Simulation and enhancement of a cardiovascular device test rig

Cardiovascular assist devices are tested in mock circulation loops (MCLs) prior to animal and clinical testing. These MCLs rely on characteristics such as pneumatic parameters to create pressure and flow, and pipe dimensions to replicate the resistance, compliance and fluid inertia of the natural cardiovascular system. A mathematical simulation was developed in SIMULINK to simulate an existing MCL. Model validation was achieved by applying the physical MCL characteristics to the simulation and comparing the resulting pressure traces. These characteristics were subsequently altered to improve and thus predict the performance of a more accurate physical system. The simulation was successful in simulating the physical mock circulation loop, and proved to be a useful tool in the development of improved cardiovascular device test rigs.

Changing musical emotion : a computational rule system for modifying score and performance

When communicating emotion in music, composers and performers encode their expressive intentions through the control of basic musical features such as: pitch, loudness, timbre, mode, and articulation. The extent to which emotion can be controlled through the systematic manipulation of these features has not been fully examined. In this paper we present CMERS, a Computational Music Emotion Rule System for the control of perceived musical emotion that modifies features at the levels of score and performance in real-time. CMERS performance was evaluated in two rounds of perceptual testing. In experiment I, 20 participants continuously rated the perceived emotion of 15 music samples generated by CMERS. Three music works, each with five emotional variations were used (normal, happy, sad, angry, and tender). The intended emotion by CMERS was correctly identified 78% of the time, with significant shifts in valence and arousal also recorded, regardless of the works’ original emotion.

Adiabatic compression testing - part II : background and approach to estimating severity of test methodology

Adiabatic compression testing of components in gaseous oxygen is a test method that is utilized worldwide and is commonly required to qualify a component for ignition tolerance under its intended service. This testing is required by many industry standards organizations and government agencies; however, a thorough evaluation of the test parameters and test system influences on the thermal energy produced during the test has not yet been performed. This paper presents a background for adiabatic compression testing and discusses an approach to estimating potential differences in the thermal profiles produced by different test laboratories. A “Thermal Profile Test Fixture” (TPTF) is described that is capable of measuring and characterizing the thermal energy for a typical pressure shock by any test system. The test systems at Wendell Hull & Associates, Inc. (WHA) in the USA and at the BAM Federal Institute for Materials Research and Testing in Germany are compared in this manner and some of the data obtained is presented. The paper also introduces a new way of comparing the test method to idealized processes to perform system-by-system comparisons. Thus, the paper introduces an “Idealized Severity Index” (ISI) of the thermal energy to characterize a rapid pressure surge. From the TPTF data a “Test Severity Index” (TSI) can also be calculated so that the thermal energies developed by different test systems can be compared to each other and to the ISI for the equivalent isentropic process. Finally, a “Service Severity Index” (SSI) is introduced to characterizing the thermal energy of actual service conditions. This paper is the second in a series of publications planned on the subject of adiabatic compression testing.

Trauma and Injury Severity Score (TRISS) coefficients 2009 revision

Background: Currently used Trauma and Injury Severity Score (TRISS) coefficients, which measure probability of survival (Ps), were derived from the Major Trauma Outcome Study (MTOS) in 1995 and are now unlikely to be optimal. This study aims to estimate new TRISS coefficients using a contemporary database of injured patients presenting to emergency departments in the United States; and to compare these against the MTOS coefficients.---------- Methods: Data were obtained from the National Trauma Data Bank (NTDB) and the NTDB National Sample Project (NSP). TRISS coefficients were estimated using logistic regression. Separate coefficients were derived from complete case and multistage multiple imputation analyses for each NTDB and NSP dataset. Associated Ps over Injury Severity Score values were graphed and compared by age (adult ≥ 15 years; pediatric < 15 years) and injury mechanism (blunt; penetrating) groups. Area under the Receiver Operating Characteristic curves was used to assess coefficients’ predictive performance.---------- Results: Overall 1,072,033 NTDB and 1,278,563 weighted NSP injury events were included, compared with 23,177 used in the original MTOS analyses. Large differences were seen between results from complete case and imputed analyses. For blunt mechanism and adult penetrating mechanism injuries, there were similarities between coefficients estimated on imputed samples, and marked divergences between associated Ps estimated and those from the MTOS. However, negligible differences existed between area under the receiver operating characteristic curves estimates because the overwhelming majority of patients had minor trauma and survived. For pediatric penetrating mechanism injuries, variability in coefficients was large and Ps estimates unreliable.---------- Conclusions: Imputed NTDB coefficients are recommended as the TRISS coefficients 2009 revision for blunt mechanism and adult penetrating mechanism injuries. Coefficients for pediatric penetrating mechanism injuries could not be reliably estimated.

