Sleep quantity and quality during heat-based training and the effects of cold-water immersion recovery

- Introduction Heat-based training (HT) is becoming increasingly popular as a means of inducing acclimation before athletic competition in hot conditions and/or to augment the training impulse beyond that achieved in thermo-neutral conditions. Importantly, current understanding of the effects of HT on regenerative processes such as sleep and the interactions with common recovery interventions remain unknown. This study aimed to examine sleep characteristics during five consecutive days of training in the heat with the inclusion of cold-water immersion (CWI) compared to baseline sleep patterns. - Methods Thirty recreationally-trained males completed HT in 32 ± 1 °C and 60% rh for five consecutive days. Conditions included: 1) 90 min cycling at 40 % power at VO2max (Pmax) (90CONT; n = 10); 90 min cycling at 40 % Pmax with a 20 min CWI (14 ± 1 °C; 90CWI; n = 10); and 30 min cycling alternating between 40 and 70 % Pmax every 3 min, with no recovery intervention (30HIT; n = 10). Sleep quality and quantity was assessed during HT and four nights of 'baseline' sleep (BASE). Actigraphy provided measures of time in and out of bed, sleep latency, efficiency, total time in bed and total time asleep, wake after sleep onset, number of awakenings, and wakening duration. Subjective ratings of sleep were also recorded using a 1-5 Likert scale. Repeated measures analysis of variance (ANOVA) was completed to determine effect of time and condition on sleep quality and quantity. Cohen's d effect sizes were also applied to determine magnitude and trends in the data. - Results Sleep latency, efficiency, total time in bed and number of awakenings were not significantly different between BASE and HT (P > 0.05). However, total time asleep was significantly reduced (P = 0.01; d = 1.46) and the duration periods of wakefulness after sleep onset was significantly greater during HT compared with BASE (P = 0.001; d = 1.14). Comparison between training groups showed latency was significantly higher for the 30HIT group compared to 90CONT (P = 0.02; d = 1.33). Nevertheless, there were no differences between training groups for sleep efficiency, total time in bed or asleep, wake after sleep onset, number of awakenings or awake duration (P > 0.05). Further, cold-water immersion recovery had no significant effect on sleep characteristics (P > 0.05). - Discussion Sleep plays an important role in athletic recovery and has previously been demonstrated to be influenced by both exercise training and thermal strain. Present data highlight the effect of HT on reduced sleep quality, specifically reducing total time asleep due to longer duration awake during awakenings after sleep onset. Importantly, although cold water recovery accelerates the removal of thermal load, this intervention did not blunt the negative effects of HT on sleep characteristics. - Conclusion Training in hot conditions may reduce both sleep quantity and quality and should be taken into consideration when administering this training intervention in the field.

An operational-level multi-stage mine production timetabling model for optimally synchronising drilling, blasting and excavating operations

This paper proposes a new multi-stage mine production timetabling (MMPT) model to optimise open-pit mine production operations including drilling, blasting and excavating under real-time mining constraints. The MMPT problem is formulated as a mixed integer programming model and can be optimally solved for small-size MMPT instances by IBM ILOG-CPLEX. Due to NP-hardness, an improved shifting-bottleneck-procedure algorithm based on the extended disjunctive graph is developed to solve large-size MMPT instances in an effective and efficient way. Extensive computational experiments are presented to validate the proposed algorithm that is able to efficiently obtain the near-optimal operational timetable of mining equipment units. The advantages are indicated by sensitivity analysis under various real-life scenarios. The proposed MMPT methodology is promising to be implemented as a tool for mining industry because it is straightforwardly modelled as a standard scheduling model, efficiently solved by the heuristic algorithm, and flexibly expanded by adopting additional industrial constraints.

