Sources and legitimacy of financial liberalization

AbstractThis article seeks to clarify how we understand domestic and international sources of globalization and specifically how we explain financial liberalization across countries. The article also develops our understanding of the underlying legitimacy of financial liberalization. We debate e.g. Abiad and Mody (2005) and others who have found political factors to have little impact on financial openness. Using the same data undergirding such conclusions we argue, in contrast, that even a slight broadening of the political variables employed in the model and much closer attention to “input” and “output” aspects of the political legitimacy of financial liberalization over time reveal a more central role for politics in shaping liberalization. Input legitimacy involves the representation of stakeholders in initial and ongoing decisions to liberalize, while “output” legitimacy concerns liberalization's distributional consequences and management thereof over time. Several empirical measures of domestic-national and international political factors plausibly influence such aspects of legitimacy and are found to play a significant role in shaping liberalization, suggesting legitimation politics to be more important to financial openness than existing studies have typically acknowledged

Finite Element Model study of the Effect of Corner Rounding on Detectability of Corner Cracks using Bolt-Hole Eddy Current

Recent work has shown that the detectability of corner cracks in bolt-holes is compromised when rounding of corners arises, as might occur during bolt-hole removal. Probability of Detection (POD) studies normally require a large number of samples of both fatigue cracks and electric discharge machined notches. In the particular instance of rounding of bolt-hole corners, the generation of such a large set of samples representing the full spectrum of potential rounding would be prohibitive. In this paper, the application of Finite Element Method (FEM) modeling is used to supplement the study of detection of cracks forming at the rounded corners of bolt-holes. FEM models show that rounding of the corner of the bolt-hole reduces the size of the response to a corner crack to a greater extent than can be accounted for by loss of crack area. This reduced sensitivity can be ascribed to a lower concentration of eddy currents at the rounded corner surface and greater lift-off of pick-up coils relative to that of a straight-edge corner. A rounding with a radius of 0.4 mm (.016 inch) showed a 20% reduction in the strength of the crack signal. Assuming linearity of the crack signal with crack size, this would suggest an increase in the minimum detectable size by 25%. Modeling results are consistent with measurements performed on cracks grown on bolt-hole samples extracted from service

The seminal legacy of the Southern African Bird Atlas Project

The first Southern African Bird Atlas Project was launched in 1986 and gathered bird distribution data from six countries of southern Africa. The project culminated with the publication of The Atlas of Southern African Birds in 1997. The database generated by the project, seven million bird distribution records, has been widely used by four groups: environmental consultants (for example, to locate electricity transmission lines), conservationists (planning conservation strategies), research scientists (especially macro-ecologists and biogeographers) and birders (ecotourism materials). By 2007, the database had spawned 50 research publications and eight Ph.D.s and master's degrees. These products are a tribute to the more than 5000 'citizen scientists', who gathered the bulk of the data. The atlas concept has been extended to frogs, reptiles, spiders and butterflies; a second bird atlas started in 2007 and will, for example, facilitate knowledge of the impact of environmental change on birds. The South African National Biodiversity Institute is playing a lead role in initiating these new projects

Evaluation of Machine Learning Tools for Inspection of Steam Generator Tube Structures using Pulsed Eddy Current

Inspection of multi-component systems, such as nuclear steam generator (SG) tube support structures, is complicated by multiple overlapping degradation modes. The simultaneous and precise measurement of more than two interdependent parameters is challenging when standard statistical regression analysis tools are used. Artificial neural networks (ANNs) have recently been applied to pulsed eddy current (PEC) data for inspection of Alloy 800 SG tube fretting, in the presence of tube off-set within a corroded ferromagnetic support structure. Signals were analyzed using modified principal component analysis (MPCA) followed by an ANN analysis, which simultaneously targeted four parameters associated with the support structure. These were hole diameter, tube off-centering in two mutually orthogonal directions and fret depth. In this work, the ANN analysis is compared with that performed by a Support Vector Machine (SVM) analysis of the same data. Comparable results are achieved for some parameters with both machine learning analysis tools. However, parameters with changing signal variance, such as those associated with support structure diameter, are not as easily compensated for using standard SVM analysis. Both techniques also rely on the availability of a representative training data set that may be difficult to come by for general inspection conditions