The Dimension of Subcode-Subfields of Shortened Generalized Reed Solomon Codes

Reed-Solomon (RS) codes are among the most ubiquitous codes due to their good parameters as well as efficient encoding and decoding procedures. However, RS codes suffer from having a fixed length. In many applications where the length is static, the appropriate length can be obtained by an RS code by shortening or puncturing. Generalized Reed-Solomon (GRS) codes are a generalization of RS codes, whose subfield-subcodes are extensively studied. In this paper we show that a particular class of GRS codes produces many subfield-subcodes with large dimension. An algorithm for searching through the codes is presented as well as a list of new codes obtained from this method

Quantum-accelerated constraint programming

Constraint programming (CP) is a paradigm used to model and solve constraint satisfaction and combinatorial optimization problems. In CP, problems are modeled with constraints that describe acceptable solutions and solved with backtracking tree search augmented with logical inference. In this paper, we show how quantum algorithms can accelerate CP, at both the levels of inference and search. Leveraging existing quantum algorithms, we introduce a quantum-accelerated filtering algorithm for the $\texttt{alldifferent}$ global constraint and discuss its applicability to a broader family of global constraints with similar structure. We propose frameworks for the integration of quantum filtering algorithms within both classical and quantum backtracking search schemes, including a novel hybrid classical-quantum backtracking search method. This work suggests that CP is a promising candidate application for early fault-tolerant quantum computers and beyond.Comment: published in Quantu

The diversity and utility of amyloid fibrils formed by short amyloidogenic peptides

Amyloidogenic peptides are well known for their involvement in diseases such as type 2 diabetes and Alzheimer's disease. However, more recently, amyloid fibrils have been shown to provide scaffolding and protection as functional materials in a range of organisms from bacteria to humans. These roles highlight the incredible tensile strength of the cross-β amyloid architecture. Many amino acid sequences are able to self-assemble to form amyloid with a cross-β core. Here we describe our recent advances in understanding how sequence contributes to amyloidogenicity and structure. For example, we describe penta- and hexapeptides that assemble to form different morphologies; a 12mer peptide that forms fibrous crystals; and an eight-residue peptide originating from α-synuclein that has the ability to form nanotubes. This work provides a wide range of peptides that may be exploited as fibrous bionanomaterials. These fibrils provide a scaffold upon which functional groups may be added, or templated assembly may be performed

A Genome-Wide Screen Identifies Genes That Affect Somatic Homolog Pairing in Drosophila

In Drosophila and other Dipterans, homologous chromosomes are in close contact in virtually all nuclei, a phenomenon known as somatic homolog pairing. Although homolog pairing has been recognized for over a century, relatively little is known about its regulation. We performed a genome-wide RNAi-based screen that monitored the X-specific localization of the male-specific lethal (MSL) complex, and we identified 59 candidate genes whose knockdown via RNAi causes a change in the pattern of MSL staining that is consistent with a disruption of X-chromosomal homolog pairing. Using DNA fluorescent in situ hybridization (FISH), we confirmed that knockdown of 17 of these genes has a dramatic effect on pairing of the 359 bp repeat at the base of the X. Furthermore, dsRNAs targeting Pr-set7, which encodes an H4K20 methyltransferase, cause a modest disruption in somatic homolog pairing. Consistent with our results in cultured cells, a classical mutation in one of the strongest candidate genes, pebble (pbl), causes a decrease in somatic homolog pairing in developing embryos. Interestingly, many of the genes identified by our screen have known roles in diverse cell-cycle events, suggesting an important link between somatic homolog pairing and the choreography of chromosomes during the cell cycle

Determination of the Cosmic Distance Scale from Sunyaev-Zel'dovich Effect and Chandra X-ray Measurements of High Redshift Galaxy Clusters

We determine the distance to 38 clusters of galaxies in the redshift range 0.14 < z < 0.89 using X-ray data from Chandra and Sunyaev-Zeldovich Effect data from the Owens Valley Radio Observatory and the Berkeley-Illinois-Maryland Association interferometric arrays. The cluster plasma and dark matter distributions are analyzed using a hydrostatic equilibrium model that accounts for radial variations in density, temperature and abundance, and the statistical and systematic errors of this method are quantified. The analysis is performed via a Markov chain Monte Carlo technique that provides simultaneous estimation of all model parameters. We measure a Hubble constant of 76.9 +3.9-3.4 +10.0-8.0 km/s/Mpc (statistical followed by systematic uncertainty at 68% confidence) for an Omega_M=0.3, Omega_Lambda=0.7 cosmology. We also analyze the data using an isothermal beta model that does not invoke the hydrostatic equilibrium assumption, and find H_0=73.7 +4.6-3.8 +9.5-7.6 km/s/Mpc; to avoid effects from cool cores in clusters, we repeated this analysis excluding the central 100 kpc from the X-ray data, and find H_0=77.6 +4.8-4.3 +10.1-8.2 km/s/Mpc. The consistency between the models illustrates the relative insensitivity of SZE/X-ray determinations of H_0 to the details of the cluster model. Our determination of the Hubble parameter in the distant universe agrees with the recent measurement from the Hubble Space Telescope key project that probes the nearby universe.Comment: ApJ submitted (revised version

