The Effect of Cigarette Excise Taxes on Smoking Before, During and After Pregnancy

Recent analyses suggest that cigarette excise taxes lower prenatal smoking. It is unclear, however, whether the association between taxes and prenatal smoking represents a decline among women of reproductive age or a particular response by pregnant women. We address this question directly with an analysis of quit and relapse behavior during and after pregnancy. We find that the price elasticity of prenatal quitting and postpartum relapse is close to one in absolute value. We conclude that direct financial incentives to stop smoking during and after pregnancy should be considered.

Groundwater Flow and Thermal Modeling to Support a Preferred Conceptual Model for the Large Hydraulic Gradient North of Yucca Mountain

This task will create a two-dimensional, saturated zone, vertical cross-section model of groundwater flow and thermal transport through the large hydraulic gradient (LHG). This model is referenced herein as the thermal model. The scope of this study is limited to presenting a postulated hydrogeologic configuration of the LHG. The conceptualization will include the use of postulated hydrogeologic structures and material properties. The thermal model will be spatially limited to the area immediately upgradient and downgradient of the LHG and will not reproduce the many hydrogeologic features of the existing regional and site-scale models. The thermal model will be orientated north to south, approximately along a saturated zone streamline. The results of the thermal modeling will be compared to temperature data reported for site wells by the U.S. Geological Survey (USGS) and in peer-reviewed journals. Most, if not all, of this reported data is non- qualified. This task will not qualify the reported data and the reported data will be used only as a basis of comparison for the model simulations

AGN's Deadness Over Cosmic Time: UVJ Diagrams of X-Ray-Selected AGN

Active Galactic Nuclei (AGN) are intensely accreting supermassive black holes at the centers of massive galaxies. Though these objects occupy little spatial extent of the galaxy itself, they are thought to have far reaching affects, impacting the galaxy's star formation, and possibly it's lifespan until it becomes 'red and dead'. Typical galaxies demonstrate that, over cosmic time, they tend to separate into a bimodal distribution of 'red and dead' or blue and star forming. We examine whether active galaxies evolve over cosmic time in a similar way, and whether this can reveal anything about the complexities of the relationship between an AGN and the host galaxy. We use the Stripe82X survey to identify 3940 X-ray AGN spanning z=0-2.5, and we measure the rest-frame UVJ colors of each galaxy. We classify AGN as star-forming or quiescent based on their location in a UVJ color diagram. We find that there is not a clear bimodal distribution between AGN in star forming and quiescent galaxies. Furthermore, the most luminous X-ray sources tend to lie in the star forming region, which may indicate a correlation between central engine activity and increased rates of star formation.Comment: 4 pages, 1 figur

Bayesian High-Redshift Quasar Classification from Optical and Mid-IR Photometry

We identify 885,503 type 1 quasar candidates to i<22 using the combination of optical and mid-IR photometry. Optical photometry is taken from the Sloan Digital Sky Survey-III: Baryon Oscillation Spectroscopic Survey (SDSS-III/BOSS), while mid-IR photometry comes from a combination of data from the Wide-Field Infrared Survey Explorer (WISE) "ALLWISE" data release and several large-area Spitzer Space Telescope fields. Selection is based on a Bayesian kernel density algorithm with a training sample of 157,701 spectroscopically-confirmed type-1 quasars with both optical and mid-IR data. Of the quasar candidates, 733,713 lack spectroscopic confirmation (and 305,623 are objects that we have not previously classified as photometric quasar candidates). These candidates include 7874 objects targeted as high probability potential quasars with 3.5<z<5 (of which 6779 are new photometric candidates). Our algorithm is more complete to z>3.5 than the traditional mid-IR selection "wedges" and to 2.2<z<3.5 quasars than the SDSS-III/BOSS project. Number counts and luminosity function analysis suggests that the resulting catalog is relatively complete to known quasars and is identifying new high-z quasars at z>3. This catalog paves the way for luminosity-dependent clustering investigations of large numbers of faint, high-redshift quasars and for further machine learning quasar selection using Spitzer and WISE data combined with other large-area optical imaging surveys.Comment: 54 pages, 17 figures; accepted by ApJS Data for tables 1 and 2 available at http://www.physics.drexel.edu/~gtr/outgoing/optirqsos/data/master_quasar_catalogs.011414.fits.bz2 and http://www.physics.drexel.edu/~gtr/outgoing/optirqsos/data/optical_ir_quasar_candidates.052015.fits.bz

