Does the effect of weight lifting on lymphedema following breast cancer differ by diagnostic method: results from a randomized controlled trial

The lymphedema diagnostic method used in descriptive or intervention studies may influence results found. The purposes of this work were to compare baseline lymphedema prevalence in the physical activity and lymphedema (PAL) trial cohort and to subsequently compare the effect of the weight-lifting intervention on lymphedema, according to four standard diagnostic methods. The PAL trial was a randomized controlled intervention study, involving 295 women who had previously been treated for breast cancer, and evaluated the effect of 12 months of weight lifting on lymphedema status. Four diagnostic methods were used to evaluate lymphedema outcomes: (i) interlimb volume difference through water displacement, (ii) interlimb size difference through sum of arm circumferences, (iii) interlimb impedance ratio using bioimpedance spectroscopy, and (iv) a validated self-report survey. Of the 295 women who participated in the PAL trial, between 22 and 52% were considered to have lymphedema at baseline according to the four diagnostic criteria used. No between-group differences were noted in the proportion of women who had a change in interlimb volume, interlimb size, interlimb ratio, or survey score of ≥5, ≥5, ≥10%, and 1 unit, respectively (cumulative incidence ratio at study end for each measure ranged between 0.6 and 0.8, with confidence intervals spanning 1.0). The variation in proportions of women within the PAL trial considered to have lymphoedema at baseline highlights the potential impact of the diagnostic criteria on population surveillance regarding prevalence of this common morbidity of treatment. Importantly though, progressive weight lifting was shown to be safe for women following breast cancer, even for those at risk or with lymphedema, irrespective of the diagnostic criteria used.

Multiuser virtual safety training system for tower crane dismantlement

Tower crane dismantling is one of the most dangerous activities in the construction industry. Tower crane erection and dismantlement causes 10–12% of the fatalities of all crane accidents. The nature of the task is such that off-the-job training is not practicable, and the knowledge and expertise needed has to be gained on the job. However, virtual trainers such as Microsoft Flight Simulator for airplane pilots and mission rehearsal exercise (MRE) for army personnel have been developed and are known to provide a highly successful means of overcoming the risks involved in such on-the-job learning and clearly have potential in construction situations. This paper describes the newly developed multiuser virtual safety training system (MVSTS) aimed at providing a similar learning environment for those involved in tower crane dismantlement. The proposed training system is developed by modifying an existing game engine. Within the close-to-reality virtual environment, trainees can participate in a virtual dismantling process. During the process, they learn the correct dismantling procedure and working location and to cooperate with other trainees by virtually dismantling the crane. The system allows the trainees to experience the complete procedure in a risk-free environment. A case study is provided to demonstrate how the system works and its practical application. The proposed system was evaluated by interviews with 30 construction experts with different backgrounds, divided into three groups according to their experience and trained by the traditional and virtual methods, respectively. The results indicate that the trainees of the proposed system generally learned better than those using the traditional method. The ratings also indicate that the system generally has great potential as a training platform.

Rail incident investigator training: Is there support for a standardised Australasian training framework?

Background: Historically rail organisations have been operating in silos and devising their own training agendas. However with the harmonisation of the Australian workplace health and safety legislation and the appointment of a national rail safety regulator in 2013, rail incident investigator experts are exploring the possibility of developing a unified approach to investigator training. Objectives: The Australian CRC for Rail Innovation commissioned a training needs analysis to identify if common training needs existed between organisations and to assess support for the development of a national competency framework for rail incident investigations. Method: Fifty-two industry experts were consulted to explore the possibility of the development of a standardised training framework. These experts were sourced from within 19 Australasian organisations, comprising Rail Operators and Regulators in Queensland, New South Wales, Victoria, Western Australia, South Australia and New Zealand. Results: Although some competency requirements appear to be organisation specific, the vast majority of reported training requirements were generic across the Australasian rail operators and regulators. Industry experts consistently reported strong support for the development of a national training framework. Significance: The identification of both generic training requirements across organisations and strong support for standardised training indicates that the rail industry is receptive to the development of a structured training framework. The development of an Australasian learning framework could: increase efficiency in course development and reduce costs; establish recognised career pathways; and facilitate consistency with regards to investigator training.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

Gradual training of cascaded shape regression for facial landmark localization and pose estimation

Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.

