A Pragmatic Approach to Ethical Inquiry on Transhuman Athletes and Gene Doping in Sport

Gene doping is the most recent addition to the list of banned practices formulated by the World Anti-doping Agency. It is a subset of doping that utilizes the technology involved in gene therapy. The latter is still in the experimental phase but has the potential to be used as a type of medical treatment involving alterations of a patient‘s genes. I apply a pragmatic form of ethical inquiry to evaluate the application of this medical innovation in the context of sport for performance-enhancement purposes and how it will affect sport, the individual, society and humanity at large. I analyze the probable ethical implications that will emerge from such procedures in terms of values that lie at the heart of the major arguments offered by scholars on both affirmative and opposing sides of the debate on gene doping, namely fairness, autonomy and the conception of what it means to be human.

Delineation of within-site terroir effects using soil and vine water measurements in Riesling vineyards within the Niagara Peninsula

The major focus of this dissertation was to explain terroir effects that impact wine varietal character and to elucidate potential determinants of terroir by testing vine water status (VWS) as the major factor of the terroir effect. It was hypothesized that consistent water status zones could be identified within vineyard sites, and, that differences in vine performance, fruit composition and wine sensory attributes could be related to VWS. To test this hypothesis, ten commercial Riesling vineyards representative of each Vintners Quality Alliance sub-appellation were selected. Vineyards were delineated using global positioning systems and 75 to 80 sentinel vines per vineyard were geo-referenced for data collection. During the 2005 to 2007 growing seasons, VWS measurements [midday leaf water potential ('l')] were collected from a subset of these sentinel vines. Data were collected on soil texture and composition, soil moisture, vine performance (yield components, vine size) and fruit composition. These variables were mapped using global information system (GIS) software and relationships between them were elucidated. Vines were categorized into "low" and "high" water status regions within each vineyard block and replicate wines were made from each. Many geospatial patterns and relationships were spatially and temporally stable within vineyards. Leaf'l' was temporally stable within vineyards despite different weather conditions during each growing season. Generally, spatial relationships between 'l', soil moisture, vine size, berry weight and yield were stable from year to year. Leaf", impacted fruit composition in several vineyards. Through sorting tasks and multidimensional scaling, wines of similar VWS had similar sensory properties. Descriptive analysis further indicated that VWS impacted wine sensory profiles, with similar attributes being different for wines from different water status zones. Vineyard designation had an effect on wine profiles, with certain sensory and chemical attributes being associated from different subappellations. However, wines were generally grouped in terms of their regional designation ('Lakeshore', 'Bench', 'Plains') within the Niagara Peninsula. Through multivariate analyses, specific sensory attributes, viticulture and chemical variables were associated with wines of different VWS. Vine water status was a major contributor to the terroir effect, as it had a major impact on vine size, berry weight and wine sensory characteristics.

Regulation of Systemic Acquired Resistance through the Interaction of Arabidopsis thaliana Transcription factors TGAI and TGA2 with NPRI

Arabidopsis thaliana is an established model plant system for studying plantpathogen interactions. The knowledge garnered from examining the mechanism of induced disease resistance in this model system can be applied to eliminate the cost and danger associated with current means of crop protection. A specific defense pathway, known as systemic acquired resistance (SAR), involves whole plant protection from a wide variety of bacterial, viral and fungal pathogens and remains induced weeks to months after being triggered. The ability of Arabidopsis to mount SAR depends on the accumulation of salicylic acid (SA), the NPRI (non-expressor of pathogenesis related gene 1) protein and the expression of a subset of pathogenesis related (PR) genes. NPRI exerts its effect in this pathway through interaction with a closely related class of bZIP transcription factors known as TGA factors, which are named for their recognition of the cognate DNA motif TGACG. We have discovered that one of these transcription factors, TGA2, behaves as a repressor in unchallenged Arabidopsis and acts to repress NPRI-dependent activation of PRJ. TGA1, which bears moderate sequence similarity to TGA2, acts as a transcriptional activator in unchallenged Arabidopsis, however the significance of this activity is J unclear. Once SAR has been induced, TGAI and TGA2 interact with NPRI to form complexes that are capable of activating transcription. Curiously, although TGAI is capable of transactivating, the ability of the TGAI-NPRI complex to activate transcription results from a novel transactivation domain in NPRI. This transactivation domain, which depends on the oxidation of cysteines 521 and 529, is also responsible for the transactivation ability of the TGA2-NPRI complex. Although the exact mechanism preventing TGA2-NPRI interaction in unchallenged Arabidopsis is unclear, the regulation of TGAI-NPRI interaction is based on the redox status of cysteines 260 and 266 in TGAl. We determined that a glutaredoxin, which is an enzyme capable of regulating a protein's redox status, interacts with the reduced form of TGAI and this interaction results .in the glutathionylation of TGAI and a loss of interaction with NPRl. Taken together, these results expand our understanding of how TGA transcription factors and NPRI behave to regulate events and gene expression during SAR. Furthermore, the regulation of the behavior of both TGAI and NPRI by their redox status and the involvement of a glutaredoxin in modulating TGAI-NPRI interaction suggests the redox regulation of proteins is a general mechanism implemented in SAR.

