Oil prices and emerging market exchange rates

This paper investigates the role of oil prices in explaining the dynamics of selected emerging countries exchange rates. Using daily data series, the study concludes that a rise in oil price is leading to a significant appreciation in emerging economies currencies against the US dollar. In our study, we divide daily returns from 03/01/2003 to 02/06/2010 into 3 subsamples and test the role of oil price changes on exchange rate movements. We employ generalized impulse response functions to trace out the dynamic response of each exchange rate in three different time periods. Our findings suggest that oil price dynamics are changing significantly in the sample period and the relation between oil prices and exchange rates becomes more relevant after the 2008 financial crisis.oil prices; emerging market exchange rates; international financial markets; financial crisis

The Second International: The Impact of Domestic Factors on International Organization Dysfunction

Cataloged from PDF version of article.This article explores the role of domestic factors in international organization dysfunction, exemplified by the failure of the Second International to agree on a common stance and policy for the prevention of the First World War. Focusing on the French and cof these socialist parties. It concludes that these domestic differences were the source of discrepancy and lack of orchestrated action among the members of the Second International. As a result of these differences, the Second International failed to coordinate and produce a binding resolution that would commit its members to a uniform action against war, hence culminating in international organization dysfunction. © 2013 The Authors. © 2013 Political Studies Association

Optimization of morphological data in numerical taxonomy analysis using genetic algorithms feature selection method

Studies in Numerical Taxonomy are carried out by measuring characters as much as possible. The workload over scientists and labor to perform measurements will increase proportionally with the number of variables (or characters) to be used in the study. However, some part of the data may be irrelevant or sometimes meaningless. Here in this study, we introduce an algorithm to obtain a subset of data with minimum characters that can represent original data. Morphological characters were used in optimization of data by Genetic Algorithms Feature Selection method. The analyses were performed on an 18 character*11 taxa data matrix with standardized continuous characters. The analyses resulted in a minimum set of 2 characters, which means the original tree based on the complete data can also be constructed by those two characters

Added Complexity of Social Entrepreneurship: A Knowledge-Based Approach

Social entrepreneurship evades easy definition and conceptualization. In this paper we attempt to advance social entrepreneurship theoretically by examining it conceptually, from a theory of the firm perspective. If social entrepreneurship entails pursuit of a double bottom line (Dees 1998), the added complexity of the social entrepreneurial venture identified by Tracey and Phillips (2007) should be discoverable from a theory of the firm perspective. Applying the knowledge-based theory of the firm to social entrepreneurship, we aver that social entrepreneurship’s added complexity is manifest when social entrepreneurs make decisions about their knowledge. In contrast to ordinary entrepreneurs, social entrepreneurs have to balance two incommensurable objectives when they form their attitude toward protection of their knowledge

Amino-terminal cysteine residues of RGS16 are required for palmitoylation and modulation of G(i)- and G(q)-mediated signaling

RGS proteins (Regulators of G protein Signaling) are a recently discovered family of proteins that accelerate the GTPase activity of heterotrimeric G protein α subunits of the i, q, and 12 classes. The proteins share a homologous core domain but have divergent amino-terminal sequences that are the site of palmitoylation for RGS-GAIP and RGS4. We investigated the function of palmitoylation for RGS16, which shares conserved amino-terminal cysteines with RGS4 and RGS5. Mutation of cysteine residues at residues 2 and 12 blocked the incorporation of [3H]palmitate into RGS16 in metabolic labeling studies of transfected cells or into purified RGS proteins in a cell-free palmitoylation assay. The purified RGS16 proteins with the cysteine mutations were still able to act as GTPase-activating protein for Giα. Inhibition or a decrease in palmitoylation did not significantly change the amount of protein that was membrane-associated. However, palmitoylation-defective RGS16 mutants demonstrated impaired ability to inhibit both Gi- and Gq-linked signaling pathways when expressed in HEK293T cells. These findings suggest that the amino-terminal region of RGS16 may affect the affinity of these proteins for Gα subunits in vivo or that palmitoylation localizes the RGS protein in close proximity to Gα subunits on cellular membranes

Predictive Missile Guidance with Online Trajectory Learning

This study presents a predictive guidance scheme for tactical missiles. The modern day targets, with improved manoeuverability, have revealed insufficient performance of the conventional guidance laws. The underlying cause of this poor performance is the reactive nature of the conventional guidance laws such as proportional navigation (PN) and pure pursuit (PP). Predictive guidance offers an alternative approach to the classical methods by taking proactive actions by estimating target’s future trajectory. However, most of the existing predictive guidance approaches assume that the interceptor have a model of the target dynamics. A guidance strategy is developed in this study, that can learn the target dynamics iteratively and adapt the interceptor actions accordingly. A recursive least squares (RLS) estimation algorithm is employed for learning and estimating the possible future target positions, and a fixed horizon nonlinear program is employed for selecting the optimal interception action. Monte-Carlo simulations show that the guidance algorithm introduced in this work demonstrates a significantly improved performance compared to the alternatives in terms of interception time and miss distance