Failure to repeatedly supercompensate muscle glycogen stores in highly trained men

Purpose: It is not known whether it is possible to repeatedly supercompensate muscle glycogen stores after exhaustive exercise bouts undertaken within several days. Methods: We evaluated the effect of repeated exercise-diet manipulation on muscle glycogen and triacylglycerol (IMTG) metabolism and exercise capacity in six well-trained subjects who completed an intermittent, exhaustive cycling protocol (EX) on three occasions separated by 48 h (i.e., days 1, 3, and 5) in a 5-d period. Twenty-four hours before day 1, subjects consumed a moderate (6 g·kg-1)-carbohydrate (CHO) diet, followed by 5 d of a high (12 g·kg-1·d -1)-CHO diet. Muscle biopsies were taken at rest, immediately post-EX on days 1, 3, and 5, and after 3 h of recovery on days 1 and 3. Results: Compared with day 1, resting muscle [glycogen] was elevated on day 3 but not day 5 (435 ± 57 vs 713 ± 60 vs 409 ± 40 mmol·kg -1, P < 0.001). [IMTG] was reduced by 28% (P < 0.05) after EX on day 1, but post-EX levels on days 3 and 5 were similar to rest. EX was enhanced on days 3 and 5 compared with day 1 (31.9 ± 2.5 and 35.4 ± 3.8 vs 24.1 ± 1.4 kJ·kg-1, P < 0.05). Glycogen synthase activity at rest and immediately post-EX was similar between trials. Additionally, the rates of muscle glycogen accumulation were similar during the 3-h recovery period on days 1 and 3. Conclusion: We show that well-trained men cannot repeatedly supercompensate muscle [glycogen] after glycogen-depleting exercise and 2 d of a high-CHO diet, suggesting that the mechanisms responsible for glycogen accumulation are attenuated as a consequence of successive days of glycogen-depleting exercise.

Motivational interventions may have greater sustained impact if they trained imagery-based self-management

McCambridge & Rollnick [1] argue that increased benefits from brief motivational interventions (MIs) for alcohol abuse may be obtained if they addressed patients’ con- cerns more directly, especially in severe dependence and primary care. We agree, but take the idea a step further. Recent research on comorbidity has illustrated the power of simultaneously addressing multiple issues in an integrated manner, especially when these changes have synergistic effects (as typically occurs with psycho- sis and substance use [2]). Integrated MI for comorbidity can even be used productively in a single-session format [3]. This idea may have wider application. Recent work in remote Indigenous Australian communities has highlighted the benefits of a broad-ranging discussion of key relationships, activities and resources that confer strength, as well as aspects that worry them or cause dissatisfaction [4]. If excessive drinking is present, its impact on other life areas is reviewed, as in standard MI. However, it is considered alongside other highly valued goals. While the approach has demonstrated effects on both alcohol use and mental health [5], its impact is restricted only by the range of goals that are selected...

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

Scrutinising the other : incapacity, suspicion and manipulation in a death investigation

In common law countries like England, Australia, the USA and Canada, certain deaths come to be investigated through the coronial system. These include sudden, unnatural or suspicious deaths as well as those which appear to be the result of naturally occurring disease but the precise cause is unknown. When a reportable death occurs in Australia, a number of professional groups become involved in its investigation – police, coroners, pathologists and counsellors. While research has demonstrated the importance of training and education for staff in the context of criminal investigations – with its over-representation of vulnerable and marginalised populations – this is less likely to occur in the context of death investigations, despite such investigations also involving the over-representation of vulnerable populations. This paper, part of larger funded research on the decision-making of coronial professionals in the context of cultural and religious difference, explores the ways in which cultural and religious minority groups – in this case Islam, Judaism and Indigeneity – become differently positioned during the death investigation based upon how they are perceived as ‘other’. Our research raises three issues. First, positioning as ‘the other’ is dependent on the professional training of the staff member, with police and pathologists far more likely than coroners to be suspicious or ignorant of difference. Second, specific historical and contemporary events effect the Othering of religious and cultural difference. Third, the grieving practices associated with religious and cultural difference can be collectively Othered through their perceived opposition to modernity.

Well-trained, healthy triathletes experience no adverse health risks regarding oxidative stress and DNA damage by participating in an ultra-endurance event

Also physical exercise in general is accepted to be protective, acute and strenuous exercise has been shown to induce oxidative stress. Enhanced formation of free radicals leads to oxidation of macromolecules and to DNA damage. On the other hand ultra-endurance events which require strenuous exercise are very popular and the number of participants is continuously increasing worldwide. Since only few data exists on Ironman triathletes, who are prototypes of ultra-endurance athletes, this study was aimed at assessing the risk of oxidative stress and DNA damage after finishing a triathlon and to predict a possible health risk. Blood samples of 42 male athletes were taken 2 days before, within 20 min after the race, 1, 5 and 19 days post-race. Oxidative stress marker increased only moderately after the race and returned to baseline after 5 days. Marker of DNA damage measured by the SCGE assay with and without restriction enzymes as well as by the sister chromatid exchange assay did either show no change or deceased within the first day after the race. Due to intake during the race and the release by the cells plasma concentrations of vitamin C and α-tocopherol increased after the event and returned to baseline 1 day after. This study indicates that despite a temporary increase in some oxidative stress markers, there is no persistent oxidative stress and no DNA damage in response to an Ironman triathlon in trained athletes, mainly due to an appropriate antioxidant intake and general protective alterations in the antioxidant defence system.

