Contextualising the teaching and learning of measurement in Torres Strait Islander schools

This paper reports on a mathematics project conducted with six Torres Strait Islander schools and communities by the research team at the YuMi Deadly Centre at QUT. Data collected is from a small focus group of six teachers and two teacher aides. We investigated how measurement is taught and learned by students, their teachers and teacher aides in the community schools. A key focus of the project was that the teaching and learning of measurement be contextualised to the students’ culture, community and home languages. A significant finding from the project was that the teachers had differing levels of knowledge and understanding about how to contextualise measurement to support student learning. For example, an Indigenous teacher identified that mathematics and the environment are relational, that is, they are not discrete and in isolation from one another, rather they mesh together, thus affording the articulation and interchange among and between mathematics and Torres Strait Islander culture.

Variability in estimation of self-reported dietary intake data from elite athletes resulting from coding by different sports dietitians

A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.

Static load bearing exercises of individuals with transfemoral amputation fitted with an osseointegrated implant: Reliability of kinetic data

This study aimed at presenting the intra-tester reliability of the static load bearing exercises (LBEs) performed by individuals with transfemoral amputation (TFA) fitted with an osseointegrated implant to stimulate the bone remodelling process. There is a need for a better understanding of the implementation of these exercises particularly the reliability. The intra-tester reliability is discussed with a particular emphasis on inter-load prescribed, inter-axis and inter-component reliabilities as well as the effect of body weight normalisation. Eleven unilateral TFAs fitted with an OPRA implant performed five trials in four loading conditions. The forces and moments on the three axes of the implant were measured directly with an instrumented pylon including a six-channel transducer. Reliability of loading variables was assessed using intraclass correlation coefficients (ICCs) and percentage standard error of measurement values (%SEMs). The ICCs of all variables were above 0.9 and the %SEM values ranged between 0 and 87%. This study showed a high between-participants’ variance highlighting the lack of loading consistency typical of symptomatic population as well as a high reliability between the loading sessions indicating a plausible correct repetition of the LBE by the participants. However, these outcomes must be understood within the framework of the proposed experimental protocol.

Major project managers’ internal and external stakeholder relationships: The development and validation of measurement scales

In this paper, we detail the development of two stakeholder relationships scales. The scales measure major project managers' perceived competence in developing (establishing and maintaining) high quality, effective relationships with stakeholders who are internal and external to their organization. Our sample consists of 373 major project managers from a sub-set of the Australian defense industry. Both the internal stakeholder relationships scale and the external stakeholder relationships scale demonstrated validity and reliability. This research has implications for the interpersonal work relationships literature and the stakeholder management literature. We recommend that researchers test these scales with multiple samples, across different project types and project industries in the future. The stakeholder relationship scales should be versatile enough to be applied to project management generally but are perhaps best suited to major project environments.

Household carbon emission research: An analytical review of measurement, influencing factors and mitigation prospects

Greenhouse gas (GHG) emissions are simultaneously exhausting the world's supply of fossil fuels and threatening the global climate. In many developing countries, significant improvement in living standards in recent years due to the accelerating development of their economies has resulted in a disproportionate increase in household energy consumption. Therefore, a major reduction in household carbon emissions (HCEs) is essential if global carbon reduction targets are to be met. To do this, major Organisation for Economic Co-operation and Development (OECD) states have already implemented policies to alleviate the negative environmental effects of household behaviors and less carbon-intensive technologies are also proposed to promote energy efficiency and reduce carbon emissions. However, before any further remedial actions can be contemplated, though, it is important to fully understand the actual causes of such large HCEs and help researchers both gain deep insights into the development of the research domain and identify valuable research topics for future study. This paper reviews existing literature focusing on the domain of HCEs. This critical review provides a systematic understanding of current work in the field, describing the factors influencing HCEs under the themes of household income, household size, age, education level, location, gender and rebound effects. The main quantification methodologies of input–output models, life cycle assessment and emission coefficient methods are also presented, and the proposed measures to mitigate HCEs at the policy, technology and consumer levels. Finally, the limitations of work done to date and further research directions are identified for the benefit of future studies.

