A Simple Model of Capital Imports

Following Ramsey (1928) theoretical framework, this paper develops a dynamic model where a community is assumed to be importing two forms of foreign capital: external debt and foreign direct investment (FDI). The community is assumed to derive utility from consumption of goods and positive externalities of FDI, while deriving disutility from negative externalities of external borrowing. Results suggest that: first, a higher disutility of debt implies a higher shadow interest rate.1 The higher the utility derived from FDI, however, the lower the shadow interest rate. Second, external borrowing will be attractive as long as the relevant interest rate is less or equal to the net marginal product of capital. Third, the study of the social optimum shows that the externalities that arise from foreign capital do not affect the steady state which is always a saddle point.External borrowing, External debt, Dynamic optimization

Efficient sensitivity analysis of chaotic systems and applications to control and data assimilation

Sensitivity analysis is indispensable for aeronautical engineering applications that require optimisation, such as flow control and aircraft design. The adjoint method is the standard approach for sensitivity analysis, but it cannot be used for chaotic systems. This is due to the high sensitivity of the system trajectory to input perturbations; a characteristic of many turbulent systems. Although the instantaneous outputs are sensitive to input perturbations, the sensitivities of time-averaged outputs are well-defined for uniformly hyperbolic systems, but existing methods to compute them cannot be used. Recently, a set of alternative approaches based on the shadowing property of dynamical systems was proposed to compute sensitivities. These approaches are computationally expensive, however. In this thesis, the Multiple Shooting Shadowing (MSS) [1] approach is used, and the main aim is to develop computational tools to allow for the implementation of MSS to large systems. The major contributor to the cost of MSS is the solution of a linear matrix system. The matrix has a large condition number, and this leads to very slow convergence rates for existing iterative solvers. A preconditioner was derived to suppress the condition number, thereby accelerating the convergence rate. It was demonstrated that for the chaotic 1D Kuramoto Sivashinsky equation (KSE), the rate of convergence was almost independent of the #DOF and the trajectory length. Most importantly, the developed solution method relies only on matrix-vector products. The adjoint version of the preconditioned MSS algorithm was then coupled with a gradient descent method to compute a feedback control matrix for the KSE. The adopted formulation allowed all matrix elements to be computed simultaneously. Within a single iteration, a stabilising matrix was computed. Comparisons with standard linear quadratic theory (LQR) showed remarkable similarities (but also some differences) in the computed feedback control kernels. A preconditioned data assimilation algorithm was then derived for state estimation purposes. The preconditioner was again shown to accelerate the rate of convergence significantly. Accurate state estimations were computed for the Lorenz system.Open Acces

One gene, many phenotypes

Phenotype descriptions are valuable information right at the interface of medicine and biology. With the rapid advancement in the fi eld of genetics, thousands of genes involved in human diseases have been cloned. It was expected that knowledge of mutations would lead to consistent genotype-phenotype correlations. The understanding of mechanisms underlying genotype-phenotype discrepancies is important, as it will move clinical genetics towards predictive medicine, allowing better selection of therapeutic strategies and individualized counseling of persons affected with genetic disorders.Keywords: Gene, phenotype, mosaicism, epigenetics, pleiotropy

Feature based three-dimensional object recognition using disparity maps

The human vision system is able to recognize objects it has seen before even if the particular orientation of the object being viewed was not specifically seen before. This is due to the adaptability of the cognitive abilities of the human brain to categorize objects by different features. The features and experience used in the human recognition system are also applicable to a computer recognition system. The recognition of three-dimensional objects has been a popular area in computer vision research in recent years, as computer and machine vision is becoming more abundant in areas such as surveillance and product inspection. The purpose of this study is to explore and develop an adaptive computer vision based recognition system which can recognize 3D information of an object from a limited amount of training data in the form of disparity maps. Using this system, it should be possible to recognize an object in many different orientations, even if the specific orientation had not been seen before, as well as distinguish between different objects

ISLAM AND POLITICAL ECONOMY A Study of the Influence of Religiosity and Religiously Motivated Attitudes on Macroeconomic Performance in Countries with Substantial Muslim Presence

This thesis consists of three empirical chapters studying the relationship be- tween religion and political economy for a sample of countries with substantial Muslim presence. Chapter one is a study of the relationship between religiously motivated at- titudes and FDI for a panel of predominantly Muslim countries over a period of ten years stretching from 1997 to 2006. Instrumenting for the attitude variables, I �nd that countries with more progressive attitudes towards women and higher levels of openness towards foreigners tend to be more attractive to FDI. Chapter two examines the relationship between Islam and economic growth for a panel of countries with substantial Muslim presence over the period 1990-2008. Using instrumental variables, I show that higher levels of religiosity, measured by belief and attendance, depress economic growth. Following up on the �ndings of chapters two and three, in chapter three I inves- tigate how di�erent patterns of religious behaviour map onto economically relevant attitudes for a sample of individuals from predominantly Muslim countries. The empirical �ndings suggest that religiosity in predominantly Muslim countries is associated with conservative attitudes towards women, and intolerance towards strangers. On the other hand, religiosity is found to be associated with con�dence in state institutions, the respect of law, and pro-market attitudes. Testing for the in uence of September 11 on religiosity, I �nd that Muslims after 2001 are more religious. In this thesis I �nd that religion negatively in uences FDI by encouraging conservative attitudes towards women and intolerance towards foreigners. These attitudes are also plausible channels through which the negative in uence of reli- gion on economic growth works. I also �nd that the pro-market attitudes produced by religion are another plausible channel through which the negative in uence of religion works. Finally, the increase in religiosity after the September 11 attacks, ceteris paribus, could plausibly mean that the negative in uence of religiosity in countries with substantial Muslim presence on economic performance would in- crease

