418 research outputs found

    Calculation of two-loop virtual corrections to b --> s l+ l- in the standard model

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    We present in detail the calculation of the virtual O(alpha_s) corrections to the inclusive semi-leptonic rare decay b --> s l+ l-. We also include those O(alpha_s) bremsstrahlung contributions which cancel the infrared and mass singularities showing up in the virtual corrections. In order to avoid large resonant contributions, we restrict the invariant mass squared s of the lepton pair to the range 0.05 < s/mb^2 < 0.25. The analytic results are represented as expansions in the small parameters s/mb^2, z = mc^2/mb^2 and s/(4 mc^2). The new contributions drastically reduce the renormalization scale dependence of the decay spectrum. For the corresponding branching ratio (restricted to the above s-range) the renormalization scale uncertainty gets reduced from +/-13% to +/-6.5%.Comment: 41 pages including 9 postscript figures; in version 2 some typos and inconsistent notation correcte

    Effect of sonication on the viscosity of reconstituted skim milk powder and milk protein concentrate as influenced by solids concentration, temperature and sonication

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    Skim milk powder (SMP) and milk protein concentrates (MPCs) are manufactured by evaporation followed by spray drying and are widely used as functional and nutritional ingredients. This study investigated the effects of temperature (40–60 °C) and total solids content (TS) on the viscosity of reconstituted MPC (rMPC) (≥30% TS) and SMP (rSMP) (≥46% TS) in laboratory conditions. Additionally, the influence of sonication in batch (70% amplitude) and flow through systems (90% amplitude) was studied in a laboratory setting. The viscosity increased for all treatments with an increase in TS and decreased with an increase in temperature. Overall, sonication in both batch (30 s) and flow through systems (10.1, 20.2, and 30.2 s) resulted in significant decreases in viscosity for both rSMP and rMPC. An increase in viscosity was observed after post-sonication circulation; however, the viscosity did not return to the pre-sonication values

    THE DATA REDUCTION PIPELINE FOR THE APACHE POINT OBSERVATORY GALACTIC EVOLUTION EXPERIMENT

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    The Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey III, explores the stellar populations of the Milky Way using the Sloan 2.5-m telescope linked to a high resolution (R ~ 22,500), near-infrared (1.51–1.70 µm) spectrograph with 300 optical fibers. For over 150,000 predominantly red giant branch stars that APOGEE targeted across the Galactic bulge, disks and halo, the collected high signal-to-noise ratio (>100 per half-resolution element) spectra provide accurate (~0.1 km s-1) RVs, stellar atmospheric parameters, and precise (lesssim0.1 dex) chemical abundances for about 15 chemical species. Here we describe the basic APOGEE data reduction software that reduces multiple 3D raw data cubes into calibrated, well-sampled, combined 1D spectra, as implemented for the SDSS-III/APOGEE data releases (DR10, DR11 and DR12). The processing of the near-IR spectral data of APOGEE presents some challenges for reduction, including automated sky subtraction and telluric correction over a 3°-diameter field and the combination of spectrally dithered spectra. We also discuss areas for future improvement

    Cellulase recycling in biorefineriesis : is it possible?

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    On a near future, bio-based economy will assume a key role in our lives. Lignocellulosic materials (e.g., agroforestry residues, industrial/solid wastes) represent a cheaper and environmentally friendly option to fossil fuels. Indeed, following suitable processing, they can be metabolized by different microorganisms to produce a wide range of compounds currently obtained by chemical synthesis. However, due to the recalcitrant nature of these materials, they cannot be directly used by microorganisms, the conversion of polysaccharides into simpler sugars being thus required. This conversion, which is usually undertaken enzymatically, represents a significant part on the final cost of the process. This fact has driven intense efforts on the reduction of the enzyme cost following different strategies. Here, we describe the fundamentals of the enzyme recycling technology, more specifically, cellulase recycling. We focus on the main strategies available for the recovery of both the liquid- and solid-bound enzyme fractions and discuss the relevant operational parameters (e.g., composition, temperature, additives, and pH). Although the efforts from the industry and enzyme suppliers are primarily oriented toward the development of enzyme cocktails able to quickly and effectively process biomass, it seems clear by now that enzyme recycling is technically possible.Financial support from FEDER and Fundação para a Ciência e a Tecnologia (FCT): GlycoCBMs Project PTDC/AGR-FOR/3090/2012–FCOMP-01-0124- FEDER-027948 and Strategic Project PEst-OE/EQB/LA0023/2013, Project BBioInd-Biotechnology and Bioengineering for improved Industrial and Agro-Food processes, REF. NORTE-07-0124-FEDER-000028 Cofunded by the Programa Operacional Regional do Norte (ON.2–O Novo Norte), QREN, FEDER and the PhD grant to DG (SFRH/BD/88623/ 2012) and ACR (SFRH/BD/89547/2012)

    Hierarchical multiple-factor analysis for classifying genotypes based on phenotypic and genetic data

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    A numerical classifi cation problem encountered by breeders and gene-bank curators is how to partition the original heterogeneous population of genotypes into non-overlapping homogeneous subpopulations. The measure of distance that may be defi ned depends on the type of variables measured (i.e., continuous and/or discrete). The key points are whether and how a distance may be defi ned using all types of variables to achieve effective classifi cation. The objective of this research was to propose an approach that combines the use of hierarchical multiple-factor analysis (HMFA) and the two-stage Ward Modifi ed Location Model (Ward-MLM) classifi cation strategy that allows (i) combining different types of phenotypic and genetic data simultaneously; (ii) balancing out the effects of the different phenotypic, genetic, continuous, and discrete variables; and (iii) measuring the contribution of each original variable to the new principal axes (PAs). Of the two strategies applied for developing PA scores to be used for clustering genotypes, the strategy that used the fi rst few PA scores to which phenotypic and genetic variables each contributed 50% (i.e., a balanced contribution) formed better groups than those formed by the strategy that used a large number of PA scores explaining 95% of total variability. Phenotypic variables account for much variability in the initial PA; then their contributions decrease. The importance of genetic variables increases in later PAs. Results showed that various phenotypic and genetic variables made important contributions to the new PA. The HMFA uses all phenotypic and genetic variables simultaneously and, in conjunction with the Ward-MLM method, it offers an effective unifying approach for the classifi cation of breeding genotypes into homogeneous groups and for the formation of core subsets for genetic resource conservation
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