Characteristics of utility cyclists in Queensland, Australia : an examination of the associations between individual, social and environmental factors and utility cycling

Background: Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia.

Methods: An online survey was administered to adult members of a state-based cycling community and advocacy group (n=1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables.

Results: Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were >5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling (p<0.05). Perceiving cycling to be a cheap or a convenient form of transport were associated with utility cycling (p<0.05).

Conclusions: The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.

Assessment of fracture risk : value of random population-based samples - the Geelong Osteoporosis Study

Fracture risk is determined by bone mineral density (BMD). The T-score, a measure of fracture risk, is the position of an individual's BMD in relation to a reference range. The aim of this study was to determine the magnitude of change in the T-score when different sampling techniques were used to produce the reference range. Reference ranges were derived from three samples, drawn from the same region: (1) an age-stratified population-based random sample, (2) unselected volunteers, and (3) a selected healthy subset of the population-based sample with no diseases or drugs known to affect bone. T-scores were calculated using the three reference ranges for a cohort of women who had sustained a fracture and as a group had a low mean BMD (ages 35-72 yr; n = 484). For most comparisons, the T-scores for the fracture cohort were more negative using the population reference range. The difference in T-scores reached 1.0 SD. The proportion of the fracture cohort classified as having osteoporosis at the spine was 26, 14, and 23% when the population, volunteer, and healthy reference ranges were applied, respectively. The use of inappropriate reference ranges results in substantial changes to T-scores and may lead to inappropriate management.

Comparison theory in economic psychology regarding the easterlin paradox and decreasing marginal utility : a critique

This paper challenges the assumption within Economics that the relationship between money and subjective wellbeing is determined by processes of cognitive comparison. An alternative explanation for such well known phenomena as the Easterlin Paradox and Decreasing Marginal Utility are provided through a consideration of affect. The theoretical basis for such explanations relies on theory from Psychology usually overlooked by Economists, such as affect heuristics and Subjective Wellbeing Homeostasis. The presented evidence for this alternative source of explanation melds psychological theory with empirical data. It is concluded that affective processes offer a coherent alternative explanation for the phenomena under discussion.

AdaBoost.MRF: boosted Markov random forests and application to multilevel activity recognition

Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov random field (MRF), known as the dynamic conditional random field (DCRF). Parameter estimation in general MRFs using maximum likelihood is known to be computationally challenging (except for extreme cases), and thus we propose an efficient boosting-based algorithm AdaBoost.MRF for this task. Distinct from most existing work, our algorithm can handle hidden variables (missing labels) and is particularly attractive for smarthouse domains where reliable labels are often sparsely observed. Furthermore, our method works exclusively on trees and thus is guaranteed to converge. We apply the AdaBoost.MRF algorithm to a home video surveillance application and demonstrate its efficacy.

Random Subspace Two-Dimensional PCA for face recognition

The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA method in recognising human face. However, in many cases, this method tends to be overfitted to sample data. In this paper, we proposed a novel method named random subspace two-dimensional PCA (RS-2DPCA), which combines the 2DPCA method with the random subspace (RS) technique. The RS-2DPCA inherits the advantages of both the 2DPCA and RS technique, thus it can avoid the overfitting problem and achieve high recognition accuracy. Experimental results in three benchmark face data sets -the ORL database, the Yale face database and the extended Yale face database B - confirm our hypothesis that the RS-2DPCA is superior to the 2DPCA itself.

Hierarchical semi-markov conditional random fields for recursive sequential data

Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov chains to model complex hierarchical, nested Markov processes. It is parameterised in a discriminative framework and has polynomial time algorithms for learning and inference. Importantly, we develop efficient algorithms for learning and constrained inference in a partially-supervised setting, which is important issue in practice where labels can only be obtained sparsely. We demonstrate the HSCRF in two applications: (i) recognising human activities of daily living (ADLs) from indoor surveillance cameras, and (ii) noun-phrase chunking. We show that the HSCRF is capable of learning rich hierarchical models with reasonable accuracy in both fully and partially observed data cases.

