Spontaneity and international marketing performance

Purpose: The purpose of this paper is to ascertain how today’s international marketers can perform better on the global scene by harnessing spontaneity. Design/methodology/approach: The authors draw on contingency theory to develop a model of the spontaneity – international marketing performance relationship, and identify three potential moderators, namely, strategic planning, centralization, and market dynamism. The authors test the model via structural equation modeling with survey data from 197 UK exporters. Findings: The results indicate that spontaneity is beneficial to exporters in terms of enhancing profit performance. In addition, greater centralization and strategic planning strengthen the positive effects of spontaneity. However, market dynamism mitigates the positive effect of spontaneity on export performance (when customer needs are volatile, spontaneous decisions do not function as well in terms of ensuring success). Practical implications: Learning to be spontaneous when making export decisions appears to result in favorable outcomes for the export function. To harness spontaneity, export managers should look to develop company heuristics (increase centralization and strategic planning). Finally, if operating in dynamic export market environments, the role of spontaneity is weaker, so more conventional decision-making approaches should be adopted. Originality/value: The international marketing environment typically requires decisions to be flexible and fast. In this context, spontaneity could enable accelerated and responsive decision-making, allowing international marketers to realize superior performance. Yet, there is a lack of research on decision-making spontaneity and its potential for international marketing performance enhancement.

Students’ Use of Knowledge Resources in Environmental Interaction on an Outdoor Learning Trail

This study examined how students leveraged different types of knowledge resources on an outdoor learning trail. We positioned the learning trail as an integral part of the curriculum with a pre- and post-trail phase to scaffold and to support students’ meaning-making process. The study was conducted with two classes of secondary two students. We coded two groups’ discourse to examine the use of knowledge resource types in the meaning-making process in an outdoor learning setting: contextual resource, new conceptual resource, prior knowledge resource, as well as the relationship among these knowledge resource types. Next, we also examined environmental interaction and integration in the students’ use of these knowledge resource types. Analysis showed that contextual resources are chiefly instrumental in fostering students’ capacity to harness new conceptual resource and to activate prior knowledge resource in interacting with and integrating the outdoor learning environment in the meaning-making process.

Complete framework for efficient characterisation of non-Markovian processes

A non-Markovian process is one that retains `memory' of its past. A systematic understanding of these processes is necessary to fully describe and harness a vast range of complex phenomena; however, no such general characterisation currently exists. This long-standing problem has hindered advances in understanding physical, chemical and biological processes, where often dubious theoretical assumptions are made to render a dynamical description tractable. Moreover, the methods currently available to treat non-Markovian quantum dynamics are plagued with unphysical results, like non-positive dynamics. Here we develop an operational framework to characterise arbitrary non-Markovian quantum processes. We demonstrate the universality of our framework and how the characterisation can be rendered efficient, before formulating a necessary and sufficient condition for quantum Markov processes. Finally, we stress how our framework enables the actual systematic analysis of non-Markovian processes, the understanding of their typicality, and the development of new master equations for the effective description of memory-bearing open-system evolution.

A state-of-the-art review and feasibility analysis of high altitude wind power in Northern Ireland

In many countries wind energy has become an indispensable part of the electricity generation mix. The opportunity for ground based wind turbine systems are becoming more and more constrained due to limitations on turbine hub heights, blade lengths and location restrictions linked to environmental and permitting issues including special areas of conservation and social acceptance due to the visual and noise impacts. In the last decade there have been numerous proposals to harness high altitude winds, such as tethered kites, airfoils and dirigible based rotors. These technologies are designed to operate above the neutral atmospheric boundary layer of 1,300 m, which are subject to more powerful and persistent winds thus generating much higher electricity capacities. This paper presents an in-depth review of the state-of-the-art of high altitude wind power, evaluates the technical and economic viability of deploying high altitude wind power as a resource in Northern Ireland and identifies the optimal locations through considering wind data and geographical constraints. The key findings show that the total viable area over Northern Ireland for high altitude wind harnessing devices is 5109.6 km2, with an average wind power density of 1,998 W/m2 over a 20-year span, at a fixed altitude of 3,000 m. An initial budget for a 2MW pumping kite device indicated a total cost £1,751,402 thus proving to be economically viable with other conventional wind-harnessing devices.

