Strategies for Increasing Self-Efficacy in Long-Term Welfare Recipients

With the imposition of lifetime limitations on an individual\u27s ability to receive cash assistance, there is a group of long-term Temporary Assistance for Needy Families (TANF) recipients that have approached the lifetime limitation without becoming gainfully employed. Many long term TANF recipients report low levels of self-efficacy which inhibits their ability to successfully transition off welfare and into the workforce. However, most welfare-to-work programs do not address the emotional or psychological well-being of their clients, instead they focus on job placement and job readiness skills. The purpose of this sequential–exploratory mixed methods study is to identify the primary barriers to employment that have a negative effect on long term TANF recipient\u27s self-efficacy. Albert Bandura\u27s self-efficacy theory was the theoretical foundation for this study. Semi structured interviews with 20 long term TANF recipients helped answer the central research questions regarding barrier identification. The participants agreed that support for completing GED, as well as a more holistic approach to addressing their barriers is most effective in helping them transition off welfare and into the workforce. Hong\u27s Employment Hope Scale (EHS-14) was used to collect the quantitative data for this study. The quantitative data were analyzed by multiple regression analysis and found that level of education has a statistically significant moderating effect on length of time on welfare and level of self-efficacy. This study may inform welfare-to-work providers and programmers on the importance of addressing TANF recipients\u27 psychological needs, such as low self-efficacy before attempting to transition them into the workforce

Examination of Changes in Hygroscopicity and CCN Activation Efficiency During Particle Growth Events

The growth and evolution of newly formed atmospheric particles were examined using an array of instruments located at a rural site northwest of Houston, TX. The focused study described here was designed to evaluate the influence of nucleated particles on same day and next day CCN concentrations. An integrated differential mobility analyzer / tandem differential mobility analyzer / CCN counter was used to track the size, hygroscopicity, and cloud nucleating efficiency of the population of particles that formed during the morning and grew throughout day and into the night. As has been observed using similar instrumentation at other locations, the hygroscopicity of the recently formed particles exhibited a diel pattern having a maximum in the early afternoon and a minimum before sunrise. To attribute the growth and evolving properties of these particles to the responsible mechanisms, complementary measurements of gas phase precursors and oxidants, which were made concurrently to particle measurements, will be compared in a future project. Of particular interest would be the link between nighttime nitrate radical concentration and the rates at which the diameter of the particles increased and at which their critical supersaturation decreased. Ultimately, these data can help constrain the relative importance of organic and inorganic precursors and of differing oxidants to the production of CCN in regions for which both anthropogenic and biogenic emissions sources are significant

Revisiting the evolution of mouse LINE-1 in the genomic era

Background LINE-1 (L1) is the dominant category of transposable elements in placental mammals. L1 has significantly affected the size and structure of all mammalian genomes and understanding the nature of the interactions between L1 and its mammalian host remains a question of crucial importance in comparative genomics. For this reason, much attention has been dedicated to the evolution of L1. Among the most studied elements is the mouse L1 which has been the subject of a number of studies in the 1980s and 1990s. These seminal studies, performed in the pre-genomic era when only a limited number of L1 sequences were available, have significantly improved our understanding of L1 evolution. Yet, no comprehensive study on the evolution of L1 in mouse has been performed since the completion of this genome sequence. Results Using the Genome Parsing Suite we performed the first evolutionary analysis of mouse L1 over the entire length of the element. This analysis indicates that the mouse L1 has recruited novel 5’UTR sequences more frequently than previously thought and that the simultaneous activity of non-homologous promoters seems to be one of the conditions for the co-existence of multiple L1 families or lineages. In addition the exchange of genetic information between L1 families is not limited to the 5’UTR as evidence of inter-family recombination was observed in ORF1, ORF2, and the 3’UTR. In contrast to the human L1, there was little evidence of rapid amino-acid replacement in the coiled-coil of ORF1, although this region is structurally unstable. We propose that the structural instability of the coiled-coil domain might be adaptive and that structural changes in this region are selectively equivalent to the rapid evolution at the amino-acid level reported in the human lineage. Conclusions The pattern of evolution of L1 in mouse shows some similarity with human suggesting that the nature of the interactions between L1 and its host might be similar in these two species. Yet, some notable differences, particularly in the evolution of ORF1, suggest that the molecular mechanisms involved in host-L1 interactions might be different in these two species

