Towards a model for student selection in clinical psychology

Background Selection of candidates for clinical psychology programmes is arguably the most important decision made in determining the clinical psychology workforce. However, there are few models to inform the development of selection tools to support selection procedures. The study, using a factor analytic structure, has operationalised the model predicting applicants' capabilities. Method Eighty-eight clinical applicants for entry into a postgraduate clinical psychology programme were assessed on a series of tasks measuring eight capabilities: guided reflection, communication skills, ethical decision making, writing, conceptual reasoning, empathy, and awareness of mind and self-observation. Results Factor analysis revealed three capabilities: labelled “awareness” accounting for 35.71% of variance; “reflection” accounting for 20.56%; and “reasoning” accounting for 18.24% of variance. Fourth year grade point average (GPA) did not correlate with performance on any of the selection capabilities other than a weak correlation with performance on the ethics capability. Conclusions Eight selection capabilities are identified for the selection of candidates independent of GPA. While the model is tentative, it is hoped that the findings will stimulate the development and validation of assessment procedures with good predictive validity which will benefit the training of clinical psychologists and, ultimately, effective service delivery.

Communicating personal amnesty : a model for health promotion in an Australian disability context

Currently pathological and illness-centric policy surrounds the evaluation of the health status of a person experiencing disability. In this research partnerships were built between disability service providers, community development organizations and disability arts organizations to build a translational evaluative methodology prior to implementation of an arts-based workshop that was embedded in a strengths-based approach to health and well-being. The model consisted of three foci: participation in a pre-designed drama-based workshop program; individualized assessment and evaluation of changing health status; and longitudinal analysis of participants changing health status in their public lives following the culmination of the workshop series. Participants (n = 15) were recruited through disability service providers and disability arts organizations to complete a 13-week workshop series and public performance. The study developed accumulative qualitative analysis tools and member-checking methods specific to the communication systems used by individual participants. Principle findings included increased confidence for verbal and non-verbal communicators; increased personal drive, ambition and goal-setting; increased arts-based skills including professional engagements as artists; demonstrated skills in communicating perceptions of health status to private and public spheres. Tangential positive observations were evident in the changing recreational, vocational and educational activities participants engaged with pre- and post- the workshop series; participants advocating for autonomous accommodation and health provision and changes in the disability service staff's culture. The research is an example of translational health methodologies in disability studies.

A flexible Bayesian model for describing temporal variability of N2O emissions from an Australian pasture

Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

Mathematical model of counter flow v-grove solar air collector

Double-pass counter flow v-grove collector is considered one of the most efficient solar air-collectors. In this design of the collector, the inlet air initially flows at the top part of the collector and changes direction once it reaches the end of the collector and flows below the collector to the outlet. A mathematical model is developed for this type of collector and simulation is carried out using MATLAB programme. The simulation results were verified with three distinguished research results and it was found that the simulation has the ability to predict the performance of the air collector accurately as proven by the comparison of experimental data with simulation. The difference between the predicted and experimental results is, at maximum, approximately 7% which is within the acceptable limit considering some uncertainties in the input parameter values to allow comparison. A parametric study was performed and it was found that solar radiation, inlet air temperature, flow rate and length has a significant effect on the efficiency of the air collector. Additionally, the results are compared with single flow V-groove collector.

Spatiotemporal model or time series model for assessing city-wide temperature effects on mortality?

Most studies examining the temperature–mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.

To what extent is the Mayer and Salovey (1997) model of emotional intelligence a useful predictor of leadership style and perceived leadership outcomes in Australian educational institutions?

Researchers have found that transformational leadership is related to positive outcomes in educational institutions. Hence, it is important to explore constructs that may predict leadership style in order to identify potential transformational leaders in assessment and selection procedures. Several studies in non-educational settings have found that emotional intelligence is a useful predictor of transformational leadership, but these studies have generally lacked methodological rigor and contextual relevance. This project, set in Australian educational institutions, employed a more rigorous methodology to answer the question: to what extent is the Mayer and Salovey (1997) model of emotional intelligence a useful predictor of leadership style and perceived leadership outcomes? The project was designed to move research in the field forward by using valid and reliable instruments, controlling for other predictors, obtaining an adequately sized sample of current leaders and collecting multiple ratings of their leadership behaviours. The study (N = 144 leaders and 432 raters) results indicated that emotional intelligence was not a useful predictor of leadership style and perceived leadership outcomes. In contrast, several of the other predictors in the study were found to predict leadership style.