Characterization of High-Performance Organic Dyes for Dye-Sensitized Solar Cell: A DFT/TDDFT Study

Dye-sensitized solar cell (DSSC) is currently a promising technology that makes solar energy efficient and cost-effective to harness. In DSSC, metal free dyes, such indoline-containing D149 and D205, are proved to be potential alternatives for traditional metal organic dyes. In this work, a DFT/TDDFT characterization for D149 and D205 were carried out using different functionals, including B3LYP, MPW1K, CAM-B3LYP and PBE0. Three different conformers for D149 and four different conformers for D205 were identified and calculated in vacuum. The performance of different functionals on calculating the maximum absorbance of the dyes in vacuum and five common solvents (acetonitrile, chloroform, ethanol, methanol, and THF) were examined and compared to determine the suitable computational setting for predicting properties of these two dyes. Furthermore, deprotonated D149 and D205 in solvents were also considered, and the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were calculated, which elucidates the substitution effect on the rhodanine ring of D149 and D205 dyes on their efficiency. Finally, D149 and D205 molecules were confirmed to be firmly anchored on ZnO surface by periodic DFT calculations. These results would shed light on the design of new highly efficiency metal-free dyes.

Challenges and Opportunities in Edge Computing

Many cloud-based applications employ a data centre as a central server to process data that is generated by edge devices, such as smartphones, tablets and wearables. This model places ever increasing demands on communication and computational infrastructure with inevitable adverse effect on Quality-of-Service and Experience. The concept of Edge Computing is predicated on moving some of this computational load towards the edge of the network to harness computational capabilities that are currently untapped in edge nodes, such as base stations, routers and switches. This position paper considers the challenges and opportunities that arise out of this new direction in the computing landscape.

Emergence and Innovation in Digital Learning: Foundations and Applications

Educational systems worldwide are facing an enormous shift as a result of sociocultural, political, economic, and technological changes. The technologies and practices that have developed over the last decade have been heralded as opportunities to transform both online and traditional education systems. While proponents of these new ideas often postulate that they have the potential to address the educational problems facing both students and institutions and that they could provide an opportunity to rethink the ways that education is organized and enacted, there is little evidence of emerging technologies and practices in use in online education. Because researchers and practitioners interested in these possibilities often reside in various disciplines and academic departments the sharing and dissemination of their work across often rigid boundaries is a formidable task. Contributors to Emergence and Innovation in Digital Learning include individuals who are shaping the future of online learning with their innovative applications and investigations on the impact of issues such as openness, analytics, MOOCs, and social media. Building on work first published in Emerging Technologies in Distance Education, the contributors to this collection harness the dispersed knowledge in online education to provide a one-stop locale for work on emergent approaches in the field. Their conclusions will influence the adoption and success of these approaches to education and will enable researchers and practitioners to conceptualize, critique, and enhance their understanding of the foundations and applications of new technologies.

DESARROLLO DE APLICACIÓN MÓVIL DE REALIDAD AUMENTADA PARA INSTITUCIONES EDUCATIVAS.

El propósito de esta investigación es el desarrollo de una aplicación que pueda instalarse y utilizarse en dispositivos móviles, tales como celulares o tablets, mediante la cual los usuarios tendrán acceso inmediato a contenidos multimedia que brindarán información complementaria a los materiales de estudio presentados en carreras de grado, tecnicaturas, diplomaturas y cursos. Dicho programa tendrá la capacidad de escanear e interpretar un patrón de Realidad Aumentada ubicado en materiales impresos permitiendo la reproducción de vídeos, archivos de audio y gráficos en 3D, entre otros usos. Este desarrollo, utilizado como recurso didáctico para la enseñanza, enriquecerá la experiencia del alumno durante el momento de estudio ya que le permitirá integrar realidad y virtualidad de manera inmediata generando una interactividad con los contenidos que lo llevará a ser un participante activo del proceso de aprendizaje, lo que redundará en un aumento de la motivación y la eficacia de los materiales de estudio. The purpose of this research is to develop an application that can be installed and used on mobile devices such as phones or tablets, through which users will have immediate access to multimedia content that will provide additional information to study materials presented in racing degree, technical programs and courses. This program will have the ability to scan and interpret a pattern of augmented reality located in printed materials allowing playback of video, audio and 3D graphics, among other uses. This development, which is used as a teaching resource for teaching, enrich the student""s experience during the time of study as it will enable to integrate reality and virtuality immediately generate interactivity with the content that will be an active participant in the learning process, which will result in increased motivation and the effectiveness of the study materials.

Approaches to Developing Educational Resources Using AI Embedded in Computer Game Technology. A Case Study: Primary School Literacy

In this extended abstract, we discuss recent research at Worcester into the inclusion of AI into ‘Serious Games’. Serious Games research intends to harness the power of computer game technology to produce educational and training materials. We prefer the name ‘Immersive Environments’ (IEs) since this emphasises the human psychological dimension. Creation of compelling and convincing learning software requires a rich engagement of the learner, and a convincing learning experience. We believe that various aspects of the AI tradition can inform the production of such learning.