Wireless aquatic navigator for detection and analysis (WANDA)

The cost of monitoring and detecting pollutants in natural waters is of major concern. Current and forthcoming bodies of legislation will continue to drive demand for spatial and selective monitoring of our environment, as the focus increasingly moves towards effective enforcement of legislation through detection of events, and unambiguous identification of perpetrators. However, these monitoring demands are not being met due to the infrastructure and maintenance costs of conventional sensing models. Advanced autonomous platforms capable of performing complex analytical measurements at remote locations still require individual power, wireless communication, processor and electronic transducer units, along with regular maintenance visits. Hence the cost base for these systems is prohibitively high, and the spatial density and frequency of measurements are insufficient to meet requirements. In this paper we present a more cost effective approach for water quality monitoring using a low cost mobile sensing/communications platform together with very low cost stand-alone ‘satellite’ indicator stations that have an integrated colorimetric sensing material. The mobile platform is equipped with a wireless video camera that is used to interrogate each station to harvest information about the water quality. In simulation experiments, the first cycle of measurements is carried out to identify a ‘normal’ condition followed by a second cycle during which the platform successfully detected and communicated the presence of a chemical contaminant that had been localised at one of the satellite stations

Television news and the symbolic criminalisation of young people

This is an Author's Accepted Manuscript of an article published in Journalism Studies, 9(1), 75 - 90, 2008, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/14616700701768105.This essay combines quantitative and qualitative analysis of six UK television news programmes. It seeks to analyse the representation of young people within broadcast news provision at a time when media representations, political discourse and policy making generally appear to be invoking young people as something of a folk devil or a locus for moral panics. The quantitative analysis examines the frequency with which young people appear as main actors across a range of different subjects and analyses the role of young people as news sources. It finds a strong correlation between young people and violent crime. A qualitative analysis of four “special reports” or backgrounders on channel Five's Five News explores the representation of young people in more detail, paying attention to contradictions and tensions in the reports, the role of statistics in crime reporting, the role of victims of crime and the tensions between conflicting news frames.Arts and Humanities Research Counci

WANDA: A Radically New Approach for Low-Cost Environmental Monitoring

The cost of monitoring pollutants within natural waters is of major concern. Existing and forthcoming bodies of legislation continually drive the demand for spatial and selective monitoring of key pollutants within our environment. Although research and commercial entities continue to drive down the cost of the infrastructure involved in environmental sensing systems (with an aim to increase scalability), the realisation of deploying a number of such systems even now remains out of reach. High cost and maintenance continue to persist as the major limiting factors. The aim of this work is to combine recent advances in robotics with chemical sensing techniques to remove all but the chemo-responsive material from each sensing node, and package the sensing element within a low cost, mobile, biomimetic robotic fish for effective water quality monitoring. Consequently, this approach is believed to radically reduce the systemic cost and maintenance per node and in doing so it will increase the scalability for spatial and selective monitoring of key pollutants within our environment

Predicting suicide attempts and suicide deaths among adolescents following outpatient visits

BACKGROUND: Few studies report on machine learning models for suicide risk prediction in adolescents and their utility in identifying those in need of further evaluation. This study examined whether a model trained and validated using data from all age groups works as well for adolescents or whether it could be improved. METHODS: We used healthcare data for 1.4 million specialty mental health and primary care outpatient visits among 256,823 adolescents across 7 health systems. The prediction target was 90-day risk of suicide attempt following a visit. We used logistic regression with least absolute shrinkage and selection operator (LASSO) and generalized estimating equations (GEE) to predict risk. We compared performance of three models: an existing model, a recalibrated version of that model, and a newly-learned model. Models were compared using area under the receiver operating curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: The AUC produced by the existing model for specialty mental health visits estimated in adolescents alone (0.796; [0.789, 0.802]) was not significantly different than the AUC of the recalibrated existing model (0.794; [0.787, 0.80]) or the newly-learned model (0.795; [0.789, 0.801]). Predicted risk following primary care visits was also similar: existing (0.855; [0.844, 0.866]), recalibrated (0.85 [0.839, 0.862]), newly-learned (0.842, [0.829, 0.854]). LIMITATIONS: The models did not incorporate non-healthcare risk factors. The models relied on ICD9-CM codes for diagnoses and outcome measurement. CONCLUSIONS: Prediction models already in operational use by health systems can be reliably employed for identifying adolescents in need of further evaluation

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

Expressions 1994-1995

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