Impact of Huntington's across the entire disease spectrum: the phases and stages of disease from the patient perspective

Although Huntington's disease (HD) is a neurodegenerative disease characterized by motor, cognitive and behavioural disturbances, there has been little empirical data examining what patients are most concerned about throughout the different stages of disease, which can span many years. Semi-structured face-to-face interviews were individually conducted with 31 people living with different stages of Huntington's, from pre-clinical gene carriers to advanced stage. We examined how often participants raised issues and concerns regarding the impact of Huntington's on everyday life. The Physical/functional theme hardly featured pre-clinically, but was strongly present from Stage 1, rose steadily and peaked at Stage 5. There were no significant changes between stages for the Emotional, Social, and Self themes that all featured across all stages, indicating that these issues were not raised more frequently over the course of the disease. Likewise, the more rarely mentioned Financial and Legal themes also remained similar across stages. However, the Cognitive theme only featured between Stages 1 and 4, and hardly at all pre-clinically and at Stage 5. These findings provide insight into patients' important and unique perspective and have implications for the management and development of interventions across the spectrum of HD stages.

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

A conceptual framework for aligning business and information systems from organisational learning perspective

The three decades of on-going executives’ concerns of how to achieve successful alignment between business and information technology shows the complexity of such a vital process. Most of the challenges of alignment are related to knowledge and organisational change and several researchers have introduced a number of mechanisms to address some of these challenges. However, these mechanisms pay less attention to multi-level effects, which results in a limited un-derstanding of alignment across levels. Therefore, we reviewed these challenges from a multi-level learning perspective and found that business and IT alignment is related to the balance of exploitation and exploration strategies with the intellec-tual content of individual, group and organisational levels.

Assessing pragmatic interoperability of information systems from a semiotic perspective

Most of studies on interoperability of systems integration focus on technical and semantic levels, but hardly extend investigations on pragmatic level. Our past work has addressed pragmatic interoperability, which is concerned with the relationship between signs and the potential behaviour and intention of responsible agents. We also define the pragmatic interoperability as a level concerning with the aggregation and optimisation of various business processes for achieving intended purposes of different information systems. This paper, as the extension of our previous research, is to propose an assessment method for measuring pragmatic interoperability of information systems. We firstly propose interoperability analysis framework, which is based on the concept of semiosis. We then develop pragmatic interoperability assessment process from two dimensions including six aspects (informal, formal, technical, substantive, communication, and control). We finally illustrate the assessment process in an example.

The 'welfare of the child' in Shari'a law: an analysis of child custody law and practices in Bangladesh from a feminist perspective

The paper seeks to draw attention to some of the recent cases relating to child custody law in Bangladesh where, deviating from orthodox Shari’a rules, courts have looked to ‘the welfare’ of the child in determining which parent shall have custody. In studying the recent ‘welfare of child’ standard that has been advanced by the courts in Bangladesh, the paper aims to explore its implications for Muslim women from a feminist perspective.

Quantifying the relative importance of land cover change from climate and land-use in the representative concentration pathways

Climate change is projected to cause substantial alterations in vegetation distribution, but these have been given little attention in comparison to land-use in the Representative Concentration Pathway (RCP) scenarios. Here we assess the climate-induced land cover changes (CILCC) in the RCPs, and compare them to land-use land cover change (LULCC). To do this, we use an ensemble of simulations with and without LULCC in earth system model HadGEM2-ES for RCP2.6, RCP4.5 and RCP8.5. We find that climate change causes an expansion poleward of vegetation that affects more land area than LULCC in all of the RCPs considered here. The terrestrial carbon changes from CILCC are also larger than for LULCC. When considering only forest, the LULCC is larger, but the CILCC is highly variable with the overall radiative forcing of the scenario. The CILCC forest increase compensates 90% of the global anthropogenic deforestation by 2100 in RCP8.5, but just 3% in RCP2.6. Overall, bigger land cover changes tend to originate from LULCC in the shorter term or lower radiative forcing scenarios, and from CILCC in the longer term and higher radiative forcing scenarios. The extent to which CILCC could compensate for LULCC raises difficult questions regarding global forest and biodiversity offsetting, especially at different timescales. This research shows the importance of considering the relative size of CILCC to LULCC, especially with regard to the ecological effects of the different RCPs.

Reflections on the concept of the common good from an economic perspective

The chapter considers how the common good can be implemented when opinions differ within society about the nature of the common good. It explains how economic analysis can shed light on efficient conflict-management in these circumstances. The chapter argues, more generally, that virtue theorists make too little use of economics because they have an unduly restricted view of the nature and scope of the discipline

Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective

Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally. the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study. (C) 2009 Elsevier B.V. All rights reserved.

Are schools able to bring sense into pupils' lives? - an experiment to use Antonovsky's concept sense of coherence from a school perspective. : Paper presented at the ENIRDEM conference in Kilkenny, Ireland 26th-29th September, 2002

Young people now spend a longer and longer period of their lives at school then ever before. Not always because that they want to, but because society has nothing else to offer. The situation in many schools may also, in different aspects, be seen as highly problematic. Andersson (2001) has, for example, found in a large longitudinal study - The Life Project – that schools seem to be adapted to the needs of only a minority of the students - around 30%. On the other hand school is badly adjusted to the requirements of another 30 %. This group of students often find school meaningless, uninteresting and boring. For these students school is mostly a waste of time. In such circumstances, it seems natural that society has a responsibility to offer young people a meaningful time at school, both here and now and to prepare them for a future live as adults, not only as a part of the work force.As a part of departure I briefly describe the model that Antonovsky has developed and try to use it in a school context instead. I have here, of course, no possibility to make a deeper analysis of a complex problem such as this.In Antonovsky’s spirit, using a salutogenic perspective, instead of asking ourselves why do pupils fail or perhaps also not like being at school we have to ask, instead: What it is that makes pupils successful? From this background the purpose of this paper is to discuss some aspects of how pupils may use different strategies to handle their school situation in a proper way.

Evaluation of the Cartographic Communication Performance of a Route Guidance and Navigation System

This study evaluates the influence of different cartographic representations of in-car navigation systems on visual demand, subjective preference, and navigational error. It takes into account the type and complexity of the representation, maneuvering complexity, road layout, and driver gender. A group of 28 drivers (14 male and 14 female) participated in this experiment which was performed in a low-cost driving simulator. The tests were performed on a limited number of instances for each type of representation, and their purpose was to carry out a preliminary assessment and provide future avenues for further studies. Data collected for the visual demand study were analyzed using non-parametric statistical analyses. Results confirmed previous research that showed that different levels of design complexity significantly influence visual demand. Non-grid-like road networks, for example, influence significantly visual demand and navigational error. An analysis of simple maneuvers on a grid-like road network showed that static and blinking arrows did not present significant differences. From the set of representations analyzed to assess visual demand, both arrows were equally efficient. From a gender perspective, women seem to took at the display more than men, but this factor was not significant. With respect to subjective preferences, drivers prefer representations with mimetic landmarks when they perform straight-ahead tasks. For maneuvering tasks, landmarks in a perspective model created higher visual demands.