The Extended Environment of M17: A Star Formation History

M17 is one of the youngest and most massive nearby star-formation regions in the Galaxy. It features a bright H II region erupting as a blister from the side of a giant molecular cloud (GMC). Combining photometry from the Spitzer GLIMPSE survey with complementary infrared (IR) surveys, we identify candidate young stellar objects (YSOs) throughout a 1.5 deg x 1 deg field that includes the M17 complex. The long sightline through the Galaxy behind M17 creates significant contamination in our YSO sample from unassociated sources with similar IR colors. Removing contaminants, we produce a highly-reliable catalog of 96 candidate YSOs with a high probability of association with the M17 complex. We fit model spectral energy distributions to these sources and constrain their physical properties. Extrapolating the mass function of 62 intermediate-mass YSOs (M >3 Msun), we estimate that >1000 stars are in the process of forming in the extended outer regions of M17. From IR survey images from IRAS and GLIMPSE, we find that M17 lies on the rim of a large shell structure ~0.5 deg in diameter (~20 pc at 2.1 kpc). We present new maps of CO and 13CO (J=2-1) emission, which show that the shell is a coherent, kinematic structure associated with M17 at v = 19 km/s. The shell is an extended bubble outlining the photodissociation region of a faint, diffuse H II region several Myr old. We provide evidence that massive star formation has been triggered by the expansion of the bubble. The formation of the massive cluster ionizing the M17 H II region itself may have been similarly triggered. We conclude that the star formation history in the extended environment of M17 has been punctuated by successive waves of massive star formation propagating through a GMC complex.Comment: 31 pages, 15 figures, accepted for publication in ApJ. For a version with higher-quality figures, see http://www.astro.wisc.edu/glimpse/Povich2009_M17.pd

A Spitzer Space Telescope Infrared Survey of Supernova Remnants in the Inner Galaxy

Using Infrared Array Camera (IRAC) images at 3.6, 4.5, 5.8, and 8 microns from the GLIMPSE Legacy science program on the Spitzer Space Telescope, we searched for infrared counterparts to the 95 known supernova remnants that are located within galactic longitudes 65>|l|>10 degrees and latitudes |b|<1 degree. Eighteen infrared counterparts were detected. Many other supernova remnants could have significant infrared emission but are in portions of the Milky Way too confused to allow separation from bright HII regions and pervasive mid-infrared emission from atomic and molecular clouds along the line of sight. Infrared emission from supernova remnants originates from synchrotron emission, shock-heated dust, atomic fine-structure lines, and molecular lines. The detected remnants are G11.2-0.3, Kes 69, G22.7-0.2, 3C 391, W 44, 3C 396, 3C 397, W 49B, G54.4-0.3, Kes 17, Kes 20A, RCW 103, G344.7-0.1, G346.6-0.2, CTB 37A, G348.5-0.0, and G349.7+0.2. The infrared colors suggest emission from molecular lines (9 remnants), fine-structure lines (3), and PAH (4), or a combination; some remnants feature multiple colors in different regions. None of the remnants are dominated by synchrotron radiation at mid-infrared wavelengths. The IRAC-detected sample emphasizes remnants interacting with relatively dense gas, for which most of the shock cooling occurs through molecular or ionic lines in the mid-infrared.Comment: Accepted 10/18/2005 for publication in "The Astronomical Journal". The figures in this astro-ph submission are drastically reduced in quality in order to fit within its limit

Evaluation of the KCl Denuder Method for Gaseous Oxidized Mercury using HgBr₂ at an In-Service AMNet Site

