Calibrating Long Period Variables as Standard Candles with Machine Learning

Variable stars with well-calibrated period-luminosity relationships provide accurate distance measurements to nearby galaxies and are therefore a vital tool for cosmology and astrophysics. While these measurements typically rely on samples of Cepheid and RR-Lyrae stars, abundant populations of luminous variable stars with longer periods of $10 - 1000$ days remain largely unused. We apply machine learning to derive a mapping between lightcurve features of these variable stars and their magnitude to extend the traditional period-luminosity (PL) relation commonly used for Cepheid samples. Using photometric data for long period variable stars in the Large Magellanic cloud (LMC), we demonstrate that our predictions produce residual errors comparable to those obtained on the corresponding Cepheid population. We show that our model generalizes well to other samples by performing a blind test on photometric data from the Small Magellanic Cloud (SMC). Our predictions on the SMC again show small residual errors and biases, comparable to results that employ PL relations fitted on Cepheid samples. The residual biases are complementary between the long period variable and Cepheid fits, which provides exciting prospects to better control sources of systematic error in cosmological distance measurements. We finally show that the proposed methodology can be used to optimize samples of variable stars as standard candles independent of any prior variable star classification.Comment: 14 pages, 10 figures, 1 table, updated to match the version accepted by the MNRA

Photometric Redshift Uncertainties in Weak Gravitational Lensing Shear Analysis: Models and Marginalization

Recovering credible cosmological parameter constraints in a weak lensing shear analysis requires an accurate model that can be used to marginalize over nuisance parameters describing potential sources of systematic uncertainty, such as the uncertainties on the sample redshift distribution $n(z)$. Due to the challenge of running Markov Chain Monte-Carlo (MCMC) in the high dimensional parameter spaces in which the $n(z)$ uncertainties may be parameterized, it is common practice to simplify the $n(z)$ parameterization or combine MCMC chains that each have a fixed $n(z)$ resampled from the $n(z)$ uncertainties. In this work, we propose a statistically-principled Bayesian resampling approach for marginalizing over the $n(z)$ uncertainty using multiple MCMC chains. We self-consistently compare the new method to existing ones from the literature in the context of a forecasted cosmic shear analysis for the HSC three-year shape catalog, and find that these methods recover similar cosmological parameter constraints, implying that using the most computationally efficient of the approaches is appropriate. However, we find that for datasets with the constraining power of the full HSC survey dataset (and, by implication, those upcoming surveys with even tighter constraints), the choice of method for marginalizing over $n(z)$ uncertainty among the several methods from the literature may significantly impact the statistical uncertainties on cosmological parameters, and a careful model selection is needed to ensure credible parameter intervals.Comment: 15 pages, 8 figures, submitted to mnra

Weak Lensing Tomographic Redshift Distribution Inference for the Hyper Suprime-Cam Subaru Strategic Program three-year shape catalogue

We present posterior sample redshift distributions for the Hyper Suprime-Cam Subaru Strategic Program Weak Lensing three-year (HSC Y3) analysis. Using the galaxies' photometry and spatial cross-correlations, we conduct a combined Bayesian Hierarchical Inference of the sample redshift distributions. The spatial cross-correlations are derived using a subsample of Luminous Red Galaxies (LRGs) with accurate redshift information available up to a photometric redshift of $z < 1.2$. We derive the photometry-based constraints using a combination of two empirical techniques calibrated on spectroscopic- and multiband photometric data that covers a spatial subset of the shear catalog. The limited spatial coverage induces a cosmic variance error budget that we include in the inference. Our cross-correlation analysis models the photometric redshift error of the LRGs to correct for systematic biases and statistical uncertainties. We demonstrate consistency between the sample redshift distributions derived using the spatial cross-correlations, the photometry, and the posterior of the combined analysis. Based on this assessment, we recommend conservative priors for sample redshift distributions of tomographic bins used in the three-year cosmological Weak Lensing analyses.Comment: 23 pages, 11 figures, 1 table, submitted to the MNRAS; comments welcom

The Forum: Fall 2003

Fall 2003 journal of the Honors Program at the University of North Dakota. The issue includes stories, poems, essays and art by undergraduate students.https://commons.und.edu/und-books/1052/thumbnail.jp

Comprehensive Open Access Dataset of Sustainable Energy Consumption Initiatives (SECIs) : Deliverable 2.3

This document (ENERGISE D2.3) provides a background report on the process and result of developing and constructing a comprehensive open access dataset of sustainable energy consumption initiatives (SECIs) that have been collected and assessed as part of Work Package 2 (WP2) in ENERGISE. The dataset is designed as a map that is intended to be a user-friendly device that provides an overview of sustainable energy consumption initiatives (SECIs) in Europe. In particular, the map shows the variety in scope, content and approach in the identified SECIs

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

DNMT3A Loss Drives Enhancer Hypomethylation in FLT3-ITD-Associated Leukemias.