Evolutionary dynamics under various modes of reproduction

Thesis (Ph.D.)--University of Washington, 2016-08

From Aari to Zulu: Massively Multilingual Creation of Language Tools using Interlinear Glossed Text

Thesis (Ph.D.)--University of Washington, 2016-08

Gobernar la educación a través de los padrespolítica educativa y construcción de subjetividades neoliberales en Inglaterra. (Governing education through parents: education policy and the construction of neoliberal subjectivities in England)

In this paper we explore the relationship between market norms and practices and the development of the figure of the parent within British education policy. Since the 1970s parents in England have been called upon to perform certain duties and obligations in their relation to the state. These duties include internalizing responsibility for risks, liabilities, inequities and the spectre of crises formerly managed by the state. Rather than characterize this situation in terms of the ‘hollowing of the state’, we argue that the role of the state includes enabling the functioning of the parent as a neoliberal subject, so that they may successfully harness the power of the market to their own advantage and (hopefully) minimize the kinds of risk generated through a deregulated education system. In this paper we examine how parents are compelled to embody certain market norms and practices as they navigate the field of education. In particular we focus on how parents are 1) summoned as consumers or choosers of education services, and thus encouraged to embody through their behaviour a competitive orientation; 2) summoned as governors and custodians of schools, with a focus on assessing financial and educational performance; and 3) summoned as producers and founders of schools, with a focus on entrepreneurial and innovative activity.

Governing through parents: a genealogical enquiry of education policy and the construction of neoliberal subjectivities in England

In this paper we explore the various spaces and sites through which the figure of the parent is summoned and activated to inhabit and perform market norms and practices in the field of education in England. Since the late 1970s successive governments have called on parents to enact certain duties and obligations in relation to the state. These duties include adopting and internalizing responsibility for all kinds of risks, liabilities and inequities formerly managed by the Keynesian welfare state. Rather than characterize this situation in terms of the ‘hollowing of the state’, we argue that the role of the state includes enabling the functioning of the parent as a neoliberal subject so that they may successfully harness the power of the market to their own advantage and (hopefully) minimize the kinds of risk and inequity generated through a market-based, deregulated education system. In this paper we examine how parents in England are differently, yet similarly, compelled to embody certain market norms and practices as they navigate the field of education. Adopting genealogical enquiry and policy discourse analysis as our methodology, we explore how parents across three policy sites or spaces are constructed as objects and purveyors of utility and ancillaries to marketisation. This includes a focus on how parents are summoned as 1) consumers or choosers of education services; 2) governors and overseers of schools; and 3) producers and founders of schools.

Conception optimale d’une chaîne de traction électrique pour une voiture de type Formule SAE

La Formule SAE (Society of Automotive Engineers) est une compétition étudiante consistant en la conception et la fabrication d’une voiture de course monoplace. De nombreux événements sont organisés à chaque année au cours desquels plusieurs universités rivalisent entre elles lors d’épreuves dynamiques et statiques. Celles-ci comprennent l’évaluation de la conception, l’évaluation des coûts de fabrication, l’accélération de la voiture, etc. Avec plus de 500 universités participantes et des événements annuels sur tous les continents, il s’agit de la plus importante compétition d’ingénierie étudiante au monde. L’équipe ULaval Racing a participé pendant plus de 20 ans aux compétitions annuelles réservées aux voitures à combustion. Afin de s’adapter à l’électrification des transports et aux nouvelles compétitions destinées aux voitures électriques, l’équipe a conçu et fabriqué une chaîne de traction électrique haute performance destinée à leur voiture 2015. L’approche traditionnelle employée pour concevoir une motorisation électrique consiste à imposer les performances désirées. Ces critères comprennent l’inclinaison maximale que la voiture doit pouvoir gravir, l’autonomie désirée ainsi qu’un profil de vitesse en fonction du temps, ou tout simplement un cycle routier. Cette approche n’est malheureusement pas appropriée pour la conception d’une traction électrique pour une voiture de type Formule SAE. Ce véhicule n’étant pas destiné à la conduite urbaine ou à la conduite sur autoroute, les cycles routiers existants ne sont pas représentatifs des conditions d’opération du bolide à concevoir. Ainsi, la réalisation de ce projet a nécessité l’identification du cycle d’opération routier sur lequel le véhicule doit opérer. Il sert de point de départ à la conception de la chaîne de traction composée des moteurs, de la batterie ainsi que des onduleurs de tension. L’utilisation d’une méthode de dimensionnement du système basée sur un algorithme d’optimisation génétique, suivie d’une optimisation locale couplée à une analyse par éléments-finis a permis l’obtention d’une solution optimale pour les circuits de type Formule SAE. La chaîne de traction conçue a été fabriquée et intégrée dans un prototype de voiture de l’équipe ULaval Racing lors de la saison 2015 afin de participer à diverses compétitions de voitures électriques.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.