Cosmological Constraints from Galaxy Clustering and the Mass-to-Number Ratio of Galaxy Clusters: Marginalizing over the Physics of Galaxy Formation

Many approaches to obtaining cosmological constraints rely on the connection between galaxies and dark matter. However, the distribution of galaxies is dependent on their formation and evolution as well as the cosmological model, and galaxy formation is still not a well-constrained process. Thus, methods that probe cosmology using galaxies as a tracer for dark matter must be able to accurately estimate the cosmological parameters without knowing the details of galaxy formation a priori. We apply this reasoning to the method of obtaining $\Omega_m$ and $\sigma_8$ from galaxy clustering combined with the mass-to-number ratio of galaxy clusters. To test the sensitivity of this method to variations due to galaxy formation, we consider several different models applied to the same cosmological dark matter simulation. The cosmological parameters are then estimated using the observables in each model, marginalizing over the parameters of the Halo Occupation Distribution (HOD). We find that for models where the galaxies can be well represented by a parameterized HOD, this method can successfully extract the desired cosmological parameters for a wide range of galaxy formation prescriptions.Comment: 10 pages, 7 figures, Submitted to Ap

Enhancing microRNA167A expression in seed decreases the α-linolenic acid content and increases seed size in Camelina sativa.

Despite well established roles of microRNAs in plant development, few aspects have been addressed to understand their effects in seeds especially on lipid metabolism. In this study, we showed that overexpressing microRNA167A (miR167OE) in camelina (Camelina sativa) under a seed-specific promoter changed fatty acid composition and increased seed size. Specifically, the miR167OE seeds had a lower α-linolenic acid with a concomitantly higher linoleic acid content than the wild-type. This decreased level of fatty acid desaturation corresponded to a decreased transcriptional expression of the camelina fatty acid desaturase3 (CsFAD3) in developing seeds. MiR167 targeted the transcription factor auxin response factor (CsARF8) in camelina, as had been reported previously in Arabidopsis. Chromatin immunoprecipitation experiments combined with transcriptome analysis indicated that CsARF8 bound to promoters of camelina bZIP67 and ABI3 genes. These transcription factors directly or through the ABI3-bZIP12 pathway regulate CsFAD3 expression and affect α-linolenic acid accumulation. In addition, to decipher the miR167A-CsARF8 mediated transcriptional cascade for CsFAD3 suppression, transcriptome analysis was conducted to implicate mechanisms that regulate seed size in camelina. Expression levels of many genes were altered in miR167OE, including orthologs that have previously been identified to affect seed size in other plants. Most notably, genes for seed coat development such as suberin and lignin biosynthesis were down-regulated. This study provides valuable insights into the regulatory mechanism of fatty acid metabolism and seed size determination, and suggests possible approaches to improve these important traits in camelina

Asymmetry in crystal facet dynamics of homoepitaxy by a continuum model

In the absence of external material deposition, crystal surfaces usually relax to become flat by decreasing their free energy. We study an asymmetry in the relaxation of macroscopic plateaus, facets, of a periodic surface corrugation in 1+1 dimensions via a continuum model below the roughening transition temperature. The model invokes a highly degenerate parabolic partial differential equation (PDE) for surface diffusion, which is related to the weighted-$H^{-1}$ (nonlinear) gradient flow of a convex, singular surface free energy in homoepitaxy. The PDE is motivated both by an atomistic broken-bond model and a mesoscale model for steps. By constructing an explicit solution to the PDE, we demonstrate the lack of symmetry in the evolution of top and bottom facets in periodic surface profiles. Our explicit, analytical solution is compared to numerical simulations of the PDE via a regularized surface free energy.Comment: 23 pages, 5 figures, comments welcome! Text slightly modified, references updated in Version 2. Referee comments addresse

Memory-Based High-Level Synthesis Optimizations Security Exploration on the Power Side-Channel

High-level synthesis (HLS) allows hardware designers to think algorithmically and not worry about low-level, cycle-by-cycle details. This provides the ability to quickly explore the architectural design space and tradeoffs between resource utilization and performance. Unfortunately, security evaluation is not a standard part of the HLS design flow. In this article, we aim to understand the effects of memory-based HLS optimizations on power side-channel leakage. We use Xilinx Vivado HLS to develop different cryptographic cores, implement them on a Spartan-6 FPGA, and collect power traces. We evaluate the designs with respect to resource utilization, performance, and information leakage through power consumption. We have two important observations and contributions. First, the choice of resource optimization directive results in different levels of side-channel vulnerabilities. Second, the partitioning optimization directive can greatly compromise the hardware cryptographic system through power side-channel leakage due to the deployment of memory control logic. We describe an evaluation procedure for power side-channel leakage and use it to make best-effort recommendations about how to design more secure architectures in the cryptographic domain

Calibration of a superconducting transformer by measuring critical current of a NbTi Rutherford cable

Large high field superconducting magnets often requires high current superconducting cables. In order to develop these cables, a facility capable of providing high magnetic field with large sampling area as well as electrical current of tens of kA is essential. A superconducting transformer is an energy-efficient and low-cost way to provide large current to superconducting cables. Previously, we co-developed a superconducting transformer and successfully tested it to a maximum output current of 45 kA in zero magnetic field. In this work, this superconducting transformer is installed to the 12 T split solenoid magnet at the National High Magnetic Field Laboratory (NHMFL). We calibrated it by using this facility to measure critical current of a NbTi Rutherford cable as a function of magnetic field up to 10 T, and compare the results with those available in the literature. In addition, a strand extracted from the NbTi cable is tested for critical current. The critical current of the extracted strand is scaled and compared with critical current of the cable. The accuracy of the critical current measurement using this superconducting transformer is discussed in detail. This work concludes the commissioning of this superconducting transformer which combined with the 12 T split magnet will provide unique cable testing capability for future cable development for the NHMFL and its users.Comment: 11 pages, 9 figure

Analysis on binary responses with ordered covariates and missing data

We consider the situation of two ordered categorical variables and a binary outcome variable, where one or both of the categorical variables may have missing values. The goal is to estimate the probability of response of the outcome variable for each cell of the contingency table of categorical variables while incorporating the fact that the categorical variables are ordered. The probability of response is assumed to change monotonically as each of the categorical variables changes level. A probability model is used in which the response is binomial with parameters p ij for each cell ( i , j ) and the number of observations in each cell is multinomial. Estimation approaches that incorporate Gibbs sampling with order restrictions on p ij induced via a prior distribution, two-dimensional isotonic regression and multiple imputation to handle missing values are considered. The methods are compared in a simulation study. Using a fully Bayesian approach with a strong prior distribution to induce ordering can lead to large gains in efficiency, but can also induce bias. Utilizing isotonic regression can lead to modest gains in efficiency, while minimizing bias and guaranteeing that the order constraints are satisfied. A hybrid of isotonic regression and Gibbs sampling appears to work well across a variety of scenarios. The methods are applied to a pancreatic cancer case–control study with two biomarkers. Copyright © 2007 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56130/1/2815_ftp.pd