Predicting depressive and anxiety disorders with the YASR internalising scales (empirical and DSM-oriented)

Background The Achenbach problem behaviour scales (CBCL/YSR) are widely used. The DSM-oriented anxiety and depression scales have been created to improve concordance between Achenbach’s internalising scales and DSM-IV depression and anxiety. To date no study has examined the concurrent utility of the young adult (YASR) internalising scales, either the empirical or newly developed DSM-oriented depressive or anxiety scales. Methods A sample of 2,551 young adults, aged 18–23 years, from an Australian cohort study. The association between the empirical and DSM-oriented anxiety and depression scales were individually assessed against DSMIV depression and anxiety diagnoses derived from structured interview. Odds ratios, ROC analyses and diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values) were used to report findings. Results YASR empirical internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. DSM-oriented depressive or anxiety scales did not appear to improve the concordance with DSM-IV diagnosed depression or anxiety. The internalising scales were much more effective at identifying those with comorbid depression and anxiety, with Ors between 10.1 and 21.7 depending on the internalising scale used. Conclusion DSM-oriented scales perform no better than the standard internalising in identifying young adults with DSM-IV mood or anxiety disorder.

The ISR and ESR scales : measures of the project manager-stakeholder relationship

In this paper, we develop two stakeholder relationships scales. These scales assess project managers’ perceived competence in establishing and maintaining high quality, effective relationships with people internal to the project as well as those stakeholders who are external to the project. We developed the scales using an online survey study of three hundred and seventy three complex project managers from a sub-set of the Australian Defence Industry. Both the internal stakeholder relationships’ scale and the external stakeholder relationships’ scale demonstrated validity and reliability. This research has implications for the interpersonal work relationships’ literature and the stakeholder management literature. We recommend future research tests these scales with multiple samples, across different project types and project industries. The stakeholder relationships’ scales should be versatile enough to be applied to project management generally but are best suited to large-scale complex project environments.

A review of sedation scales for the cardiac catheterization laboratory

Sedation scales have the potential to facilitate effective procedural sedation and analgesia in the cardiac catheterization laboratory (CCL). For this potential to become realised, a scale that is suitable for use in the CCL either needs to be identified or developed. To identify sedation scales, a review of Medline and CINHAL was conducted. One sedation scale for the CCL, the NASPE SED, and 15 Intensive Care Unit (ICU) scales met the inclusion and exclusion criteria. Analysis of the scale’s item structures and psychometric properties was then performed. None of these scales were deemed suitable for use in the CCL. As such, further research is required to develop a new scale. The new scale should consist of more than one item because it will be the most effective for tracking the patient’s response to medications. Specific tests required to conduct a rigorous evaluation of the new scale’s psychometric properties are outlined in this paper.

The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data. Given a spatial point-based dataset (such as occurrence of a disease), we study the geographical variation of residual disease risk using regular grid cells. The individual disease risk is modelled using a logistic model with the inclusion of spatially unstructured and/or spatially structured random effects. Three spatial smoothness priors for the spatially structured component are employed in modelling, namely an intrinsic Gaussian Markov random field, a second-order random walk on a lattice, and a Gaussian field with Matern correlation function. We investigate how changes in grid cell size affect model outcomes under different spatial structures and different smoothness priors for the spatial component. A realistic example (the Humberside data) is analyzed and a simulation study is described. Bayesian computation is carried out using an integrated nested Laplace approximation. The results suggest that the performance and predictive capacity of the spatial models improve as the grid cell size decreases for certain spatial structures. It also appears that different spatial smoothness priors should be applied for different patterns of point data.

Towards bio-inspired place recognition over multiple spatial scales

This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

Assessing the construct validity and reliability of the parental perception on antibiotics (PAPA) scales

Background: The overuse of antibiotics is becoming an increasing concern. Antibiotic resistance, which increases both the burden of disease, and the cost of health services, is perhaps the most profound impact of antibiotics overuse. Attempts have been made to develop instruments to measure the psychosocial constructs underlying antibiotics use, however, none of these instruments have undergone thorough psychometric validation. This study evaluates the psychometric properties of the Parental Perceptions on Antibiotics (PAPA) scales. The PAPA scales attempt to measure the factors influencing parental use of antibiotics in children. Methods: 1111 parents of children younger than 12 years old were recruited from primary schools’ parental meetings in the Eastern Province of Saudi Arabia from September 2012 to January 2013. The structure of the PAPA instrument was validated using Confirmatory Factor Analysis (CFA) with measurement model fit evaluated using the raw and scaled χ2, Goodness of Fit Index, and Root Mean Square Error of Approximation. Results: A five-factor model was confirmed with the model showing good fit. Constructs in the model include: Knowledge and Beliefs, Behaviors, Sources of information, Adherence, and Awareness about antibiotics resistance. The instrument was shown to have good internal consistency, and good discriminant and convergent validity. Conclusion: The availability of an instrument able to measure the psychosocial factors underlying antibiotics usage allows the risk factors underlying antibiotic use and overuse to now be investigated.

