The peer leader capacity building model: A student learning journey

The benefits of peer leader experiences in building graduate skills and capabilities, is well documented and recognised in the higher education sector (Ender & Kay, 2001; Lindsey, Weiler, Zarich, Haddock, Krafchick, & Zimmerman, 2014; Shook & Keup, J., 2012). While benefits are acknowledged, responsibility for identifying, structuring and recording the learning experiences and learning outcomes is charged to the student. This poster describes a framework ‘The Peer Leader Capacity Building Model’ that purposefully structures the peer-leader’s learning journey providing: timely training, moments of critical reflection and goal setting. The model articulates the fundamental interplay of learning and peer leader service which forms the peer ‘learnership’. The journey begins with the ‘aspiration’ phase where students come to understand their leadership opportunities, progressing through ‘enabling’ and ‘mastering’ phases where students shape their learner-leader experience, and finally, to the ‘contributing graduate’ phase where students emerge as competent graduates able to confidently participate in their communities and workplaces. In shifting from a program centric approach that priorities the needs of the mentees, the Peer Leader Capacity Building Model focuses on the individual as a peer leader encouraging the student to shape their individual ‘learnscape’ through consciously navigating both their curricula and co-curricular learning experiences.

Sport across cultures: Applications of the human capital model in refugee communities

When working with the world’s most vulnerable populations there are questions surrounding the salience of physical activity promotion programs given the multitude of basic needs that must first be met. Indeed, physical activity may be a low priority for individuals seeking safety, reunification with loved ones, and food for their families, as a subsistence lifestyle makes excess weight gain, diabetes, and cardiovascular disease irrelevant. Yet, when working with people from a refugee background for whom these challenges all too frequently apply, opportunities for sport and activity have repeatedly surfaced as desirable and needed, yet are utterly deficient. If we conceptualize physical activity purely as a chronic disease prevention tool, its significance within under-resourced communities is most assuredly lost; however, if we harness the power of physical activity to serve as an agent of positive social change, then it instantly becomes more meaningful and necessary.

A configurable airport reference model for passenger facilitation

The air transport industry is a complex environment facing many challenges while coping with changing global imperatives. International airport passenger facilitation is a part of the socio-technical system where these challenges manifest, impacting businesses in terms of time, cost and quality. This research inductively develops an extensible configurable reference model by capturing and merging the cross-organisational facilitation process from five Australian airports. The reference model can be filtered according to the contextual needs of airport users to inform relevant and accurate business process design. The domain and methodological contributions constitute the first reported application of questionnaire-based configurability to airport processes.

An Aboriginal nurse-led working model for success in graduating Indigenous Australian nurses

Australia needs more Indigenous nurses. This is widely recognised in both academic literature and government policy. In 2012, only 0.8 percent of the Australian nursing workforce was Indigenous (AIHW, 2012). In spite of the clear need, there is little discussion about how to successfully recruit, retain and graduate Indigenous nursing students. This paper describes a successful program being implemented at the University of Southern Queensland (USQ). Between 2000 and 2012, USQ graduated 80 Indigenous nurses and midwives, at both undergraduate and postgraduate levels. In this paper, the authors outline the journey they undertook to develop the successful program at USQ: the Indigenous Nursing Support (INS) Model: Helping Hands. They argue that four elements underpin success for Indigenous nursing students: the availability of Indigenous academics, Indigenous health content in the nursing curriculum, Indigenous-specific recruitment materials, and individual mentoring and nurturing of Indigenous students.

Development and validation of a multilevel model for predicting workload under routine and nonroutine conditions in an air traffic management center

Objective: The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Background: Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. Method: A multilevel workload model was developed in Study 1 with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters. The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Results: Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. Conclusion: The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Application: Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs. Tactical uses include the dynamic reallocation of resources to meet changes in demand.

Coronary calcium scoring: Calcium location needs to be integrated!

Coronary calcium scoring (CCS) has been a topic of great interest lately. In a large population-based study comprising 6,722 patients, Detrano et al. (1) have effectively shown that CCS can be a strong predictor of incident coronary heart disease among different racial groups. Henneman et al. (2) have, however, reported that CCS does not reliably exclude the presence of (significant) atherosclerosis. This topic is quite controversial as there is significant evidence from Detrano's work that higher CCS is associated with an increased risk of acute coronary events. We think that the location of calcium within the coronary arteries should also be considered. Li et al. (3,4) have shown that the position of the calcium in the plaque is a better determinant of plaque vulnerability than the total calcium load. Using a biomechanical model, predicted maximum stress was found to increase by 47.5% when calcium deposits were located in the thin fibrous cap. The presence of calcium deposits in the lipid core or remote from the fibrous cap resulted in no increase in maximum stress. It was also noted that the presence of calcification within the lipid core may even stabilize the plaque. Integration of calcium location in CCS will, therefore, enable better assessment of severity of atherosclerosis and prediction of future cardiovascular events.

