Health and well-being implications surrounding the use of wearable GPS devices in professional rugby league: A Foucauldian disciplinary analysis of the normalised use of a common surveillance aid

Wearable GPS tracking devices have become commonplace coaching aids across professional field sports to enhance sports performances and reduce injury rates, despite the implications of the technology being poorly understood. This study looked at how GPS devices are used and the impact constant surveillance has upon the physical, psychological, and emotional health of rugby football workers. The disciplinary analysis of Michel Foucault was used to investigate how British Super League teams use wearable GPS technology, to investigate the dominant 'truth' that promotes surveillance technologies as 'universally beneficial' to athlete sports performance, health and well-being. Data was drawn from semi-structured interviews with three performance analysts/strength and conditioning coaches at three different Super League clubs across the North of England. Participants confessed data generated from wearable GPS is often totally ignored, despite being specifically produced to protect athlete health and wellbeing. When used, GPS data can become a 'disciplinary tool' to normalise and coerce players to comply with potentially unhealthy physical and psychological demands of a professional playing career. Importantly, regardless of how GPS data was used, the employment of wearable GPS devices was constantly and rigorously implemented. The constant surveillance experience by working players, when mismanaged or adopted as a coercive disciplinary tool, magnifies the uncertainty and fear of failure central to the predominant challenges that arise during a working football career. This leads to the acceptance of problematic norms damaging to physical, psychological, and emotional health. If GPS or other surveillance based performance analysis technologies are to be used in sport, coaches need to regulate or re-think their day-to-day use to avoid creating new harms to athlete health and well-being

Electricity Industry Competition and Market Power with High Renewable Penetrations

Globally, energy systems are expected to undergo a complete transition from fossil- fuelled generation to renewable energy in the coming decades, with a majority of energy supplied by wind and solar in many countries. In much of the developed world, this transition will take place in the context of restructured electricity markets. This thesis examines whether electricity markets, which are intended to be the key drivers of electricity industry operation and investment, are suitably designed and implemented for transitioning to high penetrations of renewable energy. Of particular interest is the role of competition in delivering efficient market outcomes, the potential for exertion of market power in high-penetration renewable energy scenarios, and whether current auction designs to incentivise efficient behaviour will be effective in the context of energy delivered at near-zero marginal cost. Previous work on electricity market competition in Australia has focused on measuring market concentration, a commonly used indicator of competitiveness, on short-term time horizons, based on historical data. However, competitiveness in Australia’s National Electricity Market (NEM) in the long term has not been assessed, nor how it might change as a result of the transition to high penetrations of variable renewable energy (VRE). This may be due in part to lack of suitable measures of competition in markets with multiple interconnected regions, but also the theory and evidence around VRE bidding patterns now and into the future has not yet been confirmed. Assessing competitiveness of future markets requires new methods for modelling and assessing potential market dynamics that affect market power. While capacity expansion modelling has been used for understanding the future technical and economic performance of electricity systems with different generation technologies, there have been very few attempts to relate these models back to the concepts of competition and market concentration. Machine learning techniques may also have the potential to provide new insights into the strategic behaviour of participants in future energy systems and have been used for modelling and solving many other complex multi-agent interactions, but to date a straightforward method for applying modern machine learning techniques to models of competitive electricity markets has not been proposed. Furthermore, significant changes that are under consideration to facilitate the energy transition, such as the introduction of a new two-sided market design in the NEM that would require all demand-side participants to submit bids, have not been considered in modelling to date. This thesis aims to investigate competition and market power in restructured electricity markets as well as their role in the clean energy transition. It investigates whether the Australian NEM has been and will continue to be a competitive market through the transition to renewable energy and how renewable generators participate in electricity auctions now and into the future. Additionally, it examines the way new tools and frameworks might further understandings of incentives and behaviour to enable more efficient and stable market designs. In order to establish a theoretical base and explore what causes market mechanism failure, a literature review and case study are undertaken into episodes of the exercise of market power globally, with a specific focus on the Californian electricity crisis. To establish how well market mechanisms are currently working, a range of competition metrics are applied to historical datasets in order to study the level of competitiveness of the Australian National Electricity Market. This leads to new answers to the question of whether the NEM is currently a competitive market, showing that current market concentration indicators provide conflicting results depending on how they are applied. A new measure of competition is provided which demonstrates that most regions are generally competitive, but some, such as Queensland, have notable periods of constraint. In order to determine how the transition to renewables might impact competition in the NEM, new indicators of competitiveness are also applied to simulations of future high-penetration renewable energy scenarios. These analyses demonstrate that swings between surplus and constraint can lead to an increase in the frequency of opportunities to exercise market power. This is an important result that shows how high-penetration renewables may significantly disrupt the function of wholesale electricity spot markets. To understand both the underlying incentives acting on renewable generators in the NEM and the current bidding strategies of these generators a case study of these generators in the NEM is undertaken. It is seen that these participants generally offer energy at or below $0/MWh, but are occasionally seen to bid at very high prices, possibly in an attempt to push up the spot price. Following this analysis, in order to examine what strategic incentives might be present in future high-penetration renewable energy grids, new equilibria for near-zero marginal cost generators are proposed. Following on from these investigations, the performance of a two-sided market in a 99% renewable energy grid is explored. In a two-sided market, flexible demand-side participants would be required to enter bids into the wholesale market. Based on forecasts of flexible demand response and renewable energy performance in a 99% renewable energy scenario, this modelling showed that demand response was, counterintuitively, less likely to be present in a two-sided market; additionally, the two-sided market was seen to mitigate the impacts of the exercise of market power because the more elastic supply curve placed upper limits on strategic generator offers. In order to develop a new modelling framework for renewable bidding behaviour in recognition of the difficulties in modelling competitive equilibria for future high- penetration renewable electricity market conditions, a market simulator is developed for the OpenAI platform that can be used to train deep learning models of electricity market bidding. Such models may be extremely useful in the context of the transition to high-penetration renewables, because competitive dynamics could be accurately predicted and understood before new capacity is built and operated. There are several key contributions of this work; it presents a new method for calculating and estimating levels of competition in electricity markets such as the NEM, which are comprised of multiple regions with constrained interconnectors, provides and applies a new methodology for exploring thresholds of competitiveness in simulations of future energy systems, develops the first long-term exploration of renewable bidding behaviour in Australia’s NEM, gives a new tool for running market behaviour experiments with emerging AI tools, and provides an early analysis of the impact of implementing a two-sided market mechanism, as proposed by Australia’s Energy Security Board. Together, these contributions may help to significantly enhance current understandings of the opportunities and challenges associated with transitioning to high-penetration renewable energy within a wholesale electricity market

