Motivational Interviewing (MINT) improves Continuous Positive Airway Pressure (CPAP) acceptance and adherence : a randomised controlled trial

Objective: Adherence to Continuous Positive Airway Pressure Therapy (CPAP) for Obstructive Sleep Apnoea (OSA) is poor. We assessed the effectiveness of a motivational interviewing intervention (MINT) in addition to best practice standard care to improve acceptance and adherence to CPAP therapy in people with a new diagnosis of OSA. Method: 106 Australian adults (69% male) with a new diagnosis of obstructive sleep apnoea and clinical recommendation for CPAP treatment were recruited from a tertiary sleep disorders centre. Participants were randomly assigned to receive either three sessions of a motivational interviewing intervention ‘MINT’ (n=53; mean age=55.4 years), or no intervention ‘Control’ (n=53; mean age=57.74). The primary outcome was the difference between the groups in objective CPAP adherence at 1 month, 2 months, 3 months and 12 months follow-up. Results: Fifty (94%) participants in the MINT group and 50 (94%) of participants in the control group met all inclusion and exclusion criteria and were included in the primary analysis. The hours of CPAP use per night in the MINT group at 3 months was 4.63 hours and 3.16 hours in the control group (p=0.005). This represents almost 50% better adherence in the MINT group relative to the control group. Patients in the MINT group were substantially more likely to accept CPAP treatment. Conclusions: MINT is a brief, manualized, effective intervention which improves CPAP acceptance and objective adherence rates as compared to standard care alone.

Loop closure detection on a suburban road network using a continuous appearance-based trajectory

This paper presents a novel technique for performing SLAM along a continuous trajectory of appearance. Derived from components of FastSLAM and FAB-MAP, the new system dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM) augments appearancebased place recognition with particle-filter based ‘pose filtering’ within a probabilistic framework, without calculating global feature geometry or performing 3D map construction. For loop closure detection CAT-SLAM updates in constant time regardless of map size. We evaluate the effectiveness of CAT-SLAM on a 16km outdoor road network and determine its loop closure performance relative to FAB-MAP. CAT-SLAM recognizes 3 times the number of loop closures for the case where no false positives occur, demonstrating its potential use for robust loop closure detection in large environments.

Using incomplete online metric maps for topological exploration with the Gap Navigation Tree

This paper presents a general, global approach to the problem of robot exploration, utilizing a topological data structure to guide an underlying Simultaneous Localization and Mapping (SLAM) process. A Gap Navigation Tree (GNT) is used to motivate global target selection and occluded regions of the environment (called “gaps”) are tracked probabilistically. The process of map construction and the motion of the vehicle alters both the shape and location of these regions. The use of online mapping is shown to reduce the difficulties in implementing the GNT.

CAT-SLAM : probabilistic localisation and mapping using a continuous appearance-based trajectory

This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

New maps of learning for quality art education : what pre-service teachers should learn and be able to do

It would be a rare thing to visit an early years setting or classroom in Australia that does not display examples of young children’s artworks. This practice serves to give schools a particular ‘look’, but is no guarantee of quality art education. The Australian National Review of Visual Arts Education (NRVE) (2009) has called for changes to visual art education in schools. The planned new National Curriculum includes the arts (music, dance, drama, media and visual arts) as one of the five learning areas. Research shows that it is the classroom teacher that makes the difference, and teacher education has a large part to play in reforms to art education. This paper provides an account of one foundation unit of study (Unit 1) for first year university students enrolled in a 4-year Bachelor degree program who are preparing to teach in the early years (0–8 years). To prepare pre-service teachers to meet the needs of children in the 21st century, Unit 1 blends old and new ways of seeing art, child and pedagogy. Claims for the effectiveness of this model are supported with evidence-based research, conducted over the six years of iterations and ongoing development of Unit 1.

Continuous intravenous infusion of glucose induces endogenous hyperinsulinaemia and lamellar histopathology in Standardbred horses

Endocrinopathic laminitis is frequently associated with hyperinsulinaemia but the role of glucose in the pathogenesis of the disease has not been fully investigated. This study aimed to determine the endogenous insulin response to a quantity of glucose equivalent to that administered during a laminitis-inducing, euglycaemic, hyperinsulinaemic clamp, over 48. h in insulin-sensitive Standardbred racehorses. In addition, the study investigated whether glucose infusion, in the absence of exogenous insulin administration, would result in the development of clinical and histopathological evidence of laminitis. Glucose (50% dextrose) was infused intravenously at a rate of 0.68 mL/kg/h for 48. h in treated horses (n = 4) and control horses (n = 3) received a balanced electrolyte solution (0.68 mL/kg/h). Lamellar histology was examined at the conclusion of the experiment. Horses in the treatment group were insulin sensitive (M value 0.039 ± 0.0012. mmol/kg/min and M-to-I ratio (100×) 0.014 ± 0.002) as determined by an approximated hyperglycaemic clamp. Treated horses developed glycosuria, hyperglycaemia (10.7 ± 0.78. mmol/L) and hyperinsulinaemia (208 ± 26.1. μIU/mL), whereas control horses did not. None of the horses became lame as a consequence of the experiment but all of the treated horses developed histopathological evidence of laminitis in at least one foot. Combined with earlier studies, the results showed that laminitis may be induced by either insulin alone or a combination of insulin and glucose, but that it is unlikely to be due to a glucose overload mechanism. Based on the histopathological data, the potential threshold for insulin toxicity (i.e. laminitis) in horses may be at or below a serum concentration of ∼200. μIU/mL.

