Создание развитых интернет-программ на примере построения виджет-программ

Рассмотрено применение методологии создания развитых Интернет-программ на основе Adobe Flex 2.0 с применением паттернов проектирования и архитектурного каркаса. Подход проиллюстрирован построением виджет-программ

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Car drivers’ characteristics and the maximum walking distance between parking facility and final destination

In this paper the relationship between car drivers’ personal and trip characteristics and the maximum distance car drivers are willing to walk between a parking facility and the final destination(s) will be discussed. The willingness to walk is investigated in the context of four different trip purposes: weekly shopping, non-weekly shopping, work, and social activities. The analyses are based on responses of almost 340 members of the Eindhoven University of Technology’s University Parking Panel. The questions regarding car drivers’ willingness to walk were included in an Internet-based questionnaire that was distributed in 2011. It appears that car drivers are willing to walk short distances in the case of weekly shopping and work. Longer walking distances are accepted in the case of non-weekly shopping. The influence of car drivers’ personal and trip characteristics was investigated using multinomial regression analysis. This analysis shows that the most influential characteristics are the trip-related characteristics “frequency of car use” and “visit duration.” The parameter estimates show that in the case of weekly and non-weekly shopping, the more the car is used and the longer car drivers stay at a destination, the higher the probabilities of longer-distance categories. For the trip purposes work and leisure, the opposite holds true

Modeling the Impact of Key Events on Long-Term Transport Mode Choice Decisions: Decision Network Approach Using Event History Data

This paper describes the first phase of a study of the impact of key events on long-term transport mode choice decisions. The suggested complexity of transport mode choice is modeled with a Bayesian decision network. An Internet-based questionnaire was designed to measure the various conditional probability tables and the conditional utility tables of the Bayesian decision network. Seven key events were implemented in the questionnaire: change in residential location, change in household composition, change in work location, change in study location, change in car availability, change in availability of public transport pass, and change in household income. Data from 554 respondents were used to illustrate how the tables can be constructed on the basis of event history data

Modeling the Impact of Key Events on Long-Term Transport Mode Choice Decisions: Decision Network Approach Using Event History Data

This paper describes the first phase of a study of the impact of key events on long-term transport mode choice decisions. The suggested complexity of transport mode choice is modeled with a Bayesian decision network. An Internet-based questionnaire was designed to measure the various conditional probability tables and the conditional utility tables of the Bayesian decision network. Seven key events were implemented in the questionnaire: change in residential location, change in household composition, change in work location, change in study location, change in car availability, change in availability of public transport pass, and change in household income. Data from 554 respondents were used to illustrate how the tables can be constructed on the basis of event history data

Car drivers’ knowledge and preferences regarding additional services at parking facilities

The paper presents a study on car drivers’ knowledge and preferences regarding additional services at parking facilities. The following eight services are investigated the presence of public toilets, parking spaces for challenged people, lockers, refreshment machines, elevators, charging points for electric vehicles, a free newspaper service, and AED-equipment. The data were collected about the city of ‘s-Hertogenbosch using an online questionnaire. In total, 435 car drivers completed the questionnaire. Car drivers know the absence/presence of lockers, a free newspaper service, and AED-equipment best. The services they prefer most are restrooms, parking facilities for disabled people, charging points for electric cars, and AED-equipment. The relationship between car drivers’ preference and personal and visit characteristics is analyzed using binary logistic regression analysis. A significant relationship is found for the characteristics age, education, visiting day, visit motif, visit party, and visit frequency