Rationally designed peptide receptors for investigating RNA recognition module proteins

The supramolecular chemistry of protein-RNA binding remains poorly understood despite a recent explosion of interest in physiological and pathological protein-RNA aggregates and condensates, which occur in plants, bacteria, and many animals including humans. Viscous intranuclear droplets known as coacervates or condensates, which consist of highly-concentrated RNA and RNA-binding proteins, have been reported to form via liquid-liquid phase separation (LLPS). They have been observed to perform various cellular functions such as sequestration of specific proteins, enhancement of enzymatic functions, and regulation of intracellular and intranuclear processes. Additionally, fibrous protein-RNA aggregates are implicated in diseases such as Alzheimer’s, Parkinson’s, and ALS. This project uses a library of synthetic peptides and RNA oligonucleotides to model the most important RNA-binding domain found in RNA-binding proteins – the RNA recognition module (RRM). The RRM binds polynucleotides across a highly-conserved β-sheet consisting of four β-strands, of which the central two are understood to be more important for binding. In this thesis, these central two β-strands are modeled by a library of hairpin-shaped peptides in order to investigate the mechanisms of RRM-RNA binding, and better understand the influence of single amino acids within the RRM’s β-sheet. These studies are achieved by titrating the model peptides against a group of four synthetic RNA oligonucleotides. The overarching goal of this work is to obtain a coherent understanding of RRMs’ binding to RNA via electrostatic, aromatic, and hydrogen-bonding interactions. This understanding can be applied to understand the phenomena of coacervation, protein-RNA aggregation, and their related physiological and pathological consequences. A batch of five peptides mimicking the most common structural variants of RRMs have successfully been shown to bind to RNA oligonucleotides with binding constants between −35.4 and –29.4 kJ mol-1 and mild nucleobase selectivity. Titrations in PBS buffer supplemented with 500 mM MgCl2 reveal almost identical binding constants, effectively ruling out Coulombic attraction as the dominant interaction mode.

The influence of aluminium additions on titanium during machining through the application of a novel orthogonal cutting test method

Due to the high production rates of civil aircraft the demands for increased rates of production through high speed machining are ever increasing. A lack of consistency in the current practices for determining `machinability' means that a bespoke trial is needed to ascertain whether a particular combination of material, tool and machining parameters yields a sufficiently beneficial outcome. The current approach of large scale trials, while effective, is inefficient and costly to OEMs. Most significantly, with the aerospace industries desire to build engines outside the capabilities of current alloys, conventional machining trials cannot be conducted on new alloys that have yet to reach production scale due to the material quantities required in large scale trials. With regard to titanium alloys, the majority of alloys contain some level of aluminium as a major addition. A research programme has been undertaken to investigate the influence of aluminium on the sub-surface deformation of Ti-xAl binary alloys during high speed machining processes with a view to developing a testing method for determining `machinability'. Such a novel test method would fast track the current inefficient and uneconomical approach. Microstructural analysis of the region immediately below the machined surface has been performed for high speed milled material, focusing on quantifying the depth to which deformation occurs and the dominant plastic deformation mode by backscatter electron imaging and light microscopy. The influence of aluminium was measured through the penetration of the severe plastic deformation region and twin depth penetration and showed that the behaviour was parabolic, with Ti - 4 wt.\% Al showing the maximum level of deformation. The resultant plastic deformation from high speed milling also causes the near surface material to undergo a crystallographic reorientation, demonstrating characteristics of a simple shear process. Comparisons were made with a well established simple shear test method, axisymmetric compression testing, analysing the deformation behaviour, from high speed milling, with the mechanical behaviour of axisymmetric compressions. Use of work hardening principles, traditionally applied to FCC materials, were used to identify characteristics that exhibit trends comparable to those observed during high speed milling, in contrast to conventional mechanical behaviours such as yield stress. A novel orthogonal cut test was successfully developed to generate deformation behaviour from high speed milling and flow behaviour from axisymmetric compression tests in a single test method. This suggests the potential to incorporate `machinability' testing during alloy development rather then a final test once large scale production has commenced