A study of brand preference: An experiential view

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityConsumer brand preference is an essential step to understand consumer choice behaviour, and has therefore always received great attention from marketers. Brand preferences reveal the type of attributes a brand possesses, to strengthen its position and increase its market share. Moreover, it forms a critical input in developing a company’s successful brand strategy, and gives insight for product development. However, the shift to experiential marketing broadens the role of the brand from a bundle of attributes to experiences. Experiential marketing also considers both, the rational and irrational assumptions of consumer behaviour. The technological advancement helped increasing the similarities between the brands attributes and product commoditisation. Consequently, consumers cannot shape their preferences among brands using rational attributes only. They seek the brand that creates experience; intrigue them in a sensorial, emotional, and creative way. Companies’ competitiveness in such market has, therefore become increasingly difficult. Their survival requires building their competitive advantage by delivering memorable experiences, which would influence consumers’ brand preferences, and consequently stimulate consumers’ purchase decisions. In the marketing literature, the traditional models are uni-dimensional, and addressing the brand preferences by consumers’ cognitive judgement of brand attributes on a rational basis. The role of experience is limited to the impact of its type on shifting preference level. Most of prior studies are partial and focusing on one or two antecedents of brand preferences. In addition to these drawbacks, the studies also ignore consequences determining the consumer purchase decisions. Based on these limitations in the literature, a lack of understanding of how consumers develop their brand preferences was identified. Accordingly, the aim of this study is to develop a model that provides an understanding of how brand knowledge and brand experiences determine brand preferences and to investigate its impact on brand repurchase intentions. In this model, the brand knowledge is defined by attribute-based beliefs, referring to consumers’ salient beliefs about the brand intrinsic cues, and non-attribute beliefs, reflected in the price, appearance, brand personality, and self-congruity. Therefore, the relative importance of brand knowledge factors contributing to brand preference is determined. Furthermore, the model addresses the interactions between the brand knowledge and brand experience in shaping brand preference. Thus, addressing how the experiences reflect embedded value in the brand offerings influencing consumer preferences. To achieve the aim of this study, a sequential mixed-method methodology combining both qualitative and quantitative research was adopted. The aim of the first qualitative phase is exploratory, using focus groups, to refine the proposed model and generate items for questionnaire development. The second phase, quantitative research, is the survey conducted using self-administrated questionnaires. The structural equation modelling (AMOS) software is used to analyse the data. The findings confirm that brand knowledge and brand experience are key sources of brand preferences. In addition, all the factors of brand knowledge have a direct positive impact on brand preferences. However, the role of brand personality on brand preference is realised through brand experience. The findings also support that the impacts of the general brand attributes and appearance on brand preference are partially mediated by brand experience. Furthermore, brand preference positively impacts repurchase intentions. The ultimate contribution of this study stems from revealing that both cognitive information processing and experiential responses form the bases of developing brand preferences, which form the link to future psychological reactions. Methodologically, the study measures the multi-dimensional constructs, brand experience and brand personality, at the aggregate level. In addition, it validates the “big-five personality” as a measure of brand personality. Pragmatically, the study suggests three levels for building brands of technological products to win consumer preferences. At the first level lies the brand functional attributes, at the second level, are the brand symbolic attributes reflected in the imagery associations and aesthetic appearance while at the third level is the brand experience. Noteworthy, these experiences are private in nature and cannot be commoditised. This model extends the notion of brand experience on preference development and can be extended in future research to build long-term consumer-brand relationship.Egyptian Ministry of Higher Education and Egyptian Cultural Bureau in Londo

Plant Growth Hormones

Many factors can cause and affect cell growth in the plant such as external (environmental) and internal factors; one of the most important internal factors is plant growth hormones. Many hormones required for cell growth, such as auxins, gibberellins, brassinosteroids, ethylene, jasmonates, salicylic acid, strigolactones and cytokinins which able to accelerate or promote growth, but, some hormone-like abscisic acid has an adverse effect on growth which increases seed dormancy by inhibiting cell growth. Also, plant hormones are able to breakdowns dormancy for many plants and can alleviate abiotic stress (salinity, extreme temperatures and, drought,…) which led to enhance germination and improve growth for many plants, whether naturally occurring in the plant or by adding it to the plant in its artificially formed or in the form of bio- or nano-fertilization in order to increase the productivity and improve its efficiency under extreme conditions. Therefore, this chapter will highlight and will provide data for the positive or/and negative effect of these hormones on many plants to achieve a rapid germination method. It will also shed light on the relationship of these hormones to some enzymes to accelerate growth