ExtSym: a program to aid space-group determination from powder diffraction data

Once unit-cell dimensions have been determined from a powder diffraction data set and therefore the crystal system is known (e.g. orthorhombic), the method presented by Markvardsen, David, Johnson & Shankland [Acta Cryst. (2001), A57, 47-54] can be used to generate a table ranking the extinction symbols of the given crystal system according to probability. Markvardsen et al. tested a computer program (ExtSym) implementing the method against Pawley refinement outputs generated using the TF12LS program [David, Ibberson & Matthewman (1992). Report RAL-92-032. Rutherford Appleton Laboratory, Chilton, Didcot, Oxon, UK]. Here, it is shown that ExtSym can be used successfully with many well known powder diffraction analysis packages, namely DASH [David, Shankland, van de Streek, Pidcock, Motherwell & Cole (2006). J. Appl. Cryst. 39, 910-915], FullProf [Rodriguez-Carvajal (1993). Physica B, 192, 55-69], GSAS [Larson & Von Dreele (1994). Report LAUR 86-748. Los Alamos National Laboratory, New Mexico, USA], PRODD [Wright (2004). Z. Kristallogr. 219, 1-11] and TOPAS [Coelho (2003). Bruker AXS GmbH, Karlsruhe, Germany]. In addition, a precise description of the optimal input for ExtSym is given to enable other software packages to interface with ExtSym and to allow the improvement/modification of existing interfacing scripts. ExtSym takes as input the powder data in the form of integrated intensities and error estimates for these intensities. The output returned by ExtSym is demonstrated to be strongly dependent on the accuracy of these error estimates and the reason for this is explained. ExtSym is tested against a wide range of data sets, confirming the algorithm to be very successful at ranking the published extinction symbol as the most likely. (C) 2008 International Union of Crystallography Printed in Singapore - all rights reserved.

Optimization of a sea ice model using basinwide observations of Arctic sea ice thickness, extent, and velocity

A stand-alone sea ice model is tuned and validated using satellite-derived, basinwide observations of sea ice thickness, extent, and velocity from the years 1993 to 2001. This is the first time that basin-scale measurements of sea ice thickness have been used for this purpose. The model is based on the CICE sea ice model code developed at the Los Alamos National Laboratory, with some minor modifications, and forcing consists of 40-yr ECMWF Re-Analysis (ERA-40) and Polar Exchange at the Sea Surface (POLES) data. Three parameters are varied in the tuning process: Ca, the air–ice drag coefficient; P*, the ice strength parameter; and α, the broadband albedo of cold bare ice, with the aim being to determine the subset of this three-dimensional parameter space that gives the best simultaneous agreement with observations with this forcing set. It is found that observations of sea ice extent and velocity alone are not sufficient to unambiguously tune the model, and that sea ice thickness measurements are necessary to locate a unique subset of parameter space in which simultaneous agreement is achieved with all three observational datasets.

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

The dynamical state of galaxy groups and their luminosity content

We analyse the dependence of the luminosity function (LF) of galaxies in groups on group dynamical state. We use the Gaussianity of the velocity distribution of galaxy members as a measurement of the dynamical equilibrium of groups identified in the Sloan Digital Sky Survey Data Release 7 by Zandivarez & Martinez. We apply the Anderson-Darling goodness-of-fit test to distinguish between groups according to whether they have Gaussian or non-Gaussian velocity distributions, i.e. whether they are relaxed or not. For these two subsamples, we compute the (0.1)r-band LF as a function of group virial mass and group total luminosity. For massive groups, , we find statistically significant differences between the LF of the two subsamples: the LFs of groups that have Gaussian velocity distributions have a brighter characteristic absolute magnitude (similar to 0.3 mag) and a steeper faint-end slope (similar to 0.25). We detect a similar effect when comparing the LF of bright [M-0.1r(group) - 5log(h) < -23.5] Gaussian and non-Gaussian groups. Our results indicate that, for massive/luminous groups, the dynamical state of the system is directly related to the luminosity of its galaxy members.

THE SLOAN DIGITAL SKY SURVEY CO-ADD: A GALAXY PHOTOMETRIC REDSHIFT CATALOG

We present and describe a catalog of galaxy photometric redshifts (photo-z) for the Sloan Digital Sky Survey (SDSS) Co-add Data. We use the artificial neural network (ANN) technique to calculate the photo-z and the nearest neighbor error method to estimate photo-z errors for similar to 13 million objects classified as galaxies in the co-add with r < 24.5. The photo-z and photo-z error estimators are trained and validated on a sample of similar to 83,000 galaxies that have SDSS photometry and spectroscopic redshifts measured by the SDSS Data Release 7 (DR7), the Canadian Network for Observational Cosmology Field Galaxy Survey, the Deep Extragalactic Evolutionary Probe Data Release 3, the VIsible imaging Multi-Object Spectrograph-Very Large Telescope Deep Survey, and the WiggleZ Dark Energy Survey. For the best ANN methods we have tried, we find that 68% of the galaxies in the validation set have a photo-z error smaller than sigma(68) = 0.031. After presenting our results and quality tests, we provide a short guide for users accessing the public data.

The cyclotron production and nuclear imaging of bromine-77

In this investigation, bromine-77 was produced with a medical cyclotron and imaged with gamma cameras. Br-77 emits a 240 kev photon with a half life of 56 hours. The C-Br bond is stronger than the C-I bond and bromine is not collected in the thyroid. Bromine can be used to label many organic molecules by methods analogous to radioiodination. The only North American source of Br-77 in the 70's and 80's was Los Alamos National Laboratory, but it discontinued production in 1989. In this method, a p,3n reaction on Br-77 produces Kr-77 which decays with a 1.2 hour half life to Br-77. A cyclotron generated 40 MeV proton beam is incident on a nearly saturated NaBr or LiBr solution contained in a copper or titanium target. A cooling chamber through which helium gas is flowed separates the solution from the cyclotron beam line. Helium gas is also flowed through the solution to extract Kr-77 gas. The mixture flows through a nitrogen trap where Kr-77 freezes and is allowed to decay to Br-77. Eight production runs were performed, three with a copper target and five with a titanium target with yields of 40, 104, 180, 679, 1080, 685, 762 and 118 uCi respectively. Gamma ray spectroscopy has shown the product to be very pure, however corrosion has been a major obstacle, causing the premature retirement of the copper target. Phantom and in-vivo rat nuclear images, and an autoradiograph in a rat are presented. The quality of the nuclear scans is reasonable and the autoradiograph reveals high isotope uptake in the renal parenchyma, a more moderate but uniform uptake in pulmonary and hepatic tissue, and low soft tissue uptake. There is no isotope uptake in the brain or the gastric mucosa. ^

The Hansen-Roach cross sections : a graphical representation /

"October 1988."