X-ray and Sunyaev-Zel'dovich Effect Measurements of the Gas Mass Fraction in Galaxy Clusters

We present gas mass fractions of 38 massive galaxy clusters spanning redshifts from 0.14 to 0.89, derived from Chandra X-ray data and OVRO/BIMA interferometric Sunyaev-Zel'dovich Effect measurements. We use three models for the gas distribution: (1) an isothermal beta-model fit jointly to the X-ray data at radii beyond 100 kpc and to all of the SZE data,(2) a non-isothermal double beta-model fit jointly to all of the X-ray and SZE data, and (3) an isothermal beta-model fit only to the SZE spatial data. We show that the simple isothermal model well characterizes the intracluster medium (ICM) outside of the cluster core in clusters with a wide range of morphological properties. The X-ray and SZE determinations of mean gas mass fractions for the 100 kpc-cut isothermal beta-model are fgas(X-ray)=0.110 +0.003-0.003 +0.006-0.018 and fgas(SZE)=0.116 +0.005-0.005 +0.009-0.026, where uncertainties are statistical followed by systematic at 68% confidence. For the non-isothermal double beta-model, fgas(X-ray)=0.119 +0.003-0.003 +0.007-0.014 and fgas(SZE)=0.121 +0.005-0.005 +0.009-0.016. For the SZE-only model, fgas(SZE)=0.120 +0.009-0.009 +0.009-0.027. Our results indicate that the ratio of the gas mass fraction within r2500 to the cosmic baryon fraction is 0.68 +0.10-0.16 where the range includes statistical and systematic uncertainties. By assuming that cluster gas mass fractions are independent of redshift, we find that the results are in agreement with standard LambdaCDM cosmology and are inconsistent with a flat matter dominated universe.Comment: ApJ, submitted. 47 pages, 5 figures, 8 table

The Value of End-Use Energy Efficiency in Mitigation of U.S. Carbon Emissions

This report documents a scenario analysis exploring the value of advanced technologies in the U.S. buildings, industrial, and transportation sectors in stabilizing atmospheric greenhouse gas concentrations. The analysis was conducted by staff members of Pacific Northwest National Laboratory (PNNL), working at the Joint Global Change Research Institute (JGCRI) in support of the strategic planning process of the U.S. Department of Energy (U.S. DOE) Office of Energy Efficiency and Renewable Energy (EERE). The conceptual framework for the analysis is an integration of detailed buildings, industrial, and transportation modules into MiniCAM, a global integrated assessment model. The analysis is based on three technology scenarios, which differ in their assumed rates of deployment of new or presently available energy-saving technologies in the end-use sectors. These technology scenarios are explored with no carbon policy, and under two CO2 stabilization policies, in which an economic price on carbon is applied such that emissions follow prescribed trajectories leading to long-term stabilization of CO2 at roughly 450 and 550 parts per million by volume (ppmv). The costs of meeting the emissions targets prescribed by these policies are examined, and compared between technology scenarios. Relative to the reference technology scenario, advanced technologies in all three sectors reduce costs by 50% and 85% for the 450 and 550 ppmv policies, respectively. The 450 ppmv policy is more stringent and imposes higher costs than the 550 ppmv policy; as a result, the magnitude of the economic value of energy efficiency is four times greater for the 450 ppmv policy than the 550 ppmv policy. While they substantially reduce the costs of meeting emissions requirements, advanced end-use technologies do not lead to greenhouse gas stabilization without a carbon policy. This is due mostly to the effects of increasing service demands over time, the high consumption of fossil fuels in the electricity sector, and the use of unconventional feedstocks in the liquid fuel refining sector. Of the three end-use sectors, advanced transportation technologies have the greatest potential to reduce costs of meeting carbon policy requirements. Services in the buildings and industrial sectors can often be supplied by technologies that consume low-emissions fuels such as biomass or, in policy cases, electricity. Passenger transportation, in contrast, is especially unresponsive to climate policies, as the fuel costs are small compared to the time value of transportation and vehicle capital and operating costs. Delaying the transition from reference to advanced technologies by 15 years increases the costs of meeting 450 ppmv stabilization emissions requirements by 21%, but the costs are still 39% lower than the costs assuming reference technology. The report provides a detailed description of the end-use technology scenarios and provides a thorough analysis of the results. Assumptions are documented in the Appendix