Reproducibility of fatmax and fat oxidation rates during exercise in recreationally trained males

Aerobic exercise training performed at the intensity eliciting maximal fat oxidation (Fatmax) has been shown to improve the metabolic profile of obese patients. However, limited information is available on the reproducibility of Fatmax and related physiological measures. The aim of this study was to assess the intra-individual variability of: a) Fatmax measurements determined using three different data analysis approaches and b) fat and carbohydrate oxidation rates at rest and at each stage of an individualized graded test. Fifteen healthy males [body mass index 23.1±0.6 kg/m2, maximal oxygen consumption () 52.0±2.0 ml/kg/min] completed a maximal test and two identical submaximal incremental tests on ergocycle (30-min rest followed by 5-min stages with increments of 7.5% of the maximal power output). Fat and carbohydrate oxidation rates were determined using indirect calorimetry. Fatmax was determined with three approaches: the sine model (SIN), measured values (MV) and 3rd polynomial curve (P3). Intra-individual coefficients of variation (CVs) and limits of agreement were calculated. CV for Fatmax determined with SIN was 16.4% and tended to be lower than with P3 and MV (18.6% and 20.8%, respectively). Limits of agreement for Fatmax were −2±27% of with SIN, −4±32 with P3 and −4±28 with MV. CVs of oxygen uptake, carbon dioxide production and respiratory exchange rate were <10% at rest and <5% during exercise. Conversely, CVs of fat oxidation rates (20% at rest and 24–49% during exercise) and carbohydrate oxidation rates (33.5% at rest, 8.5–12.9% during exercise) were higher. The intra-individual variability of Fatmax and fat oxidation rates was high (CV>15%), regardless of the data analysis approach employed. Further research on the determinants of the variability of Fatmax and fat oxidation rates is required.

A taxonomic approach to understanding managerial ethical decision making approaches of clinically and non-clinically trained healthcare managers in Australia

Objective To understand differences in the managerial ethical decision-making styles of Australian healthcare managers through the exploratory use of the Managerial Ethical Profiles (MEP) Scale. Background Healthcare managers (doctors, nurses, allied health practitioners and non-clinically trained professionals) are faced with a raft of variables when making decisions within the workplace. In the absence of clear protocols and policies healthcare managers rely on a range of personal experiences, personal ethical philosophies, personal factors and organizational factors to arrive at a decision. Understanding the dominant approaches to managerial ethical decision-making, particularly for clinically trained healthcare managers, is a fundamental step in both increasing awareness of the importance of how managers make decisions, but also as a basis for ongoing development of healthcare managers. Design Cross-sectional. Methods The study adopts a taxonomic approach that simultaneously considers multiple ethical factors that potentially influence managerial ethical decision-making. These factors are used as inputs into cluster analysis to identify distinct patterns of influence on managerial ethical decision-making. Results Data analysis from the participants (n=441) showed a similar spread of the five managerial ethical profiles (Knights, Guardian Angels, Duty Followers, Defenders and Chameleons) across clinically trained and non-clinically trained healthcare managers. There was no substantial statistical difference between the two manager types (clinical and non-clinical) across the five profiles. Conclusion This paper demonstrated that managers that came from clinical backgrounds have similar ethical decision-making profiles to non-clinically trained managers. This is an important finding in terms of manager development and how organisations understand the various approaches of managerial decision-making across the different ethical profiles.

CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters

A novel system for recognition of handprinted alphanumeric characters has been developed and tested. The system can be employed for recognition of either the alphabet or the numeral by contextually switching on to the corresponding branch of the recognition algorithm. The two major components of the system are the multistage feature extractor and the decision logic tree-type catagorizer. The importance of ldquogoodrdquo features over sophistication in the classification procedures was recognized, and the feature extractor is designed to extract features based on a variety of topological, morphological and similar properties. An information feedback path is provided between the decision logic and the feature extractor units to facilitate an interleaved or recursive mode of operation. This ensures that only those features essential to the recognition of a particular sample are extracted each time. Test implementation has demonstrated the reliability of the system in recognizing a variety of handprinted alphanumeric characters with close to 100% accuracy.

Bayesian adaptation and adaptively trained systems

As the use of found data increases, more systems are being built using adaptive training. Here transforms are used to represent unwanted acoustic variability, e.g. speaker and acoustic environment changes, allowing a canonical model that models only the "pure" variability of speech to be trained. Adaptive training may be described within a Bayesian framework. By using complexity control approaches to ensure robust parameter estimates, the standard point estimate adaptive training can be justified within this Bayesian framework. However during recognition there is usually no control over the amount of data available. It is therefore preferable to be able to use a full Bayesian approach to applying transforms during recognition rather than the standard point estimates. This paper discusses various approximations to Bayesian approaches including a new variational Bayes approximation. The application of these approaches to state-of-the-art adaptively trained systems using both CAT and MLLR transforms is then described and evaluated on a large vocabulary speech recognition task. © 2005 IEEE.