The role of intensity of interval training on fat oxidation and eating behaviour in overweight/obese men

The increasing prevalence of obesity in society has been associated with a number of atherogenic risk factors such as insulin resistance. Aerobic training is often recommended as a strategy to induce weight loss, with a greater impact of high-intensity levels on cardiovascular function and insulin sensitivity, and a greater impact of moderate-intensity levels on fat oxidation. Anaerobic high-intensity (supramaximal) interval training has been advocated to improve cardiovascular function, insulin sensitivity and fat oxidation. However, obese individuals tend to have a lower tolerance of high-intensity exercise due to discomfort. Furthermore, some obese individuals may compensate for the increased energy expenditure by eating more and/or becoming less active. Recently, both moderate- and high-intensity aerobic interval training have been advocated as alternative approaches. However, it is still uncertain as to which approach is more effective in terms of increasing fat oxidation given the issues with levels of fitness and motivation, and compensatory behaviours. Accordingly, the objectives of this thesis were to compare the influence of moderate- and high-intensity interval training on fat oxidation and eating behaviour in overweight/obese men. Two exercise interventions were undertaken by 10-12 overweight/obese men to compare their responses to study variables, including fat oxidation and eating behaviour during moderate- and high-intensity interval training (MIIT and HIIT). The acute training intervention was a methodological study designed to examine the validity of using exercise intensity from the graded exercise test (GXT) - which measured the intensity that elicits maximal fat oxidation (FATmax) - to prescribe interval training during 30-min MIIT. The 30-min MIIT session involved 5-min repetitions of workloads 20% below and 20% above the FATmax. The acute intervention was extended to involve HIIT in a cross-over design to compare the influence of MIIT and HIIT on eating behaviour using subjective appetite sensation and food preference through the liking and wanting test. The HIIT consisted of 15-sec interval training at 85 %VO2peak interspersed by 15-sec unloaded recovery, with a total mechanical work equal to MIIT. The medium term training intervention was a cross-over 4-week (12 sessions) MIIT and HIIT exercise training with a 6-week detraining washout period. The MIIT sessions consisted of 5-min cycling stages at ±20% of mechanical work at 45 %VO2peak, and the HIIT sessions consisted of repetitive 30-sec work at 90 %VO2peak and 30-sec interval rests, during identical exercise sessions of between 30 and 45 mins. Assessments included a constant-load test (45 %VO2peak for 45 mins) followed by 60-min recovery at baseline and the end of 4-week training, to determine fat oxidation rate. Participants’ responses to exercise were measured using blood lactate (BLa), heart rate (HR) and rating of perceived exertion (RPE) and were measured during the constant-load test and in the first intervention training session of every week during training. Eating behaviour responses were assessed by measuring subjective appetite sensations, liking and wanting and ad libitum energy intake. Results of the acute intervention showed that FATmax is a valid method to estimate VO2 and BLa, but is not valid to estimate HR and RPE in the MIIT session. While the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax (0.16 ±0.09 and 0.14 ±0.08 g/min, respectively), fat oxidation was significantly higher at minute 25 of MIIT (P≤0.01). In addition, there was no significant difference between MIIT and HIIT in the rate of appetite sensations after exercise, but there was a tendency towards a lower rate of hunger after HIIT. Different intensities of interval exercise also did not affect explicit liking or implicit wanting. Results of the medium-term intervention indicated that current interval training levels did not affect body composition, fasting insulin and fasting glucose. Maximal aerobic capacity significantly increased (P≤0.01) (2.8 and 7.0% after MIIT and HIIT respectively) during GXT, and fat oxidation significantly increased (P≤0.01) (96 and 43% after MIIT and HIIT respectively) during the acute constant-load exercise test. RPE significantly decreased after HIIT greater than MIIT (P≤0.05), and the decrease in BLa was greater during the constant-load test after HIIT than MIIT, but this difference did not reach statistical significance (P=0.09). In addition, following constant-load exercise, exercise-induced hunger and desire to eat decreased after HIIT greater than MIIT but were not significant (p value for desire to eat was 0.07). Exercise-induced liking of high-fat sweet (HFSW) and high-fat non-sweet (HFNS) foods increased after MIIT and decreased after HIIT (p value for HFNS was 0.09). The intervention explained 12.4% of the change in fat intake (p = 0.07). This research is significant in that it confirmed two points in the acute study. While the rate of fat oxidation increased during MIIT, the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax. In addition, manipulating the intensity of acute interval exercise did not affect appetite sensations and liking and wanting. In the medium-term intervention, constant-load exercise-induced fat oxidation significantly increased after interval training, independent of exercise intensity. In addition, desire to eat, explicit liking for HFNS and fat intake collectively confirmed that MIIT is accompanied by a greater compensation of eating behaviour than HIIT. Findings from this research will assist in developing exercise strategies to provide obese men with various training options. In addition, the finding that overweight/obese men expressed a lower RPE and decreased BLa after HIIT compared with MIIT is contrary to the view that obese individuals may not tolerate high-intensity interval training. Therefore, high-intensity interval training can be advocated among the obese adult male population. Future studies may extend this work by using a longer-term intervention.

