Non-BBN Constraints On The Key Cosmological Parameters

Since the baryon-to-photon ratio "eta" is in some doubt at present, we ignore the constraints on eta from big bang nucleosynthesis (BBN) and fit the three key cosmological parameters (h, Omega_M, eta) to four other observational constraints: Hubble parameter, age of the universe, cluster gas (baryon) fraction, and effective shape parameter "Gamma". We consider open and flat CDM models and flat "Lambda"-CDM models, testing goodness of fit and drawing confidence regions by the Delta-chi^2 method. CDM models with Omega_M = 1 (SCDM models) are accepted only because we allow a large error on h, permitting h < 0.5. Open CDM models are accepted only for Omega_M \gsim 0.4. Lambda-CDM models give similar results. In all of these models, large eta (\gsim 6) is favored strongly over small eta, supporting reports of low deuterium abundances on some QSO lines of sight, and suggesting that observational determinations of primordial 4He may be contaminated by systematic errors. Only if we drop the crucial Gamma constraint are much lower values of Omega_M and eta permitted.Comment: 12 pages, Kluwer Latex, 2 Postscript figures, to appear in the proceedings of the ISSI Workshop, "The Primordial Nuclei and Their Galactic Evolution" (Bern, May 6-10, 1997), ed. N. Prantzos, M. Tosi, and R. von Steiger (Kluwer, Dordrecht

Environmental Costs of Government-Sponsored Agrarian Settlements in Brazilian Amazonia

Brazil has presided over the most comprehensive agrarian reform frontier colonization program on Earth, in which ~1.2 million settlers have been translocated by successive governments since the 1970's, mostly into forested hinterlands of Brazilian Amazonia. These settlements encompass 5.3% of this ~5 million km2 region, but have contributed with 13.5% of all land conversion into agropastoral land uses. The Brazilian Federal Agrarian Agency (INCRA) has repeatedly claimed that deforestation in these areas largely predates the sanctioned arrival of new settlers. Here, we quantify rates of natural vegetation conversion across 1911 agrarian settlements allocated to 568 Amazonian counties and compare fire incidence and deforestation rates before and after the official occupation of settlements by migrant farmers. The timing and spatial distribution of deforestation and fires in our analysis provides irrefutable chronological and spatially explicit evidence of agropastoral conversion both inside and immediately outside agrarian settlements over the last decade. Deforestation rates are strongly related to local human population density and road access to regional markets. Agrarian settlements consistently accelerated rates of deforestation and fires, compared to neighboring areas outside settlements, but within the same counties. Relocated smallholders allocated to forest areas undoubtedly operate as pivotal agents of deforestation, and most of the forest clearance occurs in the aftermath of government-induced migration

Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogs from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multi-band deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalog created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of $\sigma_{\Delta z} = 0.007$, which is a 60% improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.Comment: 24 pages, 11 figures; matches version accepted to MNRA

Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors

HOST GALAXY IDENTIFICATION FOR SUPERNOVA SURVEYS

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope, which will discover SNe by the thousands. Spectroscopic resources are limited, and so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey

VDES J2325-5229 a z=2.7 gravitationally lensed quasar discovered using morphology independent supervised machine learning

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift $\textit{zs}$ = 2.74 and image separation of 2.9 arcsec lensed by a foreground $\textit{zl}$ = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and $\textit{gi}$ multicolour photometric observations from the Dark Energy Survey (DES), near-IR $\textit{JK}$ photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with $\textit{iAB}$ = 18.61 and $\textit{iAB}$ = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of $\textit{z}$ = 2.739 ± 0.003 and a foreground early-type galaxy with $\textit{z}$ = 0.400 ± 0.002. We model the system as a single isothermal ellipsoid and find the Einstein radius θE ∼ 1.47 arcsec, enclosed mass $\textit{M}$enc ∼ 4 × 10$^{11}$$\textit{M}$⊙ and a time delay of ∼52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.FO is supported jointly by CAPES (the Science without Borders programme) and the Cambridge Commonwealth Trust. RGM, CAL, MWA, MB, SLR acknowledge the support of UK Science and Technology Research Council (STFC). AJC acknowledges the support of a Raymond and Beverly Sackler visiting fellowship at the Institute of Astronomy. For further information regarding funding please visit the publisher's website

Dose-Dependent Immunomodulation of Human Dendritic Cells by the Probiotic Lactobacillus rhamnosus Lcr35

The response of the immune system to probiotics remains controversial. Some strains modulate the cytokine production of dendritic cells (DCs) in vitro and induce a regulatory response, while others induce conversely a pro-inflammatory response. These strain-dependent effects are thought to be linked to specific interactions between bacteria and pattern recognition receptors. We investigated the effects of a well characterized probiotic strain, Lactobacillus rhamnosus Lcr35, on human monocyte-derived immature DCs, using a wide range of bacterial concentrations (multiplicity of infection, MOI, from 0.01 to 100). DNA microarray and qRT-PCR analysis showed that the probiotic induced a large-scale change in gene expression (nearly 1,700 modulated genes, with 3-fold changes), but only with high doses (MOI, 100). The upregulated genes were mainly involved in immune response and identified a molecular signature of inflammation according to the model of Torri. Flow cytometry analysis also revealed a dose-dependent maturation of the DC membrane phenotype, until DCs reached a semi-mature state, with an upregulation of the membrane expression of CD86, CD83, HLA-DR and TLR4, associated with a down-regulation of DC-SIGN, MR and CD14. Measurement of the DC-secreted cytokines showed that Lcr35 induced a strong dose-dependent increase of the pro-Th1/Th17 cytokine levels (TNFα, IL-1β, IL-12p70, IL-12p40 and IL-23), but only a low increase in IL-10 concentration. The probiotic L. rhamnosus Lcr35 therefore induce a dose-dependent immunomodulation of human DCs leading, at high doses, to the semi-maturation of the cells and to a strong pro-inflammatory effect. These results contribute to a fuller understanding of the mechanism of action of this probiotic, and thus of its potential clinical indications in the treatment of either infectious or IgE-dependent allergic diseases

On the relative bias of void tracers in the Dark Energy Survey

Luminous tracers of large-scale structure are not entirely representative of the distribution of mass in our Universe. As they arise from the highest peaks in the matter density field, the spatial distribution of luminous objects is biased towards those peaks. On large scales, where density fluctuations are mild, this bias simply amounts to a constant offset in the clustering amplitude of the tracer, known as linear bias. In this work we focus on the relative bias between galaxies and galaxy clusters that are located inside and in the vicinity of cosmic voids, extended regions of relatively low density in the large-scale structure of the Universe. With the help of mock data we verify that the relation between galaxy and cluster overdensity around voids remains linear. Hence, the void-centric density profiles of different tracers can be linked by a single multiplicative constant. This amounts to the same value as the relative linear bias between tracers for the largest voids in the sample. For voids of small sizes, which typically arise in higher density regions, this constant has a higher value, possibly showing an environmental dependence similar to that observed for the linear bias itself. We confirm our findings by analysing data obtained during the first year of observations by the Dark Energy Survey. As a side product, we present the first catalogue of three-dimensional voids extracted from a photometric survey with a controlled photo-z uncertainty. Our results will be relevant in forthcoming analyses that attempt to use voids as cosmological probes