Cultural relativism in the Poisonwood Bible

In her novel The Poisonwood Bible, Barbara Kingsolver explores this same ethnocentric missionary zeal when critiquing the ways in which Western countries relate to “foreign” countries. She creates an allegory where the Price Family and the Congolese people are a microcosm of the United States and its relations to “foreign” countries. In this allegory, Kingsolver suggests that the attempt of the U.S. to change what it does not understand can be detrimental and unethical – that the attempt to spread an ethical system becomes the most unethical idea of all

An analytical model of crenulate shaped beaches

An analytical model for the development of crenulate shaped beaches is constructed. It is assumed that the shape of the crenulate shaped beach remains constant with time and expands with a rate according to a time function. Based upon a sediment balance, a simplified model of wave diffraction and refraction and a nearshore current model an expression for the shape function and the time function of crenulate shaped beaches is derived. It is shown that in the diffraction zone the time function should follow a t1/3 law, while for the refraction zone the well known t1/2 law is found. This implies that the evolution of a crenulate beach in the diffraction zone should initially be faster and on the long term slower than is found in refraction zones. The hypothesis is verified using available data. The resulting shape function of crenulate shaped beaches is expressed in terms of the diffracted wave field

A global-local optimization method for problems in structural dynamics

The optimization of complex structures involving many design variables and constraints can be performed using a multi-level approach: a structure consisting of several components is optimized as a whole (global) and on the component level (local). Earlier work [1], [2], [3], described a multilevel technique developed for the optimization the Airbus A380 vertical tail plane. In this application, a global model is used to calculate the loads on each of the components. These components are then optimized using the prescribed loads, followed by a new global calculation to update the loads. The component optimization strategy is based on Neural Networks (NN) and Genetic Algorithms (GA). This paper describes a strategy that makes this global-local optimization method possible for problems in structural dynamics. It is established that a parametrization of the component interactions (e.g. component loads) is problematic due to frequency dependence. Hence, a modified method is proposed in which the speed of Component Mode Synthesis (CMS) is used to avoid this parametrization. The effectiveness of this method is demonstrated in a test case concerning the placement of sensor and actuator locations in Active Structural Acoustic Control (ASAC). Special attention is paid to the behavior of the optimization strategy

Water Emissions Trading in Europe: A Literature Overview and Discussion of Opportunities

This report is about Water Emissions Trading (WET or Water Quality Trading) in Europe. The goal is to inform about the basic principles, provide an overview of studies done in Europe, and suggest some future opportunities for WET in Europe

The pick-up of cometary protons by the solar wind

The High Energy Range Spectrometer (HERS) of the Ion Mass Spectrometer on the Giotto spacecraft measured the 3-dimensional distribution of picked-up cometary protons over a distance of approximately 8 million km upstream of the bow shock of Comet Halley. The protons were observed to be elastically scattered out of their original cycloidal trajectories such that they were nonuniformly distributed over a spherical shell in velocity space. The shell radius (relative to its expected radius) and thickness increased as the bow shock was approached. Downstream of the shock, the cometary protons could not be distinguished from the heated solar wind protons

Numerical modelling of erosion and sedimentation around offshore pipelines

In this paper a numerical model is presented for the description of the erosion and sedimentation near pipelines on the sea bottom. The model is based on the Navier-Stokes equations and the equation of motion and continuity of sediment.\ud \ud The results of the simulations have been compared with the results of tests in a large-scale facility. The agreement between the results of the simulations and the experimental results is good.\ud \ud The applicability of the method is twofold: firstly, the processes of erosion and sedimentation around bodies on the sea bottom can be simulated; secondly, the method can be used for the design of pipelines, including erosion stimulating elements, such as spoilers

Assessment of flood damages and benefits of remedial actions: "What are the weak links?"; with application to the Loire

Flood damage models are used to determine the impact of measures to reduce damage due to river flooding. Such models are characterized by uncertainty. This uncertainty may affect the decisions made on the basis of the model outcomes. To reduce uncertainty effectively, the most important sources of uncertainty must be found. Uncertainty analysis serves this purpose.\ud \ud By way of a questionnaire experts were asked about their judgment of the significance of uncertainty sources in flood damage assessment. The results of this questionnaire are compared to an uncertainty analysis by Monte Carlo Simulation, which Torterotot (1993) applied to the French model CIFLUPEDE.\ud \ud The paper concludes that the role of uncertainty in flood damage assessment is highly significant and cannot be neglected. Both the experts and the analysis on the flood damage assessment model indicate the hydrologic relations ‘frequence of occurrence — river discharge — river water level’ and the damage estimates as the most important uncertainty sources. For embanked rivers dike breach is the most significant uncertainty source.\ud \ud A question which appears is, taking into account these uncertainties, to what level of precision can flood damage assessment models predict the expected annual flood damage and the costs and revenues of flood alleviation measures? It is of importance to explore the boundaries of flood damage modeling and to try to find ways to move these boundaries. The uncertainty analysis presented in this paper can be seen as one more step on the way to this goal

A multivariate semiparametric Bayesian spatial modeling framework for hurricane surface wind fields

Storm surge, the onshore rush of sea water caused by the high winds and low pressure associated with a hurricane, can compound the effects of inland flooding caused by rainfall, leading to loss of property and loss of life for residents of coastal areas. Numerical ocean models are essential for creating storm surge forecasts for coastal areas. These models are driven primarily by the surface wind forcings. Currently, the gridded wind fields used by ocean models are specified by deterministic formulas that are based on the central pressure and location of the storm center. While these equations incorporate important physical knowledge about the structure of hurricane surface wind fields, they cannot always capture the asymmetric and dynamic nature of a hurricane. A new Bayesian multivariate spatial statistical modeling framework is introduced combining data with physical knowledge about the wind fields to improve the estimation of the wind vectors. Many spatial models assume the data follow a Gaussian distribution. However, this may be overly-restrictive for wind fields data which often display erratic behavior, such as sudden changes in time or space. In this paper we develop a semiparametric multivariate spatial model for these data. Our model builds on the stick-breaking prior, which is frequently used in Bayesian modeling to capture uncertainty in the parametric form of an outcome. The stick-breaking prior is extended to the spatial setting by assigning each location a different, unknown distribution, and smoothing the distributions in space with a series of kernel functions. This semiparametric spatial model is shown to improve prediction compared to usual Bayesian Kriging methods for the wind field of Hurricane Ivan.Comment: Published at http://dx.doi.org/10.1214/07-AOAS108 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org