The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development.

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children's polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Factors affecting transition to second year of an engineering degree

Much research has focused on students’ transition from secondary school to university. Less is known about the transition from first to second year of a university degree programme. Given the difficulties that many students face at this stage of their education, research into the relevant factors is required. Through questionnaires and focus groups, views of second- and third-year aerospace and mechanical engineering students in our university have been gathered. A large majority believed that both the volume and difficulty of work increased in second year. Many stated that first year was slightly too trivial and could have been made more challenging to prepare them better for second year. Different teaching and assessment styles in second year were considered to affect attendance and performance. The survey revealed that students were generally very well settled into university life by the end of first year and were happy with their choice of course and only 23% reported that financial responsibilities have had a negative effect on their academic performance. Differences were observed between male and female students. Male students believed that transition was helped by having regular assessments and by worked examples in lectures. Females found the teaching staff were the most helpful factor for a successful transition. The results indicate that males require more structure and guidance whereas females are more independent and settle in better.

Positive psychology – The second wave

It is nearly twenty years since Martin Seligman used his 1998 American Psychological Association presidential address to inaugurate the notion of ‘positive psychology.’ The rationale for its creation was Seligman’s contention that psychology had hitherto tended to focus mainly on what is wrong with people, on dysfunction, disorder and distress. There were of course pockets of scholarship that held a candle for human potential and excellence, like humanistic psychology. Nevertheless, on the whole, he argued that concepts such as happiness did not attract much attention or credibility in mainstream psychology. Emerging to redress this lacuna, positive psychology soon became a fertile new paradigm, encompassing research into a panoply of processes and qualities that could be deemed ‘positive,’ from overarching constructs such as flourishing, to more specific concepts like hope.

Accessible Immersion Metrics (AIM) for Second Language Acquisition : A Constructivist Innovation for the ESL Classroom

Abstract: This study was designed to validate a constructivist learning framework, herein referred to as Accessible Immersion Metrics (AIM), for second language acquisition (SLA) as well as to compare two delivery methods of the same framework. The AIM framework was originally developed in 2009 and is proposed as a “How to” guide for the application of constructivist learning principles to the second language classroom. Piloted in 2010 at Champlain College St-Lambert, the AIM model allows for language learning to occur, free of a fixed schedule, to be socially constructive through the use of task-based assessments and relevant to the learner’s life experience by focusing on the students’ needs rather than on course content.||Résumé : Cette étude a été principalement conçu pour valider un cadre d'apprentissage constructiviste, ci-après dénommé Accessible Immersion Metrics - AIM, pour l'acquisition d'une langue seconde - SLA. Le cadre de l'AIM est proposé comme un mode d'emploi pour l'application des principes constructivistes à l'apprentissage d’une langue seconde. Créé en 2009 par l'auteur, et piloté en 2010 au Collège Champlain St-Lambert, le modèle de l'AIM permet l'apprentissage des langues à se produire, sans horaire fixe et socialement constructive grâce à l'utilisation des évaluations alignées basées sur des tâches pertinentes à l'expérience de vie de l'étudiant en se concentrant sur les besoins des élèves plutôt que sur le contenu des cours.

Our own language: Scots verse translation and the second-generation Scottish renaissance