Dosage Compensation And Sex Determination In Drosophila - Mechanism Of Measurement Of The X/A Ratio

We propose a molecular mechanism for the intra-cellular measurement of the ratio of the number of X chromosomes to the number of sets of autosomes, a process central to both sex determination and dosage compensation in Drosophila melanogaster. In addition to the two loci, da and Sxl, which have been shown by Cline (Genetics, 90, 683, 1978)and others to be involved in these processes, we postulate two other loci, one autosomal (ω) and the other, X-linked (π). The product of the autosomal locus da stimulates ω and initiates synthesis of a limited quantity of repressor. Sxl and π ,both of which are X-linked, compete for this repressor as well as for RNA polymerase. It is assumed that Sxl has lower affinity than π for repressor as well as polymerase and that the binding of polymerase to one of these sites modulates the binding affinity of the other site for the enzyme. It can be shown that as a result of these postulated interactions transcription from the Sxl site is proportional to the X/A ratio such that the levels of Sxl+ product are low in males, high in females and intermediate in the intersexes. If, as proposed by Cline, the Sxl- product is an inhibitor of X chromosome activity, this would result in dosage compensation. The model leads to the conclusion that high levels of Sxl+ product promote a female phenotype and low levels, a male phenotype. One interesting consequence of the assumptions on which the model is based is that the level of Sxl+ product in the cell, when examined as a function of increasing repressor concentration, first goes up and then decreases, yielding a bell-shaped curve. This feature of the model provides an explanation for some of the remarkable interactions among mutants at the Sxl, da and mle loci and leads to several predictions. The proposed mechanism may also have relevance to certain other problems, such as size regulation during development, which seem to involve measurement of ratios at the cellular level.

On-board correction of systematic error of Earth sensors

Infrared Earth sensors are used in spacecraft for attitude sensing. Their accuracy is limited by systematic and random errors. Dominant sources of systematic errors are analyzed for a typical scanning infrared Earth sensor used in a remote-sensing satellite in a 900-km sun-synchronous orbit. The errors considered arise from 1) seasonable variation of infrared radiation, 2) oblate shape of the Earth, 3) ambient temperature of sensors, 4) changes in spin/scan period, and 5) misalignment of the axis of the sensors. Simple relations are derived using least-squares curve fitting for onboard correction of these errors. With these, it is possible to improve the accuracy of attitude determination by eight fold and achieve performance comparable to ground-based post-facto attitude computation.

Effect of measurement noise on Granger causality

Most of the signals recorded in experiments are inevitably contaminated by measurement noise. Hence, it is important to understand the effect of such noise on estimating causal relations between such signals. A primary tool for estimating causality is Granger causality. Granger causality can be computed by modeling the signal using a bivariate autoregressive (AR) process. In this paper, we greatly extend the previous analysis of the effect of noise by considering a bivariate AR process of general order p. From this analysis, we analytically obtain the dependence of Granger causality on various noise-dependent system parameters. In particular, we show that measurement noise can lead to spurious Granger causality and can suppress true Granger causality. These results are verified numerically. Finally, we show how true causality can be recovered numerically using the Kalman expectation maximization algorithm.

Intraobserver error associated with anthropometric measurements made by dietitians

Este trabajo se encuentra bajo la licencia Creative Commons Attribution 3.0.

Macroscopically Dissipative Systems with Underlying Microscopic Dynamics : Properties and Limits of Measurement

While some of the deepest results in nature are those that give explicit bounds between important physical quantities, some of the most intriguing and celebrated of such bounds come from fields where there is still a great deal of disagreement and confusion regarding even the most fundamental aspects of the theories. For example, in quantum mechanics, there is still no complete consensus as to whether the limitations associated with Heisenberg's Uncertainty Principle derive from an inherent randomness in physics, or rather from limitations in the measurement process itself, resulting from phenomena like back action. Likewise, the second law of thermodynamics makes a statement regarding the increase in entropy of closed systems, yet the theory itself has neither a universally-accepted definition of equilibrium, nor an adequate explanation of how a system with underlying microscopically Hamiltonian dynamics (reversible) settles into a fixed distribution.

Motivated by these physical theories, and perhaps their inconsistencies, in this thesis we use dynamical systems theory to investigate how the very simplest of systems, even with no physical constraints, are characterized by bounds that give limits to the ability to make measurements on them. Using an existing interpretation, we start by examining how dissipative systems can be viewed as high-dimensional lossless systems, and how taking this view necessarily implies the existence of a noise process that results from the uncertainty in the initial system state. This fluctuation-dissipation result plays a central role in a measurement model that we examine, in particular describing how noise is inevitably injected into a system during a measurement, noise that can be viewed as originating either from the randomness of the many degrees of freedom of the measurement device, or of the environment. This noise constitutes one component of measurement back action, and ultimately imposes limits on measurement uncertainty. Depending on the assumptions we make about active devices, and their limitations, this back action can be offset to varying degrees via control. It turns out that using active devices to reduce measurement back action leads to estimation problems that have non-zero uncertainty lower bounds, the most interesting of which arise when the observed system is lossless. One such lower bound, a main contribution of this work, can be viewed as a classical version of a Heisenberg uncertainty relation between the system's position and momentum. We finally also revisit the murky question of how macroscopic dissipation appears from lossless dynamics, and propose alternative approaches for framing the question using existing systematic methods of model reduction.