Reliability and variability of day-to-day vault training measures in artistic gymnastics

Inter-day training reliability and variability in artistic gymnastics vaulting was determined using a customised infra-red timing gate and contact mat timing system. Thirteen Australian high performance gymnasts (eight males and five females) aged 11-23 years were assessed during two consecutive days of normal training. Each gymnast completed a number of vault repetitions per daily session. Inter-day variability of vault run-up velocities (at -18 to -12 m, -12 to -6 m, -6 to -2 m, and -2 to 0 m from the nearest edge of the beat board), and board contact, pre-flight, and table contact times were determined using mixed modelling statistics to account for random (within-subject variability) and fixed effects (gender, number of subjects, number of trials). The difference in the mean (Mdiff) and Cohen's effect sizes for reliability assessment and intra-class correlation coefficients, and the coefficient of variation percentage (CV%) were calculated for variability assessment. Approach velocity (-18 to -2 m, CV = 2.4-7.8%) and board contact time (CV = 3.5%) were less variable measures when accounting for day-to-day performance differences, than pre-flight time (CV = 17.7%) and table contact time (CV = 20.5%). While pre-flight and table contact times are relevant training measures, approach velocity and board contact time are more reliable when quantifying vaulting performance.

Hydrologic landscape regionalisation using deductive classification and random forests

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.

Phase asymmetry of heart rate variability signal

Heart rate asymmetry (HRA) is considered as a physiological phenomenon in healthy subjects. In this article, we propose a novel HRA index, Slope Index (SI), to quantify phase asymmetry of heart rate variability (HRV) system. We assessed the performance of proposed index in comparison with conventional (Guzik's Index (GI) and Porta's Index (PI)) HRA indices. As illustrative examples, we used two case studies: (i) differentiate physiologic RR series from synthetic RR series; and (ii) discriminate arrhythmia subjects from Healthy using beat-to-beat heart rate time series. The results showed that SI is a superior parameter than GI and PI for both case studies with maximum ROC area of 0.84 and 0.82 respectively. In contrast, GI and PI had ROC areas {0.78, 0.61} and {0.50, 0.56} in two case studies respectively. We also performed surrogate analysis to show that phase asymmetry is caused by a physiologic phenomena rather than a random nature of the signal. In conclusion, quantification of phase asymmetry of HRV provides additional information on HRA, which might have a potential clinical use to discriminate pathological HRV in future.