Understanding video based parent training intervention for children with autism

This paper investigates the challenges of delivering parent training intervention for autism over video. We conducted a qualitative field study of an intervention, which is based on a well-established training program for parents of children with autism, called Hanen More Than Words. The study was conducted with a Hanen Certified speech pathologist who delivered video based training to two mothers, each with a son having autism. We conducted observations of 14 sessions of the intervention spanning 3 months along with 3 semi-structured interviews with each participant. We identified different activities that participants performed across different sessions and analysed them based upon their implications on technology. We found that all the participants welcomed video based training but they also faced several difficulties, particularly in establishing rapport with other participants, inviting equal participation, and in observing and providing feedback on parent-child interactions. Finally, we reflect on our findings and motivate further investigations by defining three design sensitivities of Adaptation, Group Participation, and Physical Setup.

Is corporate rescue a realistic ideal? Business as usual in Australia and the United Kingdom

This paper seeks to review the operation of Australian corporate law rescue regimes in the context of those originally contemplated by Sir Kenneth Cork and more latterly in Australia, primarily in the hands of Ron Harmer. In doing so, it draws upon some of the observations made by Professor Fletcher in the second wave of 20th century corporate rescue reform in the United Kingdom.

Training the natives as nurses in Australia: So what went wrong?

The story of the Aboriginal women who participated in Australias nursing history remains largely untold. In the first six decades of the twentieth century, Aboriginal people were confronted with harsh exclusionary practices that forced them to live in settlements, reserves and missions.¹ While many Aboriginal women worked in domestic roles (in white peoples homes and on rural properties), small numbers were trained at public hospitals and some Aboriginal women received training to be native nurses who worked in hospitals on settlements

In this chapter, an indigenous historical lens is applied to the status of Indigenous nurses and midwives in Australia.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Blended learning in medical imaging pre-clinical skills training – does it work?

Undergraduate Medical Imaging (MI)students at QUT attend their first clinical placement towards the end of semester two. Students undertake two (pre)clinical skills development units – one theory and one practical. Students gain good contextual and theoretical knowledge during these units via a blended learning model with multiple learning methods employed. Students attend theory lectures, practical sessions, tutorial sessions in both a simulated and virtual environment and also attend pre-clinical scenario based tutorial sessions. The aim of this project is to evaluate the use of blended learning in the context of 1st year Medical Imaging Radiographic Technique and its effectiveness in preparing students for their first clinical experience. It is hoped that the multiple teaching methods employed within the pre-clinical training unit at QUT builds students clinical skills prior to the real situation. A quantitative approach will be taken, evaluating via pre and post clinical placement surveys. This data will be correlated with data gained in the previous year on the effectiveness of this training approach prior to clinical placement. In 2014 59 students were surveyed prior to their clinical placement demonstrated positive benefits of using a variety of learning tools to enhance their learning. 98.31%(n=58)of students agreed or strongly agreed that the theory lectures were a useful tool to enhance their learning. This was followed closely by 97% (n=57) of the students realising the value of performing role-play simulation prior to clinical placement. Tutorial engagement was considered useful for 93.22% (n=55) whilst 88.14% (n=52) reasoned that the x-raying of phantoms in the simulated radiographic laboratory was beneficial. Self-directed learning yielded 86.44% (n=51). The virtual reality simulation software was valuable for 72.41% (n=42) of the students. Of the 4 students that disagreed or strongly disagreed with the usefulness of any tool they strongly agreed to the usefulness of a minimum of one other learning tool. The impact of the blended learning model to meet diverse student needs continues to be positive with students engaging in most offerings. Students largely prefer pre -clinical scenario based practical and tutorial sessions where 'real-world’ situations are discussed.

Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

Airway Inflammation and Bronchial Hyperresponsiveness in Elite Cross-Country Skiers and in Patients with Newly Diagnosed Asthma: A Bronchial Biopsy Study

The objective of these studies was to evaluate possible airway inflammation and remodeling at the bronchial level in cross-country skiers without a prior diagnosis of asthma, and relate the findings to patients with mild chronic asthma and patients with newly diagnosed asthma. We also studied the association of airway inflammatory changes and bronchial hyperresponsivess (BHR), and treatment effects in cross-country skiers and in patients with newly diagnosed asthma. Bronchial biopsies were obtained from the subjects by flexible bronchoscopy, and the inflammatory cells (eosinophils, mast cells, T-lymphocytes, macrophages, and neutrophils) were identified by immunohistochemistry. Tenascin (Tn) immunoreactivity in the bronchial basement membrane (BM) was identified by immunofluorescence staining. Lung function was measured with spirometry, and BHR was assessed by methacholine (skiers) or histamine (asthmatics) challenges. Skiers with BHR and asthma-like symptoms were recruited to a drug-intervention study. Skiers were given treatment (22 weeks) with placebo or budesonide (400 µg bid). Patients with newly diagnosed asthma were given treatment for 16 weeks with placebo, salmeterol (SLM) (50 µg bid), fluticasone propionate (FP) (250 µg bid), or disodium cromoglicate (DSCG) (5 mg qid). Bronchial biopsies were obtained at baseline and at the end of the treatment period. In the skiers a distinct airway inflammation was evident. In their bronchial biopsy specimens, T-lymphocyte, macrophage, and eosinophil counts were, respectively greater by 43-fold (P<0.001), 26-fold (P<0.001, and 2-fold (P<0.001) in skiers, and by 70-fold (p>0.001), 63-fold (P<0.001), and 8-fold (P<0.001) in asthmatic subjects than in controls. In skiers, neutrophil counts were more than 2-fold greater than in asthmatic subjects (P<0.05). Tn expression was higher in skiers than in controls and lower in skiers than in mild asthmatics. No significant changes were seen between skiers with or without BHR in the inflammatory cell counts or Tn expression. Treatment with inhaled budesonide did not attenuate asthma-like symptoms, the inflammatory cell infiltration, or BM Tn expression in the skiers. In newly diagnosed asthmatic patients, SLM, FP, and DSCG reduced asthma symptoms, and need for rescue medication (P<0.04). BHR was reduced by doubling doses 2.78, 5.22, and 1.35 respectively (all P<0.05). SLM and placebo had no effect on cell counts or Tn expression. FP and DSCG reduced eosinophil counts in the bronchial biopsy specimens (P<0.02 and <0.048, respectively). No significant change in tenascin expression appeared in any treatment group. Regarding to atopy, no significant differences existed in the inflammatory cell counts in the bronchial mucosa of subjects with newly diagnosed asthma or in elite cross country skiers. Tn expression in the BM was significantly higher in atopic asthma than in those with nonatopic asthma. Airway inflammation occurred in elite cross-country skiers with and without respiratory symptoms or BHR. Their inflammatory cell pattern differed from that in asthma. Infiltration with eosinophils, macrophages, and mast cells was milder, but lymphocyte counts did not differ from counts in asthmatic airways. Neutrophilic infiltration was more extensive in skiers than in asthmatics. Remodeling took place in the skiers’ airways, as reflected by increased expression of BM tenascin These inflammatory changes and Tn expression may be caused by prolonged exposure of the lower airways to inadequately humidified cold air. In skiers inflammatory changes and remodeling were not reversed with anti-inflammatory treatment. In contrast, in patients with newly diagnosed asthma, anti-inflammatory treatment did attenuate eosinophilic inflammation in the bronchial mucosa. In skiers, anti-inflammatory treatment did not attenuate BHR as it did in asthmatic patients. The BHR in skiers was attenuated spontaneously during placebo treatment, with no difference from budesonide treatment. Lower training intensity during the treatment period may explain this spontaneous decrease in BHR. The origin of BHR probably differs in skiers and in asthmatics. No significant association between BHR and inflammatory cell counts or between BHR and Tn expression was evident in cross-country skiers or asthmatic subjects. Airway remodeling differed between atopic and nonatopic asthma. As opposed to nonatopic asthma, Tn expression was higher in atopic asthma and is related to inflammatory cell densities.

Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.