Educator Evaluation of Academic and Social Competence in Students with Acquired Brain Injury (ABI) Relative to Assessed Performance and Sense of Belonging

Acquired brain injury (ABI) is the leading cause of death and disability amongst children and adolescents andpresents itself with challenges associated in cognitive, social, emotional, and behavioural domains. These changes may interfere with academic performance and social inclusion, influencing self-esteem and personal success. The current study examined a subset of data to capture the sense of academic and social belonging for students with ABI as a function of the classroom teachers’ subjective perception of ability, their ABI knowledge, and student identification. Overall, a discrepancy was found between educators’ subjective ratings of student performance and students’ neurocognitive capacity. Educator knowledge and identification of ABI influenced student success in academic and social domains independent of teaching approach. This research has implications for the identification of ABI in the classroom and related challenges students experience. Educators are underprepared for the reintegration of students returning to school and lack appropriate knowledge and strategies to accommodate individual needs.

A Survey of hMLH1 mRNA Splicing Profiles in Human Cell Lines: Comparing Primary Cultured Fibroblasts Before and After Oxidative Stress and Transiently versus Stably Demethylated Colon Cancer Derived Cell Lines

Most human genes undergo alternative splicing and loss of splicing fidelity is associated with disease. Epigenetic silencing of hMLH 1 via promoter cytosine methylation is causally linked to a subset of sporadic non-polyposis colon cancer and is reversible by 5-aza-2' -deoxycytidine treatment. Here I investigated changes in hMLHI mRNA splicing profiles in normal fibroblasts and colon cancer-derived human cell lines. I established the types and frequencies of hMLHI mRNA transcripts generated under baseline conditions, after hydrogen peroxide induced oxidative stress, and in acutely 5-aza-2' -deoxycytidine-treated and stably derepressed cancer cell lines. I found that hMLHI is extensively spliced under all conditions including baseline (50% splice variants), the splice variant distribution changes in response to oxidative stress, and certain splice variants are sensitive to 5- aza-2' -deoxycytidine treatment: Splice variant diversity and frequency of exon 17 skipping correlates with the level of hMLHI promoter methylation suggesting a link between promoter methylation and mRNA splicing.

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes.

In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only require the existence of conditional densities. They are proved for possibly nonstationary and/or non-Gaussian multivariate Markov processes. In the context of a linear regression model with AR(1) errors, we show how these results can be used to simplify the distributional properties of the model by conditioning a subset of the data on the remaining observations. This transformation leads to a new model which has the form of a two-sided autoregression to which standard classical linear regression inference techniques can be applied. We show how to derive tests and confidence sets for the mean and/or autoregressive parameters of the model. We also develop a test on the order of an autoregression. We show that a combination of subsample-based inferences can improve the performance of the procedure. An application to U.S. domestic investment data illustrates the method.

Efficiency in Uncertain Cooperative Games

A contingent contract in a transferable utility game under uncertainty specifies an outcome for each possible state. It is assumed that coalitions evaluate these contracts by considering the minimal possible excesses. A main question of the paper concerns the existence and characterization of efficient contracts. It is shown that they exist if and only if the set of possible coalitions contains a balanced subset. Moreover, a characterization of values that result in efficient contracts in the case of minimally balanced collections is provided.