A microscopic simulation model to estimate bus rapid transit station bus capacity

The Bus Rapid Transit (BRT) station is the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on BRT line capacity. This study uses microscopic traffic simulation modeling to treat the BRT station operation and to analyze the relationship between station bus capacity and BRT line bus capacity. First, the simulation model is developed for the limit state scenario and then a statistical model is defined and calibrated for a specified range of controlled scenarios of dwell time characteristics. A field survey was conducted to verify the parameters such as dwell time, clearance time and coefficient of variation of dwell time to obtain relevant station bus capacity. The proposed model for BRT bus capacity provides a better understanding of BRT line capacity and is useful to transit authorities in BRT planning, design and operation.

Towards a model of spray-canopy interactions : interception, shatter, bounce and retention of droplets on horizontal leaves

Pesticides used in agricultural systems must be applied in economically viable and environmentally sensitive ways, and this often requires expensive field trials on spray deposition and retention by plant foliage. Computational models to describe whether a spray droplet sticks (adheres), bounces or shatters on impact, and if any rebounding parent or shatter daughter droplets are recaptured, would provide an estimate of spray retention and thereby act as a useful guide prior to any field trials. Parameter-driven interactive software has been implemented to enable the end-user to study and visualise droplet interception and impaction on a single, horizontal leaf. Living chenopodium, wheat and cotton leaves have been scanned to capture the surface topography and realistic virtual leaf surface models have been generated. Individual leaf models have then been subjected to virtual spray droplets and predictions made of droplet interception with the virtual plant leaf. Thereafter, the impaction behaviour of the droplets and the subsequent behaviour of any daughter droplets, up until re-capture, are simulated to give the predicted total spray retention by the leaf. A series of critical thresholds for the stick, bounce, and shatter elements in the impaction process have been developed for different combinations of formulation, droplet size and velocity, and leaf surface characteristics to provide this output. The results show that droplet properties, spray formulations and leaf surface characteristics all influence the predicted amount of spray retained on a horizontal leaf surface. Overall the predicted spray retention increases as formulation surface tension, static contact angle, droplet size and velocity decreases. Predicted retention on cotton is much higher than on chenopodium. The average predicted retention on a single horizontal leaf across all droplet size, velocity and formulations scenarios tested, is 18, 30 and 85% for chenopodium, wheat and cotton, respectively.

Effects of hyperbaric oxygen and inducible nitric oxide synthase inhibitor treatment on femoral head osteonecrosis in a rat model

Introduction: Apoptosis is the final destiny of many cells in the body, though this process has been observed in some pathological processes. One of these pathological processes is femoral head non-traumatic osteonecrosis. Among many pro/anti-apoptotic factors, nitric oxide has recently been an area of further interest. Osteocyte apoptosis and its relation to pro-apoptotic action invite further research, and the inducible form of nitric oxide synthase (iNOS)—which produces a high concentration of nitric oxide—has been flagged. The aim of this study was to investigate the effect of hyperbaric oxygen (HBO) and inducible NOS suppressor (Aminoguanidine) in prevention of femoral head osteonecrosis in an experimental model of osteonecrosis in spontaneous hypertensive rats (SHRs). Methods: After animal ethic approval 34 SHR rats were divided into four groups. Ten rats were allocated to the control group without any treatment, and eight rats were allocated to three treatment groups namely: HBO, Aminoguanidine (AMG), and the combination of HBO and AMG treatments (HBO+AMG). The HBO group received 250 kPa of oxygen via hyperbaric chamber for 30 days started at their 5th week of life; the AMG group received 1mg/ml of AMG in drinking water from the fifth week till the 17th week of life; and the last group received a combination of these treatments. Rats were sacrificed at the end of the 17th week of life and both femurs were analysed for evidence of osteonecrosis using Micro CT scan and H&E staining. Also, osteocyte apoptosis and the presence of two different forms of NOS (inducible (iNOS) and endothelial (eNOS)) were analysed by immunostaining and apoptosis staining (Hoechst and TUNEL). Results: Bone morphology of metaphyseal and epiphyseal area of all rats were investigated and analysed. Micro CT findings revealed significantly higher mean fractional trabecular bone volume (FBV) of metaphyseal area in untreated SHRs compared with all other treatments (HBO, P<0.05, HBO+AMG, P<0.005, and AMG P<0.001). Bone surface to volume ratio also significantly increased with HBO+AMG and AMG treatments when compared with the control group (18.7 Vs 20.8, P<0.05, and 18.7 Vs 21.1, P<0.05). Epiphyseal mean FBV did not change significantly among groups. In the metaphyseal area, trabecular thickness and numbers significantly decreased with AMG treatment, while trabecular separation significantly increased with both AMG and HBO+AMG treatment. Histological ratio of no ossification and osteonecrosis was 37.5%, 43.7%, 18.7% and 6.2% of control, HBO, HBO+AMG and AMG groups respectively with only significant difference observed between HBO and AMG treatment (P<0.01). High concentration of iNOS was observed in the region of osteonecrosis while there was no evidence of eNOS activity around that region. In comparison with the control group, the ratio of osteocyte apoptosis significantly reduced in AMG treatment (P<0.005). We also observed significantly fewer apoptotic osteocytes in AMG group comparing with HBO treatment (P<0.05). Conclusion: None of our treatments prevents osteonecrosis at the histological or micro CT scan level. High concentration of iNOS in the region of osteonecrosis and significant reduction of osteocyte apoptosis with AMG treatment were supportive of iNOS modulating osteocyte apoptosis in SHRs.

