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

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

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

Point contact Andreev reflection spectroscopy of NdFeAsO_0.85

The newly discovered oxypnictide family of superconductors show very high critical temperatures of up to 55K. Whilst there is growing evidence that suggests a nodal order parameter, point contact Andreev reflection spectroscopy can provide crucial information such as the gap value and possibly the number of energy gaps involved. For the oxygen deficient NdFeAsO0.85 with a Tc of 45.5K, we show that there is clearly a gap value at 4.2K that is of the order of 7meV, consistent with previous studies on oxypnictides with lower Tc. Additionally, taking the spectra as a function of gold tip contact pressure reveals important changes in the spectra which may be indicative of more complex physics underlying this structure.Comment: 11 pages, 3 figures. New references included, extra discussion. This version is accepted in Superconductor Science and Technolog

Practice Induces Function-Specific Changes in Brain Activity

Practice can have a profound effect on performance and brain activity, especially if a task can be automated. Tasks that allow for automatization typically involve repeated encoding of information that is paired with a constant response. Much remains unknown about the effects of practice on encoding and response selection in an automated task.To investigate function-specific effects of automatization we employed a variant of a Sternberg task with optimized separation of activity associated with encoding and response selection by means of m-sequences. This optimized randomized event-related design allows for model free measurement of BOLD signals over the course of practice. Brain activity was measured at six consecutive runs of practice and compared to brain activity in a novel task.Prompt reductions were found in the entire cortical network involved in encoding after a single run of practice. Changes in the network associated with response selection were less robust and were present only after the third run of practice.This study shows that automatization causes heterogeneous decreases in brain activity across functional regions that do not strictly track performance improvement. This suggests that cognitive performance is supported by a dynamic allocation of multiple resources in a distributed network. Our findings may bear importance in understanding the role of automatization in complex cognitive performance, as increased encoding efficiency in early stages of practice possibly increases the capacity to otherwise interfering information