Nicotinic acid adenine dinucleotide phosphate (NAADP) is a potent Ca²⁺ mobilising messenger in mammalian and non-mammalian cells. Studies on a variety of cell types suggest that NAADP evokes Ca²⁺ release from a lysosome-related store and via activation of a receptor distinct from either ryanodine receptors (RyR) or inositol 1,4,5-trisphosphate (IP₃) receptors (IP₃R). However, the identity of the NAADP receptor has, until now, remained elusive. In this thesis I have shown that NAADP-evoked Ca²⁺ release from lysosomes is underpinned by two-pore channels (TPCs), of which there are 3 subtypes, TPC1, TPC2 and TPC3. When stably over-expressed in HEK293 cells, TPC2 was found to be specifically targeted to lysosomes, while TPC1 and TPC3 were targeted to endosomes. Initial Ca²⁺ signals via TPC2, but not those via TPC1, were amplified into global Ca²⁺ waves by Ca²⁺-induced Ca²⁺ release (CICR) from the endoplasmic reticulum (ER) via IP₃Rs. I have shown that, consistent with a role for TPCs in NAADP-mediated Ca²⁺ release, TPC2 is expressed in pulmonary arterial smooth muscle cells (PASMCs), is likely targeted to lysosomal membranes, and that TPCs also underpin NAADP-evoked Ca²⁺ signalling in this cell type. However, and in contrast to HEK293 cells, in PASMCs NAADP evokes spatially restricted Ca²⁺ bursts that are amplified into global Ca²⁺ waves by CICR from the sarcoplasmic reticulum (SR) via a subpopulation of RyRs, but not via IP₃Rs. I have demonstrated that lysosomes preferentially co-localise with RyR subtype 3 (RyR3) in the perinuclear region of PASMCs to comprise a “trigger zone” for Ca²⁺ signalling by NAADP, away from which a propagating Ca²⁺ wave may be carried by subsequent recruitment of RyR2. The identification of TPCs as a family of NAADP receptors may further our understanding of the mechanisms that confer the versatility of Ca²⁺ signalling which is required to regulate such diverse cellular functions as gene expression, fertilization, cell growth, and ultimately cell death.

The purpose of this study is to find out the effect of government spending on capital investments in the American Recovery and Reinvestment Act (ARRA) of 2009 on GDP and employment growth. This research utilized US quarterly data from 2003 QI to 2013 QII. In the first part the research used variables from the Keynes economic model and utilized two-stage least square analysis to assess the effect of government spending on GDP. The results from the regression analysis indicate that an increase of one dollar in government spending increases GDP by 1.569 dollars. The researcher found that the general government spending multiplier was 1.9. The coefficient for government spending in the Recovery Act was 0.383, implying that for every one dollar in government spending, Recovery Act spending on capital investments contributed 0.383 dollars. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

Part I comprises three chapters (2-4) that analyse the optimal combination of a universal benefit (B≥0) and categorical benefit (C≥0) for an economy where individuals differ in both their ability to work and, if able to work, their productivity. C is ex-ante conditioned on applicants being unable to work, and ex-post conditioned on recipients not working. In Chapter 2 the benefit budget is fixed but the test awarding C makes Type I and Type II errors. Type I errors guarantee B > 0 at the optimum to ensure all unable individuals have positive consumption. The analysis with Type II errors depends on the enforcement of the ex-post condition. Under No Enforcement C > 0 at the optimum conditional on the awards test having some discriminatory power; whilst maximum welfare falls with both error propensities. Under Full Enforcement C > 0 at the optimum always; and whilst maximum welfare falls with the Type I error propensity it may increase with the Type II error propensity. Chapters 3 and 4 generalise the analysis to a linear-income tax framework. In Chapter 3 categorical status is perfectly observable. Optimal linear and piecewise-linear tax expressions are written more generally to capture cases where it is suboptimal to finance categorical transfers to eliminate inequality in the average social marginal value of income. Chapter 4 then derives the optimal linear income tax for the case with classification errors and Full Enforcement. Both equity and efficiency considerations capture the incentives an increase in the tax rate generates for able individuals to apply for C. Part II (Chapter 5) focuses on the decisions of individuals to work when receiving C, given a risk of being detected and fined proportional to C. Under CARA preferences the risk premium associated with the variance in benefit income is convex-increasing in C, thus giving C a role in enforcement.