Using a Capability Maturity Model to build on the generational approach to student engagement practices

The generational approach to conceptualising first year student learning behaviour has made a useful contribution to understanding student engagement. It has an explicit focus on student behaviour and we suggest that a capability maturity model interpretation may provide a complementary extension of that understanding as it builds on the generational approach by allowing an assessment of institutional capability to initiate, plan, manage, evaluate and review institutional student engagement practices. The development of a Student Engagement, Success and Retention Maturity Model (SESR-MM) is discussed along with its application in an Australian higher education institution. In this case study, the model identified first, second and third generation approaches and in addition achieved a ‘complementary extension’ of the generational approach, building on it by identifying additional practices not normally considered within the generational concept and indicating the capability of the institution to provide and implement the practices.

Management issues in developing a sustainable model for supporting entrepreneurs in Africa

Small and micro-enterprises play a significant part in economic growth and poverty alleviation in developing African countries. There are, however, a range of management issues that arise when looking at the support required for local enterprise development, the role and management style of the local support agency and the role and style of the, usually Western, funding body. This paper explores the management philosophy required to establish and resource micro-enterprise development and compares the local management processes with those expected by a Western funding body.

Heat-producing crust regulation of subsurface temperatures : a stochastic model re-evaluation of the geothermal potential in western Queensland, Australia

A large subsurface, elevated temperature anomaly is well documented in Central Australia. High Heat Producing Granites (HHPGs) intersected by drilling at Innamincka are often assumed to be the dominant cause of the elevated subsurface temperatures, although their presence in other parts of the temperature anomaly has not been confirmed. Geological controls on the temperature anomaly remain poorly understood. Additionally, methods previously used to predict temperature at 5 km depth in this area are simplistic and possibly do not give an accurate representation of the true distribution and magnitude of the temperature anomaly. Here we re-evaluate the geological controls on geothermal potential in the Queensland part of the temperature anomaly using a stochastic thermal model. The results illustrate that the temperature distribution is most sensitive to the thermal conductivity structure of the top 5 km. Furthermore, the results indicate the presence of silicic crust enriched in heat producing elements between and 40 km.

An androgen receptor mutation in the MDA-MB-453 cell line model of molecular apocrine breast cancer compromises receptor activity

