A Method for Exploring the Habitability of Earth-Like Exoplanets: Applications to TESS Objects of Interest 203 b, 256 b, and 700 d

The Transiting Exoplanet Survey Satellite (TESS) has and is continuing to discover a multitude of potentially habitable planet candidates. As more planets are detected and confirmed, it becomes increasingly important to strategically search for signs of habitability with which to differentiate and prioritize them for further observation, in particular with the James Webb Space Telescope (JWST). To facilitate this, I have created a method for prioritizing TESS planet candidates based on parameters derived from their light curves and have applied the method to the TESS Candidate Target List (CTL). This data set uses preliminary fits to transit modeling which can rely on erroneous assumptions about the system, such as the use of a sun-like star to fit TESS Object of Interest (TOI) 700 d (Gilbert et al., 2020; Rodriguez et al. 2020). Such systems require additional followup fitting with proper inputs which is done after the initial prioritization. Nevertheless, this method identified two high-priority TOIs that lacked the extensive habitability study in this work: 256 and 203. I have further created a new modeling procedure and applied it to these TOIs as well as TOI 700 with the aim to constrain the possibility of liquid water being present. In most of the recent cases of observations targeting exoplanets, 3D General Circulation Models (GCMs) are used to infer planet composition and structure or to predict observations of scientific interest. However, previous modeling has focused on parameter spaces that are not statistically linked to the observational data (e.g. Del Genio et al. 2019a, Turbet et al. 2016). Accurate statistical modeling is vital to the confirmation of other habitable worlds. To address the problem, I have created a method to statistically investigate the habitability of exoplanets with a suite of 1D and 3D models using the \textit{VPlanet} software package (Barnes et al. 2020) and the ROCKE-3D GCM (Way et al. 2017). Furthermore, I have applied this method to the two TESS-observed planets and candidates which were most highly prioritized as well as TOI 700 d. This constitutes an end-to-end investigation of real TESS exoplanets and the potential for liquid water on their surfaces. This provides guidance for current and future NASA missions like JWST, helping to answer the question: is there life beyond Earth

A Method for Exploring the Habitability of Earth-Like Exoplanets: Applications to TESS Objects of Interest 203 b, 256 b, and 700 d

The Transiting Exoplanet Survey Satellite (TESS) has and is continuing to discover a multitude of potentially habitable planet candidates. As more planets are detected and confirmed, it becomes increasingly important to strategically search for signs of habitability with which to differentiate and prioritize them for further observation, in particular with the James Webb Space Telescope (JWST). To facilitate this, I have created a method for prioritizing TESS planet candidates based on parameters derived from their light curves and have applied the method to the TESS Candidate Target List (CTL). This data set uses preliminary fits to transit modeling which can rely on erroneous assumptions about the system, such as the use of a sun-like star to fit TESS Object of Interest (TOI) 700 d (Gilbert et al., 2020; Rodriguez et al. 2020). Such systems require additional followup fitting with proper inputs which is done after the initial prioritization. Nevertheless, this method identified two high-priority TOIs that lacked the extensive habitability study in this work: 256 and 203. I have further created a new modeling procedure and applied it to these TOIs as well as TOI 700 with the aim to constrain the possibility of liquid water being present. In most of the recent cases of observations targeting exoplanets, 3D General Circulation Models (GCMs) are used to infer planet composition and structure or to predict observations of scientific interest. However, previous modeling has focused on parameter spaces that are not statistically linked to the observational data (e.g. Del Genio et al. 2019a, Turbet et al. 2016). Accurate statistical modeling is vital to the confirmation of other habitable worlds. To address the problem, I have created a method to statistically investigate the habitability of exoplanets with a suite of 1D and 3D models using the \textit{VPlanet} software package (Barnes et al. 2020) and the ROCKE-3D GCM (Way et al. 2017). Furthermore, I have applied this method to the two TESS-observed planets and candidates which were most highly prioritized as well as TOI 700 d. This constitutes an end-to-end investigation of real TESS exoplanets and the potential for liquid water on their surfaces. This provides guidance for current and future NASA missions like JWST, helping to answer the question: is there life beyond Earth

“Not bad for a 28-page report”: experts respond to the SmithCommission’s proposals on Scottish governance

The Smith Commission yesterday published its official recommendations for the future of Scottish governance following the Scottish independence referendum. Democratic Audit asked Iain McLean, Coree Brown, Norman Bonney, Craig McAngus and Paul Cairney to give their views on the proposals and their implications

Kick proficiency and skill adaptability increase from an Australian football small-sided game intervention