The Alcohol Intervention Training Program (AITP): a response to alcohol misuse in the farming community

Background Farm men and women in Australia have higher levels of problematic alcohol use than their urban counterparts and experience elevated health risks associated with excessive alcohol consumption. The Sustainable Farm Families (SFF) program has worked successfully with farm men and women to address health, well- being and safety and has identified that further research and training is required to understand and address alcohol misuse behaviours. This project will add an innovative component to the program by training health professionals working with farm men and women to discuss and respond to alcohol-related physical and mental health problems. Methods/Design A mixed method design with multi-level evaluation will be implemented following the development and delivery of a training program (The Alcohol Intervention Training Program {AITP}) for Sustainable Farm Families health professionals. Pre-, post- and follow-up surveys will be used to assess both the impact of the training on the knowledge, confidence and skills of the health professionals to work with alcohol misuse and associated problems, and the impact of the training on the attitudes, behaviour and mental health of farm men and women who participate in the SFF project. Evaluations will take a range of forms including self-rated outcome measures and interviews. Discussion The success of this project will enhance the health and well-being of a critical population, the farm men and women of Australia, by producing an evidence-based strategy to assist them to adopt more positive alcohol-related behaviours that will lead to better physical and mental health.

Found in translation : debating the abstract elements of cultures through actor training styles

While the synthesis of acting methodologies in intercultural acting has been discussed at length, little discussion has focussed on the potential of diverse actor training styles to affect performance making and audience reception. This article explores a project where the abstract elements of the British and American cultures were translated in rehearsal and in production through the purposeful juxtaposition of two differing actor training styles: the British ‘traditional’ approach and the American Method. William Nicholson’s Shadowlands was produced by Crossbow Productions at the Brisbane Powerhouse in 2010. Nicholson’s play contains a discourse on the cultural cringe of British – American relations. As a research project, the production aimed to extend and augment audience experience of the socio-cultural tensions inherent in the play by juxtaposing two seemingly culturally inscribed approaches to acting. Actors were chosen who had been trained under a traditional conservatoire approach and the American Method. A brief overview of these acting approaches is followed by a discussion centred on the project. This article analyses how from the casting room to the rehearsal room to the mise en scene and into the audience discussions, cultural issues were articulated, translated and debated through the language of acting.

Is foot ulcer simulation training (FUST) really effective? Participants’ supervisors speak out

Background Foot ulcers are a common reason for diabetes-related hospitalisation. Foot ulcer simulation training (FUST) programs have increased podiatry participants self-confidence to manage foot ulcers. However, supervisors’ perspectives on their participants attending these simulation programs have not been investigated. This mixed method (quantitative and qualitative) study aimed to investigate home clinical supervisors’ perspectives on any changes to their participants’ competence and practice following FUST. Methods Clinical supervisors of fifteen podiatrists, who participated in a two-day Foot Ulcer Simulation Training (FUST) course, were recruited. Supervisors completed quantitative surveys evaluating their participants’ foot ulcer competence pre-FUST and 6-months post-FUST, via a purposed designed 21-item survey using a five-point Likert scale (1=Very limited, 5=Highly competent). Supervisors also attended a semi-structured qualitative group interview to investigate supervisors’ perspectives on FUST. Results Supervisors surveys returned were pre-FUST (n=10) and post-FUST (n=12). Significant competence improvements were observed at the 6-month survey (mean scores 2.84 cf. 3.72, p < 0.05). Five supervisors attended the group interview. Five sub-themes emerged: i) FUST provided a good foundation for future learning, ii) FUST modelled good clinical behaviour, iii) clinical practice improvement was evident in most participants, iv) clinical improvements were dependent on participant’s willingness to change and existing workplace culture, v) FUST needs to be reinforced back in the home clinic. Conclusion Overall, supervisors of FUST participants indicated that the course improved their participants’ competence and clinical practice. However, the degree of improvement appears dependant on the participants’ home workplace culture and willingness to embrace change.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