Non-additive response of the high-latitude Southern Hemisphere climate to aerosol forcing in a climate model with interactive chemistry

A suite of chemistry‐climate model simulations, forced by pairs of anthropogenic forcings [comprising greenhouse gases (GHGs), ozone depleting substances (ODSs), or aerosols], were employed to investigate whether the high‐latitude Southern Hemisphere (SH) circulation response to these forcings is linearly additive, a common assumption in attribution studies. We find that the geographical pattern of sea‐level pressure (SLP) response to a combination of GHGs and ODSs is linearly additive. However, we find significant differences in the SLP response when combining GHGs and aerosols compared to the sum of the individual forcings, a non‐additivity that is currently masked by the dominance of the ODSs forcing. This non‐linearity also results in changes to the SH split jet. These results were obtained using a coupled chemistry‐climate model, indicating that the non‐linear response is due to chemical interactions between the forcing agents. As such, future simulations investigating a post‐ozone hole Southern Hemisphere climate should consider this chemical interaction

Anisotropic Small-Polaron Hopping In W:Bivo4 Single Crystals

DC electrical conductivity, Seebeck and Hall coefficients are measured between 300 and 450 K on single crystals of monoclinic bismuth vanadate that are doped n-type with 0.3% tungsten donors (W:BiVO4). Strongly activated small-polaron hopping is implied by the activation energies of the Arrhenius conductivities (about 300 meV) greatly exceeding the energies characterizing the falls of the Seebeck coefficients' magnitudes with increasing temperature (about 50 meV). Small-polaron hopping is further evidenced by the measured Hall mobility in the ab-plane (10(-1) cm(2) V-1 s(-1) at 300 K) being larger and much less strongly activated than the deduced drift mobility (about 5 x 10(-5) cm(2) V-1 s(-1) at 300 K). The conductivity and n-type Seebeck coefficient is found to be anisotropic with the conductivity larger and the Seebeck coefficient's magnitude smaller and less temperature dependent for motion within the ab-plane than that in the c-direction. These anisotropies are addressed by considering highly anisotropic next-nearest-neighbor (approximate to 5 angstrom) transfers in addition to the somewhat shorter (approximate to 4 angstrom), nearly isotropic nearest-neighbor transfers. (C) 2015 AIP Publishing LLC.U.S. Department of Energy (DOE), DE-FG02-09ER16119Welch Foundation Grant F-1436Hemphill-Gilmore Endowed FellowshipNSF MIRT DMR 1122603Chemical EngineeringTexas Materials InstituteChemistr

Clemson University’s Teacher Learning Progression Program: Personalized Advanced Credentials for Teachers

This chapter provides an overview of Clemson University\u27s Teacher Learning Progression program, which offers participating middle school science, technology, engineering, and/or mathematics (STEM) teachers with personalized advanced credentials. In contrast to typical professional development (PD) approaches, this program identifies individualized pathways for PD based on teachers\u27 unique interests and needs and offers PD options through the use of a “recommender system”—a system providing context-specific recommendations to guide teachers toward the identification of preferred PD pathways and content. In this chapter, the authors introduce the program and highlight (1) the data collection and instrumentation needed to make personalized PD recommendations, (2) the recommender system, and (3) the personalized advanced credential options. The authors also discuss lessons learned through initial stages of project implementation and consider future directions for the use of recommender systems to support teacher PD, considering both research and applied implications and settings

Climate change modulates the stratospheric volcanic sulfate aerosol lifecycle and radiative forcing from tropical eruptions.

Explosive volcanic eruptions affect climate, but how climate change affects the stratospheric volcanic sulfate aerosol lifecycle and radiative forcing remains unexplored. We combine an eruptive column model with an aerosol-climate model to show that the stratospheric aerosol optical depth perturbation from frequent moderate-magnitude tropical eruptions (e.g. Nabro 2011) will be reduced by 75% in a high-end warming scenario compared to today, a consequence of future tropopause height rise and unchanged eruptive column height. In contrast, global-mean radiative forcing, stratospheric warming and surface cooling from infrequent large-magnitude tropical eruptions (e.g. Mt. Pinatubo 1991) will be exacerbated by 30%, 52 and 15% in the future, respectively. These changes are driven by an aerosol size decrease, mainly caused by the acceleration of the Brewer-Dobson circulation, and an increase in eruptive column height. Quantifying changes in both eruptive column dynamics and aerosol lifecycle is therefore key to assessing the climate response to future eruptions