Traversability estimation for a planetary rover via experimental kernel learning in a Gaussian process framework

A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.

Motion planning and stochastic control with experimental validation on a planetary rover

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This model is used to construct a control policy for navigation to a goal region in a terrain map built using an on-board RGB-D camera. The terrain includes flat ground, small rocks, and non-traversable rocks. We report the results of 200 simulated and 35 experimental trials that validate the approach and demonstrate the value of considering control uncertainty in maintaining platform safety.

Enhanced locomotion control for a planetary rover

This article presents an approach to improve and monitor the behavior of a skid-steering rover on rough terrains. An adaptive locomotion control generates speeds references to avoid slipping situations. An enhanced odometry provides a better estimation of the distance travelled. A probabilistic classification procedure provides an evaluation of the locomotion efficiency on-line, with a detection of locomotion faults. Results obtained with a Marsokhod rover are presented throughout the paper

Feral pig populations are structured at fine spatial scales in tropical Queensland, Australia

Feral pigs occur throughout tropical far north Queensland, Australia and are a significant threat to biodiversity and World Heritage values, agriculture and are a vector of infectious diseases. One of the constraints on long-lasting, local eradication of feral pigs is the process of reinvasion into recently controlled areas. This study examined the population genetic structure of feral pigs in far north Queensland to identify the extent of movement and the scale at which demographically independent management units exist. Genetic analysis of 328 feral pigs from the Innisfail to Tully region of tropical Queensland was undertaken. Seven microsatellite loci were screened and Bayesian clustering methods used to infer population clusters. Sequence variation at the mitochondrial DNA control region was examined to identify pig breed. Significant population structure was identified in the study area at a scale of 25 to 35 km, corresponding to three demographically independent management units (MUs). Distinct natural or anthropogenic barriers were not found, but environmental features such as topography and land use appear to influence patterns of gene flow. Despite the strong, overall pattern of structure, some feral pigs clearly exhibited ancestry from a MU outside of that from which they were sampled indicating isolated long distance dispersal or translocation events. Furthermore, our results suggest that gene flow is restricted among pigs of domestic Asian and European origin and non-random mating influences management unit boundaries. We conclude that the three MUs identified in this study should be considered as operational units for feral pig control in far north Queensland. Within a MU, coordinated and simultaneous control is required across farms, rainforest areas and National Park Estates to prevent recolonisation from adjacent localities.

Mechanics of microfilaments networks : a cross-scales study

The mechanical properties of microfilament networks are systematically summarized at different special scales in this paper. We have presented the mechanical models of single microfilaments and microfilament networks at microscale. By adopting a coarse-grained simulation strategy, the mechanical stability of microfilaments related cellular structures are analysed. Structural analysis is conducted to microfilament networks to understand the stress relaxation under compression. The nanoscale molecular mechanisms of the microfilaments deformation is also summarized from the viewpoint of molecular dynamics simulation. This paper provides the fundaments of multiscale modelling framework for the mechanical behaviours simulation of hierarchical microfilament networks.

Estimating local stream fish assemblage attributes: Sampling effort and efficiency at two spatial scales

As part of a wider study to develop an ecosystem-health monitoring program for wadeable streams of south-eastern Queensland, Australia, comparisons were made regarding the accuracy, precision and relative efficiency of single-pass backpack electrofishing and multiple-pass electrofishing plus supplementary seine netting to quantify fish assemblage attributes at two spatial scales (within discrete mesohabitat units and within stream reaches consisting of multiple mesohabitat units). The results demonstrate that multiple-pass electrofishing plus seine netting provide more accurate and precise estimates of fish species richness, assemblage composition and species relative abundances in comparison to single-pass electrofishing alone, and that intensive sampling of three mesohabitat units (equivalent to a riffle-run-pool sequence) is a more efficient sampling strategy to estimate reach-scale assemblage attributes than less intensive sampling over larger spatial scales. This intensive sampling protocol was sufficiently sensitive that relatively small differences in assemblage attributes (<20%) could be detected with a high statistical power (1-β > 0.95) and that relatively few stream reaches (<4) need be sampled to accurately estimate assemblage attributes close to the true population means. The merits and potential drawbacks of the intensive sampling strategy are discussed, and it is deemed to be suitable for a range of monitoring and bioassessment objectives.