Influence of regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and running performance

Abstract

This study investigated the influence of the regression model and initial intensity during an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and performance in elite-standard runners. Twenty-three well-trained runners completed a discontinuous incremental running test on a treadmill. Speed started at 9 km · h^?1 and increased by 1.5 km · h^?1 every 4 min until exhaustion, with a minute of recovery for blood collection. Lactate–speed data were fitted by exponential and polynomial models. The lactate threshold was determined for both models, using all the co-ordinates, excluding the first and excluding the first and second points. The exponential lactate threshold was greater than the polynomial equivalent in any co-ordinate condition (P < 0.001). For both models, the lactate threshold was lower when all co-ordinates were used than when the first and the first and second points were excluded (P < 0.001). 10-km race pace was correlated with both the exponential and polynomial lactate thresholds for all the co-ordinate conditions (r ≥ 0.75, P < 0.001 and r ≥ 0.56, P < 0.05, respectively). The results suggest that the exponential lactate threshold should be used instead of the polynomial equivalent since it is more strongly associated with performance and is independent of the initial intensity of the test.     

Rhetoric and reality: using ICT to enhance pupil learning—Harry Potter and the Warley Woods Mystery—Case study 2

How can we use ICT to enhance the quality of pupil learning? The case study below deliberately embedded ICT within the context of an existing scheme of work to develop 11–12 year olds’ understanding of the skills and processes of historical investigation. It also mapped onto the existing teaching styles of the teachers involved, and reflected their orientation—beliefs and values. The role for the ICT was to present the pupils with a problem that would intrigue, excite and motivate them. Accordingly, we asked them to act in role as assistants to Harry and Hermione in investigating the strange death of Sam Woodhouse in 1822. The pupils carried out the investigation using a hyperlinked set of clues. They had undertaken two identical kinds of investigation earlier in the year. One was a murder mystery, the other the disappearance of the Princes in the Tower in 1483. For both these mysteries the clues were on cards. Comparisons of the results of the ICT mystery with those of the earlier two investigations suggest that the hyperlink version was equally effective in terms of developing understanding, with some clear advantages in developing pupils’ overall understanding of the problem and ability to make links between disparate clues and pieces of information.     

Exploring the ethical implications of MOOCs

Massive open online courses (MOOCs) represent a potentially exciting opportunity to use technology to realise many of the long-promised benefits of universal higher education. While there are many positive aspects to the MOOCs on offer and in development, there are also significant ethical concerns arising from various initiatives. These include the academic duties of care and integrity, commercial exploitation of learners, as well as research ethics concerns arising from the analytical and other work being done by academics and institutions. These issues are explored and a set of heuristics for individuals and institutions provided as a starting point for ethical analysis of MOOCs and associated activities.     

Assessing Outcomes: Practical Methods and Evidence

University counseling center clients’ (N = 52) perceptions of precounseling functioning were highly correlated with their actual well‐being scores at intake. The magnitude of change based on perceptions of precounseling functioning to current well‐being was approximately double of what is found from the difference of actual precounseling well‐being to current well‐being scores. Retrospective methods for assessing precounseling functioning are best suited for comparison among clients or counseling processes.     

Novel model reference adaptive control laws for improved transient dynamics and guaranteed saturation constraints

In classical model reference adaptive control (MRAC), the adaptive rates must be tuned to meet multiple competing objectives. Large adaptive rates guarantee rapid convergence of the trajectory tracking error to zero. However, large adaptive rates may also induce saturation of the actuators and excessive overshoots of the closed-loop system’s trajectory tracking error. Conversely, low adaptive rates may produce unsatisfactory trajectory tracking performances. To overcome these limitations, in the classical MRAC framework, the adaptive rates must be tuned through an iterative process. Alternative approaches require to modify the plant’s reference model or the reference command input. This paper presents the first MRAC laws for nonlinear dynamical systems affected by matched and parametric uncertainties that constrain both the closed-loop system’s trajectory tracking error and the control input at all times within user-defined bounds, and enforce a user-defined rate of convergence on the trajectory tracking error. By applying the proposed MRAC laws, the adaptive rates can be set arbitrarily large and both the plant’s reference model and the reference command input can be chosen arbitrarily. The user-defined rate of convergence of the closed-loop plant’s trajectory is enforced by introducing a user-defined auxiliary reference model, which converges to the trajectory tracking error obtained by applying the classical MRAC laws before its transient dynamics has decayed, and steering the trajectory tracking error to the auxiliary reference model at a rate of convergence that is higher than the rate of convergence of the plant’s reference model. The ability of the proposed MRAC laws to prescribe the performance of the closed-loop system’s trajectory tracking error and control input is guaranteed by barrier Lyapunov functions. Numerical simulations illustrate both the applicability of our theoretical results and their effectiveness compared to other techniques such as prescribed performance control, which allows to constrain both the rate of convergence and the maximum overshoot on the trajectory tracking error of uncertain systems.