Reflection on the use of rating and score cards for asset and service assessment

The concept of star rating council facilities has progressively gained traction in Australia following the work of Dean Taylor at Marochy Shire Council in Queensland in 2006 – 2007 and more recently by the Victorian STEP asset management program. The following paper provides a brief discussion on the use and merits of star rating within community asset management. We suggest that the current adoption of the star rating system to manage community investment in services is lacking in consistency. It is suggested that the major failing is a lack of clear understanding in the purpose being served by the systems. The discussion goes on to make some recommendations on how the concept of a star system could be further enhanced to serve the needs of our communities better.

The Federal circuit in Bilski : the machine-or-transformation test

In a much anticipated judgment, the Federal Circuit has sought to clarify the standards applicable in determining whether a claimed method constitutes patent-eligible subject matter. In Bilski, the Federal Circuit identified a test to determine whether a patentee has made claims that pre-empt the use of a fundamental principle or an abstract idea or whether those claims cover only a particular application of a fundamental principle or abstract idea. It held that the sole test for determining subject matter eligibility for a claimed process under § 101 is that: (1) it is tied to a particular machine or apparatus, or (2) it transforms a particular article into a different state or thing. The court termed this the “machine-or-transformation test.” In so doing it overruled its earlier State Street decision to the extent that it deemed its “useful, tangible and concrete result” test as inadequate to determine whether an alleged invention recites patent-eligible subject matter.

Learning approach and perception of learning context in economics education : a causality test

In the study of student learning literature, the traditional view holds that when students are faced with heavy workload, poor teaching, and content that they cannot relate to – important aspects of the learning context, they will more likely utilise the surface approach to learning due to stresses, lack of understanding and lack of perceived relevance of the content (Kreber, 2003; Lizzio, Wilson, & Simons, 2002; Ramdsen, 1989; Ramsden, 1992; Trigwell & Prosser, 1991; Vermunt, 2005). For example, in studies involving health and medical sciences students, courses that utilised student-centred, problem-based approaches to teaching and learning were found to elicit a deeper approach to learning than the teacher-centred, transmissive approach (Patel, Groen, & Norman, 1991; Sadlo & Richardson, 2003). It is generally accepted that the line of causation runs from the learning context (or rather students’ self reported data on the learning context) to students’ learning approaches. That is, it is the learning context as revealed by students’ self-reported data that elicit the associated learning behaviour. However, other research studies also found that the same teaching and learning environment can be perceived differently by different students. In a study of students’ perceptions of assessment requirements, Sambell and McDowell (1998) found that students “are active in the reconstruction of the messages and meanings of assessment” (p. 391), and their interpretations are greatly influenced by their past experiences and motivations. In a qualitative study of Hong Kong tertiary students, Kember (2004) found that students using the surface learning approach reported heavier workload than students using the deep learning approach. According to Kember if students learn by extracting meanings from the content and making connections, they will more likely see the higher order intentions embodied in the content and the high cognitive abilities being assessed. On the other hand, if they rote-learn for the graded task, they fail to see the hierarchical relationship in the content and to connect the information. These rote-learners will tend to see the assessment as requiring memorising and regurgitation of a large amount of unconnected knowledge, which explains why they experience a high workload. Kember (2004) thus postulate that it is the learning approach that influences how students perceive workload. Campbell and her colleagues made a similar observation in their interview study of secondary students’ perceptions of teaching in the same classroom (Campbell et al., 2001). The above discussions suggest that students’ learning approaches can influence their perceptions of assessment demands and other aspects of the learning context such as relevance of content and teaching effectiveness. In other words, perceptions of elements in the teaching and learning context are endogenously determined. This study attempted to investigate the causal relationships at the individual level between learning approaches and perceptions of the learning context in economics education. In this study, students’ learning approaches and their perceptions of the learning context were measured. The elements of the learning context investigated include: teaching effectiveness, workload and content. The authors are aware of existence of other elements of the learning context, such as generic skills, goal clarity and career preparation. These aspects, however, were not within the scope of this present study and were therefore not investigated.

