The impact of alcohol and drug use on employment: A labor market study using the National Longitudinal Survey of Youth

The purpose of this study was, first, to estimate of the impact of alcohol and drug use on the employment status of men and women, and second, to examine whether a history of past use, as opposed to current use, adversely affects the propensity to be employed. Using data from the National Longitudinal Survey of Youth we conducted a cross-sectional and a longitudinal analysis with logistic regression estimation to model the probability that a person was employed in 1992. In addition to usual regressors, interactions between substance use measures, between substance use measures and human capital variables, and between substance use measures and race dummies were included in the equation. The longitudinal analysis utilized a conditional likelihood method based on employment data in 1992 and 1988 and included the difference between 1992 regressors and their 1988 counterparts. A comparison was made between the prediction accuracy of the logit choice model, linear discriminant analysis, k-nearest neighbor analysis, and three modern classification methods that are used extensively in the area of machine learning. Results showed that the logit model performs relatively well in classifying individuals into employed and unemployed categories based on individual attributes. Results of the cross-sectional and longitudinal analysis were mixed, but not inconsistent with our prior expectations that use of alcohol or drug has a negative impact on a person's propensity to be employed. Cross-sectional results show a clear negative impact of past substance use on a person's employment probability among all demographic groups examined (by gender: all persons, blacks, Hispanics, families with income below the poverty line, and high users of alcohol or drugs). However, when current and past use are considered together, only women seem to experience negative impacts. The results of the longitudinal analysis are less clear, although they do indicate that negative impacts are associated with the interaction between substance use measures and human capital variables. Limitations of the study are pointed out and suggestions are made for future research.

An Integer GARCH model for a Poisson process with time varying zero-inflation

A time-varying zero-inflated serially dependent Poisson process is proposed. The model assumes that the intensity of the Poisson Process evolves according to a generalized autoregressive conditional heteroscedastic (GARCH) formulation. The proposed model is a generalization of the zero-inflated Poisson Integer GARCH model proposed by Fukang Zhu in 2012, which in return is a generalization of the Integer GARCH (INGARCH) model introduced by Ferland, Latour, and Oraichi in 2006. The proposed model builds on previous work by allowing the zero-inflation parameter to vary over time, governed by a deterministic function or by an exogenous variable. Both the Expectation Maximization (EM) and the Maximum Likelihood Estimation (MLE) approaches are presented as possible estimation methods. A simulation study shows that both parameter estimation methods provide good estimates. Applications to two real-life data sets show that the proposed INGARCH model provides a better fit than the traditional zero-inflated INGARCH model in the cases considered

A Multi-Step Nonlinear Dimension-Reduction Approach with Applications to Bigdata

In this paper, a multi-step dimension-reduction approach is proposed for addressing nonlinear relationships within attributes. In this work, the attributes in the data are first organized into groups. In each group, the dimensions are reduced via a parametric mapping that takes into account nonlinear relationships. Mapping parameters are estimated using a low rank singular value decomposition (SVD) of distance covariance. Subsequently, the attributes are reorganized into groups based on the magnitude of their respective singular values. The group-wise organization and the subsequent reduction process is performed for multiple steps until a singular value-based user-defined criterion is satisfied. Simulation analysis is utilized to investigate the performance with five big data-sets

Direct Error Driven Learning for Deep Neural Networks with Applications to Bigdata

In this paper, generalization error for traditional learning regimes-based classification is demonstrated to increase in the presence of bigdata challenges such as noise and heterogeneity. To reduce this error while mitigating vanishing gradients, a deep neural network (NN)-based framework with a direct error-driven learning scheme is proposed. To reduce the impact of heterogeneity, an overall cost comprised of the learning error and approximate generalization error is defined where two NNs are utilized to estimate the costs respectively. To mitigate the issue of vanishing gradients, a direct error-driven learning regime is proposed where the error is directly utilized for learning. It is demonstrated that the proposed approach improves accuracy by 7 % over traditional learning regimes. The proposed approach mitigated the vanishing gradient problem and improved generalization by 6%

A Statistical Solution to a Text Decoding Challenge Problem

Given an encoded unknown text message in the form of a three dimensional spatial series generated by the use of four smooth nonlinear functions, we use a method based on simple statistical reasoning to pick up samples for rebuilding the four functions. The estimated functions are then used to decode the sequence. The experimental results show that our method gives a nearly perfect decoding, enabling us to submit a 100% accurate solution to the IJCNN challenge proble

Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion

Human exposure to volatile organic compounds (VOCs) via vapor intrusion (VI) is an emerging public health concern with notable detrimental impacts on public health. Phytoforensics, plant sampling to semi-quantitatively delineate subsurface contamination, provides a potential non-invasive screening approach to detect VI potential, and plant sampling is effective and also time- and cost-efficient. Existing VI assessment methods are time- and resourceintensive, invasive, and require access into residential and commercial buildings to drill holes through basement slabs to install sampling ports or require substantial equipment to install groundwater or soil vapor sampling outside the home. Tree-core samples collected in 2 days at the PCE Southeast Contamination Site in York, Nebraska were analyzed for tetrachloroethene (PCE) and results demonstrated positive correlations with groundwater, soil, soil-gas, sub-slab, and indoor-air samples collected over a 2-year period. Because treecore samples were not collocated with other samples, interpolated surfaces of PCE concentrations were estimated so that comparisons could be made between pairs of data. Results indicate moderate to high correlation with average indoor-air and sub-slab PCE concentrations over long periods of time (months to years) to an interpolated tree-core PCE concentration surface, with Spearman\u27s correlation coefficients (ρ) ranging from 0.31 to 0.53 that are comparable to the pairwise correlation between sub-slab and indoor-air PCE concentrations (ρ = 0.55, n = 89). Strong correlations between soil-gas, sub-slab, and indoor-air PCE concentrations and an interpolated tree-core PCE concentration surface indicate that trees are valid indicators of potential VI and human exposure to subsurface environment pollutants. The rapid and non-invasive nature of tree sampling are notable advantages: even with less than 60 trees in the vicinity of the source area, roughly 12 hours of tree-core sampling with minimal equipment at the PCE Southeast Contamination Site was sufficient to delineate vapor intrusion potential in the study area and offered comparable delineation to traditional sub-slab sampling performed at 140 properties over a period of approximately 2 years

MODELING SLEEP AND WAKE BOUTS IN DROSOPHILA MELANOGASTER

Adequate sleep restores vital processes required for health and well-being; but the function and regulation of sleep is not well understood. Unfortunately, a definition of adequate sleep is unclear. On an hours-long timescale, consolidated and cycling sleep results in better health and performance outcomes. At shorter timescales, older studies report conflicting results regarding the relationship between sleep and wake bout durations. One approach to this problem has been to simply analyze the distribution of bout durations. While informative, this method eliminates the time relationship between bouts, which may be important. Here, we develop a model that describes the relationship between sleep and wake bout durations using the model organism, Drosophila melanogaster, which exhibits behavioral and molecular homology to human sleep. We present an exploratory analysis of the data to gain a better understanding of the sleep bout duration distribution by considering a broader range of potential distributions than considered in previous studies. We use the results of the distribution analysis to develop a model for sleep bout durations in the fly based upon their past sleep and wake history and find that this relationship should not be ignored

Enhanced Mutant Compensates for Defects in Rhodopsin Phosphorylation in the Presence of Endogenous Arrestin-1

We determined the effects of different expression levels of arrestin-1-3A mutant with enhanced binding to light-activated rhodopsin that is independent of phosphorylation. To this end, transgenic mice that express mutant rhodopsin with zero, one, or two phosphorylation sites, instead of six in the WT mouse rhodopsin, and normal complement of WT arrestin-1, were bred with mice expressing enhanced phosphorylation-independent arrestin-1-3A mutant. The resulting lines were characterized by retinal histology (thickness of the outer nuclear layer, reflecting the number of rod photoreceptors, and the length of the outer segments, which reflects rod health), as well as single- and double-flash ERG to determine the functionality of rods and the rate of photoresponse recovery. The effect of co-expression of enhanced arrestin-1-3A mutant with WT arrestin-1 in these lines depended on its level: higher (240% of WT) expression reduced the thickness of ONL and the length of OS, whereas lower (50% of WT) expression was harmless in the retinas expressing rhodopsin with zero or one phosphorylation site, and improved photoreceptor morphology in animals expressing rhodopsin with two phosphorylation sites. Neither expression level increased the amplitude of the a- and b-wave of the photoresponse in any of the lines. However, high expression of enhanced arrestin-1-3A mutant facilitated photoresponse recovery 2-3-fold, whereas lower level was ineffective. Thus, in the presence of normal complement of WT arrestin-1 only supra-physiological expression of enhanced mutant is sufficient to compensate for the defects of rhodopsin phosphorylation

Kandyan home gardens: Faunal repositories in Sri Lanka.

Kandyan home gardens are one of the major designs of sustainable land use systems that have evolved over hundreds of years incorporating high biodiversity and providing a diverse and stable supply of socio-economic products and service benefits to householders in Sri Lanka. A study was carried out in three home gardens in the Kandy district from May to December 2009 with the objectives of (a) identifying spatial distribution of terrestrial vertebrates in different vegetation strata, (b) their diurnal and seasonal variations, (c) plant-animal interactions, (d) nesting habits and (e) diet composition. A total of 93 terrestrial vertebrate species including seven amphibians, 23 mammals, 43 birds, and 20 reptiles were recorded. These comprised 14 endemic species, 71 native, four introduced mammals and two migrant birds. Terrestrial vertebrate assemblages were similar in Home garden 1 and 3. According to the fully-nested ANOVA, statistically significant differences were found in the composition of terrestrial vertebrates and the home gardens (P=0.005<0.05), and their vegetation strata (P=0.005<0.05). However, no statistically significant differences were observed between richness of terrestrial vertebrates and the monsoonal periods (P=0.966>0.05), as well as the time of the day (P=0.775>0.05). A positive relationship was obtained between canopy cover and number of bird nests in all home gardens (rs = +1, α = 0.05).Commensalism was the most frequently recorded relationship in all three home gardens. Overall, the diversity of animals and their interactions were different in the three Kandyan Home Gardens studied. Preventing the degradation of home gardens can be considered as a means of conserving biodiversity. There is scope to develop the Kandyan Home Garden system as an important strategy to conserve biodiversity outside the natural and protected area systems