This thesis examines the role of Scots language verse translation in the second-generation or post-war Scottish Renaissance. The translation of European poetry into Scots was of central importance to the first-generation Scottish Renaissance of the nineteen twenties and thirties. As Margery Palmer McCulloch has shown, the wider cultural climate of Anglo-American modernism was key to MacDiarmid’s conception of the interwar Scottish Renaissance. What was the effect on second-generation poet-translators as the modernist moment passed? Are the many translations undertaken by the younger poets who emerged in the course of the nineteen forties and fifties a faithful reflection of this cultural inheritance? To what extent are they indicative of a new set of priorities and international influences? The five principal translators discussed in this thesis are Douglas Young (1913-1973), Sydney Goodsir Smith (1915-1975), Robert Garioch (1909-1981), Tom Scott (1918-1995) and William J. Tait (1918-1992). Each is the subject of a chapter, in many cases providing the first or most extensive treatment of particular translations. While the pioneering work of John Corbett, Bill Findlay and J. Derrick McClure, among other scholars, has drawn attention to the long history of literary translation into Scots, this thesis is the first extended critical work to take the verse translations of the post-MacDiarmid makars as its subject. The nature and extent of MacDiarmid’s influence is considered throughout, as are the wider discourses around language and translation in twentieth-century Scottish poetry. Critical engagement with a number of key insights from theoretical translation studies helps to situate these writers’ work in its global context. This thesis also explores the ways in which the specific context of Scots translation allows scholars to complicate or expand upon theories of translation developed in other cultural situations (notably Lawrence Venuti’s writing on domestication and foreignisation). The five writers upon whom this thesis concentrates were all highly individual, occasionally idiosyncratic personalities. Young’s polyglot ingenuity finds a foil in Garioch’s sharp, humane wit. Goodsir Smith’s romantic ironising meets its match in Scott’s radical certainty of cause. Tait’s use of the Shetlandic tongue sets him apart. Nonetheless, despite the great variety of style, form and tone shown by each of these translators, this thesis demonstrates that there are meaningful links to be made between them and that they form a unified, coherent group in the wider landscape of twentieth-century Scottish poetry. On the linguistic level, each engaged to some extent in the composition of a ‘synthetic’ or ‘plastic’ language deriving partly from literary sources, partly from the spoken language around them. On a more fundamental level, each was committed to enriching this language through translation, within which a number of key areas of interest emerge. One of the most important of these key areas is Gaelic – especially the poetry of Sorley MacLean, which Young, Garioch and Goodsir Smith all translated into Scots. This is to some extent an act of solidarity on the part of these Scots poets, acknowledging a shared history of marginalisation as well as expressing shared hopes for the future. The same is true of Goodsir Smith’s translations from a number of Eastern European poets (and Edwin Morgan’s own versions, slightly later in the century). The translation of verse drama by poets is another key theme sustained throughout the thesis, with Garioch and Young attempting to fill what they perceived as a gap in the Scots tradition through translation from other languages (another aspect of these writers’ legacy continued by Morgan). Beyond this, all of the writers discussed in this thesis translated extensively from European poetries from Ancient Greece to twentieth-century France. Their reasons for doing so were various, but a certain cosmopolitan idealism figures highly among them. So too does a desire to see Scotland interact with other European nations, thus escaping the potentially narrowing influence of post-war British culture. This thesis addresses the legacy of these writers’ translations, which, it argues, continue to exercise a perceptible influence on the course of poetry in Scotland. This work constitutes a significant contribution to a much-needed wider critical re-assessment of this pivotal period in modern Scottish writing, offering a fresh perspective on the formal and linguistic merits of these poets’ verse translations. Drawing upon frequently obscure book, pamphlet and periodical sources, as well as unpublished manuscripts in the National Library of Scotland and the Shetland Archives, this thesis breaks new ground in its investigation of the role of Scots verse translation in the second-generation Scottish Renaissance.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

CHARACTERISTICS OF PRIVATE HIGH SCHOOLS FOR STUDENTS WITH EMOTIONAL DISABILITIES AND PERCEPTIONS OF THEIR PUBLIC SCHOOL CASE MANAGERS

Placement of students with disabilities in private special-education schools remains costly and controversial. This is particularly concerning, given the lack of research on the characteristics and quality of these restrictive settings. The purpose of this study was to identify the academic and vocational course offerings and behavioral supports provided in private special-education schools the serve high school students with emotional disabilities (ED). Second, the research examined the perceptions of the quality of services in these setting from the perspectives of public school case managers. Using a mixed-method design to collect data, 9 administrative heads of private special-education schools were surveyed, and 7 public school case managers were interviewed. Results indicated that (a) private special-education schools offer the basic academic core courses needed to meet graduation requirements, (b) vocational options for students enrolled in these schools are quite limited, (c) these schools provide a variety of behavioral interventions and supports, and (d) case managers are concerned with the lack of academic rigor and inconsistent programming at these schools but applauded the notion that students with ED are exiting with a high school diploma. Findings from this study may have policy implications for improving and developing programming options for high school students with ED.

Golf course irrigation and self-sufficiency water in Southern Spain

During the first decade of the 21st century, many golf courses were developed in the Southeast of Spain, which greatly increased the number of these facilities. Almost all of these golf courses have been accompanied by large residential developments composed of thousands of dwelling units. This article seeks to identify the factors that influence golf courses’ water consumption and estimate the number of dwelling units that an associated residential development needs to have to provide the effluent necessary to fully meet the irrigation needs of a golf course. The study indicates that private golf courses achieve greater levels of irrigation efficiency than public golf courses and that the golf courses associated with residential developments subject the irrigation needs of the grassland to the sale requirements of the real estate properties. The study also estimates that a golf course requires approximately 3000 dwelling units with an average annual occupancy of 33% to achieve self-sufficiency for irrigation.

Corrigendum to “The envelope theorem for multiobjective convex programming via contingent derivatives” [J. Math. Anal. Appl. 372 (1) (2010) 197–207]

The aim of this note is to formulate an envelope theorem for vector convex programs. This version corrects an earlier work, “The envelope theorem for multiobjective convex programming via contingent derivatives” by Jiménez Guerra et al. (2010) [3]. We first propose a necessary and sufficient condition allowing to restate the main result proved in the alluded paper. Second, we introduce a new Lagrange multiplier in order to obtain an envelope theorem avoiding the aforementioned error.