Are organ donation communication decisions reasoned or reactive? A test of the utility of an augmented Theory of Planned Behaviour with the Prototype/Willingness Model

Objectives: To explore whether people's organ donation consent decisions occur via a reasoned and/or social reaction pathway. --------- Design: We examined prospectively students' and community members' decisions to register consent on a donor register and discuss organ donation wishes with family. --------- Method: Participants completed items assessing theory of planned behaviour (TPB; attitude, subjective norm, perceived behavioural control (PBC)), prototype/willingness model (PWM; donor prototype favourability/similarity, past behaviour), and proposed additional influences (moral norm, self-identity, recipient prototypes) for registering (N=339) and discussing (N=315) intentions/willingness. Participants self-reported their registering (N=177) and discussing (N=166) behaviour 1 month later. The utility of the (1) TPB, (2) PWM, (3) augmented TPB with PWM, and (4) augmented TPB with PWM and extensions was tested using structural equation modelling for registering and discussing intentions/willingness, and logistic regression for behaviour. --------- Results: While the TPB proved a more parsimonious model, fit indices suggested that the other proposed models offered viable options, explaining greater variance in communication intentions/willingness. The TPB, augmented TPB with PWM, and extended augmented TPB with PWM best explained registering and discussing decisions. The proposed and revised PWM also proved an adequate fit for discussing decisions. Respondents with stronger intentions (and PBC for registering) had a higher likelihood of registering and discussing. --------- Conclusions: People's decisions to communicate donation wishes may be better explained via a reasoned pathway (especially for registering); however, discussing involves more reactive elements. The role of moral norm, self-identity, and prototypes as influences predicting communication decisions were highlighted also.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

An investigation of foot and ankle problems experienced by nurses

Relatively little information has been reported about foot and ankle problems experienced by nurses, despite anecdotal evidence which suggests they are common ailments. The purpose of this study was to improve knowledge about the prevalence of foot and ankle musculoskeletal disorders (MSDs) and to explore relationships between these MSDs and proposed risk factors. A review of the literature relating to work-related MSDs, MSDs in nursing, foot and lower-limb MSDs, screening for work-related MSDs, foot discomfort, footwear and the prevalence of foot problems in the community was undertaken. Based on the review, theoretical risk factors were proposed that pertained to the individual characteristics of the nurses, their work activity or their work environment. Three studies were then undertaken. A cross-sectional survey of 304 nurses, working in a large tertiary paediatric hospital, established the prevalence of foot and ankle MSDs. The survey collected information about self-reported risk factors of interest. The second study involved the clinical examination of a subgroup of 40 nurses, to examine changes in body discomfort, foot discomfort and postural sway over the course of a single work shift. Objective measurements of additional risk factors, such as individual foot posture (arch index) and the hardness of shoe midsoles, were performed. A final study was used to confirm the test-retest reliability of important aspects of the survey and key clinical measurements. Foot and ankle problems were the most common MSDs experienced by nurses in the preceding seven days (42.7% of nurses). They were the second most common MSDs to cause disability in the last 12 months (17.4% of nurses), and the third most common MSDs experienced by nurses in the last 12 months (54% of nurses). Substantial foot discomfort (Visual Analogue Scale (VAS) score of 50mm or more) was experienced by 48.5% of nurses at sometime in the last 12 months. Individual risk factors, such as obesity and the number of self-reported foot conditions (e.g., callouses, curled toes, flat feet) were strongly associated with the likelihood of experiencing foot problems in the last seven days or during the last 12 months. These risk factors showed consistent associations with disabling foot conditions and substantial foot discomfort. Some of these associations were dependent upon work-related risk factors, such as the location within the hospital and the average hours worked per week. Working in the intensive care unit was associated with higher odds of experiencing foot problems within the last seven days, foot problems in the last 12 months and foot problems that impaired activity in the last 12 months. Changes in foot discomfort experienced within a day, showed large individual variability. Fifteen of the forty nurses experienced moderate/substantial foot discomfort at the end of their shift (VAS 25+mm). Analysis of the association between risk factors and moderate/substantial foot discomfort revealed that foot discomfort was less likely for nurses who were older, had greater BMI or had lower foot arches, as indicated by higher arch index scores. The nurses’ postural sway decreased over the course of the work shift, suggesting improved body balance by the end of the day. These findings were unexpected. Further clinical studies examining individual nurses on several work shifts are needed to confirm these results, particularly due to the small sample size and the single measurement occasion. There are more than 280,000 nurses registered to practice in Australia. The nursing workforce is ageing and the prevalence of foot problems will increase. If the prevalence estimates from this study are extrapolated to the profession generally, more than 70,000 hospital nurses have experienced substantial foot discomfort and 25-30,000 hospital nurses have been limited in their activity due to foot problems during the last 12 months. Nurses with underlying foot conditions were more likely to report having foot problems at work. Strategies to prevent or manage foot conditions exist and they should be disseminated to nurses. Obesity is a significant risk factor for foot and ankle MSDs and these nurses may need particular assistance to manage foot problems. The risk of foot problems for particular groups of nurses, e.g. obese nurses, may vary depending upon the location within the hospital. Further research is needed to confirm the findings of this study. Similar studies should be conducted in other occupational groups that require workers to stand for prolonged periods.