Respiratory muscle training (RMT) has been shown to improve exercise tolerance during a wide range of exercise modalities and durations of activity (McConnell & Romer, 2004b). However, there is a limited amount of research characterising the influence of RMT in specific athletic populations, or examining any sport-specific factors that may influence the benefits of RMT. Hence, the purpose of this dissertation was to evaluate the application of RMT in competitive rowers and to explore methods of optimising this to rowing. Results: Inspiratory muscle training (IMT) increased inspiratory muscle strength (~20-29%; p < 0.05) and attenuated inspiratory muscle fatigue (~8-28%; p < 0.05) during time trial performance in club-level and elite rowers. However, only in the club-level oarsmen was IMT associated with a measurable improvement in rowing performance (2.7% increase in mean power; p < 0.05). Expiratory muscle training (EMT) provided no ergogenic effect, and concurrent EMT and IMT did not enhance performance above that seen with IMT alone. IMT loads performed at 60-70% of maximal inspiratory mouth pressure (PImax) were equivalent to the widely used 30 repetition maximum, which is higher than reported for non-rowers (Caine & McConnell, 1998a); further, a load of 60% PImax was sufficient to activate the inspiratory muscle metaboreflex, as evidenced by a time-dependent rise in heart rate (70.1 ± 13.2 to 98.0 ± 22.8 bpm; p < 0.05) and mean arterial blood pressure (92.4 ± 8.5 to 99.7 ± 10.1 mmHg; p < 0.05). Higher and lower inspiratory loads did not activate the metaboreflex. Assessments of flow, pressure and volume in rowing relevant postures revealed no significant impairments, but optimal function occurred in the most upright postures. Conclusions: These data support the application of IMT, but not EMT, in elite and sub-elite rowers, and suggest that a load of 60-70% of PImax provides metaboreflex activation during loading. Further, the data do not support a requirement to undertake IMT in rowing relevant postures.

Cognitive ability is one of the most frequently investigated individual differences in management and psychology. Countless studies have demonstrated that tests measuring cognitive ability or intelligence predict a number of important real-world outcomes such as academic performance, vocational training performance, and job performance. Although the relationship between intelligence and real-world performance is well established, there is a lack of consensus among scholars with regard to how intelligence should be conceptualized and measured. Of the more traditional theories of intelligence, two perspectives are particularly dominant: the Cattell-Horn model of fluid and crystallized intelligence and the theory of General Cognitive Ability (GCA or g). Fluid ability (Gf) represents novel or abstract problem solving capability and is believed to have a physiological basis. In contrast, crystallized ability (Gc) is associated with learned or acculturated knowledge. Drawing on recent research in neuroscience, as well as research on past performance, the nature of work, and expert performance, I argue that compared to measures of fluid ability, crystallized ability measures should more strongly predict real-world criteria in the classroom as well as the workplace. This idea was meta-analytically examined using a large, diverse set of over 400 primary studies spanning the past 100 years. With regard to academic performance, measures of fluid ability were found to positively predict learning (as measured by grades). However, as hypothesized, crystallized ability measures were found to be superior predictors of academic performance compared to their fluid ability counterparts. This finding was true for both high school and college students. Likewise, similar patterns of results were observed with regard to both training performance and job performance. Again, crystallized ability measures were found to be better predictors of performance than fluid measures. This finding was consistent at the overall level of analysis as well as for medium complexity jobs. These findings have important implications for both intelligence theory and selection practice. Contemporary intelligence theory has placed great emphasis on the role of fluid ability, and some researchers have argued that Gf and g are essentially the same construct. However, the results of this study, which are based on criterion-related validities rather than factor-analytic evidence, demonstrate that Gc measures are superior predictors in comparison to Gf measures. This is contrary to what one would expect if Gf and g were indeed the same construct. Rather, the findings of this study are more consistent with General Cognitive Ability theory, which predicts that Gc indicators will be the best predictors of future learning and performance. Given that Gc measures demonstrate higher criterion-related validities than Gf measures, Gc measures are likely to be preferred for selection purposes. Further, Gf scores are known to decline with age while Gc scores remain relatively stable over the lifespan. Thus, when used for selection purposes, Gf tests may underpredict the performance of older workers. In contrast, research has shown that Gc measures are predictively unbiased. Additional implications for theory and practice are discussed, along with study limitations and opportunities for future research.

Abstract Flying is a three dimensional exercise that is combined with time. It includes application of theory, realistic space handling and management of time. In order to let pilot feel the handling, tempo, movement in space, aircraft attitude and radio communication procedure for flying, it is a brand new challenge to develop digitization teaching material of flying handling skill for audio/video and assisting of simulation machine function weak point of the visual effect, use it to help student pilot with understanding the knowledge of flying handling. This research initially statistically analyzed the training completion and drop-out data of 18 Basic Flying Training classes of the Chinese Air Force Academy, from the academic year of 88 to 92. The research found that the traffic pattern phase has 21.8% of drop-out rate among the 35.2% of the whole training drop-out rate. Furthermore, 16 out of 18 classes had the highest drop-out rate during the traffic pattern phase. Therefore, The purpose of this research lies in offering digitization teaching material for audio/video in order to help student pilot with understanding and learning the flying skill for traffic pattern, in hopes of assisting student pilot on handling and concept and providing effective learning method and technical instruction for both the student pilot and the training unit to advance the performance of flying training. The question of this research includes: 1. Novel flying training and teaching assistance equipments. 2. Raising the traffic pattern phase training completion rate. 3. Raising the traffic pattern phase training performance. 4. Investigating the potential problems associated with flying training. The researcher is currently the Chinese Air Force Academy instructor pilot. Therefore, the researcher hopes through studying the law as the main research approach with oneself action of action research.In this research, the researcher except that collect putting to documents in order and devotes to develop digitization teaching material for audio/video and select two of the flying training classes of the current academic year, coordinating with the basic flying training schedule of the Chinese Air Force Academy. There will be surveys and interviews with case study through analysis tool for analyzing research data, after applied the traffic pattern digital Audio/Video. Lastly, the research procedure and data analysis will discover that action research has important value in the field of flight training and conclude critical influence factors for the teaching media aspect, unit administration aspect, flying training actual practice aspect, and flying students¡¦ aspect, in order to provide training advice and future research direction. Keywords: Traffic Pattern¡BTraining Performance¡BCritical Influence Factor¡BAction Research¡BDigital Audio/Video Learning Material

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