The Impact of a Classroom Performance System on Learning Gains in a Biology Course for Science Majors

This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as “Clickers”, improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.

Character in Context: Informing Character Education Programming

The Positive Youth Development (PYD) perspective is a strength-based conceptualization of youth. It highlights the importance of mutually beneficial relationships between youth and their environment to develop the “Five Cs”, key assets that include character. Character has long been a subject of programming due to its focus on helping children lead moral, empathic, and prosocial lives. There are, however, many limitations in character research, including poorly operationalized definitions of character; a failure to examine the developmental and broader social context in which character exists; and a lack of evaluation of more practical character programming. The goal of this dissertation was to address these gaps in knowledge and inform the character education programming literature. The first study examined the relationships among age, gender, the school social context, and character. Moral character was negatively associated with grade, and being a girl was positively associated with moral character. The relationships between positive peer interactions at school and character (fairness, integrity) were stronger among students who reported low initial moral character when positive peer interactions was high. In the second study, the Build Character: Build Success Program, a character education program, was evaluated over six months to examine its effects on character behaviours, victimization, and school climate. No program effects were found for students in grades 1 to 3, but a slight decrease in victimization in one experimental school was found for students in grades 4 to 8. This lack of general program effects may be due to the short-term nature of the intervention, which may not have been long enough to result in measurable behaviour change. Implementation data indicated that teachers did not teach all program elements, which also may have influenced the results of the program evaluation. The present dissertation contributes to knowledge about character and its programming by: introducing new measures to operationalize character, discovering developmental patterns in character in school-aged children, highlighting gender differences in character, examining character within its broad social context, and evaluating short-term character education programming.

New Rigorous Decomposition Methods for Mixed-integer Linear and Nonlinear Programming

Process systems design, operation and synthesis problems under uncertainty can readily be formulated as two-stage stochastic mixed-integer linear and nonlinear (nonconvex) programming (MILP and MINLP) problems. These problems, with a scenario based formulation, lead to large-scale MILPs/MINLPs that are well structured. The first part of the thesis proposes a new finitely convergent cross decomposition method (CD), where Benders decomposition (BD) and Dantzig-Wolfe decomposition (DWD) are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. A variant of CD, which includes multiple columns per iteration of DW restricted master problem and multiple cuts per iteration of BD relaxed master problem, called multicolumn-multicut CD is then developed to improve solution time. Finally, an extended cross decomposition method (ECD) for solving two-stage stochastic programs with risk constraints is proposed. In this approach, a CD approach at the first level and DWD at a second level is used to solve the original problem to optimality. ECD has a computational advantage over a bilevel decomposition strategy or solving the monolith problem using an MILP solver. The second part of the thesis develops a joint decomposition approach combining Lagrangian decomposition (LD) and generalized Benders decomposition (GBD), to efficiently solve stochastic mixed-integer nonlinear nonconvex programming problems to global optimality, without the need for explicit branch and bound search. In this approach, LD subproblems and GBD subproblems are systematically solved in a single framework. The relaxed master problem obtained from the reformulation of the original problem, is solved only when necessary. A convexification of the relaxed master problem and a domain reduction procedure are integrated into the decomposition framework to improve solution efficiency. Using case studies taken from renewable resource and fossil-fuel based application in process systems engineering, it can be seen that these novel decomposition approaches have significant benefit over classical decomposition methods and state-of-the-art MILP/MINLP global optimization solvers.

Investigating the learning potential of the Second Quantum Revolution: development of an approach for secondary school students

In recent years we have witnessed important changes: the Second Quantum Revolution is in the spotlight of many countries, and it is creating a new generation of technologies. To unlock the potential of the Second Quantum Revolution, several countries have launched strategic plans and research programs that finance and set the pace of research and development of these new technologies (like the Quantum Flagship, the National Quantum Initiative Act and so on). The increasing pace of technological changes is also challenging science education and institutional systems, requiring them to help to prepare new generations of experts. This work is placed within physics education research and contributes to the challenge by developing an approach and a course about the Second Quantum Revolution. The aims are to promote quantum literacy and, in particular, to value from a cultural and educational perspective the Second Revolution. The dissertation is articulated in two parts. In the first, we unpack the Second Quantum Revolution from a cultural perspective and shed light on the main revolutionary aspects that are elevated to the rank of principles implemented in the design of a course for secondary school students, prospective and in-service teachers. The design process and the educational reconstruction of the activities are presented as well as the results of a pilot study conducted to investigate the impact of the approach on students' understanding and to gather feedback to refine and improve the instructional materials. The second part consists of the exploration of the Second Quantum Revolution as a context to introduce some basic concepts of quantum physics. We present the results of an implementation with secondary school students to investigate if and to what extent external representations could play any role to promote students’ understanding and acceptance of quantum physics as a personal reliable description of the world.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.