Believability and Attitudes toward Alcohol Warning Label Information: The Role of Persuasive Communications Theory

Based on tenets of persuasive communications theory, five recently proposed alcohol warning labels are examined for their differential impact on label believability and attitudes. While all warnings are rated as believable, the ones regarding birth defects and driving impairment are perceived to be significantly more believable than the others. In addition, persons with more favorable attitudes toward alcohol consumption tend to disbelieve specific instance hazards (e.g., birth defects, driving impairment and drug combination warnings), while disliking longterm risks of alcohol consumption and abuse (e.g., hypertension, liver disease, cancer and addiction warnings). Implications for public policy and researchers are discussed

Barrier island erosion and overwash study -- effect of seawalls. Volume 2

This is the second of a pair of reports documenting the effects of storms on beach systems including the presence of seawalls. With the aim of simulating the effects of overwash on barrier islands with seawalls and characterizing their response, a series of eight experiments was conducted at the Coastal Engineering Laboratory of the University of Florida. The barrier island was simulated by a 400 feet wide horizontal crest and an initially uniform mildly-sloped (1:19) beach. The effects of positioning the seawall at two different locations as well as the effects of various storm surge levels and accompanying overtopping were investigated. Experiments were conducted with both regular and irregular storm waves. With the seawall located at the slope break between the crest and the sloping beach of the barrier island, and the crest of the seawall just submerged in sand, the effects on the sediment transport process were found to be minimal. For the same position of the seawall but with the crest of the seawall raised above the surrounding ground level, overtopping caused washover of sand indicating substantial transport in suspension. Increased levels of overtopping tended to accentuate bed profile changes but supress bar formation (as did irregular waves). Positioning the seawall at the Mean Sea Level shoreline caused significant scour both immediately landward as well as immediately seaward of the seawall. A prominent scour trough developed further seaward. The longshore bar was highly three-dimensional. It appears that seawalls need to be located adequately landward of the shoreline to discharge their function effectively without adverse effect to the beach. In addition, concerns for safety warrant the presence of an adequate buffer-zone between the seawall and the upland property. (61 pp.

Using neural networks in software repositories

The first topic is an exploration of the use of neural network techniques to improve the effectiveness of retrieval in software repositories. The second topic relates to a series of experiments conducted to evaluate the feasibility of using adaptive neural networks as a means of deriving (or more specifically, learning) measures on software. Taken together, these two efforts illuminate a very promising mechanism supporting software infrastructures - one based upon a flexible and responsive technology

Believability and Attitudes toward Alcohol Warning Label Information: The Role of Persuasive Communications Theory

Based on tenets of persuasive communications theory, five recently proposed alcohol warning labels are examined for their differential impact on label believability and attitudes. While all warnings are rated as believable, the ones regarding birth defects and driving impairment are perceived to be significantly more believable than the others. In addition, persons with more favorable attitudes toward alcohol consumption tend to disbelieve specific instance hazards (e.g., birth defects, driving impairment and drug combination warnings), while disliking longterm risks of alcohol consumption and abuse (e.g., hypertension, liver disease, cancer and addiction warnings). Implications for public policy and researchers are discussed

Genome-wide mapping of gene-microbiota interactions in susceptibility to epidermolysis bullosa acquisita