The architecture of amyloid-like peptide fibrils revealed by X-ray scattering, diffraction and electron microscopy

Structural analysis of protein fibrillation is inherently challenging. Given the crucial role of fibrils in amyloid diseases, method advancement is urgently needed. A hybrid modelling approach is presented enabling detailed analysis of a highly ordered and hierarchically organized fibril of the GNNQQNY peptide fragment of a yeast prion protein. Data from small-angle X-ray solution scattering, fibre diffraction and electron microscopy are combined with existing high-resolution X-ray crystallographic structures to investigate the fibrillation process and the hierarchical fibril structure of the peptide fragment. The elongation of these fibrils proceeds without the accumulation of any detectable amount of intermediate oligomeric species, as is otherwise reported for, for example, glucagon, insulin and [alpha]-synuclein. Ribbons constituted of linearly arranged protofilaments are formed. An additional hierarchical layer is generated via the pairing of ribbons during fibril maturation. Based on the complementary data, a quasi-atomic resolution model of the protofilament peptide arrangement is suggested. The peptide structure appears in a [beta]-sheet arrangement reminiscent of the [beta]-zipper structures evident from high-resolution crystal structures, with specific differences in the relative peptide orientation. The complexity of protein fibrillation and structure emphasizes the need to use multiple complementary methods

Sunyaev-Zel'dovich Effect Imaging of Massive Clusters of Galaxies at Redshift z > 0.8

We present Sunyaev-Zel'dovich Effect (SZE) imaging observations of three distant (z > 0.8) and highly X-ray luminous clusters of galaxies, Cl1226+33, Cl0152-13 and MS1054-03. Two of the clusters, Cl1226+33 and Cl0152-13, were recently discovered in deep ROSAT x-ray images. Their high X-ray luminosity suggests that they are massive systems which, if confirmed, would provide strong constraints on the cosmological parameters of structure formation models. Our Sunyaev-Zel'dovich Effect data provide confirmation that they are massive clusters similar to the well studied cluster MS1054-03. Assuming the clusters have the same gas mass fraction as that derived from SZE measurements of eighteen known massive clusters, we are able to infer their mass and electron temperature from the SZE data. The derived electron temperatures are 9.8, 8.7, and 10.4 keV, respectively, and we infer total masses of ~2 x 10^14 h^-1 Msun within a radius of 65 arcsec (340 h^{-1} kpc) for all three clusters. For Cl0152-13 and MS1054-03 we find good agreement between our SZE derived temperatures and those inferred from X-ray spectroscopy. No X-ray derived temperatures are available for Cl1226+33, and thus the SZE data provide the first confirmation that it is indeed a massive system. The demonstrated ability to determine cluster temperatures and masses from SZE observations without access to X-ray data illustrates the power of using deep SZE surveys to probe the distant universe.Comment: 9 pages, 1 figure, accepted for publication in ApJ Letter

Combining biomarker and bulk compositional gradient analysis to assess reservoir connectivity

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Organic Geochemistry 41 (2010): 812-821, doi:10.1016/j.orggeochem.2010.05.003.Hydraulic connectivity of petroleum reservoirs represents one of the biggest uncertainties for both oil production and petroleum system studies. Here, a geochemical analysis involving bulk and detailed measures of crude oil composition is shown to constrain connectivity more tightly than is possible with conventional methods. Three crude oils collected from different depths in a single well exhibit large gradients in viscosity, density, and asphaltene content. Crude oil samples are collected with a wireline sampling tool providing samples from well‐defined locations and relatively free of contamination by drilling fluids; the known provenance of these samples minimizes uncertainties in the subsequent analysis. The detailed chemical composition of almost the entire crude oil is determined by use of comprehensive two‐dimensional gas chromatography (GC×GC) to interrogate the nonpolar fraction and negative ion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT‐ICR MS) to interrogate the polar fraction. The simultaneous presence of 25‐ norhopanes and mildly altered normal and isoprenoid alkanes is detected, suggesting that the reservoir has experienced multiple charges and contains a mixture of oils biodegraded to different extents. The gradient in asphaltene concentration is explained by an equilibrium model considering only gravitational segregation of asphaltene nanoaggregates; this grading can be responsible for the observed variation in viscosity. Combining these analyses yields a consistent picture of a connected reservoir in which the observed viscosity variation originates from gravitational segregation of asphaltene nanoaggregates in a crude oil with high asphaltene concentration resulting from multiple charges, including one charge that suffered severe biodegradation. Observation of these gradients having appropriate magnitudes suggests good reservoir connectivity with greater confidence than is possible with traditional techniques alone.The mass spectrometry work was supported by the NSF Division of Materials Research through DMR‐06‐54118, and the State of Florida