Of Flyers and Free Speech: How Student Activism Defined the Contours of One University’s 21st-Century Hate and Bias Policy

Since 1999, The University of Texas at Austin (UT Austin) operated under a Student Policy on Race Relations when handling hate and bias incidents. In February 2017, an anti-Muslim flyer was posted near campus, prompting UT administration to hold a town hall for UT student activ-ists to vocalize their concerns. Through Kezar’s (2010) description of modern student protests and Barnhardt’s (2014) framework for modern student protests, this study analyzes the marginal-ized UT Austin student voices of that town hall meeting, demonstrating how modern student activism influenced presidential rhetoric and a new Hate and Bias Incidents Policy, the first in nearly two decades at UT Austin.Educatio

Winter Conditions Influence Biological Responses of Migrating Hummingbirds

Conserving biological diversity given ongoing environmental changes requires the knowledge of how organisms respond biologically to these changes; however, we rarely have this information. This data deficiency can be addressed with coordinated monitoring programs that provide field data across temporal and spatial scales and with process-based models, which provide a method for predicting how species, in particular migrating species that face different conditions across their range, will respond to climate change. We evaluate whether environmental conditions in the wintering grounds of broad-tailed hummingbirds influence physiological and behavioral attributes of their migration. To quantify winter ground conditions, we used operative temperature as a proxy for physiological constraint, and precipitation and the normalized difference vegetation index (NDVI) as surrogates of resource availability. We measured four biological response variables: molt stage, timing of arrival at stopover sites, body mass, and fat. Consistent with our predictions, we found that birds migrating north were in earlier stages of molt and arrived at stopover sites later when NDVI was low. These results indicate that wintering conditions impact the timing and condition of birds as they migrate north. In addition, our results suggest that biologically informed environmental surrogates provide a valuable tool for predicting how climate variability across years influences the animal populations

Ozone loss derived from balloon-borne tracer measurements in the 1999/2000 Arctic winter

Balloon-borne measurements of CFC11 (from the DIRAC in situ gas chromatograph and the DESCARTES grab sampler), ClO and O3 were made during the 1999/2000 Arctic winter as part of the SOLVE-THESEO 2000 campaign, based in Kiruna (Sweden). Here we present the CFC11 data from nine flights and compare them first with data from other instruments which flew during the campaign and then with the vertical distributions calculated by the SLIMCAT 3D CTM. We calculate ozone loss inside the Arctic vortex between late January and early March using the relation between CFC11 and O3 measured on the flights. The peak ozone loss (~1200ppbv) occurs in the 440-470K region in early March in reasonable agreement with other published empirical estimates. There is also a good agreement between ozone losses derived from three balloon tracer data sets used here. The magnitude and vertical distribution of the loss derived from the measurements is in good agreement with the loss calculated from SLIMCAT over Kiruna for the same days

Theory and observations: Model simulations of the period 1955-1985

The main objective of the theoretical studies presented here is to apply models of stratospheric chemistry and transport in order to understand the processes that control stratospheric ozone and that are responsible for the observed variations. The model calculations are intended to simulate the observed behavior of atmospheric ozone over the past three decades (1955-1985), for which there exists a substantial record of both ground-based and, more recently, satellite measurements. Ozone concentrations in the atmosphere vary on different time scales and for several different causes. The models described here were designed to simulate the effect on ozone of changes in the concentration of such trace gases as CFC, CH4, N2O, and CO2. Changes from year to year in ultraviolet radiation associated with the solar cycle are also included in the models. A third source of variability explicitly considered is the sporadic introduction of large amounts of NO sub x into the stratosphere during atmospheric nuclear tests

Data mining: a tool for detecting cyclical disturbances in supply networks.

Disturbances in supply chains may be either exogenous or endogenous. The ability automatically to detect, diagnose, and distinguish between the causes of disturbances is of prime importance to decision makers in order to avoid uncertainty. The spectral principal component analysis (SPCA) technique has been utilized to distinguish between real and rogue disturbances in a steel supply network. The data set used was collected from four different business units in the network and consists of 43 variables; each is described by 72 data points. The present paper will utilize the same data set to test an alternative approach to SPCA in detecting the disturbances. The new approach employs statistical data pre-processing, clustering, and classification learning techniques to analyse the supply network data. In particular, the incremental k-means clustering and the RULES-6 classification rule-learning algorithms, developed by the present authors’ team, have been applied to identify important patterns in the data set. Results show that the proposed approach has the capability automatically to detect and characterize network-wide cyclical disturbances and generate hypotheses about their root cause

Using δ13C-CH4 and δD-CH4 to constrain Arctic methane emissions

We present a global methane modelling study assessing the sensitivity of Arctic atmospheric CH4 mole fractions, δ13C-CH4 and δD-CH4 to uncertainties in Arctic methane sources. Model simulations include methane tracers tagged by source and isotopic composition and are compared with atmospheric data at four northern high-latitude measurement sites. We find the model's ability to capture the magnitude and phase of observed seasonal cycles of CH4 mixing ratios, δ13C-CH4 and δD-CH4 at northern high latitudes is much improved using a later spring kick-off and autumn decline in northern high-latitude wetland emissions than predicted by most process models. Results from our model simulations indicate that recent predictions of large methane emissions from thawing submarine permafrost in the East Siberian Arctic Shelf region could only be reconciled with global-scale atmospheric observations by making large adjustments to high-latitude anthropogenic or wetland emission inventories