Bayesian Analysis for a Theory of Random Consumer Demand: The Case of Indivisible Goods

McCausland (2004a) describes a new theory of random consumer demand. Theoretically consistent random demand can be represented by a \"regular\" \"L-utility\" function on the consumption set X. The present paper is about Bayesian inference for regular L-utility functions. We express prior and posterior uncertainty in terms of distributions over the indefinite-dimensional parameter set of a flexible functional form. We propose a class of proper priors on the parameter set. The priors are flexible, in the sense that they put positive probability in the neighborhood of any L-utility function that is regular on a large subset bar(X) of X; and regular, in the sense that they assign zero probability to the set of L-utility functions that are irregular on bar(X). We propose methods of Bayesian inference for an environment with indivisible goods, leaving the more difficult case of indefinitely divisible goods for another paper. We analyse individual choice data from a consumer experiment described in Harbaugh et al. (2001).

Von Neumann-Morgenstern Stable Sets in Matching Problems

The following properties of the core of a one well-known: (i) the core is non-empty; (ii) the core is a lattice; and (iii) the set of unmatched agents is identical for any two matchings belonging to the core. The literature on two-sided matching focuses almost exclusively on the core and studies extensively its properties. Our main result is the following characterization of (von Neumann-Morgenstern) stable sets in one-to-one matching problem only if it is a maximal set satisfying the following properties : (a) the core is a subset of the set; (b) the set is a lattice; (c) the set of unmatched agents is identical for any two matchings belonging to the set. Furthermore, a set is a stable set if it is the unique maximal set satisfying properties (a), (b) and (c). We also show that our main result does not extend from one-to-one matching problems to many-to-one matching problems.

Top-Cycle Rationalizability

We identify necessary and sufficient conditions for the choice set from every subset A of a (finite) universal set X to coincide with the top cycle in A of some fixed tournament on X.

Etude théorique des propriétés électroniques et optiques des super-réseaux de Si/SiO2

FRANCAIS: L'observation d'une intense luminescence dans les super-réseaux de Si/SiO2 a ouvert de nouvelles avenues en recherche théorique des matériaux à base de silicium, pour des applications éventuelles en optoélectronique. Le silicium dans sa phase cristalline possède un gap indirect, le rendant ainsi moins intéressant vis-à-vis d'autres matériaux luminescents. Concevoir des matériaux luminescents à base de silicium ouvrira donc la voie sur de multiples applications. Ce travail fait état de trois contributions au domaine. Premièrement, différents modèles de super-réseaux de Si/SiO2 ont été conçus et étudiés à l'aide de calculs ab initio afin d'en évaluer les propriétés structurales, électroniques et optiques. Les deux premiers modèles dérivés des structures cristallines du silicium et du dioxyde de silicium ont permis de démontrer l'importance du rôle de l'interface Si/SiO2 sur les propriétés optiques. De nouveaux modèles structurellement relaxés ont alors été construits afin de mieux caractériser les interfaces et ainsi mieux évaluer la portée du confinement sur les propriétés optiques. Deuxièmement, un gap direct dans les modèles structurellement relaxés a été obtenu. Le calcul de l'absorption (par l'application de la règle d'or de Fermi) a permis de confirmer que les propriétés d'absorption (et d'émission) du silicium cristallin sont améliorées lorsque celui-ci est confiné par le SiO2. Un décalage vers le bleu avec accroissement du confinement a aussi été observé. Une étude détaillée du rôle des atomes sous-oxydés aux interfaces a de plus été menée. Ces atomes ont le double effet d'accroître légèrement le gap d'énergie et d'aplanir la structure électronique près du niveau de Fermi. Troisièmement, une application directe de la théorique des transitions de Slater, une approche issue de la théorie de la fonctionnelle de la densité pour des ensembles, a été déterminée pour le silicium cristallin puis comparée aux mesures d'absorption par rayons X. Une très bonne correspondance entre cette théorie et l'expérience est observée. Ces calculs ont été appliqués aux super-réseaux afin d'estimer et caractériser leurs propriétés électroniques dans la zone de confinement, dans les bandes de conduction.

Sustainability = Good Design

Sustainable design is fundamentally a subset of good design.The description of good design will eventually include criteria for the creation of a healthy environment and energy efficiency. These goals will be achieved by an emergent paradigm of design practice:integration.At every level design interests will come together to facilitate common goals for the creation of a rewarding present and a healthy future. Interdisciplinary design teams will flourish. Inter-accommodating and fluidly communicating political structures will grow. Coalescing social values and economic forces will propel integrated strategies. Unique and innovative solutions will increasingly become the objective. One eventual outcome of this integrated or sustainable design practice will be the development of buildings that produce more energy than they consume.