Simplified Mathematical Model for Effects of Freezing on the Low-Temperature Performance of the Lead-Acid Battery

Discharge periods of lead-acid batteries are significantly reduced at subzero centigrade temperatures. The reduction is more than what can he expected due to decreased rates of various processes caused by a lowering of temperature and occurs despite the fact that active materials are available for discharge. It is proposed that the major cause for this is the freezing of the electrolyte. The concentration of acid decreases during battery discharge with a consequent increase in the freezing temperature. A battery freezes when the discharge temperature falls below the freezing temperature. A mathematical model is developed for conditions where charge-transfer reaction is the rate-limiting step. and Tafel kinetics are applicable. It is argued that freezing begins from the midplanes of electrodes and proceeds toward the reservoir in-between. Ionic conduction stops when one of the electrodes freezes fully and the time taken to reach that point, namely the discharge period, is calculated. The predictions of the model compare well to observations made at low current density (C/5) and at -20 and -40 degrees C. At higher current densities, however, diffusional resistances become important and a more complicated moving boundary problem needs to be solved to predict the discharge periods. (C) 2009 The Electrochemical Society.

Assessing performance in critical care nursing practice using the Benner Novice to expert model: A pilot study

Background It is often believed that by ensuring the ongoing completion of competency documents and life-long learning in nursing practice guarantees quality patient care. This is probably true in most cases where it provides reassurances that the nursing team is maintaining a safe “generalised” level of practice. However, competency does not always promise quality performance. There are a number of studies that have reported differences in what practitioners know and what they actually do despite being deemed competent. Aim The aim of this study was to assess whether our current competency documentation is fit for purpose and to ascertain whether performance assessment needs to be a key component in determining competence. Method 15 nurses within a General ICU who had been on the unit <4 years agreed to participate in this project. Using participant observation and assessing performance against key indicators of the Benner Novice to Expert5 model the participants were supported and assessed over the course of a ‘normal’ nursing shift. Results The results were surprising both positively and negatively. First, the nurses felt more empowered in their clinical decision making skills; second, it identified individual learning needs and milestones in educational development. There were some key challenges identified which included 5 nurses over estimating their level of competence, practice was still very much focused on task acquisition and skill and surprisingly some nurses still felt dominated by the other health professionals within the unit. Conclusion We found that the capacity and capabilities of our nursing workforce needs continual ongoing support especially if we want to move our staff from capable task-doer to competent performers. Using the key novice to expert indicators identified the way forward for us in how we assess performance and competence in practice particularly where promotion to higher grades is based on existing documentation.

Design thinking using a collaborative model for skin cancer prevention

Physical activity is well recognised as a means to reduce cancer risk; however, outdoor activity can increase sun exposure and consequential skin cancer risk. It is proposed, one of the key potential solutions to promote active lifestyles whilst enhancing protection against skin cancer is design resolution for active apparel that considers Australia’s sub-tropical climate whilst maintaining comfort, aesthetic appeal and performance. Using a design thinking approach, facilitated through collaboration between an NGO and a university, student designers were tasked with developing apparel prototypes to explore this challenge. Through practical ideation of problems, potential design solutions were developed within a modest NGO budget and adherence to specific brand guidelines. This project is novel as it demonstrates a low cost yet effective way of collaboratively creating a product to meet multiple needs, rather than reactively assessing already manufactured sun protection products for endorsement. It is a nimble and unique stepping stone in integrating sun safety considerations into clothing that is appealing to the population and creating cross-industry understandings of how design can better contribute to human health and wellbeing. Outcomes to be shared include empirical insights for updating sun safe clothing guidelines, issues around the aesthetic nature of sun safe apparel, and the role of design education for sun safety.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Inhibition of Thrombin in Cardiac Surgery : experiments in a porcine model