The skin is in constant contact with the environment and serves a critical barrier function, yet provides a range of niches to inhabiting microbial communities. A multitude of interactions between the skin microbiota, host and environment contribute to community structure and its potential contribution to changes in health status is well known. Susceptibility to chronic inflammatory diseases is determined by the interaction of immunogenetic and environmental risk factors. In particular, resident microbial communities as environmental factors are the subject of intense scrutiny due to numerous observations of differences in community composition or structure are of primary etiological importance or secondary to the altered inflammatory environment remains largely unknown. Epidermolysis bullosa acquisita (EBA) is a chronic skin blistering disease of autoimmune origin characterized by antibodies to type VII collagen (COL7). This study provides experimental evidence for host gene-microbiota interactions contributing to disease risk in a mouse immunization model of EBA. By using an advanced intercross mouse population, genetic loci contributing to variability in the skin microbiota were simultaneously identified along with susceptibility to EBA and their overlap. QTL mapping of the skin microbiota with susceptibility to EBA demonstrates the involvement of host gene-microbe interactions in disease. Furthermore, treating the abundances of individual bacterial species as covariates with disease lead to the discovery of a novel disease locus. The majority of the identified covariate taxa were characterized by a reduction in abundance being associated with increased disease risk. This provides evidence of a primary role for individual bacterial species abundances in disease susceptibility and underscores their importance in protection from disease. Interestingly, in a parallel study in this thesis, mice that did not develop clinical disease showed a higher diversity in their skin microbial communities before disease induction. This further demonstrates the importance of skin community in predictive of EBA disease outcome. Thus, further characterization of these putative probiotic species or species assemblages offers promising potential for preventative and therapeutic treatment development.Table of Contents Acknowledgements .......................................................................................................... I Declaration of Author’s Contribution ......................................................................... II List of Figures ................................................................................................................ V List of Tables .............................................................................................................. VIII Summary ....................................................................................................................... IX 1. Introduction ................................................................................................................. 1 1.1 Skin microbiota ..................................................................................................................... 2 1.1.1 Skin microbiota characterization ......................................................................................... 3 1.1.2 Factors influencing skin microbiota composition ............................................................... 6 1.1.3 Skin microbiota association with health and disease .......................................................... 7 1.2 Autoimmunity and Autoimmune diseases ......................................................................... 8 1.2.1 Why study Autoimmune diseases? ...................................................................................... 8 1.2.2 Autoimmune skin blistering diseases .................................................................................. 9 1.3 Epidermolysis Bullosa Acquisita ....................................................................................... 10 1.3.1 Mouse models to study EBA ............................................................................................. 11 1.3.2 Genetics of EBA ................................................................................................................ 13 1.4 Scope of the thesis ............................................................................................................... 15 2 Materials and Methods .............................................................................................. 19 2.1 Generation of a four way advanced intercross lines ....................................................... 19 2.2 SJL/J mice ........................................................................................................................... 19 2.3 Recombinant peptides ........................................................................................................ 20 2.4 Induction of experimental EBA and observation protocol ............................................. 20 2.5 Genomic DNA extraction for genotyping ......................................................................... 21 2.6 G4 population genotyping .................................................................................................. 21 2.7 Bacterial DNA extraction and 16S rRNA gene pyrosequencing .................................... 22 2.8 454 pyrosequencing data analysis ..................................................................................... 23 2.8.1 Pre-processing steps .......................................................................................................... 23 2.8.2 OTU determination ............................................................................................................ 24 2.8.3 Sequence alignment ........................................................................................................... 25 2.8.4 Normalization using rarefaction method ........................................................................... 26 2.8.5 Alpha diversity analysis .................................................................................................... 27 2.8.6 Beta diversity analysis ....................................................................................................... 29 2.8.7 Indicator species analysis .................................................................................................. 30 2.8.8 Taxonomy classification .................................................................................................... 31 2.9 Data preparation for QTL analysis .................................................................................. 32 2.10 Core measurement microbiota ........................................................................................ 32 2.11 QTL analysis ..................................................................................................................... 33 2.11.1 Model selection ............................................................................................................... 35 2.11.2 QTL mapping .................................................................................................................. 36 3. Results ........................................................................................................................ 40 3.1 Skin bacterial diversity ....................................................................................................... 40 3.1.1 Microbial communities in healthy and EBA afflicted individuals .................................... 45 3.1.1.1 Alpha diversity ................................................................................................................ 46 3.1.1.2 Beta diversity .................................................................................................................. 49 3.1.1.3 Indicator species analysis ................................................................................................ 51 3.2 Skin microbiota role in EBA susceptibility ...................................................................... 54 3.3 Factors influencing skin microbiota .................................................................................. 59 3.3.1 Cage .................................................................................................................................. 59 3.3.2 Family ............................................................................................................................... 60 3.4 QTL analysis of skin microbiota ....................................................................................... 60 3.4.1 Effects of immunization on QTL mapping ........................................................................ 62 3.5 Genetics association of EBA ............................................................................................... 64 3.6 Genetics and skin microbiota interaction ......................................................................... 64 4. Discussion ................................................................................................................... 71 5. Bibliography .............................................................................................................. 80 6. Appendices ................................................................................................................. 95 6.1 Appendix A – Additional figures ....................................................................................... 95 6.2 Appendix B – Additional tables ....................................................................................... 104 7. Scientific achievements during doctoral research ................................................ 122 8. Affidavit ................................................................................................................... 125 9. Copyright Statement ............................................................................................... 126 10. Index ....................................................................................................................... 13

A neural net-based approach to software metrics

Software metrics provide an effective method for characterizing software. Metrics have traditionally been composed through the definition of an equation. This approach is limited by the fact that all the interrelationships among all the parameters be fully understood. This paper explores an alternative, neural network approach to modeling metrics. Experiments performed on two widely accepted metrics, McCabe and Halstead, indicate that the approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics

Non-local quantum correlations and detection processes in QFT

Quantum detection processes in QFT must play a key role in the description of quantum field correlations, such as the appearance of entanglement, and of causal effects. We consider the detection in the case of a simple QFT model with a suitable interaction to exact treatment, consisting of a quantum scalar field coupled linearly to a classical scalar source. We then evaluate the response function to the field quanta of two-level point-like quantum model detectors, and analyze the effects of the approximation adopted in standard detection theory. We show that the use of the RWA, that characterizes the Glauber detection model, leads in the detector response to non-local terms corresponding to an instantaneously spreading of source effects over the whole space. Other detector models, obtained with non-standard or the no-application of RWA, give instead local responses to field quanta, apart from source independent vacuum contribution linked to preexisting correlations of zero-point field.Comment: 23 page