Associations amongst Mental Health Indicators and Adolescent Risk Behaviors: The 2003 North Carolina Youth Risk Behavior Survey

This investigation examined the relationship between self-reported mental health difficulties and risk behaviors in adolescents. The first question asked whether or not gender, race, or disability status predicted adolescent responses to selected mental health indicators from the 2003 North Carolina Youth Risk Behavior Survey (YRBS). The second question examined whether or not the experience of mental health indicators predicted engagement in the selected risk behavior indicators. Finally, the third question examined interactions between the mental health indicators and gender, race, and ethnicity to determine whether those interactions would predict experience of the risk behavior indicators. Participants were 9th, 10th, 11th, and 12th grade high school students (N=2553) from randomly selected high schools in North Carolina. While all of the models analyzed showed that the data itself demonstrated a good fit statistically, none of the models using mental health or risk behavior indicators as an outcome were successful for predicting group membership. Although significant contributions to the outcome variables were found for all models, the variance explained by the predictor variables was very small, ranging from 1% to 13%. Among the most consistent predictors were gender, disability status, and suicidal ideation. These results support the need for further research on the relationship between mental health and risk behaviors as the basis for defining prevention and intervention programs.Doctor of Philosoph

In-situ Estimation of Time-averaging Uncertainties in Turbulent Flow Simulations

The statistics obtained from turbulent flow simulations are generally uncertain due to finite time averaging. The techniques available in the literature to accurately estimate these uncertainties typically only work in an offline mode, that is, they require access to all available samples of a time series at once. In addition to the impossibility of online monitoring of uncertainties during the course of simulations, such an offline approach can lead to input/output (I/O) deficiencies and large storage/memory requirements, which can be problematic for large-scale simulations of turbulent flows. Here, we designed, implemented and tested a framework for estimating time-averaging uncertainties in turbulence statistics in an in-situ (online/streaming/updating) manner. The proposed algorithm relies on a novel low-memory update formula for computing the sample-estimated autocorrelation functions (ACFs). Based on this, smooth modeled ACFs of turbulence quantities can be generated to accurately estimate the time-averaging uncertainties in the corresponding sample mean estimators. The resulting uncertainty estimates are highly robust, accurate, and quantitatively the same as those obtained by standard offline estimators. Moreover, the computational overhead added by the in-situ algorithm is found to be negligible. The framework is completely general and can be used with any flow solver and also integrated into the simulations over conformal and complex meshes created by adopting adaptive mesh refinement techniques. The results of the study are encouraging for the further development of the in-situ framework for other uncertainty quantification and data-driven analyses relevant not only to large-scale turbulent flow simulations, but also to the simulation of other dynamical systems leading to time-varying quantities with autocorrelated samples

Explorative In-situ Analysis of Turbulent Flow Data Based on a Data-Driven Approach

The Proper Orthogonal Decomposition (POD) has been used for several years in the post-processing of highly-resolved Computational Fluid Dynamics (CFD) simulations. While the POD can provide valuable insights into the spatial-temporal behaviour of single transient flows, it can be challenging to evaluate and compare results when applied to multiple simulations. Therefore, we propose a workflow based on data-driven techniques, namely dimensionality reduction and clustering to extract knowledge from large simulation bundles from transient CFD simulations. We apply this workflow to investigate the flow around two cylinders that contain complex modal structures in the wake region. A special emphasis lies on the formulation of in-situ algorithms to compute the data-driven representations during run-time of the simulation. This can reduce the amount of data inand output and enables a simulation monitoring to reduce computational efforts. Finally, a classifier is trained to predict characteristic physical behaviour in the flow only based on the input parameters

