Flavor Singlet Axial Vector Coupling of the Proton with Dynamical Wilson Fermions

We present the results of a full QCD lattice calculation of the flavor singlet axial vector coupling $G_A^1$ of the proton. The simulation has been carried out on a $16^3\times 32$ lattice at $\beta=5.6$ with $n_f=2$ dynamical Wilson fermions. It turns out that the statistical quality of the connected contribution to $G_A^1$ is excellent, whereas the disconnected part is accessible but suffers from large statistical fluctuations. Using a 1st order tadpole improved renormalization constant $Z_A$, we estimate $G_A^1 = 0.20(12)$.Comment: 13 pages, 5 eps figures, minor changes to text and citation

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods

All-sky search for long-duration gravitational wave transients with initial LIGO

We present the results of a search for long-duration gravitational wave transients in two sets of data collected by the LIGO Hanford and LIGO Livingston detectors between November 5, 2005 and September 30, 2007, and July 7, 2009 and October 20, 2010, with a total observational time of 283.0 days and 132.9 days, respectively. The search targets gravitational wave transients of duration 10-500 s in a frequency band of 40-1000 Hz, with minimal assumptions about the signal waveform, polarization, source direction, or time of occurrence. All candidate triggers were consistent with the expected background; as a result we set 90% confidence upper limits on the rate of long-duration gravitational wave transients for different types of gravitational wave signals. For signals from black hole accretion disk instabilities, we set upper limits on the source rate density between 3.4×10-5 and 9.4×10-4 Mpc-3 yr-1 at 90% confidence. These are the first results from an all-sky search for unmodeled long-duration transient gravitational waves. © 2016 American Physical Society

All-sky search for long-duration gravitational wave transients with initial LIGO

We present the results of a search for long-duration gravitational wave transients in two sets of data collected by the LIGO Hanford and LIGO Livingston detectors between November 5, 2005 and September 30, 2007, and July 7, 2009 and October 20, 2010, with a total observational time of 283.0 days and 132.9 days, respectively. The search targets gravitational wave transients of duration 10-500 s in a frequency band of 40-1000 Hz, with minimal assumptions about the signal waveform, polarization, source direction, or time of occurrence. All candidate triggers were consistent with the expected background; as a result we set 90% confidence upper limits on the rate of long-duration gravitational wave transients for different types of gravitational wave signals. For signals from black hole accretion disk instabilities, we set upper limits on the source rate density between 3.4×10-5 and 9.4×10-4 Mpc-3 yr-1 at 90% confidence. These are the first results from an all-sky search for unmodeled long-duration transient gravitational waves. © 2016 American Physical Society

Synthetische Referenzoele. Referenzoele fuer Waelz- und Gleitlager-, Zahnrad- und Kupplungsversuche Datensammlung fuer Syntheseoele

Available from TIB Hannover: RN 3358(316) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

SHARD: Spherical harmonic-based robust outlier detection for HARDI methods

High Angular Resolution Diffusion Imaging (HARDI) models are used to capture complex intra-voxel microarchitectures. The magnetic resonance imaging sequences that are sensitized to diffusion are often highly accelerated and prone to motion, physiologic, and imaging artifacts. In diffusion tensor imaging, robust statistical approaches have been shown to greatly reduce these adverse factors without human intervention. Similar approaches would be possible with HARDI methods, but robust versions of each distinct HARDI approach would be necessary. To avoid the computational and pragmatic burdens of creating individual robust HARDI analysis variants, we propose a robust outlier imputation model to mitigate outliers prior to traditional HARDI analysis. This model uses a weighted spherical harmonic fit of diffusion weighted magnetic resonance imaging scans to estimate the values which had been corrupted during acquisition to restore them. Briefly, spherical harmonics of 6th order were used to generate basis function which were weighted by diffusion signal for detection of outliers. For validation, a single healthy volunteer was scanned for a single session comprising of two scans one without head movement and the other with deliberate head movement at a b-value of 3000 s/mm2 with 64 diffusion weighted directions with a single b0 (5 averages) per scan. The deliberate motion from the volunteer created natural artifacts in the acquisition of one of the scans. The imputation model shows reduction in root mean squared error of the raw signal intensities and improvement for the HARDI method Q-ball in terms of the Angular Correlation Coefficient. The results reveal that there is quantitative and qualitative improvement. The proposed model can be used as general pre-processing model before implementing any HARDI model in general to restore the artifacts which are created because of the outlier diffusion signal in certain gradient volumes. ?? COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only

Harmonization of white and gray matter features in diffusion microarchitecture for cross-sectional studies

Understanding of the specific processes involved in the development of brain microarchitecture and how these are altered by genetic, cognitive, or environmental factors is a key to more effective and efficient interventions. With the increasing number of publicly available neuroimaging databases, there is an opportunity to combine large-scale imaging studies to increase the power of statistical analyses to test common biological hypotheses. However, cross-study, cross-sectional analyses are confounded by inter-scanner variability that can cause both spatially and anatomically dependent signal aberrations. In particular, scanner-related differences in the diffusion-weighted magnetic resonance imaging (DW-MRI) signal are substantially different in tissue types like cortical/subcortical gray matter and white matter. Recent studies have shown effective harmonization using the ComBat technique (adopted from genomics) to address inter-site variability in white matter using diffusion tensor imaging (DTI) microstructure indices like fractional anisotropy (FA) or mean diffusivity (MD). In this study, we propose (1) to apply the correction at voxel level using tract-based spatial statistics (TBSS) in FA, (2) to correct variability across scanners with different gradient strengths in DTI, and (3) to apply the ComBat technique to advanced DW-MRI models, i.e., neurite orientation dispersion and density imaging (NODDI), to correct for variability of orientation dispersion index (ODI) in gray matter using gray matter-based spatial statistics tool (GSBSS). We show that the biological variability with age is retained or improved while correcting for variability across scanners. ?? Springer Nature Switzerland AG 2019