The dissertation suggests that geographical, institutional, religious and cultural links may be determinants of growth. We address a number of issues in this thesis. The starting point is naturally a study on growth, while the main focus is on the analysis of inequalities between countries with respect to their environment, and also on inequalities within countries.<p>The very first step of the study, presented in Chapter one, is to build such non-physical relations between countries. In this chapter, we present both the choices and methods used to model the institutional and cultural weights matrices. Chapter 1 also presents a comparative study between the different matrices built. The final aim of this chapter is to identify the differences between the geographical, institutional and cultural environment.<p>The following chapter incorporates these innovative new types of matrices in a study on growth. An externality growth model is therefore developed that takes proximities between entities into account, whether geographical, institutional or cultural. The purpose of the chapter is threefold. First, it compares the results obtained from spatial econometrics methods with classical regression, where observations of growth are considered as independent. Second, it examines whether the development of an externality model improves the quality of the estimation. Third, it investigates whether the institutional and cultural types of proximity make sense compared to the geographical one.<p>Chapter 3 narrows the analysis of countries’ dependency with regard to their neighborhood, whether geographical, institutional or religious, and a quintile regression approach allows us to check whether the countries' wealth level matters. Do the poorest countries react in the same way as richer ones regarding the wealth of their geographical, institutional and religious neighbors? The gross impact of neighboring wealth on a country’s wealth is then estimated, and some relative effects of the three matrices combined are also shown, as well as the robustness of the estimates.<p><p>Finally, Chapter 4 analyzes the dependence of poverty regarding neighborhood. The relative wealth and poverty of the neighborhood are examined as factors that can influence a country’s poverty level. The poverty index used is the proportion of people living on less than one or two dollars a day. The study only considers the developing countries as data for the developed countries on the proportion of this variable is near zero. Once again, the final aim is to check whether a country’s poverty is exacerbated by its geographical, institutional and religious neighborhood poverty or if it takes advantage of neighborhood wealth to manage its own poverty issues.<p> / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Energy and environmental impacts are two factors that will influence urban region composition in the near future. One emerging issue is the effect on water usage resulting from changes in regional or urban transportation trends. With many regions experiencing stresses on water availability, transportation planners and users need to combine information on transportation-related water consumption for any region and assess potential impacts on local water resources from the expansion of alternative transportation modes. This thesis will focus on use-phase water consumption factors for multiple vehicle modes, energy and fuel pathways, roads, and vehicle infrastructure for a given transportation network. While there are studies examining life cycle impacts for energy generation and vehicle usage, few repeatable models exist for assessing overall water consumption across several transportation modes within urban regions. As such, the question is: is it possible to develop a traceable decision support model that combines and assesses water consumption from transportation modes and related mobility infrastructure for a given mobility network? Based on this, an object-oriented system model of transportation elements was developed using the Systems Modeling Language (SysML) and Model-Based Systems Engineering principles to compare water consumption across vehicle modes for assessing the resiliency of existing infrastructure and water resources. To demonstrate the intent of this model, daily network usage water consumption will be analyzed for current and alternative network scenarios projected by policies regarding the expansion of alternative energy. The model is expected to show variations in water consumption due to fluctuations in energy pathways, market shares, and driving conditions, from which the model should help determine the feasibility of expanding alterative vehicles and fuels in these networks. While spatially explicit data is limited compared to the national averages that are used as model inputs, the analytical framework within this model closely follows that of existing assessments and the reusable nature of SysML model elements allows for the future expansion of additional transportation modes and infrastructure as well as other environmental analyses.