Classification of minimal actions of a compact Kac algebra with amenable dual

We show the uniqueness of minimal actions of a compact Kac algebra with amenable dual on the AFD factor of type II$_1$. This particularly implies the uniqueness of minimal actions of a compact group. Our main tools are a Rohlin type theorem, the 2-cohomology vanishing theorem, and the Evans-Kishimoto type intertwining argument.Comment: 68 pages, Introduction rewritten; minor correction

Extracting the Groupwise Core Structural Connectivity Network: Bridging Statistical and Graph-Theoretical Approaches

Finding the common structural brain connectivity network for a given population is an open problem, crucial for current neuro-science. Recent evidence suggests there's a tightly connected network shared between humans. Obtaining this network will, among many advantages , allow us to focus cognitive and clinical analyses on common connections, thus increasing their statistical power. In turn, knowledge about the common network will facilitate novel analyses to understand the structure-function relationship in the brain. In this work, we present a new algorithm for computing the core structural connectivity network of a subject sample combining graph theory and statistics. Our algorithm works in accordance with novel evidence on brain topology. We analyze the problem theoretically and prove its complexity. Using 309 subjects, we show its advantages when used as a feature selection for connectivity analysis on populations, outperforming the current approaches

Construction of wedge-local nets of observables through Longo-Witten endomorphisms. II

In the first part, we have constructed several families of interacting wedge-local nets of von Neumann algebras. In particular, there has been discovered a family of models based on the endomorphisms of the U(1)-current algebra of Longo-Witten. In this second part, we further investigate endomorphisms and interacting models. The key ingredient is the free massless fermionic net, which contains the U(1)-current net as the fixed point subnet with respect to the U(1) gauge action. Through the restriction to the subnet, we construct a new family of Longo-Witten endomorphisms on the U(1)-current net and accordingly interacting wedge-local nets in two-dimensional spacetime. The U(1)-current net admits the structure of particle numbers and the S-matrices of the models constructed here do mix the spaces with different particle numbers of the bosonic Fock space.Comment: 33 pages, 1 tikz figure. The final version is available under Open Access. CC-B

Ground state representations of loop algebras

Let g be a simple Lie algebra, Lg be the loop algebra of g. Fixing a point in S^1 and identifying the real line with the punctured circle, we consider the subalgebra Sg of Lg of rapidly decreasing elements on R. We classify the translation-invariant 2-cocycles on Sg. We show that the ground state representation of Sg is unique for each cocycle. These ground states correspond precisely to the vacuum representations of Lg.Comment: 22 pages, no figur

Suicide and suicide prevention in Asia

Access the book via http://www.who.int/mental_health/resources/suicide_prevention_asia.pd

Magnetoelastic effects in Jahn-Teller distorted CrF2_2 and CuF2_2 studied by neutron powder diffraction

We have studied the temperature dependence of crystal and magnetic structures of the Jahn-Teller distorted transition metal difluorides CrF$_2$ and CuF$_2$ by neutron powder diffraction in the temperature range 2-280 K. The lattice parameters and the unit cell volume show magnetoelastic effects below the N\'eel temperature. The lattice strain due to the magnetostriction effect couples with the square of the order parameter of the antiferromagnetic phase transition. We also investigated the temperature dependence of the Jahn-Teller distortion which does not show any significant effect at the antiferromagnetic phase transition but increases linearly with increasing temperature for CrF$_2$ and remains almost independent of temperature in CuF$_2$. The magnitude of magnetovolume effect seems to increase with the low temperature saturated magnetic moment of the transition metal ions but the correlation is not at all perfect

Twisted duality of the CAR-Algebra

We give a complete proof of the twisted duality property M(q)'= Z M(q^\perp) Z* of the (self-dual) CAR-Algebra in any Fock representation. The proof is based on the natural Halmos decomposition of the (reference) Hilbert space when two suitable closed subspaces have been distinguished. We use modular theory and techniques developed by Kato concerning pairs of projections in some essential steps of the proof. As a byproduct of the proof we obtain an explicit and simple formula for the graph of the modular operator. This formula can be also applied to fermionic free nets, hence giving a formula of the modular operator for any double cone.Comment: 32 pages, Latex2e, to appear in Journal of Mathematical Physic

