Regulation of zinc-responsive Slc39a5 (Zip5) translation is mediated by conserved elements in the 3′-untranslated region

Translation of the basolateral zinc transporter ZIP5 is repressed during zinc deficiency but Zip5 mRNA remains associated with polysomes and can be rapidly translated when zinc is repleted. Herein, we examined the mechanisms regulating translation of Zip5. The 3′-untranslated region (UTR) of Zip5 mRNA is well conserved among mammals and is predicted by mFOLD to form a very stable stem-loop structure. Three algorithms predict this structure to be flanked by repeated seed sites for miR-328 and miR-193a. RNAse footprinting supports the notion that a stable stem-loop structure exists in this 3′-UTR and electrophoretic mobility shift assays detect polysomal protein(s) binding specifically to the stem-loop structure in the Zip5 3′-UTR. miR-328 and miR-193a are expressed in tissues known to regulate Zip5 mRNA translation in response to zinc availability and both are polysome-associated consistent with Zip5 mRNA localization. Transient transfection assays using native and mutant Zip5 3′-UTRs cloned 3′ to luciferase cDNA revealed that the miRNA seed sites and the stem-loop function together to augment translation of Zip5 mRNA when zinc is replete

The Cross-correlation of MgII Absorption and Galaxies in BOSS

We present a measurement of the cross-correlation of MgII absorption and massive galaxies, using the DR11 main galaxy sample of the Baryon Oscillation Spectroscopic Survey of SDSS-III (CMASS galaxies), and the DR7 quasar spectra of SDSS-II. The cross-correlation is measured by stacking quasar absorption spectra shifted to the redshift of galaxies that are within a certain impact parameter bin of the quasar, after dividing by a quasar continuum model. This results in an average MgII equivalent width as a function of impact parameter from a galaxy, ranging from 50 kpc to more than 10 Mpc in proper units, which includes all MgII absorbers. We show that special care needs to be taken to use an unbiased quasar continuum estimator, to avoid systematic errors in the measurement of the mean stacked MgII equivalent width. The measured cross-correlation follows the expected shape of the galaxy correlation function, although measurement errors are large. We use the cross-correlation amplitude to derive the bias factor of MgII absorbers, finding bMgII = 2.33 \pm? 0.19, where the error accounts only for the statistical uncertainty in measuring the mean equivalent width. This bias factor is larger than that obtained in previous studies and may be affected by modeling uncertainties that we discuss, but if correct it suggests that MgII absorbers at redshift z \simeq 0:5 are spatially distributed on large scales similarly to the CMASS galaxies in BOSS. Keywords: galaxies: haloes, galaxies: formation, quasars: absorption lines, large-scale structure of universeComment: Accepted for publication to MNRAS. Accepted 2014 December 12. Received 2014 November 29; in original form 2014 February

Mass growth and mergers: direct observations of the luminosity function of LRG satellite galaxies out to z=0.7 from SDSS and BOSS images

We present a statistical study of the luminosity functions of galaxies surrounding luminous red galaxies (LRGs) at average redshifts =0.34 and =0.65. The luminosity functions are derived by extracting source photometry around more than 40,000 LRGs and subtracting foreground and background contamination using randomly selected control fields. We show that at both studied redshifts the average luminosity functions of the LRGs and their satellite galaxies are poorly fitted by a Schechter function due to a luminosity gap between the centrals and their most luminous satellites. We utilize a two-component fit of a Schechter function plus a log-normal distribution to demonstrate that LRGs are typically brighter than their most luminous satellite by roughly 1.3 magnitudes. This luminosity gap implies that interactions within LRG environments are typically restricted to minor mergers with mass ratios of 1:4 or lower. The luminosity functions further imply that roughly 35% of the mass in the environment is locked in the LRG itself, supporting the idea that mass growth through major mergers within the environment is unlikely. Lastly, we show that the luminosity gap may be at least partially explained by the selection of LRGs as the gap can be reproduced by sparsely sampling a Schechter function. In that case LRGs may represent only a small fraction of central galaxies in similar mass halos.Comment: ApJ accepted versio

Electronic properties of molecular solids: the peculiar case of solid Picene

Recently, a new organic superconductor, K-intercalated Picene with high transition temperatures $T_c$ (up to 18\,K) has been discovered. We have investigated the electronic properties of the undoped relative, solid picene, using a combination of experimental and theoretical methods. Our results provide detailed insight into the occuopied and unoccupied electronic states

Characterizing unknown systematics in large scale structure surveys

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.Comment: 24 pages, 6 figures; Expanded discussion of results, added figure 2; Version to be published in JCA

The Blue Tip of the Stellar Locus: Measuring Reddening with the SDSS

We present measurements of reddening due to dust using the colors of stars in the Sloan Digital Sky Survey (SDSS). We measure the color of main sequence turn-off stars by finding the "blue tip" of the stellar locus: the prominent blue edge in the distribution of stellar colors. The method is sensitive to color changes of order 18, 12, 7, and 8 mmag of reddening in the colors u-g, g-r, r-i, and i-z, respectively, in regions measuring 90' by 14'. We present maps of the blue tip colors in each of these bands over the entire SDSS footprint, including the new dusty southern Galactic cap data provided by the SDSS-III. The results disfavor the best fit O'Donnell (1994) and Cardelli et al. (1989) reddening laws, but are well described by a Fitzpatrick (1999) reddening law with R_V = 3.1. The SFD dust map is found to trace the dust well, but overestimates reddening by factors of 1.4, 1.0, 1.2, and 1.4 in u-g, g-r, r-i, and i-z, largely due to the adopted reddening law. In select dusty regions of the sky, we find evidence for problems in the SFD temperature correction. A dust map normalization difference of 15% between the Galactic north and south sky may be due to these dust temperature errors.Comment: 18 pages, 22 figure

Learning Scheduling Algorithms for Data Processing Clusters

Efficiently scheduling data processing jobs on distributed compute clusters requires complex algorithms. Current systems, however, use simple generalized heuristics and ignore workload characteristics, since developing and tuning a scheduling policy for each workload is infeasible. In this paper, we show that modern machine learning techniques can generate highly-efficient policies automatically. Decima uses reinforcement learning (RL) and neural networks to learn workload-specific scheduling algorithms without any human instruction beyond a high-level objective such as minimizing average job completion time. Off-the-shelf RL techniques, however, cannot handle the complexity and scale of the scheduling problem. To build Decima, we had to develop new representations for jobs' dependency graphs, design scalable RL models, and invent RL training methods for dealing with continuous stochastic job arrivals. Our prototype integration with Spark on a 25-node cluster shows that Decima improves the average job completion time over hand-tuned scheduling heuristics by at least 21%, achieving up to 2x improvement during periods of high cluster load

A Simple Likelihood Method for Quasar Target Selection

We present a new method for quasar target selection using photometric fluxes and a Bayesian probabilistic approach. For our purposes we target quasars using Sloan Digital Sky Survey (SDSS) photometry to a magnitude limit of g=22. The efficiency and completeness of this technique is measured using the Baryon Oscillation Spectroscopic Survey (BOSS) data, taken in 2010. This technique was used for the uniformly selected (CORE) sample of targets in BOSS year one spectroscopy to be realized in the 9th SDSS data release. When targeting at a density of 40 objects per sq-deg (the BOSS quasar targeting density) the efficiency of this technique in recovering z>2.2 quasars is 40%. The completeness compared to all quasars identified in BOSS data is 65%. This paper also describes possible extensions and improvements for this techniqueComment: Updated to accepted version for publication in the Astrophysical Journal. 10 pages, 10 figures, 3 table