Automatic estimation of nearshore wave height from video timestacks

In this paper a new method for the measurement of near-shore wave height from a digital video sequence is presented. The method identifies the location of the main wave breakzones and then detects shoaling waves inside the detected breakzone and estimate their heights. A geometric rectification is then used to convert the height measurement from image pixels to metres. Validation of the algorithm against conventional wave height measuring methods, such as a KG7WW3 indicates that the method has the potential of providing a cheap and effective alternative for existing near-shore wave height estimation methods

Long-term automated monitoring of nearshore wave height from digital video

This paper presents a new method for estimating nearshore wave height from a digital video sequence. The method identifies main wave breaking zones in the video records and estimates the height of breaking waves inside the detected breaking zones. A geometric rectification is applied to the resulting estimation to convert the height measurement from image pixels to meters. The validation of the algorithm was undertaken over three months at Surfers Paradise, Australia. The performance of the algorithm was demonstrated to be comparable with that of buoy-measured wave height, as well as manual estimates of the onshore wave height by a surf reporter. The results indicate that the method can be used as a cost-effective tool for long-term monitoring of nearshore wave conditions

EM localisation of the MNK copper transporting P-type ATPase

EM localisation of the MNK copper transporting P-type ATPas

Empirical estimation of nearshore waves from a global deep-water wave model

Global wind-wave models such as the National Oceanic and Atmospheric Administration Wave Watch 3 (NWW3) play an important role in monitoring the world’s oceans. However, untransformed data at grid points in deep water provide a poor estimate of swell characteristics at nearshore locations, which are often of significant scientific, engineering, and public interest. Explicit wave modeling, such as the Simulating Waves Nearshore (SWAN), is one method for resolving the complex wave transformations affected by bathymetry, winds, and other local factors. However, obtaining accurate bathymetry and determining parameters for such models is often difficult. When target data is available (i.e., from in situ buoys or human observers, empirical alternatives such artificial neural networks (ANNs) and linear regression may be considered for inferring nearshore conditions from offshore model output. Using a sixfold cross-validation scheme, significant wave height Hs and period were estimated at one onshore and two nearshore locations. In estimating Hs at the shoreline, the validation performance of the best ANN was r = 0.91, as compared to those of linear regression (0.82), SWAN (0.78), and the NWW3 Hs baseline (0.54)

Near-shore swell estimation from a global wind-wave model : spectral process, linear, and artificial neural network models

Estimation of swell conditions in coastal regions is important for a variety of public, government, and research applications. Driving a model of the near-shore wave transformation from an offshore global swell model such as NOAAWaveWatch3 is an economical means to arrive at swell size estimates at particular locations of interest. Recently, some work (e.g. Browne et al. [Browne, M., Strauss, D., Castelle, B., Blumenstein, M., Tomlinson, R., 2006. Local swell estimation and prediction from a global wind-wave model. IEEE Geoscience and Remote Sensing Letters 3 (4), 462–466.]) has examined an artificial neural network (ANN) based, empirical approach to wave estimation. Here, we provide a comprehensive evaluation of two data driven approaches to estimating waves near-shore (linear and ANN), and also contrast these with a more traditional spectral wave simulation model (SWAN). Performance was assessed on data gathered from a total of 17 near-shore locations, with heterogenous geography and bathymetry, around the continent of Australia over a 7 month period. It was found that the ANNs out-performed SWAN and the non-linear architecture consistently out-performed the linear method. Variability in performance and differential performance with regard to geographical location could largely be explained in terms of the underlying complexity of the local wave transformation

Scaling-up evidence-based obesity interventions: A systematic review assessing intervention adaptations and effectiveness and quantifying the scale-up penalty

Maximizing the benefits of investments in obesity research requires effective interventions to be adopted and disseminated broadly across populations (scaled-up). However, interventions often need considerable adaptation to enable implementation at scale, a process that can reduce the effects of interventions. A systematic review was undertaken for trials that sought to deliver an obesity intervention to populations on a larger scale than a preceding randomized controlled trial (RCT) that established its efficacy. Ten scaled-up obesity interventions (six prevention and four treatment) were included. All trials made adaptations to interventions as part of the scale-up process, with mode of delivery adaptations being most common. A meta-analysis of body mass index (BMI)/BMI z score (zBMI) from three prevention RCTs found no significant benefit of scaled-up interventions relative to control (standardized mean difference [SMD] = 0.03; 95% CI, −0.09 to 0.15, P = 0.639 − I 2  = 0.0%). All four treatment interventions reported significant improvement on all measures of weight status. Pooled BMI/zBMI data from prevention trials found significantly lower effects among scaled-up intervention trials than those reported in pre–scale-up efficacy trials (SMD = −0.11; 95% CI, −0.20 to −0.02, P = 0.018 − I 2  = 0.0%). Across measures of weight status, physical activity/sedentary behaviour, and nutrition, the effects reported in scaled-up interventions were typically 75% or less of the effects reported in pre–scale-up efficacy trials. The findings underscore the challenge of scaling-up obesity interventions

A new system for breakzone location and the measurement of breaking wave heights and periods

