Covariant Spectator Theory of heavy–light and heavy mesons and the predictive power of covariant interaction kernels

The Covariant Spectator Theory (CST) is used to calculate the mass spectrum and vertex functions of heavy–light and heavy mesons in Minkowski space. The covariant kernel contains Lorentz scalar, pseudoscalar, and vector contributions. The numerical calculations are performed in momentum space, where special care is taken to treat the strong singularities present in the confining kernel. The observed meson spectrum is very well reproduced after fitting a small number of model parameters. Remarkably, a fit to a few pseudoscalar meson states only, which are insensitive to spin–orbit and tensor forces and do not allow to separate the spin–spin from the central interaction, leads to essentially the same model parameters as a more general fit. This demonstrates that the covariance of the chosen interaction kernel is responsible for the very accurate prediction of the spin-dependent quark–antiquark interactions.

Farmacogenética/Farmacogenómica

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

Genome-wide association studies of quantitative traits with related individuals: Little (power) lost but much to be gained

For complex disease genetics research in human populations, remarkable progress has been made in recent times with the publication of a number of genome-wide association scans (GWAS) and subsequent statistical replications. These studies have identified new genes and pathways implicated in disease, many of which were not known before. Given these early successes, more GWAS are being conducted and planned, both for disease and quantitative phenotypes. Many researchers and clinicians have DNA samples available on collections of families, including both cases and controls. Twin registries around the world have facilitated the collection of large numbers of families, with DNA and multiple quantitative phenotypes collected on twin pairs and their relatives. In the design of a new GWAS with a fixed budget for the number of chips, the question arises whether to include or exclude related individuals. It is commonly believed to be preferable to use unrelated individuals in the first stage of a GWAS because relatives are 'over-matched' for genotypes. In this study, we quantify that for GWAS of a quantitative phenotype, relative to a sample of unrelated individuals surprisingly little power is lost when using relatives. The advantages of using relatives are manifold, including the ability to perform more quality control, the choice to perform within-family tests of association that are robust to population stratification, and the ability to perform joint linkage and association analysis. Therefore, the advantages of using relatives in GWAS for quantitative traits may well outweigh the small disadvantage in terms of statistical power.

Association of Major Power Consumers in Ontario records, 1975-1989

The Association of Major Power Consumers in Ontario (AMPCO) was founded as the Niagara Basic Power Users' Association in the early 1960s. It was a coalition of seven companies in the chemical, pulp and paper, and abrasives industries within the Niagara region. The Association was formed to address increasing electricity rates. In 1974, the name changed to the Association of Direct Customers of Ontario. This change reflected the expansion of the regional Association to a provincial one, which grew in response to Ontario Hydro’s proposed rate increases of over 30 per cent. In 1975, the Association adopted its current name. AMPCO continues to advocate for “electricity rates that are competitive, fair and efficient, and a reliable supply of electrical energy across Ontario.”

On the operationalisation of conceptions of learning in higher education and their association with students’ knowledge and experiences of their learning

Conceptions of learning, as well as other associated aspects of prior knowledge, are theoretically important factors in influencing the manner in which the content and context of learning are engaged. The present study reports on: (a) the operationalisation of some of these factors aimed at isolating sources of explanatory variation that can be used for modelling purposes; and (b) a conservative exploration of the discriminatory power of, and exhibited patterns of association between, such sources of variation as have been isolated. Based on a conservative analytical approach, the results of the present study do not support a single clearly defined empirical model of conceptions of learning and associated constructs. Instead, there is consistent evidence that underlying empirical structures appear to be sensitive to the response context and other factors.

Quantum heat engines: A thermodynamic analysis of power and efficiency

We show that the operation and the output power of a quantum heat engine that converts incoherent thermal energy into coherent cavity photons can be optimized by manipulating quantum coherences. The gain or loss in the efficiency at maximum power depends on the details of the output power optimization. Quantum effects tend to enhance the output power and the efficiency as the photon occupation in the cavity is decreased.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis.

BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Genome-wide association analysis of feed intake and residual feed intake in Nellore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Network-based genome-wide association study of Crohn's disease

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. Many recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. The current study incorporated gene network information into gene-based analysis of GWAS data for Crohn's disease (CD). The purpose was to develop statistical models to boost the power of identifying disease-associated genes and gene subnetworks by maximizing the use of existing biological knowledge from multiple sources. The results revealed that Markov random field (MRF) based mixture model incorporating direct neighborhood information from a single gene network is not efficient in identifying CD-related genes based on the GWAS data. The incorporation of solely direct neighborhood information might lead to the low efficiency of these models. Alternative MRF models looking beyond direct neighboring information are necessary to be developed in the future for the purpose of this study.^

The High Frequency Component of Heart Rate Variability and Delta EEG Power during Sleep in Healthy Women and Women with Irritable Bowel Syndrome

Thesis (Ph.D.)--University of Washington, 2016-06

Towards a definition of the performing AudioVisualist

The evolution of the laptop computer as a musical instrument in the 1990s provided a tool for empowering the solo musician and divergent approaches to the application of this technology in performance remain consistently debated.  The increasing ubiquity of digital media combined with the power of current generation notebook technology has provided the perfect platform to realise integrated audio-visual toolsets that respond to musical controllers and provide mixed-media results.  Despite emerging practitioners increasingly availing themselves to the musical affordances of this technology, theoretical discussion in the field ignores the various approaches a solo musician might take in developing integrated media works for performance.   In an increasingly crowded niche there is a clear compulsion to consider expanded modes of performance, yet lacking any formal framework these integrations can easily alienate an audience, distract from performance and lead to criticisms of novelty for novelty's sake. 

Biosecurity threats : the design of surveillance systems, based on power and risk

We consider the problem of designing a surveillance system to detect a broad range of invasive species across a heterogeneous sampling frame. We present a model to detect a range of invertebrate invasives whilst addressing the challenges of multiple data sources, stratifying for differential risk, managing labour costs and providing sufficient power of detection.We determine the number of detection devices required and their allocation across the landscape within limiting resource constraints. The resulting plan will lead to reduced financial and ecological costs and an optimal surveillance system.

Testing advertising via new media : an exploratory study of advertising practitioner attitudes

New media, as a free and universal communication tool, has had an impact on the power of the general public to comment on a variety of issues. As the public can comment favourably or unfavourably on advertisements, such as on Youtube, the advertising industry must start using weblogs to research reaction to their advertising campaigns. This exploratory study examines the responses of some advertising industry practitioners, both advertisers and agencies, on the impact of new media, specifically weblogs, and the use of new media as a source of research on advertising campaigns.