Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery

This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linear combinations of pure component spectra contaminated by an additive Gaussian noise. The abundance parameters appearing in this model satisfy positivity and additivity constraints. These constraints are naturally expressed in a Bayesian context by using appropriate abundance prior distributions. The posterior distributions of the unknown model parameters are then derived. A Gibbs sampler allows one to draw samples distributed according to the posteriors of interest and to estimate the unknown abundances. An extension of the algorithm is finally studied for mixtures with unknown numbers of spectral components belonging to a know library. The performance of the different unmixing strategies is evaluated via simulations conducted on synthetic and real data

Security Theorems via Model Theory

A model-theoretic approach can establish security theorems for cryptographic protocols. Formulas expressing authentication and non-disclosure properties of protocols have a special form. They are quantified implications for all xs . (phi implies for some ys . psi). Models (interpretations) for these formulas are *skeletons*, partially ordered structures consisting of a number of local protocol behaviors. Realized skeletons contain enough local sessions to explain all the behavior, when combined with some possible adversary behaviors. We show two results. (1) If phi is the antecedent of a security goal, then there is a skeleton A_phi such that, for every skeleton B, phi is satisfied in B iff there is a homomorphism from A_phi to B. (2) A protocol enforces for all xs . (phi implies for some ys . psi) iff every realized homomorphic image of A_phi satisfies psi. Hence, to verify a security goal, one can use the Cryptographic Protocol Shapes Analyzer CPSA (TACAS, 2007) to identify minimal realized skeletons, or "shapes," that are homomorphic images of A_phi. If psi holds in each of these shapes, then the goal holds

Inactivation of the particulate methane monooxygenase (pMMO) in Methylococcus capsulatus (Bath) by acetylene

Acetylene (HCCH) has a long history as a mechanism-based enzyme inhibitor and is considered an active-site probe of the particulate methane monooxygenase (pMMO). Here, we report how HCCH inactivates pMMO in Methylococcus capsulatus (Bath) by using high-resolution mass spectrometry and computational simulation. High-resolution MALDI-TOF MS of intact pMMO complexes has allowed us to confirm that the enzyme oxidizes HCCH to the ketene (C_2H_2O) intermediate, which then forms an acetylation adduct with the transmembrane PmoC subunit. LC-MS/MS analysis of the peptides derived from in-gel proteolytic digestion of the protein subunit identifies K196 of PmoC as the site of acetylation. No evidence is obtained for chemical modification of the PmoA or PmoB subunit. The inactivation of pMMO by a single adduct in the transmembrane PmoC domain is intriguing given the complexity of the structural fold of this large membrane-protein complex as well as the complicated roles played by the various metal cofactors in the enzyme catalysis. Computational studies suggest that the entry of hydrophobic substrates to, and migration of products from, the catalytic site of pMMO is controlled tightly within the transmembrane domain. Support of these conclusions is provided by parallel experiments with two related alkynes: propyne (CH3CCH) and trifluoropropyne (CF_3CCH). Finally, we discuss the implication of these findings to the location of the catalytic site in pMMO

Image reconstruction using the fictitious time integration method (FTIM)

In this study, we adopt the fictitious time integration method to treat the image reconstruction problem. The distorted image is considered as a result of diffused data from the initial perfect image by using a nonlinear diffusion equation. The image reconstruction problem then becomes an inverse problem by using the data in the final time to recover the data in the initial time. This inverse problem is known as the backward in time nonlinear diffusion problem which is highly ill-posed. We propose to use the fictitious time integration method to tackle this highly ill-posed image reconstruction problem and it is found that the proposed method can obtain very accurate results and even has good noise resistance. Five numerical examples are provided to show the validity of the current approach and they all show the present method is appropriate to deal with the image reconstruction problem

Solving the Cauchy Problem of the Nonlinear Steady-state Heat Equation Using Double Iteration Process

In this paper, the Cauchy inverse problem of the nonlinear steady-state heat equation is studied. The double iteration process is used to tackle this problem in which the outer loop is developed based on the residual norm based algorithm (RNBA) while the inner loop determines the evolution direction and the modified Tikhonov's regularization method (MTRM) developed by Liu (Liu, 2012) is adopted. For the conventional iteration processes, a fixed evolution direction such as F, B−1F, BTF or αF+(1-α)BTF is used where F is the residual vector, B is the Jacobian matrix, the superscript '-1' denotes the inverse, the superscript 'T' denotes the transpose of a matrix and α denotes the optimal coefficient. Unlike the conventional approaches, the current approach tries to find an appropriate direction from the initial guess BTF using the MTRM and the final evolution direction is determined once the value of a0 is less than the critical value ac. Since it may consume too much computation time for searching this appropriate evolution direction such that it makes this process computationally noneconomic, we terminate the inner iteration process as well as the whole process once the number of the iteration steps for the inner iteration exceeds a given maximum value, says Imax. Six examples are illustrated to show the validity of the current approach and results show that the proposed method is very efficient and accurate

Smooth Loops and Fiber Bundles: Theory of Principal Q-bundles

A nonassociative generalization of the principal fiber bundles with a smooth loop mapping on the fiber is presented. Our approach allows us to construct a new kind of gauge theories that involve higher ''nonassociative'' symmetries.Comment: 20 page

Specific, sensitive and rapid detection of human plasmodium knowlesi infection by loop-mediated isothermal amplification (LAMP) in blood samples

<p>Abstract</p> <p>Background</p> <p>The emergence of <it>Plasmodium knowlesi </it>in humans, which is in many cases misdiagnosed by microscopy as <it>Plasmodium malariae </it>due to the morphological similarity has contributed to the needs of detection and differentiation of malaria parasites. At present, nested PCR targeted on <it>Plasmodium </it>ssrRNA genes has been described as the most sensitive and specific method for Plasmodium detection. However, this method is costly and requires trained personnel for its implementation. Loop-mediated isothermal amplification (LAMP), a novel nucleic acid amplification method was developed for the clinical detection of <it>P. knowlesi</it>. The sensitivity and specificity of LAMP was evaluated in comparison to the results obtained via microscopic examination and nested PCR.</p> <p>Methods</p> <p>LAMP assay was developed based on <it>P. knowlesi </it>genetic material targeting the apical membrane antigen-1 (AMA-1) gene. The method uses six primers that recognize eight regions of the target DNA and it amplifies DNA within an hour under isothermal conditions (65°C) in a water-bath.</p> <p>Results</p> <p>LAMP is highly sensitive with the detection limit as low as ten copies for AMA-1. LAMP detected malaria parasites in all confirm cases (n = 13) of <it>P. knowlesi </it>infection (sensitivity, 100%) and none of the negative samples (specificity, 100%) within an hour. LAMP demonstrated higher sensitivity compared to nested PCR by successfully detecting a sample with very low parasitaemia (< 0.01%).</p> <p>Conclusion</p> <p>With continuous efforts in the optimization of this assay, LAMP may provide a simple and reliable test for detecting <it>P. knowlesi </it>malaria parasites in areas where malaria is prevalent.</p