Specialist versus generic models of psychiatry training and service provision for people with intellectual disabilities

Background  Models of service provision and professional training differ between countries. This study aims to investigate a specialist intellectual disabilities model and a generic mental health model, specifically comparing psychiatrists’ knowledge and competencies, and service quality and accessibility in meeting the mental health needs of people with intellectual disabilities. Method  Data were collected from consultant and trainee psychiatrists within a specialist intellectual disabilities model (UK) and a generic mental health model (Australia). Results  The sample sizes were 294 (UK) and 205 (Australia). Statistically significant differences were found, with UK participants having positive views about the specialist intellectual disabilities service model they worked within, demonstrating flexible and accessible working practices and service provision, responsive to the range of mental health needs of the population with intellectual disabilities, and providing a wide range of treatments and supports. The UK participants were knowledgeable, well trained and confident in their work. They wanted to work with people with intellectual disabilities. In all of these areas, the converse was found from the Australian generic mental health service model. Conclusions  The specialist intellectual disabilities model of service provision and training has advantages over the generic mental health model.

A Boundary-Oriented Chinese Segmentation Method Using NGram Mutual Information

This paper describes our participation in the Chinese word segmentation task of CIPS-SIGHAN 2010. We implemented an n-gram mutual information (NGMI) based segmentation algorithm with the mixed-up features from unsupervised, supervised and dictionarybased segmentation methods. This algorithm is also combined with a simple strategy for out-of-vocabulary (OOV) word recognition. The evaluation for both open and closed training shows encouraging results of our system. The results for OOV word recognition in closed training evaluation were however found unsatisfactory.

A virtual radiation therapy workflow training simulation

Aim Simulation forms an increasingly vital component of clinical skills development in a wide range of professional disciplines. Simulation of clinical techniques and equipment is designed to better prepare students for placement by providing an opportunity to learn technical skills in a “safe” academic environment. In radiotherapy training over the last decade or so this has predominantly comprised treatment planning software and small ancillary equipment such as mould room apparatus. Recent virtual reality developments have dramatically changed this approach. Innovative new simulation applications and file processing and interrogation software have helped to fill in the gaps to provide a streamlined virtual workflow solution. This paper outlines the innovations that have enabled this, along with an evaluation of the impact on students and educators. Method Virtual reality software and workflow applications have been developed to enable the following steps of radiation therapy to be simulated in an academic environment: CT scanning using a 3D virtual CT scanner simulation; batch CT duplication; treatment planning; 3D plan evaluation using a virtual linear accelerator; quantitative plan assessment, patient setup with lasers; and image guided radiotherapy software. Results Evaluation of the impact of the virtual reality workflow system highlighted substantial time saving for academic staff as well as positive feedback from students relating to preparation for clinical placements. Students valued practice in the “safe” environment and the opportunity to understand the clinical workflow ahead of clinical department experience. Conclusion Simulation of most of the radiation therapy workflow and tasks is feasible using a raft of virtual reality simulation applications and supporting software. Benefits of this approach include time-saving, embedding of a case-study based approach, increased student confidence, and optimal use of the clinical environment. Ongoing work seeks to determine the impact of simulation on clinical skills.

Secondary structure element alignment kernel method for prediction of protein structural classes

In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed for training a support vector machine classifier without parameter adjusting. Our method SSEAKSVM was evaluated on two low-homology datasets 25PDB and 1189 with sequence homology being 25% and 40%, respectively. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies on these two data sets are 86.3% and 84.5%, respectively, which are higher than those obtained by other existing methods. Especially, our method achieves higher accuracies (88.1% and 88.5%) for differentiating the α + β class and the α/β class compared to other methods. This suggests that our method is valuable to predict protein structural classes particularly for low-homology protein sequences. The source code of the method in this paper can be downloaded at http://math.xtu.edu.cn/myphp/math/research/source/SSEAK_source_code.rar.