Body image during pregnancy: an evaluation of the suitability of the body attitudes questionnaire

Background: 

Illumination-invariant face recognition from a single image across extreme pose using a dual dimension AAM ensemble in the thermal infrared spectrum

Over the course of the last decade, infrared (IR) and particularly thermal IR imaging based face recognition has emerged as a promising complement to conventional, visible spectrum based approaches which continue to struggle when applied in practice. While inherently insensitive to visible spectrum illumination changes, IR data introduces specific challenges of its own, most notably sensitivity to factors which affect facial heat emission patterns, e.g. emotional state, ambient temperature, and alcohol intake. In addition, facial expression and pose changes are more difficult to correct in IR images because they are less rich in high frequency detail which is an important cue for fitting any deformable model. In this paper we describe a novel method which addresses these major challenges. Specifically, when comparing two thermal IR images of faces, we mutually normalize their poses and facial expressions by using an active appearance model (AAM) to generate synthetic images of the two faces with a neutral facial expression and in the same view (the average of the two input views). This is achieved by piecewise affine warping which follows AAM fitting. A major contribution of our work is the use of an AAM ensemble in which each AAM is specialized to a particular range of poses and a particular region of the thermal IR face space. Combined with the contributions from our previous work which addressed the problem of reliable AAM fitting in the thermal IR spectrum, and the development of a person-specific representation robust to transient changes in the pattern of facial temperature emissions, the proposed ensemble framework accurately matches faces across the full range of yaw from frontal to profile, even in the presence of scale variation (e.g. due to the varying distance of a subject from the camera). The effectiveness of the proposed approach is demonstrated on the largest public database of thermal IR images of faces and a newly acquired data set of thermal IR motion videos. Our approach achieved perfect recognition performance on both data sets, significantly outperforming the current state of the art methods even when they are trained with multiple images spanning a range of head views.

An illumination invariant face recognition system for access control using video

Illumination and pose invariance are the most challenging aspects of face recognition. In this paper we describe a fully automatic face recognition system that uses video information to achieve illumination and pose robustness. In the proposed method, highly nonlinear manifolds of face motion are approximated using three Gaussian pose clusters. Pose robustness is achieved by comparing the corresponding pose clusters and probabilistically combining the results to derive a measure of similarity between two manifolds. Illumination is normalized on a per-pose basis. Region-based gamma intensity correction is used to correct for coarse illumination changes, while further refinement is achieved by combining a learnt linear manifold of illumination variation with constraints on face pattern distribution, derived from video. Comparative experimental evaluation is presented and the proposed method is shown to greatly outperform state-of-the-art algorithms. Consistent recognition rates of 94-100% are achieved across dramatic changes in illumination.

Non-nested tests of a GDP-augmented Fama–French model versus a conditional Fama–French model in the Australian stock market

We extend Vassalou (2003) by conditioning the Fama–French model with the same macroeconomic variables used to construct a GDP factor. The motivation for doing so is to ascertain whether the ability of the GDP-augmented model to explain equity returns is actually due to news about future GDP growth or whether it is due to the macroeconomic conditioning variables used to construct the GDP factor. We compare the performance of a GDP-enhanced Fama–French model with the conditional Fama–French model using non-nested testing techniques. We find that the GDP-augmented model considerably underperforms the conditional version of the model.

Tests examining skill outcomes in sport: A systematic review of measurement properties and feasibility

Background
A high level of participant skill is influential in determining the outcome of many sports. Thus, tests assessing skill outcomes in sport are commonly used by coaches and researchers to estimate an athlete’s ability level, to evaluate the effectiveness of interventions or for the purpose of talent identification.

Objective
The objective of this systematic review was to examine the methodological quality, measurement properties and feasibility characteristics of sporting skill outcome tests reported in the peer-reviewed literature.

Data Sources
A search of both SPORTDiscus and MEDLINE databases was undertaken.

Study Selection
Studies that examined tests of sporting skill outcomes were reviewed. Only studies that investigated measurement properties of the test (reliability or validity) were included. A total of 22 studies met the inclusion/exclusion criteria.

Study Appraisal and Synthesis Methods
A customised checklist of assessment criteria, based on previous research, was utilised for the purpose of this review.

Results
A range of sports were the subject of the 22 studies included in this review, with considerations relating to methodological quality being generally well addressed by authors. A range of methods and statistical procedures were used by researchers to determine the measurement properties of their skill outcome tests. The majority (95 %) of the reviewed studies investigated test–retest reliability, and where relevant, inter and intra-rater reliability was also determined. Content validity was examined in 68 % of the studies, with most tests investigating multiple skill domains relevant to the sport. Only 18 % of studies assessed all three reviewed forms of validity (content, construct and criterion), with just 14 % investigating the predictive validity of the test. Test responsiveness was reported in only 9 % of studies, whilst feasibility received varying levels of attention.

Limitations
In organised sport, further tests may exist which have not been investigated in this review. This could be due to such tests firstly not being published in the peer-review literature and secondly, not having their measurement properties (i.e., reliability or validity) examined formally.

Conclusions
Of the 22 studies included in this review, items relating to test methodological quality were, on the whole, well addressed. Test–retest reliability was determined in all but one of the reviewed studies, whilst most studies investigated at least two aspects of validity (i.e., content, construct or criterion-related validity). Few studies examined predictive validity or responsiveness. While feasibility was addressed in over half of the studies, practicality and test limitations were rarely addressed. Consideration of study quality, measurement properties and feasibility components assessed in this review can assist future researchers when developing or modifying tests of sporting skill outcomes.

Two tests of approach-iron golf skill and their ability to predict tournament performance

The aim of this study was to investigate the convergent and predictive validity of two skill tests that examine the ability of golfers to hit accurate approach-iron shots. Twenty-four high-level golfers (handicap = 2.6 ± 1.7) performed the Nine-Ball Skills Test (assesses the ability to shape/control ball trajectory with high accuracy) and the Approach-Iron Skill Test (assesses the ability to hit straight shots from varying distances with high accuracy). Participants then completed at least eight rounds of tournament golf over the following 90 days and reported an indicator of approach-iron accuracy (per cent error index). A moderate correlation (r = 0.50, P < 0.05) was noted between scores for both tests. Generalised estimating equations, using two covariates (lie of the ball and distance to hole), were used to determine model fit and the amount of variance explained for tournament per cent error index. Results showed that the Approach-Iron Skill Test was the slightly stronger predictor of on-course per cent error index. With both test scores considered together, a minimal amount of additional variance was explained. These findings suggest that either of the tests used individually or combined may be used to predict tournament approach iron performance in high-level golfers.