and [8]). Only few of them, however, take advantage of special properties of the solution that may be known in advance. If the frequency of the solution, or a reasonable
Mixed Collocation Methods for Y" = F(x,y)
, 1999
"... The collocation methods introduced here are based on linear combinations of trigonometric functions and powers. The motivation is to provide better approximations for oscillatory solutions of initialvalue problems for dierential equations of the special form y 00 = f(x; y). The resulting methods, ..."
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Cited by 1 (0 self)
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, for two or more collocation points, are implicit RungeKuttaNystrom methods with coecients which depend on both the tted angular frequency and the steplength. Algebraic and trigonometric order conditions are considered and the stability properties of some methods are examined. Particular mixed
Fast Nyström Methods for Parabolic Boundary Integral Equations
 Fast Boundary Element Methods in Engineering and Industrial Applications
"... Abstract Time dependence in parabolic boundary integral operators appears in form of an integral over the previous time evolution of the problem. The kernels are singular only at the current time and get increasingly smooth for contributions that are further back in time. The thermal layer potentia ..."
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Cited by 1 (0 self)
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developments in the area we discuss the different options to discretize Abel integral operators in time. These methods are combined with standard surface quadrature rules to obtain a Nystr¤om method for parabolic integral equations. The method is explicit and we will show how a version of the fast multipole
RungeKuttaNyströmtype parallel block predictorcorrector methods
 Appl. Numer. Math
, 1997
"... This paper describes the construction of block predictorcorrector methods based on RungeKuttaNystrom correctors. Our approach is to apply the predictorcorrector method not only with stepsize h, but, in addition (and simultaneously) with stepsizes a i h; i = 1; : : : ; r. In this way, at each st ..."
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Cited by 8 (7 self)
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, the sequential costs of these block predictorcorrector methods are comparable with those of a conventional predictorcorrector method. Furthermore, by using RungeKuttaNystr om corrector methods, the computation of the approximation at each offstep point is also highly parallel. By a number of widelyused test
A Chebyshev Spectral Method for Solving Radiative Transport Equations
"... Abstract. We present a new method for numerically solving the onedimensional, timeindependent radiative transport equation. This method uses a Chebyshev spectral approximation to treat the spatial variable, which leads to a coupled system of integral equations for the modes of the Chebyshev spectr ..."
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spectrum. These integral equations can then be numerically approximated by a Nystr"om method or an expansion method. This resultant bordered, blocktridiagonal system of equations can be efficiently solved by a deflated block elimination method. After discussing the method, we present examples
Primal Space Sparse Kernel Partial Least Squares Regression for Large Scale Problems
 In Proceedings of International Joint Conference on Neural Networks (IJCNN
, 2004
"... Kernel based methods suffer from exceeding time and memory requirements when applied on large datasets since the involved optimization problems typically scale polynomially in the number of data samples. As a remedy we propose both working on a reduced set (for fast evaluation) and at the same time ..."
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Cited by 5 (0 self)
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Kernel based methods suffer from exceeding time and memory requirements when applied on large datasets since the involved optimization problems typically scale polynomially in the number of data samples. As a remedy we propose both working on a reduced set (for fast evaluation) and at the same time
The Algorithm: Algorithm 503, An Automatic Program for Fredhohn Integral Equations of the Second Kind
"... Two automatic programs for solving linear Fredholm integral equations of the second kind are described and illustrated. It is assumed that the kernel function and solution are smooth and that they are given analytically, not as discrete data. The numerical method is based on the Nystr6m method, wit ..."
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Two automatic programs for solving linear Fredholm integral equations of the second kind are described and illustrated. It is assumed that the kernel function and solution are smooth and that they are given analytically, not as discrete data. The numerical method is based on the Nystr6m method
Results 1  10
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