Top-down and bottom-up approaches to motor skill assessment of children : are child-report and parent-report perceptions predictive of children's performance-based assessment results?

Background/ Aim: Therapists use different types of tests, scales, and instruments to assess children's motor skills, including those classified as being top-down and bottom-up. The aim of the study was to investigate the ability of measures of children's motor skill performance from the perspectives of children and parents (a type of top-down assessment) to predict children's performance-based motor ability test results (a type of bottom-up assessment).
Methods: A convenience sample of 38 children and parents was recruited from Victoria, Australia. Motor skill performance was evaluated from a top-down perspective using the Physical Self-Description Questionnaire (PSDQ) and the Movement Assessment Battery for Children – Second Edition (MABC-2) Checklist to measure children's and parents' perspectives respectively. Motor skill performance was also evaluated from a bottom-up approach using the Bruininks-Oseretsky Test of Motor Proficiency – Second Edition (BOT-2). Data were analyzed using multiple linear regression analysis to determine whether the PSDQ or MABC-2 Checklist was predictive of the children's BOT-2 performance results.
Results: Two predictive relationships were identified based on parents' perspectives, where the total score of the MABC-2 Checklist was found to be a significant predictor of the BOT-2 Manual Coordination motor composite score, accounting for 8.35% of its variance, and the BOT-2 Strength and Agility motor composite score, accounting for 11.6% of its variance. No predictive relationships were identified between the children's self-report PSDQ perspectives and the BOT-2 performance scores.
Conclusions: Therapists are encouraged to utilize a combination of top-down and bottom-up approaches and purposefully to seek parents' and children's perspectives when evaluating children's motor skill performance.

Improving Top-N recommendations with user consuming profiles

In this work, we observe that user consuming styles tend to change regularly following some profiles. Therefore, we propose a consuming profile model to capture the user consuming styles, then apply it to improve the Top-N recommendation. The basic idea is to model user consuming styles by constructing a representative subspace. Then, a set of candidate items can be estimated by measuring its reconstruction error from its projection on the representative subspace. The experiment results show that the proposed model can improve the accuracy of Top-N recommendations much better than the state-of-the-art algorithms.

Learning rating patterns for Top-N recommendations

Two rating patterns exist in the user × item rating matrix and influence each other: the personal rating patterns are hidden in each user's entire rating history, while the global rating patterns are hidden in the entire user × item rating matrix. In this paper, a Rating Pattern Subspace is proposed to model both of the rating patterns simultaneously by iteratively refining each other with an EM-like algorithm. Firstly, a low-rank subspace is built up to model the global rating patterns from the whole user × item rating matrix, then, the projection for each user on the subspace is refined individually based on his/her own entire rating history. After that, the refined user projections on the subspace are used to improve the modelling of the global rating patterns. Iteratively, we can obtain a well-trained low-rank Rating Pattern Subspace, which is capable of modelling both the personal and the global rating patterns. Based on this subspace, we propose a RapSVD algorithm to generate Top-N recommendations, and the experiment results show that the proposed method can significantly outperform the other state-of-the-art Top-N recommendation methods in terms of accuracy, especially on long tail item recommendations.

A comparison of the seasonal movements of tiger sharks and green turtles provides insight into their predator-prey relationship