In-situ Estimation of Time-averaging Uncertainties in Turbulent Flow Simulations

The statistics obtained from turbulent flow simulations are generally uncertain due to finite time averaging. The techniques available in the literature to accurately estimate these uncertainties typically only work in an offline mode, that is, they require access to all available samples of a time series at once. In addition to the impossibility of online monitoring of uncertainties during the course of simulations, such an offline approach can lead to input/output (I/O) deficiencies and large storage/memory requirements, which can be problematic for large-scale simulations of turbulent flows. Here, we designed, implemented and tested a framework for estimating time-averaging uncertainties in turbulence statistics in an in-situ (online/streaming/updating) manner. The proposed algorithm relies on a novel low-memory update formula for computing the sample-estimated autocorrelation functions (ACFs). Based on this, smooth modeled ACFs of turbulence quantities can be generated to accurately estimate the time-averaging uncertainties in the corresponding sample mean estimators. The resulting uncertainty estimates are highly robust, accurate, and quantitatively the same as those obtained by standard offline estimators. Moreover, the computational overhead added by the in-situ algorithm is found to be negligible. The framework is completely general and can be used with any flow solver and also integrated into the simulations over conformal and complex meshes created by adopting adaptive mesh refinement techniques. The results of the study are encouraging for the further development of the in-situ framework for other uncertainty quantification and data-driven analyses relevant not only to large-scale turbulent flow simulations, but also to the simulation of other dynamical systems leading to time-varying quantities with autocorrelated samples

Research Experiences for Teachers in Sensor Networks

This report discusses research on applications of logic flowcharting with a focus in autonomous robotic operations. This research project is part of Research Experiences for Teachers (RET) in Sensor Networks, a National Science Foundation (NSF) funded grant project

Research Experiences for Teachers in Sensor Networks

This report discusses research on GPS/GSM based tracking systems for the recovery of high power model rockets. This research is part of Research Experiences for Teachers (RET) in Sensor Education, a National Science Foundation (NSF) funded grant project

Ergosterol Effect on the Desaturation of 14C-Cis-Vaccenate in Tetrahymena

Supplement of ergosterol to the growth medium of the ciliated protozoan Tetrahymena pyriformis W leads to incorporation of the foreign sterol within cell membranes and suppression of synthesis of the native sterol-like compound tetrahymanol, as well as to changes in the fatty acid compositions of several major classes of membrane lipid. Alteration of fatty acid composition is thought to represent a regulatory mechanism whereby optimum membrane fluidity is maintained when the slightly dissimilar foreign sterol is added into the phospholipid bilayer of the membranes. The present study, using several different conditions of growth temperature, substrate concentrations and incubation time, and ergosterol concentrations and exposure time, is an attempt to provide evidence supporting a hypothetical regulatory mechanism. This mechanism proposes that there is a feedback regulation by membrane-bound sterol on an enzyme or enzymes involved in synthesis of the long chain fatty acids contained in membrane phospholipid. Such a mechanism could account for the balance between sterol and fatty acid content of membrane. The data presented here show that a statistically significant increase in desaturation of 14C-cis-vaccenate can be demonstrated in Tetrahymena cell cultures whose membranes contain the foreign sterol, when growth temperature is maintained at 20° or 29.5°. Tetrahymena desaturated 14C-cis-vaccenate substrate in both ergosterol supplemented and normal cultures. The 14C labeled product, 6,11-18:2 was recovered and separated by silver nitrate-Unisil column chromatography

PROSPECT: A comprehensive sample acquisition and analysis package for lunar science and exploration

PROSPECT is a comprehensive payload package developed by the European Space Agency which will support the extraction and analysis of lunar surface and subsurface samples as well as the acquisition of data from additional environmental sensors. The key elements of PROSPECT are the ProSEED drill and the ProSPA analytical laboratory. ProSEED will support the acquisition of cryogenic samples from depths up to 1 m and deliver them to the ProSPA instrument. ProSPA will receive and seal samples in miniaturized ovens, heat them, physically and chemically process the released volatiles, and analyze the obtained constituents via mass spectrometry using two types of spectrometers. Contextual information will be provided by cameras which will generate multi-spectral images of the drill working area and of acquired samples, and via temperature sensors and a permittivity sensor that are integrated in the drill rod. The package is designed for minimizing volatile loss from the sample between acquisition and analysis. Initially developed for a flight on the Russian Luna-27 mission, the payload package design was adapted for a more generic lander accommodation and will be flown on a lunar polar lander mission developed within the NASA Commercial Lunar Payload Services (CLPS) program. PROSPECT targets science and exploration in lunar areas that might harbor deposits of volatiles, and also supports the demonstration of In-Situ Resource Utilization (ISRU) techniques in the lunar environment. PROSPECT operations are designed to be automated to a significant degree but rely on operator monitoring during critical phases. Here, we report the PROSPECT flight design that will be built, tested, and qualified according to European space technology engineering standards before delivery to the lander provider for spacecraft integration. The package is currently in the hardware manufacturing and integration phase with a target delivery to the NASA-selected CLPS lander provider in 2025