Towards persistent localization and mapping with a continuous appearance-based topology

Appearance-based localization can provide loop closure detection at vast scales regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale not only with the size of the environment but also with the operation time of the platform. Additionally, repeated visits to locations will develop multiple competing representations, which will reduce recall performance over time. These properties impose severe restrictions on long-term autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. In this paper we present a graphical extension to CAT-SLAM, a particle filter-based algorithm for appearance-based localization and mapping, to provide constant computation and memory requirements over time and minimal degradation of recall performance during repeated visits to locations. We demonstrate loop closure detection in a large urban environment with capped computation time and memory requirements and performance exceeding previous appearance-based methods by a factor of 2. We discuss the limitations of the algorithm with respect to environment size, appearance change over time and applications in topological planning and navigation for long-term robot operation.

Validation of a new hand-held electronic data capture method for continuous monitoring of subjective appetite sensations

Background When large scale trials are investigating the effects of interventions on appetite, it is paramount to efficiently monitor large amounts of human data. The original hand-held Electronic Appetite Ratings System (EARS) was designed to facilitate the administering and data management of visual analogue scales (VAS) of subjective appetite sensations. The purpose of this study was to validate a novel hand-held method (EARS II (HP® iPAQ)) against the standard Pen and Paper (P&P) method and the previously validated EARS. Methods Twelve participants (5 male, 7 female, aged 18-40) were involved in a fully repeated measures design. Participants were randomly assigned in a crossover design, to either high fat (>48% fat) or low fat (<28% fat) meal days, one week apart and completed ratings using the three data capture methods ordered according to Latin Square. The first set of appetite sensations was completed in a fasted state, immediately before a fixed breakfast. Thereafter, appetite sensations were completed every thirty minutes for 4h. An ad libitum lunch was provided immediately before completing a final set of appetite sensations. Results Repeated measures ANOVAs were conducted for ratings of hunger, fullness and desire to eat. There were no significant differences between P&P compared with either EARS or EARS II (p > 0.05). Correlation coefficients between P&P and EARS II, controlling for age and gender, were performed on Area Under the Curve ratings. R2 for Hunger (0.89), Fullness (0.96) and Desire to Eat (0.95) were statistically significant (p < 0.05). Conclusions EARS II was sensitive to the impact of a meal and recovery of appetite during the postprandial period and is therefore an effective device for monitoring appetite sensations. This study provides evidence and support for further validation of the novel EARS II method for monitoring appetite sensations during large scale studies. The added versatility means that future uses of the system provides the potential to monitor a range of other behavioural and physiological measures often important in clinical and free living trials.

Building Large Scale Traversability Maps Using Vehicle Experience

Traversability maps are a global spatial representation of the relative difficulty in driving through a local region. These maps support simple optimisation of robot paths and have been very popular in path planning techniques. Despite the popularity of these maps, the methods for generating global traversability maps have been limited to using a-priori information. This paper explores the construction of large scale traversability maps for a vehicle performing a repeated activity in a bounded working environment, such as a repeated delivery task.We evaluate the use of vehicle power consumption, longitudinal slip, lateral slip and vehicle orientation to classify the traversability and incorporate this into a map generated from sparse information.

A sequential Monte Carlo approach to the sequential design for discriminating between rival continuous data models

Here we present a sequential Monte Carlo approach to Bayesian sequential design for the incorporation of model uncertainty. The methodology is demonstrated through the development and implementation of two model discrimination utilities; mutual information and total separation, but it can also be applied more generally if one has different experimental aims. A sequential Monte Carlo algorithm is run for each rival model (in parallel), and provides a convenient estimate of the marginal likelihood (of each model) given the data, which can be used for model comparison and in the evaluation of utility functions. A major benefit of this approach is that it requires very little problem specific tuning and is also computationally efficient when compared to full Markov chain Monte Carlo approaches. This research is motivated by applications in drug development and chemical engineering.