During the reproductive season, sea turtles use a restricted area in the vicinity of their nesting beaches, making them vulnerable to predation. At Raine Island (Australia), the highest density green turtle Chelonia mydas rookery in the world, tiger sharks Galeocerdo cuvier have been observed to feed on green turtles, and it has been suggested that they may specialise on such air-breathing prey. However there is little information with which to examine this hypothesis. We compared the spatial and temporal components of movement behaviour of these two potentially interacting species in order to provide insight into the predator-prey relationship. Specifically, we tested the hypothesis that tiger shark movements are more concentrated at Raine Island during the green turtle nesting season than outside the turtle nesting season when turtles are not concentrated at Raine Island. Turtles showed area-restricted search behaviour around Raine Island for ~3–4 months during the nesting period (November–February). This was followed by direct movement (transit) to putative foraging grounds mostly in the Torres Straight where they switched to area-restricted search mode again, and remained resident for the remainder of the deployment (53–304 days). In contrast, tiger sharks displayed high spatial and temporal variation in movement behaviour which was not closely linked to the movement behaviour of green turtles or recognised turtle foraging grounds. On average, tiger sharks were concentrated around Raine Island throughout the year. While information on diet is required to determine whether tiger sharks are turtle specialists our results support the hypothesis that they target this predictable and plentiful prey during turtle nesting season, but they might not focus on this less predictable food source outside the nesting season.

Rails following snakes: predator-response behaviour, potential prey, prey-flushing or curiosity?

Although snakes are both predators and prey of birds in the Rallidae family in other parts of the world, there are few documented observations of interactions between these groups in Australia. Here we describe four separate observations of Buff-banded Rails Gallirallus philippensis following snakes in a deliberate manner. Because of the large size of the different snake species encountered by the Buff- banded Rails during our observations, we consider that it is unlikely that the snakes were viewed as potential prey. The behaviours observed in our accounts, and of flufftails Sarothrura spp. in Africa, suggest that rails are aware of the predatory threat of snakes, and follow them to ensure that they move outside the rails’ area of concern. We suggest that this behaviour is likely to be a deliberate response to encountering a potential (or perceived) terrestrial predator, such as a snake, or that the snake’s movements potentially flush prey suitable for Buff-banded Rails.

Predator behaviour and predation risk in the heterogeneous Arctic environment

1. Habitat heterogeneity and predator behaviour can strongly affect predator–prey interactions but these factors are rarely considered simultaneously, especially when systems encompass multiple predators and prey.

2. In the Arctic, greater snow geese Anser caerulescens atlanticus L. nest in two structurally different habitats: wetlands that form intricate networks of water channels, and mesic tundra where such obstacles are absent. In this heterogeneous environment, goose eggs are exposed to two types of predators: the arctic fox Vulpes lagopus L. and a diversity of avian predators. We hypothesized that, contrary to birds, the hunting ability of foxes would be impaired by the structurally complex wetland habitat, resulting in a lower predation risk for goose eggs.

3. In addition, lemmings, the main prey of foxes, show strong population cycles. We thus further examined how their fluctuations influenced the interaction between habitat heterogeneity and fox predation on goose eggs.

4. An experimental approach with artificial nests suggested that foxes were faster than avian predators to find unattended goose nests in mesic tundra whereas the reverse was true in wetlands. Foxes spent 3·5 times more time between consecutive attacks on real goose nests in wetlands than in mesic tundra. Their attacks on goose nests were also half as successful in wetlands than in mesic tundra whereas no difference was found for avian predators.

5. Nesting success in wetlands (65%) was higher than in mesic tundra (56%) but the difference between habitats increased during lemming crashes (15%) compared to other phases of the cycle (5%). Nests located at the edge of wetland patches were also less successful than central ones, suggesting a gradient in accessibility of goose nests in wetlands for foxes.

6. Our study shows that the structural complexity of wetlands decreases predation risk from foxes but not avian predators in arctic-nesting birds. Our results also demonstrate that cyclic lemming populations indirectly alter the spatial distribution of productive nests due to a complex interaction between habitat structure, prey-switching and foraging success of foxes.

Influence of sea-ice structure on minke whale and other krill-predator distribution

This thesis investigated the extent to which sea-ice structure and complexity could be measured to identify suitable feeding habitat for krill-eating predators such as the Antarctic minke whale (Balaenoptera bonaerensis). The results of this study suggest that the distribution and movement of minke whales is limited by the structure of the sea ice and that the sea ice influences minke whales' habitat use more than their overall distribution. Similar relationships were found for other krill predators such as Adelie penguins and crabeater seals.