Thesis (Master's)--University of Washington, 2014During the summer of 2013, we examined the performance of KCl-coated denuders for measuring gaseous oxidized mercury (GOM) by calibrating with a known source of GOM (i.e., HgBr2) at the North Birmingham SouthEastern Aerosol Research and Characterization (SEARCH) site. We found that KCl-coated denuders have near 95% collection efficiency for HgBr2 in zero air (i.e., air scrubbed of mercury and ozone). However, in ambient air, the efficiency of KCl-coated denuders in capturing HgBr2 dropped to 20-54%. We also found that absolute humidity and ozone each demonstrate a significant inverse correlation with HgBr2 recovery in ambient air. Subsequent laboratory tests with HgBr2 and the KCl-coated denuder show that ozone and absolute humidity cause the release of gaseous elemental Hg from the denuder and thus appear to explain the low recovery in ambient air. Based on these findings, we infer that the KCl denuder method underestimates atmospheric GOM concentrations. A calibration system is needed to accurately measure GOM. The system described in this paper for HgBr2 could be implemented with existing mercury speciation instrumentation and this would improve our knowledge of the response to one potentially important GOM compound

Impacts of Biomass Burning on Ozone, Particulate Matter, and Carbon Dioxide in the Northwest U.S.

Thesis (Ph.D.)--University of Washington, 2018Wildfires (or Biomass Burning events) in the northwest U.S. have been increasing in size and frequency throughout the last few decades. This significantly affects vulnerable populations through hazardous fine particulate matter (diameter 70 µg/m3). The day after this high smoke period, a 20 ppbv enhancement in MDA8 O3 is observed in moderate smoke concentrations. The enhancement in MDA8 O3 during moderate smoke immediately following a high smoke periods implies a reduction in O3 production efficiency during high smoke concentrations. These results indicate that wildfire influenced O3 enhancements are highly variable in urban areas but generally increase up to around 60 µg/m3 of PM2.5, after which they decrease at very high smoke concentrations. This analysis also suggests that multiple tracer methodologies, such as GAM results, back-trajectories, and PAN mixing ratios, are effective at characterizing wildfire influence on MDA8 O3 in urban areas. Results from this dissertation have important implications for the identification of wildfire influences in urban and rural areas. They suggest the current suite of measurements taken may be ill-equipped or incomplete to fully investigate wildfire influences. Current CO2 and MCE criteria for wildfire influence may be biased by BL loss of CO2 during transport. ERs typical for wildfires are useful in urban areas when smoke influence is large, but less useful at moderate smoke levels due to high background concentrations of other urban pollutants already within the area. Additionally, highly variable PM2.5 concentrations in wildfire plumes can affect O3 production. While PM2.5 trends are decreasing throughout most of the U.S., policy-relevant 98th quantile PM2.5 shows an increase in the Northwest due to wildfire influence. With a predicted increase in wildfires through the end of the century, it is vitally important to develop methods to assess when wildfire emission are impacting an area. This could be achieved by developing an instrument to measure specific wildfire tracers, such as acetonitrile or a suite of volatile organic compounds (VOCs). Although there are instruments that can already measure these types of compounds, this instrument would need to be specific to wildfires compounds and not require special training or equipment to operate. This would allow cities/states/researchers to positively or negatively trace the influence of wildfires at low operational and personnel cost. This instrument would greatly expand our understanding of the impacts on air pollution due to wildfire emissions

Evaluation of the KCl Denuder Method for Gaseous Oxidized Mercury using HgBr₂ at an In-Service AMNet Site

During the summer of 2013, we examined the performance of KCl-coated denuders for measuring gaseous oxidized mercury (GOM) by calibrating with a known source of GOM (i.e., HgBr₂) at the North Birmingham SouthEastern Aerosol Research and Characterization (SEARCH) site. We found that KCl-coated denuders have near 95% collection efficiency for HgBr₂ in zero air (i.e., air scrubbed of mercury and ozone). However, in ambient air, the efficiency of KCl-coated denuders in capturing HgBr₂ dropped to 20–54%. We also found that absolute humidity and ozone each demonstrate a significant inverse correlation with HgBr₂ recovery in ambient air. Subsequent laboratory tests with HgBr₂ and the KCl-coated denuder show that ozone and absolute humidity cause the release of gaseous elemental Hg from the denuder and thus appear to explain the low recovery in ambient air. Based on these findings, we infer that the KCl denuder method underestimates atmospheric GOM concentrations and a calibration system is needed to accurately measure GOM. The system described in this paper for HgBr₂ could be implemented with existing mercury speciation instrumentation and this would improve our knowledge of the response to one potentially important GOM compound

