Variability and Uncertainty in Swedish Exposure Factors for Use in Quantitative Exposure Assessments

Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe—here represented by Sweden—and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments.     

How Opportunistic Culture Affects Financial Performance in Outsourcing Relationships: A Meta-Analysis

Although a substantial body of research has analyzed the overall impact of outsourcing on firm performance measured in shareholder value, a major portion of the between-study variance remains unexplained. Asset specificity related to the outsourcing category (e.g., a business process versus information technology) alone can explain only some of the observed differences in stock market reactions. By integrating insights from transaction cost economics and outsourcing research, we first explain how expected buyer opportunism negatively affects the overall performance of the outsourcing relationship and ultimately, the buyer's own shareholder value. We further argue that this opportunism can be predicted by national culture. We test this hypothesis by applying meta-analytic techniques to compare 4216 outsourcing announcements of firms from 19 cultural backgrounds. The results reveal that an opportunistic culture, represented by a high level of assertiveness combined with a low level of institutional collectivism, is a highly statistically significant predictor of stock market reactions to outsourcing announcements. When further integrating the outsourcing category, the meta-analytic weighted least squares regression becomes a strong predictor of stock market reactions to an outsourcing announcement.     

Measuring and Understanding Urban Parks’ Contribution to Quality of Life in Istanbul

This study details an application of an improved Water Poverty Index (iWPI) to investigate and assess state of water resources in 53 African countries for the period 2000–2012 with a special focus on an international comparison of water poverty among northern and sub-Saharan countries. A multi-faceted approach that combines physical estimates of water availability with socio-economic drivers of poverty and environmental factors, has been used to do such comparison. It is with this in mind that the iWPI was developed based on the theoretical foundations and recent development of the water poverty approach. This would permit an inclusive comprehension of the crosscutting nature of water issues and their impacts on human wellbeing and environment. The results highlight an obvious dissimilarity of water poverty situation between more developed, but water-poor countries located principally in North Africa with that of lower-income and water-rich countries in sub-Saharan region. This can be used to inform policy makers, governments, donors and other stakeholders to assist in prioritization of appropriate policies to be taken towards better service delivery and sustainable water management across space and time.     

Exact filtering in exponential families:discrete time

An exact filter is an algorithm for calculating the a-posteriori distribution of the state ξ _n of a process, given observations η_t, …,η_nup to time n. We describe a method to determine an appropriate algorithm for processes, where the distributions involved are members of exponential families, The resulting algorithm consists essen tially of a prediction term, combined with an affine transformation depending on the chosen model.     

A Bayesian approach to estimating linear mixtures with unknown covariance structure

In this paper, we study a new Bayesian approach for the analysis of linearly mixed structures. In particular, we consider the case of hyperspectral images, which have to be decomposed into a collection of distinct spectra, called endmembers, and a set of associated proportions for every pixel in the scene. This problem, often referred to as spectral unmixing, is usually considered on the basis of the linear mixing model (LMM). In unsupervised approaches, the endmember signatures have to be calculated by an endmember extraction algorithm, which generally relies on the supposition that there are pure (unmixed) pixels contained in the image. In practice, this assumption may not hold for highly mixed data and consequently the extracted endmember spectra differ from the true ones. A way out of this dilemma is to consider the problem under the normal compositional model (NCM). Contrary to the LMM, the NCM treats the endmembers as random Gaussian vectors and not as deterministic quantities. Existing Bayesian approaches for estimating the proportions under the NCM are restricted to the case that the covariance matrix of the Gaussian endmembers is a multiple of the identity matrix. The self-evident conclusion is that this model is not suitable when the variance differs from one spectral channel to the other, which is a common phenomenon in practice. In this paper, we first propose a Bayesian strategy for the estimation of the mixing proportions under the assumption of varying variances in the spectral bands. Then we generalize this model to handle the case of a completely unknown covariance structure. For both algorithms, we present Gibbs sampling strategies and compare their performance with other, state of the art, unmixing routines on synthetic as well as on real hyperspectral fluorescence spectroscopy data.     

Treacherous Productions of Fantasy: Ağaoğlu Housing Commercials

Ali A?ao?lu is the leading figure in the construction industry in Turkey, specializing in luxury housing estates. His sales figures have reached record levels since the early 2000s, far surpassing those of other similar entrepreneurs’. While governmental policies that prioritize the development of the construction sector partially account for A?ao?lu’s commercial success, we contend that the analysis of popular media images is essential in order to understand his estates’ popularity. Based on a close reading of his media appearances in housing commercials and interviews in the light of psychoanalytical theory, we argue that A?ao?lu has manufactured a realizable fantasy for his clients, which structures their desires in the cultural context of consumer capitalism. However, the limits of A?ao?lu’s fantasy world of housing were tested in an unexpected outbreak in one of his estates, where the homeowers traversed their fantasies.