Ammonia uptake and release in the MnX₂–NH₃ (X = Cl, Br) systems and structure of the Mn(NH₃)nX₂ (n = 6, 2) ammines

Hexa-ammine complexes, Mn(NH<sub>3</sub>)<sub>6</sub>X<sub>2</sub> (X = Cl, Br), have been synthesized by ammoniation of the corresponding transition metal halide and characterized by Powder X-ray diffraction (PXRD) and Raman spectroscopy. The hexa-ammine complexes are isostructural (Cubic,Fm-3m, Z = 4; a = 10.2742(6) Å and 10.527(1) Å for X = Cl, Br respectively). Temperature programmed desorption (TPD) demonstrated that ammonia release from Mn(NH<sub>3</sub>)<sub>6</sub>X<sub>2</sub> complexes occurred in three stages corresponding to the release of 4, 1 and 1 NH<sub>3</sub> equivalents respectively. The chloride and bromide both exhibit a deammoniation onset temperature below 323 K. The di-ammoniates from the first desorption step were isolated during TPD measurements and their crystal structures determined by Rietveld refinement against PXRD data (X = Cl: orthorhombicCmmm, a = 8.1991(9) Å, b = 8.2498(7) Å, c = 3.8212(4) Å, Z = 2; X = Br: orthorhombic Pbam, a = 6.0109(5) Å, b = 12.022(1) Å, c = 4.0230(2) Å, Z= 2)

Space-Varying Coefficient Models for Brain Imaging

The methodological development and the application in this paper originate from diffusion tensor imaging (DTI), a powerful nuclear magnetic resonance technique enabling diagnosis and monitoring of several diseases as well as reconstruction of neural pathways. We reformulate the current analysis framework of separate voxelwise regressions as a 3d space-varying coefficient model (VCM) for the entire set of DTI images recorded on a 3d grid of voxels. Hence by allowing to borrow strength from spatially adjacent voxels, to smooth noisy observations, and to estimate diffusion tensors at any location within the brain, the three-step cascade of standard data processing is overcome simultaneously. We conceptualize two VCM variants based on B-spline basis functions: a full tensor product approach and a sequential approximation, rendering the VCM numerically and computationally feasible even for the huge dimension of the joint model in a realistic setup. A simulation study shows that both approaches outperform the standard method of voxelwise regressions with subsequent regularization. Due to major efficacy, we apply the sequential method to a clinical DTI data set and demonstrate the inherent ability of increasing the rigid grid resolution by evaluating the incorporated basis functions at intermediate points. In conclusion, the suggested fitting methods clearly improve the current state-of-the-art, but ameloriation of local adaptivity remains desirable

Abstraction in directed model checking

Abstraction is one of the most important issues to cope with large and infinite state spaces in model checking and to reduce the verification efforts. The abstract system is smaller than the original one and if the abstract system satisfies a correctness specification, so does the concrete one. However, abstractions may introduce a behavior violating the specification that is not present in the original system. This paper bypasses this problem by proposing the combination of abstraction with heuristic search to improve error detection. The abstract system is explored in order to create a database that stores the exact distances from abstract states to the set of abstract error states. To check, whether or not the abstract behavior is present in the original system, effcient exploration algorithms exploit the database as a guidance

Physicochemical study of solid Cyclodextrin inclusion complexes of the antithrombotic Ajoene

Includes bibliographical references.This study describes the preparation and physicochemical characterization of inclusion complexes formed between selected cyclodextrins (CDs) and ajoene, an antlthrombotlc found in garlic. The E and Z isomers of ajoene (4,5,9,-trithiadodeca-1,6,11-triene-9-oxide) were reacted with α, β, γ-CD heptakis(2,6-di-O-methyl )-β-CD (DIMEB) and heptakls(2, 3, 6-tri-O-methyl )-β-CD (TRIMEB) to yield inclusion compounds α-CD·(E)-ajoene (1), α-CD·(Z)ajoene (2), β-CD·(E)-ajoene (3), β-CD·(Z)-ajoene (4), y-CD·(E)-ajoene (5), y-CD·(Z)-ajoene (6), DIMEB·(E)-ajoene (7), DIMEB·(Z)-ajoene (6), TRIMEB·(E)-ajoene·05H20 (9) and TRIMEB·(Z)-ajoene (10)

Computing economic equilibria by variable dimension algorithms: State of the art

Economics