Cardiac surgery involving cardiopulmonary bypass (CPB) induces activation of inflammation and coagulation systems and is associated with ischemia-reperfusion injury (I/R injury)in various organs including the myocardium, lungs, and intestine. I/R injury is manifested as organ dysfunction. Thrombin, the key enzyme of coagulation , plays a cenral role also in inflammation and contributes to regulation of apoptosis as well. The general aim of this thesis was to evaluate the potential of thrombin inhibition in reducing the adverse effects of I/R injury in myocardium, lungs, and intestine associated with the use of CPB and cardiac surgery. Forty five pigs were used for the studies. Two randomized blinded studies were performed. Animals underwent 75 min of normothermic CPB, 60 min of aortic clamping, and 120 min of reperfusion period. Twenty animals received iv. recombinant hirudin, a selective and effective inbitor of thrombin, or placebo. In a similar setting, twenty animals received an iv-bolus (250 IU/kg) of antithrombin (AT) or placebo. An additional group of 5 animals received 500 IU/kg in an open label setting to test dose response. Generation of thrombin (TAT), coagulation status (ACT), and hemodynamics were measured. Intramucosal pH and pCO2 were measured from the luminal surface of ileum using tonometry simultaneusly with arterial gas analysis. In addition, myocardial, lung, and intestinal biopsies were taken to quantitate leukocyte infiltration (MPO), for histological evaluation, and detection of apoptosis (TUNEL, caspase 3). In conclusion, our data suggest that r-hirudin may be an effective inhibitor of reperfusion induced thrombin generation in addition to being a direct inhibitor of preformed thrombin. Overall, the results suggest that inhibition of thrombin, beyond what is needed for efficient anticoagulation by heparin, has beneficial effects on myocardial I/R injury and hemodynamics during cardiac surgery and CPB. We showed that infusion of the thrombin inhibitor r-hirudin during reperfusion was associated with attenuated post ischemia left ventricular dysfunction and decreased systemic vascular resistance. Consequently microvascular flow was improved during ischemia-reperfusion injury. Improved recovery of myocardium during the post-ischemic reperfusion period was associated with significantly less cardiomyocyte apoptosis and with a trend in anti-inflammatory effects. Thus, inhibition of reperfusion induced thrombin may offer beneficial effects by mechanisms other than direct anticoagulant effects. AT, in doses with a significant anticoagulant effect, did not alleviate myocardial I/R injury in terms of myocardial recovery, histological inflammatory changes or post-ischemic troponin T release. Instead, AT attenuated reperfusion induced increase in pulmonary pressure after CPB. Taken the clinical significance of postoperative pulmonary hemodynamics in patients undergoing cardiopulmonary bypass, the potential positive regulatory role of AT and clinical implications needs to be studied further. Inflammatory response in the gut wall proved to be poorly associated with perturbed mucosal perfusion and the animals with the least neutrophil tissue sequestration and I/R related histological alterations tended to have the most progressive mucosal hypoperfusion. Thus, mechanisms of low-flow reperfusion injury during CPB can differ from the mechanisms seen in total ischemia reperfusion injury.

A Compact Model incorporating Quantum Effects for Ultra-Thin-Body Double-Gate MOSFETs

We propose a compact model which predicts the channel charge density and the drain current which match quite closely with the numerical solution obtained from the Full-Band structure approach. We show that, with this compact model, the channel charge density can be predicted by taking the capacitance based on the physical oxide thickness, as opposed to C-eff, which needs to be taken when using the classical solution.

A high performance scheme for EEG compression using a multichannel model

The amount of data contained in electroencephalogram (EEG) recordings is quite massive and this places constraints on bandwidth and storage. The requirement of online transmission of data needs a scheme that allows higher performance with lower computation. Single channel algorithms, when applied on multichannel EEG data fail to meet this requirement. While there have been many methods proposed for multichannel ECG compression, not much work appears to have been done in the area of multichannel EEG. compression. In this paper, we present an EEG compression algorithm based on a multichannel model, which gives higher performance compared to other algorithms. Simulations have been performed on both normal and pathological EEG data and it is observed that a high compression ratio with very large SNR is obtained in both cases. The reconstructed signals are found to match the original signals very closely, thus confirming that diagnostic information is being preserved during transmission.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

Characterization of Clean and Fouled Rail Track Ballast Subsurface Using Seismic Surface Survey Method: Model and Field Studies

The efficiency of track foundation material gradually decreases due to insufficient lateral confinement, ballast fouling, and loss of shear strength of the subsurface soil under cyclic loading. This paper presents characterization of rail track subsurface to identify ballast fouling and subsurface layers shear wave velocity using seismic survey. Seismic surface wave method of multi-channel analysis of surface wave (MASW) has been carried out in the model track and field track for finding out shear wave velocity of the clean and fouled ballast and track subsurface. The shear wave velocity (SWV) of fouled ballast increases with increase in fouling percentage, and reaches a maximum value and then decreases. This character is similar to typical compaction curve of soil, which is used to define optimum and critical fouling percentage (OFP and CFP). Critical fouling percentage of 15 % is noticed for Coal fouled ballast and 25 % is noticed for clayey sand fouled ballast. Coal fouled ballast reaches the OFP and CFP before clayey sand fouled ballast. Fouling of ballast reduces voids in ballast and there by decreases the drainage. Combined plot of permeability and SWV with percentage of fouling shows that after critical fouling point drainage condition of fouled ballast goes below acceptable limit. Shear wave velocities are measured in the selected location in the Wollongong field track by carrying out similar seismic survey. In-situ samples were collected and degrees of fouling were measured. Field SWV values are more than that of the model track SWV values for the same degree of fouling, which might be due to sleeper's confinement. This article also highlights the ballast gradation widely followed in different countries and presents the comparison of Indian ballast gradation with international gradation standards. Indian ballast contains a coarser particle size when compared to other countries. The upper limit of Indian gradation curve matches with lower limit of ballast gradation curves of America and Australia. The ballast gradation followed by Indian railways is poorly graded and more favorable for the drainage conditions. Indian ballast engineering needs extensive research to improve presents track conditions.