Lattice dynamics and structural stability of ordered Fe3Ni, Fe3Pd and Fe3Pt alloys

We investigate the binding surface along the Bain path and phonon dispersion relations for the cubic phase of the ferromagnetic binary alloys Fe3X (X = Ni, Pd, Pt) for L12 and DO22 ordered phases from first principles by means of density functional theory. The phonon dispersion relations exhibit a softening of the transverse acoustic mode at the M-point in the L12-phase in accordance with experiments for ordered Fe3Pt. This instability can be associated with a rotational movement of the Fe-atoms around the Ni-group element in the neighboring layers and is accompanied by an extensive reconstruction of the Fermi surface. In addition, we find an incomplete softening in [111] direction which is strongest for Fe3 Ni. We conclude that besides the valence electron density also the specific Fe-content and the masses of the alloying partners should be considered as parameters for the design of Fe-based functional magnetic materials.Comment: Revised version, accepted for publication in Physical Review

Visuoperception test predicts pathologic diagnosis of Alzheimer disease in corticobasal syndrome

OBJECTIVE: To use the Visual Object and Space Perception Battery (VOSP) to distinguish Alzheimer disease (AD) from non-AD pathology in corticobasal syndrome (CBS). METHODS: This clinicopathologic study assessed 36 patients with CBS on the VOSP. All were autopsied. The primary dependent variable was a binary pathologic outcome: patients with CBS who had primary pathologic diagnosis of AD (CBS-AD, n = 10) vs patients with CBS without primary pathologic diagnosis of AD (CBS-nonAD, n = 26). We also determined sensitivity and specificity of individual VOSP subtests. RESULTS: Patients with CBS-AD had younger onset (54.5 vs 63.6 years, p = 0.001) and lower memory scores on the Mattis Dementia Rating Scale-2 (16 vs 22 points, p = 0.003). Failure on the VOSP subtests Incomplete Letters (odds ratio [OR] 11.5, p = 0.006), Position Discrimination (OR 10.86, p = 0.008), Number Location (OR 12.27, p = 0.026), and Cube Analysis (OR 45.71 p = 0.0001) had significantly greater odds of CBS-AD than CBS-nonAD. These associations remained when adjusting for total Mattis Dementia Rating score, disease laterality, education, age, and sex. Receiver operating characteristic curves demonstrated significant accuracy for Incomplete Letters and all VOSP spatial subtests, with Cube Analysis performing best (area under the curve 0.91, p = 0.0004). CONCLUSIONS: In patients with CBS, failure on specific VOSP subtests is associated with greater odds of having underlying AD. There may be preferential involvement of the dorsal stream in CBS-AD. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that some subtests of the VOSP accurately distinguish patients with CBS-AD from those without AD pathology (e.g., Cube Analysis sensitivity 100%, specificity 77%)

Estimation of Brain Network Atlases using Diffusive-Shrinking Graphs:Application to Developing Brains

Many methods have been developed to spatially normalize a population of brain images for estimating a mean image as a populationaverage atlas. However, methods for deriving a network atlas from a set of brain networks sitting on a complex manifold are still absent. Learning how to average brain networks across subjects constitutes a key step in creating a reliable mean representation of a population of brain networks, which can be used to spot abnormal deviations from the healthy network atlas. In this work, we propose a novel network atlas estimation framework, which guarantees that the produced network atlas is clean (for tuning down noisy measurements) and well-centered (for being optimally close to all subjects and representing the individual traits of each subject in the population). Specifically, for a population of brain networks, we first build a tensor, where each of its frontal-views (i.e., frontal matrices) represents a connectivity network matrix of a single subject in the population. Then, we use tensor robust principal component analysis for jointly denoising all subjects’ networks through cleaving a sparse noisy network population tensor from a clean low-rank network tensor. Second, we build a graph where each node represents a frontal-view of the unfolded clean tensor (network), to leverage the local manifold structure of these networks when fusing them. Specifically, we progressively shrink the graph of networks towards the centered mean network atlas through non-linear diffusion along the local neighbors of each of its nodes. Our evaluation on the developing functional and morphological brain networks at 1, 3, 6, 9 and 12 months of age has showed a better centeredness of our network atlases, in comparison with the baseline network fusion method. Further cleaning of the population of networks produces even more centered atlases, especially for the noisy functional connectivity networks