DNMT3A, the gene encoding the de novo DNA methyltransferase 3A, is among the most frequently mutated genes in hematologic malignancies. However, the mechanisms through which DNMT3A normally suppresses malignancy development are unknown. Here, we show that DNMT3A loss synergizes with the FLT3 internal tandem duplication in a dose-influenced fashion to generate rapid lethal lymphoid or myeloid leukemias similar to their human counterparts. Loss of DNMT3A leads to reduced DNA methylation, predominantly at hematopoietic enhancer regions in both mouse and human samples. Myeloid and lymphoid diseases arise from transformed murine hematopoietic stem cells. Broadly, our findings support a role for DNMT3A as a guardian of the epigenetic state at enhancer regions, critical for inhibition of leukemic transformation.L.Y. is funded by the Robert and Janice McNair Foundation as an MD/PhD McNair Scholar. This project was funded by CPRIT (RP110028, RP110471 and RP150292 ), the NIH (DK092883 and HG007538), and the Samuel Waxman Cancer Research Foundation. We also thank the Cytometry and Cell Sorting and Genomic and RNA Profiling Cores (NCI P30CA125123, P30 AI036211, P30 CA125123, and S10 RR024574 ) at Baylor College of Medicine. Authors declare no conflicts of interest.This is the author accepted manuscript. The final version is available from Cell Press via http://dx.doi.org/10.1016/j.ccell.2016.05.00

Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the

Neuropsychiatric manifestations and sleep disturbances with dolutegravir-based antiretroviral therapy versus standard of care in children and adolescents: a secondary analysis of the ODYSSEY trial

BACKGROUND: Cohort studies in adults with HIV showed that dolutegravir was associated with neuropsychiatric adverse events and sleep problems, yet data are scarce in children and adolescents. We aimed to evaluate neuropsychiatric manifestations in children and adolescents treated with dolutegravir-based treatment versus alternative antiretroviral therapy. METHODS: This is a secondary analysis of ODYSSEY, an open-label, multicentre, randomised, non-inferiority trial, in which adolescents and children initiating first-line or second-line antiretroviral therapy were randomly assigned 1:1 to dolutegravir-based treatment or standard-of-care treatment. We assessed neuropsychiatric adverse events (reported by clinicians) and responses to the mood and sleep questionnaires (reported by the participant or their carer) in both groups. We compared the proportions of patients with neuropsychiatric adverse events (neurological, psychiatric, and total), time to first neuropsychiatric adverse event, and participant-reported responses to questionnaires capturing issues with mood, suicidal thoughts, and sleep problems. FINDINGS: Between Sept 20, 2016, and June 22, 2018, 707 participants were enrolled, of whom 345 (49%) were female and 362 (51%) were male, and 623 (88%) were Black-African. Of 707 participants, 350 (50%) were randomly assigned to dolutegravir-based antiretroviral therapy and 357 (50%) to non-dolutegravir-based standard-of-care. 311 (44%) of 707 participants started first-line antiretroviral therapy (ODYSSEY-A; 145 [92%] of 157 participants had efavirenz-based therapy in the standard-of-care group), and 396 (56%) of 707 started second-line therapy (ODYSSEY-B; 195 [98%] of 200 had protease inhibitor-based therapy in the standard-of-care group). During follow-up (median 142 weeks, IQR 124–159), 23 participants had 31 neuropsychiatric adverse events (15 in the dolutegravir group and eight in the standard-of-care group; difference in proportion of participants with ≥1 event p=0·13). 11 participants had one or more neurological events (six and five; p=0·74) and 14 participants had one or more psychiatric events (ten and four; p=0·097). Among 14 participants with psychiatric events, eight participants in the dolutegravir group and four in standard-of-care group had suicidal ideation or behaviour. More participants in the dolutegravir group than the standard-of-care group reported symptoms of self-harm (eight vs one; p=0·025), life not worth living (17 vs five; p=0·0091), or suicidal thoughts (13 vs none; p=0·0006) at one or more follow-up visits. Most reports were transient. There were no differences by treatment group in low mood or feeling sad, problems concentrating, feeling worried or feeling angry or aggressive, sleep problems, or sleep quality. INTERPRETATION: The numbers of neuropsychiatric adverse events and reported neuropsychiatric symptoms were low. However, numerically more participants had psychiatric events and reported suicidality ideation in the dolutegravir group than the standard-of-care group. These differences should be interpreted with caution in an open-label trial. Clinicians and policy makers should consider including suicidality screening of children or adolescents receiving dolutegravir