The influence of viewpoint and object detail in blind people when matching pictures to complex objects

We examined haptic viewpoint effects in blindfolded-sighted (BS) and visually impaired subjects: early blind (EB), late blind (LB), and very low vision (VLV). Participants felt complex objects and matched tangible pictures to them. In experiment 1, the EB and BS subjects had similar overall performance. Experiment 2 showed that the presence of a detail on the target object lowered performance in the BS subjects, and that matching accuracy was lower overall for top views for the blind subjects. In experiments 3 ^ 5, EB, LB, VLV, and BS subjects made judgments about perspective pictures of a model house with more salient object details. In experiment 3, performance was higher for side views than for corner views. Elevated side views were identified more readily than elevated corner views in experiment 4. Performance for top views was higher than for elevated side views in experiment 5, given the relative simplicity of the top-view depictions and salient details. The EB and BS participants had somewhat lower matching accuracy scores than the other groups. We suggest that visual experience is helpful, but not essential for picture perception. Viewpoint effects may vary with experience and object complexity, but the relevant experience need not be specifically visual in nature

Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke

IntroductionEstimating PM2.5 concentrations and their prediction uncertainties at a high spatiotemporal resolution is important for air pollution health effect studies. This is particularly challenging for California, which has high variability in natural (e.g, wildfires, dust) and anthropogenic emissions, meteorology, topography (e.g. desert surfaces, mountains, snow cover) and land use.MethodsUsing ensemble-based deep learning with big data fused from multiple sources we developed a PM2.5 prediction model with uncertainty estimates at a high spatial (1&nbsp;km&nbsp;×&nbsp;1&nbsp;km) and temporal (weekly) resolution for a 10-year time span (2008-2017). We leveraged autoencoder-based full residual deep networks to model complex nonlinear interrelationships among PM2.5 emission, transport and dispersion factors and other influential features. These included remote sensing data (MAIAC aerosol optical depth (AOD), normalized difference vegetation index, impervious surface), MERRA-2 GMI Replay Simulation (M2GMI) output, wildfire smoke plume dispersion, meteorology, land cover, traffic, elevation, and spatiotemporal trends (geo-coordinates, temporal basis functions, time index). As one of the primary predictors of interest with substantial missing data in California related to bright surfaces, cloud cover and other known interferences, missing MAIAC AOD observations were imputed and adjusted for relative humidity and vertical distribution. Wildfire smoke contribution to PM2.5 was also calculated through HYSPLIT dispersion modeling of smoke emissions derived from MODIS fire radiative power using the Fire Energetics and Emissions Research version 1.0 model.ResultsEnsemble deep learning to predict PM2.5 achieved an overall mean training RMSE of 1.54&nbsp;μg/m3 (R2: 0.94) and test RMSE of 2.29&nbsp;μg/m3 (R2: 0.87). The top predictors included M2GMI carbon monoxide mixing ratio in the bottom layer, temporal basis functions, spatial location, air temperature, MAIAC AOD, and PM2.5 sea salt mass concentration. In an independent test using three long-term AQS sites and one short-term non-AQS site, our model achieved a high correlation (&gt;0.8) and a low RMSE (&lt;3 μg/m3). Statewide predictions indicated that our model can capture the spatial distribution and temporal peaks in wildfire-related PM2.5. The coefficient of variation indicated highest uncertainty over deciduous and mixed forests and open water land covers.ConclusionOur method can be generalized to other regions, including those having a mix of major urban areas, deserts, intensive smoke events, snow cover and complex terrains, where PM2.5 has previously been challenging to predict. Prediction uncertainty estimates can also inform further model development and measurement error evaluations in exposure and health studies