Physical and linkage maps for Drosophila serrata, a model species for studies of clinal adaptation and sexual selection

Drosophila serrata is a member of the montium group, which contains more than 98 species and until recently was considered a subgroup within the melanogaster group. This Drosophila species is an emerging model system for evolutionary quantitative genetics and has been used in studies of species borders, clinal variation and sexual selection. Despite the importance of D. serrata as a model for evolutionary research, our poor understanding of its genome remains a significant limitation. Here, we provide a first-generation gene-based linkage map and a physical map for this species. Consistent with previous studies of other drosophilids we observed strong conservation of genes within chromosome arms homologous with D. melanogaster but major differences in within-arm synteny. These resources will be a useful complement to ongoing genome sequencing efforts and QTL mapping studies in this species

Discretionary use of open briefings in the Australian continuous reporting environment

The Australian Securities Exchange (ASX) listing rule 3.1 requires listed companies to immediately disclose price sensitive information to the market via the ASX’s Company Announcements Platform (CAP) prior to release through other disclosure channels. Since 1999, to improve the communication process, the ASX has permitted third-party mediation in the disclosure process that leads to the release of an Open Briefing (OB) through CAP. An OB is an interview between senior executives of the firm and an Open Briefing analyst employed by Orient Capital Pty Ltd (broaching topics such as current profit and outlook). Motivated by an absence of research on factors that influence firms to use OBs as a discretionary disclosure channel, this study examines (1) Why do firms choose to release information to the market via OBs?, (2) What are the firm characteristics that explain the discretionary use of OBs as a disclosure channel?, and (3) What are the disclosure attributes that influence firms’ decisions to regularly use OBs as a disclosure channel? Based on agency and information economics theories, a theoretical framework is developed to address research questions. This theoretical framework comprises disclosure environments such as firm characteristics and external factors, disclosure attributes and disclosure consequences. In order to address the first research question, the study investigates (i) the purpose of using OBs, (2) whether firms use OBs to provide information relating to previous public announcements, and (3) whether firms use OBs to provide routine or non-routine disclosures. In relation to the second and third research questions, hypotheses are developed to test factors expected to explain the discretionary use of OBs and firms’ decisions to regularly use OBs, and to explore the factors influencing the nature of OB disclosure. Content analysis and logistic regression models are used to investigate the research questions and test the hypotheses. Data are drawn from a hand-collected population of 1863 OB announcements issued by 239 listed firms between 2000 and 2010. The results show that types of information disclosed via an OB announcement are principally on matters relating to corporate strategies and performance and outlook. Most OB announcements are linked with a previous related announcement, with the lag between announcements significantly longer for loss-making firms than profitmaking firms. The main results show that firms which tend to be larger, have an analyst following, and have higher growth opportunities, are more likely to release OBs. Further, older firms and firms that release OB announcements containing good news, historical information and less complex information tend to be regular OB users. Lastly, firms more likely to disclose strategic information via OBs tend to operate in industries facing greater uncertainty, do not have analysts following, and have higher growth opportunities are less likely to disclose good news, historical information and complex information via OBs. This study is expected to contribute to disclosure literature in terms of disclosure attributes and firm characteristics that influence behaviour in this unique (OB) disclosure channel. With regard to practical significance, regulators can gain an understanding of how OBs are disclosed which can assist them in monitoring the use of OBs and improving the effectiveness of communications with stakeholders. In addition, investors can have a better comprehension of information contained in OB announcements, which may in turn better facilitate their investment decisions.

An examination of keystroke dynamics for continuous user authentication

Most current computer systems authorise the user at the start of a session and do not detect whether the current user is still the initial authorised user, a substitute user, or an intruder pretending to be a valid user. Therefore, a system that continuously checks the identity of the user throughout the session is necessary without being intrusive to end-user and/or effectively doing this. Such a system is called a continuous authentication system (CAS). Researchers have applied several approaches for CAS and most of these techniques are based on biometrics. These continuous biometric authentication systems (CBAS) are supplied by user traits and characteristics. One of the main types of biometric is keystroke dynamics which has been widely tried and accepted for providing continuous user authentication. Keystroke dynamics is appealing for many reasons. First, it is less obtrusive, since users will be typing on the computer keyboard anyway. Second, it does not require extra hardware. Finally, keystroke dynamics will be available after the authentication step at the start of the computer session. Currently, there is insufficient research in the CBAS with keystroke dynamics field. To date, most of the existing schemes ignore the continuous authentication scenarios which might affect their practicality in different real world applications. Also, the contemporary CBAS with keystroke dynamics approaches use characters sequences as features that are representative of user typing behavior but their selected features criteria do not guarantee features with strong statistical significance which may cause less accurate statistical user-representation. Furthermore, their selected features do not inherently incorporate user typing behavior. Finally, the existing CBAS that are based on keystroke dynamics are typically dependent on pre-defined user-typing models for continuous authentication. This dependency restricts the systems to authenticate only known users whose typing samples are modelled. This research addresses the previous limitations associated with the existing CBAS schemes by developing a generic model to better identify and understand the characteristics and requirements of each type of CBAS and continuous authentication scenario. Also, the research proposes four statistical-based feature selection techniques that have highest statistical significance and encompasses different user typing behaviors which represent user typing patterns effectively. Finally, the research proposes the user-independent threshold approach that is able to authenticate a user accurately without needing any predefined user typing model a-priori. Also, we enhance the technique to detect the impostor or intruder who may take over during the entire computer session.