Employment status passages and psychosocial well-being.

Medical students entering the labor market were studied to find out whether the improvement of psychosocial well-being depends on characteristics of their careers. Psychosocial well-being was described on the basis of psychosomatic stress symptoms, psychological distress (General Health Questionnaire), and strain resistance resources (Sense of Coherence). The 3-year follow-up showed that among women the improvement of strain resistance resources was delayed in the group with several entries into work. Among men the findings suggested associations between stress symptoms and career characteristics. Most of the results, however, did not support the hypothesis about the division of the participants into those with a stable career and improving well-being and those with a fragmented career and low well-being. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Method for characterization of triacylglycerols and fat-soluble vitamins in edible oils and fats by supercritical fluid chromatography

This study demonstrates the usefulness of capillary supercritical fluid chromatography (SFC) for the characterization of triacylglycerols of edible oils and fats. Triacylglycerols were separated according to the acyl carbon number and the degree of unsaturation on a 25% cyanopropyl/25% phenyl/50% methylpolysiloxane stationary phase. Valuable information concerning the triacylglycerol composition of berry oils was obtained, despite the overlapping of certain triacylglycerol peaks. Simultaneous analysis of fat-soluble vitamins and triacylglycerols is not practical by capillary SFC with flame-ionization detection because of the low concentration of naturally-occurring fat-soluble vitamins in edible oils. Therefore, higher loading of the sample, which led to overloading of triacylglycerols, was required to get reasonable peaks for fat-soluble vitamins. The method was applied to the characterization of triacylglycerols and tocopherols in sea buckthorn pulp and seed oil, and cloudberry seed oil without any sample purification prior to SFC. In addition, the stationary phase proved useful for separating the more complex mixtures of triacylglycerols found in milk fat and in fish oil.     

NMR imaging and differential scanning calorimetry study on drying of pine,birch, and reed pulps and their mixtures

Drying, water fractions, and water distribution were investigated for pine, birch, and reed pulps and pine–birch, pine–reed, and pine–birch–reed pulp mixtures. Gravimetrically determined drying times showed that the drying rates of the pulps decreased at two to four inflection points. Characterizations of the dried pulps by differential scanning calorimetry (DSC) showed a faster removal of free water than freezing and nonfreezing bound waters; all decreased simultaneously, however. DSC also revealed the critical water contents at which the free water and freezing bound water disappeared. The gravimetrically determined inflection points of the drying curves corresponded with the critical points determined by DSC. NMR line widths and images produced by ¹H‐NMR imaging revealed the nature and regions of the pulp drying. The constant growth rate of the NMR line widths with decreasing water content appeared to change at two inflection points, which fell approximately in the same water content regions as the inflection points of the drying curves. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 937–945, 2006     

Usability study of ME2.0

Mobile context-aware applications execute in the background of hosts mobile devices. The applications source process and aggregate hosts’ contextual and personal information. This information is disclosed to ubiquitously pervasive services that adapt their offerings to individual preferences. Unfortunately, many developers continue to ignore the user perspective in context-aware application designs as they complicate their overall task and generate exponential requirements. The additional incorporation of privacy mechanisms in context-aware applications to safeguard context and personal information disclosures also complicates users’ tasks resulting to misconfigured or completely abandoned applications. Misconfigured applications give end-users a false assurance of privacy exposing them to comprising services. We present a usability study on Mobile Electronic Personality Version 2 a privacy enhanced context-aware mobile application for personalising ubiquitous services and adapting pervasive smart-spaces. We draw conclusions on key issues related to user needs, based on user interviews, surveys, prototypes and field evaluations. Users’ needs are evaluated against five themes, learn-ability, efficiency, memorability, errors, satisfaction and privacy contention. In addition, design layout preferences, privacy manageability and consensus design comprehension are also evaluated. Clarity of priorities in context-aware mobile applications shaped by usability studies effectively increases the acceptance of levels of potential users.     

Knowledge based quality-driven architecture design and evaluation

Modelling and evaluating quality properties of software is of high importance, especially when our every day life depends on the quality of services produced by systems and devices embedded into our surroundings. This paper contributes to the body of research in quality and model driven software engineering. It does so by introducing; (1) a quality aware software architecting approach and (2) a supporting tool chain. The novel approach with supporting tools enables the systematic development of high quality software by merging benefits of knowledge modelling and management, and model driven architecture design enhanced with domain-specific quality attributes. The whole design flow of software engineering is semi-automatic; specifying quality requirements, transforming quality requirements to architecture design, representing quality properties in architectural models, predicting quality fulfilment from architectural models, and finally, measuring quality aspects from implemented source code. The semi-automatic design flow is exemplified by the ongoing development of a secure middleware for peer-to-peer embedded systems.     

Checking determinism of XML Schema content models in optimal time

We consider the determinism checking of XML Schema content models, as required by the W3C Recommendation. We argue that currently applied solutions have flaws and make processors vulnerable to exponential resource needs by pathological schemas, and we help to eliminate this potential vulnerability of XML Schema based systems. XML Schema content models are essentially regular expressions extended with numeric occurrence indicators. A previously published polynomial-time solution to check the determinism of such expressions is improved to run in linear time, and the improved algorithm is implemented and evaluated experimentally. When compared to the corresponding method of a popular production-quality XML Schema processor, the new implementation runs orders of magnitude faster. Enhancing the solution to take further extensions of XML Schema into account without compromising its linear scalability is also discussed.     

Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach

Bayesian model-based classifiers, both unsupervised and supervised, have been studied extensively and their value and versatility have been demonstrated on a wide spectrum of applications within science and engineering. A majority of the classifiers are built on the assumption of intrinsic discreteness of the considered data features or on the discretization of them prior to the modeling. On the other hand, Gaussian mixture classifiers have also been utilized to a large extent for continuous features in the Bayesian framework. Often the primary reason for discretization in the classification context is the simplification of the analytical and numerical properties of the models. However, the discretization can be problematic due to its textit{ad hoc} nature and the decreased statistical power to detect the correct classes in the resulting procedure. We introduce an unsupervised classification approach for fuzzy feature vectors that utilizes a discrete model structure while preserving the continuous characteristics of data. This is achieved by replacing the ordinary likelihood by a binomial quasi-likelihood to yield an analytical expression for the posterior probability of a given clustering solution. The resulting model can be justified from an information-theoretic perspective. Our method is shown to yield highly accurate clusterings for challenging synthetic and empirical data sets.     

Realistic eight-port homodyne detection and covariant phase space observables

We consider the quantum optical eight-port homodyne detection scheme in the case that each of the associated photon detectors is assigned with a different quantum efficiency. We give a mathematically rigorous and strictly quantum mechanical proof of the fact that the measured observable (positive operator measure) in the high-amplitude limit is a smearing of the covariant phase space observable related to the ideal measurement, that is, the measurement performed with fully efficient detectors. The result is proved for an arbitary parameter field. Furthermore, we investigate some properties of the measured observable. In particular, we show that detector inefficiencies do not affect the observable's ability to distinguish between different states.