This paper presents a new system for measuring breakzone locations, breaking wave height and wave periods across the surfzone from a digital video sequence. The system (Wave Pack) aims to provide real-time measurement of breaking and re-breaking wave heights and wave periods using low mounted video camera installations. Following on site data collection and analysis it was found that the Wave Pack system provides a low cost, robust, reliable and accurate system for measuring continuous wave height and period from a low elevation video camera aimed at the target beach under a wide range of wave conditions. These tests have verified the accuracy of Wave Pack in comparison to existing systems

A new technique for measuring breaking wave dynamics, heights and periods

A new system for measuring breakzone locations, breaking wave height and wave periods across the surfzone from a digital video sequence. The aim of the system, called Wave Pack, is to detect the breaking wave zone and measure breaking and rebreaking wave heights and incident through infragravity wave periods, based on digital video data that is streaming from a low altitude camera, located on the investigated beach. The system circumvents the need for expensive equipment, labour intensive and complicated installation presently used in hardwired surf zone sensors and inshore waverider buoys. It is a reliable system that can supply accurate results even in extreme weather and sea conditions

School-level factors associated with the sustainment of weekly physical activity scheduled in Australian elementary schools: an observational study

Background: We aimed to: (1) identify school-level factors associated with the sustainment of weekly physical activity (PA) scheduled in elementary schools following withdrawal of effective implementation support; and (2) determine teacher’s perceived usefulness of suggested strategies for sustaining the scheduling of weekly PA. Methods: A secondary exploratory analysis was employed of data from the intervention arm (n = 31 schools) of a randomised controlled trial. Self-report survey data from 134 classroom teachers in New South Wales, Australia, collected following withdrawal of initial implementation support (follow-up T1) and six-months following completion of support (follow-up T2) were used. The outcomes of sustainment of weekly overall PA and energisers (short classroom PA breaks) scheduled were measured via teachers’ completion of a daily activity logbook, with results presented as the difference in mean minutes of PA and energisers scheduled at T1 and T2. An adapted version of the Program Sustainability Assessment Tool (PSAT) was used to measure capacity for program sustainability across seven key domains at follow-up T2. Linear mixed regressions were conducted to evaluate associations between school-level sociodemographic characteristics (e.g., school size, remoteness, and type), teacher-reported school factors (i.e., seven adapted PSAT domains) and the sustainment of PA and energisers scheduled across the school week. Perceived usefulness of 14 proposed sustainability strategies was measured via the teacher survey at follow-up T2 and reported descriptively. Results: No school-level factor was statistically associated with the sustainment of overall weekly PA or energisers scheduled. Teacher-reported factors in two PSAT domains – ‘strategic planning’ and ‘program evaluation’ were statistically negatively associated with the sustainment of weekly energisers scheduled (− 6.74, 95% CI: − 13.02; − 0.47, p = 0.036 and − 6.65, 95% CI: − 12.17; − 1.12, p = 0.019 respectively). The proposed support sustainability strategy – ‘provision of PA equipment packs that enable energisers or integrated lessons’ was perceived useful by the most teachers (85%). Conclusions: Further research is required to explore additional contextual-specific, and end-user appropriate factors associated with schools’ sustainment of weekly PA scheduled. This will help accurately inform the development of strategies to address these determinants and support the sustainment and long-term benefits of school-based health interventions more broadly

The impact of school uniforms on primary school student’s physical activity at school: outcomes of a cluster randomized controlled trial

Background: Many school-based physical activity (PA) interventions are complex and have modest effects when delivered in real world contexts. A commonly reported barrier to students’ PA, particularly among girls, are uniforms that are impractical (e.g. tunic/dress and black leather shoes). Modifying student uniforms may represent a simple intervention to enhance student PA. The primary aim of this trial was to assess the impact of a PA enabling uniform intervention (shorts, polo shirt and sports shoes) on girls’ moderate-to-vigorous physical activity (MVPA) and total PA i.e. counts per minute (cpm). Methods: A cluster randomized controlled trial was undertaken in 42 primary schools in New South Wales, Australia. Schools were randomized on one school day to the intervention group, where students wore a PA enabling uniform (their sports uniform) or a control group, where students wore their usual traditional uniform. Student PA was measured using wrist-worn Actigraph GT3X and GT9X accelerometers. Linear mixed models controlling for student characteristics were used to examine the effects of the intervention. Results: Of the 3351 eligible students, 2315 (69.1%) had parental consent and 2180 of these consenting students participated (94.2%) of which 1847 (84.7%) were included in the analysis. For the primary aim the study found no significant differences between girls at schools allocated to the intervention relative to the control on change in MVPA (0.76 min, 95% CI − 0.47 to 1.99, p = 0.22) or cpm (36.99, 95% CI − 13.88 to 87.86, p = 0.15). Exploratory analysis revealed small effects for a number of findings, including significant reduction in sedentary activity (− 1.77, 95% CI − 3.40 to − 0.14, p = 0.035) among all students at schools allocated to the intervention, and non-significant improvements in girls’ light intensity PA (1.47 min, 95% CI − 0.06 to 3.00, p = 0.059) and sedentary activity (− 2.23 min; 95% CI − 4.49 to 0.02, p = 0.052). Conclusion: The findings suggests that the intervention may yield small improvements in some measure of PA and require substantiation in a larger RCT with longer-term follow-up. The inclusion of additional intervention components may be required to achieve more meaningful effects. Trial registration: The trial was prospectively registered with Australian New Zealand Clinical Trials Register ACTRN12617001266358 1st September 2017