Utility-based summarization of home videos

The aim of this work is to devise an effective method for static summarization of home video sequences. Based on the premise that the user watching a summary is interested in people related (how many, who, emotional state) or activity related aspects, we formulate a novel approach to video summarization that works to specifically expose relevant video frames that make the content spotting tasks possible. Unlike existing approaches, which work on low-level features which often produce the summary not appealing to the viewer due to the semantic gap between low-level features and high-level concepts, our approach is driven by various utility functions (identity count, identity recognition, emotion recognition, activity recognition, sense of space) that use the results of face detection, face clustering, shot clustering and within cluster frame alignment. The summarization problem is then treated as the problem of extracting the set of key frames that have the maximum combined utility.

Utility-based quality of life associated with overweight and obesity : the Australian diabetes, obesity, and lifestyle study

This study aimed to estimate utility-based quality of life (UQoL) differences between healthy body weight and excess body weight categories. Cross-sectional analysis of 10,959 adults, participating in baseline data collection of the nationally representative Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study was undertaken. Height and weight were measured by trained personnel. Body weight categories were assigned as healthy weight, overweight, and obesity subclasses I, II and III. UQoL was assessed using the SF-6D, which captures physical functioning, role limitation, social functioning, pain, mental health, and vitality on a score of 0.00–1.00 (worst-best). The relationship between body weight categories and UQoL was assessed using linear regression, adjusting for age, sex, education, and smoking. Relative to the healthy weight group (mean UQoL score 0.77), mean adjusted UQoL differences (95% confidence intervals) were 0.001 (−0.008, 0.010) for overweight, −0.012 (−0.022, −0.001) for class-I obese, −0.020 (−0.041, 0.001) for class-II obese, and −0.069 (−0.099, −0.039) for class-III obese groups. Adding metabolic syndrome markers to the covariates had little impact on these differences. Results confirmed an inverse dose–response relationship between body weight and UQoL in this study of Australian adults. This highlights the need to incorporate UQoL measures which are sensitive to the subclasses of obesity when evaluating obesity interventions.

Utility of short-term evaluation of presbyopic contact lens performance

Objectives: To establish if evaluations of multifocal contact lens performance conducted at dispensing are representative of behavior after a moderate adaptation period.

Methods: Eighty-eight presbyopic subjects, across four clinical sites, wore each of four multifocal soft contact lenses (ACUVUE BIFOCAL, Focus Progressives, Proclear Multifocal, and SofLens Multifocal) for 4 days of daily wear. Comprehensive performance assessments were conducted at dispensing and after 4 days wear and included the following objective metrics: LogMAR acuity (contrast, 90% and 10%; illumination, 250 and 10 cd/m2; distance, 6 m, 100 cm, and 40 cm), stereopsis (RANDOT), reading critical print size and maximum speed and range of clear vision at near. Subjective assessments were made, with 100-point numerical rating scales, of comfort, ghosting (distance, near), visual quality (distance, intermediate, and near), and the appearance of haloes. At two sites, subjects (n = 39) also rated visual fluctuation (distance, intermediate, and near), facial recognition, and overall satisfaction.

Results: Among the objective variables, significant differences (paired t test, P<0.05) between dispensing and 4 days were found only for range of clear vision at near (2.9 ± 2.0 cm; mean difference ± standard deviation) and high contrast near acuity in low illumination (-0.013 ± 0.011 LogMAR). With the exception of insertion comfort, all subjective variables showed significant decrements over the same period. Overall satisfaction declined by an average of 10.9 ± 5.1 points.

Conclusions: Early assessment is relatively unrepresentative of performance later on during multifocal contact lens wear. Acuity based measures of vision remain substantially unchanged over the medium term, apparently because these metrics are insensitive indicators of performance compared with subjective alternatives.