Recent evidence indicates that the estrogen receptor-a-negative, androgen receptor (AR)- positive molecular apocrine subtype of breast cancer is driven by AR signaling. The MDA-MB-453 cell line is the prototypical model of this breast cancer subtype; its proliferation is stimulated by androgens such as 5a-dihydrotestosterone (DHT) but inhibited by the progestin medroxyprogesterone acetate (MPA) via AR-mediated mechanisms. We report here that the AR gene in MDAMB- 453 cells contains a G-T transversion in exon 7, resulting in a receptor variant with a glutamine to histidine substitution at amino acid 865 (Q865H) in the ligand binding domain. Compared with wild-type AR, the Q865H variant exhibited reduced sensitivity to DHT and MPA in transactivation assays in MDA-MB-453 and PC-3 cells but did not respond to non-androgenic ligands or receptor antagonists. Ligand binding, molecular modeling, mammalian two-hybrid and immunoblot assays revealed effects of the Q865H mutation on ligand dissociation, AR intramolecular interactions, and receptor stability. Microarray expression profiling demonstrated that DHT and MPA regulate distinct transcriptional programs in MDA-MB-453 cells. Gene Set Enrichment Analysis revealed that DHT- but not MPA-regulated genes were associated with estrogen-responsive transcriptomes from MCF-7 cells and the Wnt signaling pathway. These findings suggest that the divergent proliferative responses of MDA-MB-453 cells to DHT and MPA result from the different genetic programs elicited by these two ligands through the AR-Q865H variant. This work highlights the necessity to characterize additional models of molecular apocrine breast cancer to determine the precise role of AR signaling in this breast cancer subtype. Endocrine-Related Cancer (2012) 19 599–613

Vision-based estimation of airborne target pseudobearing rate using hidden Markov model filters

The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information.

Agent-based model of passenger flows in airport terminals

Passenger flow studies in airport terminals have shown consistent statistical relationships between airport spatial layout and pedestrian movement, facilitating prediction of movement from terminal designs. However, these studies are done at an aggregate level and do not incorporate how individual passengers make decisions at a microscopic level. Therefore, they do not explain the formation of complex movement flows. In addition, existing models mostly focus on standard airport processing procedures such as immigration and security, but seldom consider discretionary activities of passengers, and thus are not able to truly describe the full range of passenger flows within airport terminals. As the route-choice decision-making of passengers involves many uncertain factors within the airport terminals, the mechanisms to fulfill the capacity of managing the route-choice have proven difficult to acquire and quantify. Could the study of cognitive factors of passengers (i.e. human mental preferences of deciding which on-airport facility to use) be useful to tackle these issues? Assuming the movement in virtual simulated environments can be analogous to movement in real environments, passenger behaviour dynamics can be similar to those generated in virtual experiments. Three levels of dynamics have been devised for motion control: the localised field, tactical level, and strategic level. A localised field refers to basic motion capabilities, such as walking speed, direction and avoidance of obstacles. The other two fields represent cognitive route-choice decision-making. This research views passenger flow problems via a "bottom-up approach", regarding individual passengers as independent intelligent agents who can behave autonomously and are able to interact with others and the ambient environment. In this regard, passenger flow formation becomes an emergent phenomenon of large numbers of passengers interacting with others. In the thesis, first, the passenger flow in airport terminals was investigated. Discretionary activities of passengers were integrated with standard processing procedures in the research. The localised field for passenger motion dynamics was constructed by a devised force-based model. Next, advanced traits of passengers (such as their desire to shop, their comfort with technology and their willingness to ask for assistance) were formulated to facilitate tactical route-choice decision-making. The traits consist of quantified measures of mental preferences of passengers when they travel through airport terminals. Each category of the traits indicates a decision which passengers may take. They were inferred through a Bayesian network model by analysing the probabilities based on currently available data. Route-choice decision-making was finalised by calculating corresponding utility results based on those probabilities observed. Three sorts of simulation outcomes were generated: namely, queuing length before checkpoints, average dwell time of passengers at service facilities, and instantaneous space utilisation. Queuing length reflects the number of passengers who are in a queue. Long queues no doubt cause significant delay in processing procedures. The dwell time of each passenger agent at the service facilities were recorded. The overall dwell time of passenger agents at typical facility areas were analysed so as to demonstrate portions of utilisation in the temporal aspect. For the spatial aspect, the number of passenger agents who were dwelling within specific terminal areas can be used to estimate service rates. All outcomes demonstrated specific results by typical simulated passenger flows. They directly reflect terminal capacity. The simulation results strongly suggest that integrating discretionary activities of passengers makes the passenger flows more intuitive, observing probabilities of mental preferences by inferring advanced traits make up an approach capable of carrying out tactical route-choice decision-making. On the whole, the research studied passenger flows in airport terminals by an agent-based model, which investigated individual characteristics of passengers and their impact on psychological route-choice decisions of passengers. Finally, intuitive passenger flows in airport terminals were able to be realised in simulation.