This investigation is the first to explore the effect of a 4 week small-sided game (SSG) and traditional training intervention on player kick proficiency and player adaptability in Australian football. Twenty-two amateur Australian football players (mean ± SD; age 22.3 ± 2.46; height 182.4 ± 5.25; weight 82.1 ± 6.10; years playing senior amateur football 3.86 ± 3.09) were randomly selected into either a traditional training group (n = 11) or a SSG group (n = 11). Traditional training involved activities where skills were generally executed in isolation and with minimal contact (e.g., kicking lane drill or possession football). The SSG training group participated in 5v6 competitive games on varied shaped areas (approximately 272 m2 per player) and changing constraints (e.g., game tempo, game rules). All players participated in the team training sessions; however, the SSG group participated in a 4 × 3min training protocol, with 60 seconds recovery, in the last 20-min of the session. The SSG group participated in these alternative sessions twice a week for 4 weeks. Results indicated only the SSG enhanced their kick proficiency (17%) and were found to be more adaptable. The intervention group executed more kicks over longer distances (i.e., 20–40 m), made quicker decisions (e.g., executing more kicks in < 1s), applied more pressure to the opposition when they were executing a skill and were more likely to “take the game on” by decreasing the amount of times a skill was executed from a stationary position. The results of this study can be used by coaches when designing and implementing training programs as different training strategies will elicit different player behavioral adaptations

Australian Football Skill-Based Assessments: A Proposed Model for Future Research

Identifying sporting talent remains a difficult task due to the complex nature of sport. Technical skill assessments are used throughout the talent pathway to monitor athletes in an attempt to more effectively predict future performance. These assessments, however, largely focus on the isolated execution of key skills devoid of any game context. When assessments are representative of match-play and applied in a setting where all four components of competition (i.e., technical, tactical, physiological, and psychological) are assessed within an integrated approach, prediction of talent is more likely to be successful. This article explores the current talent identification technical skill assessments, with a particular focus on Australian Football, and proposes a 5-level performance assessment model for athlete assessment. The model separates technical game skill on a continuum from Level-1 (i.e., laboratory analysis) to Level-5 (i.e., match-play). These levels, using the assumptions of the expert performance model and representative learning design theory, incorporate a step-wise progression of performance demands to more closely represent match-play conditions. The proposed model will provide researchers and practitioners with a structured framework to consider when assessing, or developing, new assessments of technical game-based skill

Exploring Talent Identification in Australian Rules Football: The Nuances of the Athlete Recruitment Process

The process of talent identification and recruitment is a key element of the elite athlete talent pathway. As such, it is important to understand the information and specific processes used by expert recruiters to inform talent identification decisions. Therefore, the purpose of this study was to examine the perspectives of talent identifiers in relation to their conceptions of talent and the information they collect and interpret to inform their talent identification decisions. Participating in the study were 13 heads of recruitment at elite Australian Football League clubs. They were deemed experts in their field and were responsible for the selection and recruitment of players at their respective clubs. Data were collected through semi-structured interviews conducted via teleconferencing, with thematic analysis used to identify key themes. Thematic analysis of interview data generated two first order themes: (1) Understanding Talent and (2) Talent Identification Process. Four second order themes emerged from the data: (1a) Defining Talent, (1b) Athlete Attributes, (2a) Talent List Development, and(2b) Recruiter Tasks. From these second order themes, 12 associated third order themes were produced (e.g., projecting growth/athlete potential, initial identification process, refining the list, and the final decision). In particular, the findings highlight how the recruiters assess talent based on game performance and athlete intent (i.e., "giving 100%"), rather than performance at physical testing sessions, and the psychological profile of the athletes. Overall, the findings emphasize the complexity associated with elite-level talent identification and provide insight for practitioners and researchers aiming to understand and explain the talent identification process

Exploring Talent Identification in Australian Rules Football: The Nuances of the Athlete Recruitment Process

The process of talent identification and recruitment is a key element of the elite athlete talent pathway. As such, it is important to understand the information and specific processes used by expert recruiters to inform talent identification decisions. Therefore, the purpose of this study was to examine the perspectives of talent identifiers in relation to their conceptions of talent and the information they collect and interpret to inform their talent identification decisions. Participating in the study were 13 heads of recruitment at elite Australian Football League clubs. They were deemed experts in their field and were responsible for the selection and recruitment of players at their respective clubs. Data were collected through semi-structured interviews conducted via teleconferencing, with thematic analysis used to identify key themes. Thematic analysis of interview data generated two first order themes: (1) Understanding Talent and (2) Talent Identification Process. Four second order themes emerged from the data: (1a) Defining Talent, (1b) Athlete Attributes, (2a) Talent List Development, and(2b) Recruiter Tasks. From these second order themes, 12 associated third order themes were produced (e.g., projecting growth/athlete potential, initial identification process, refining the list, and the final decision). In particular, the findings highlight how the recruiters assess talent based on game performance and athlete intent (i.e., "giving 100%"), rather than performance at physical testing sessions, and the psychological profile of the athletes. Overall, the findings emphasize the complexity associated with elite-level talent identification and provide insight for practitioners and researchers aiming to understand and explain the talent identification process