Laser Guide Star Only Adaptive Optics: The Development of Tools and Algorithms for the Determination of Laser Guide Star Tip-Tilt

Adaptive Optics (AO) is a technology which corrects for the effects of the atmosphere and so improves the optical quality of ground based astronomical observations. The bright “guide stars” required for correction are not available across the entire sky, so Laser Guide Stars (LGSs) are created. A Natural Guide Star (NGS) is still required to correct for tip-tilt as the LGS encounters turbulence on the uplink path resulting in unpredictable “jitter”, hence limiting corrected sky coverage. In this thesis an original method is proposed and investigated that promises to improve the correction performance for tomographic AO systems using only LGSs, and no NGS, by retrieving the LGS uplink tip-tilt. To investigate the viability of this method, two unique tools have been developed. A new AO simulation has been written in the Python programming language which has been designed to facilitate the rapid development of new AO concepts. It features realistic LGS simulation, ideal to test the method of LGS uplink tip-tilt retrieval. The Durham Real-Time Adaptive Optics Generalised Optical Nexus (DRAGON) is a laboratory AO test bench nearing completion, which features multiple LGS and NGS Wavefront Sensors (WFSs) intended to further improve tomographic AO. A novel method of LGS emulation has been designed, which re-creates focus anisoplanatism, elongation and uplink turbulence. Once complete, DRAGON will be the ideal test bench for further development of LGS uplink tip-tilt retrieval. Performance estimates from simulation of the LGS uplink tip-tilt retrieval method are presented. Performance is improved over tomographic LGS AO systems which do not correct for tip-tilt, giving a modest improvement in image quality over the entire night sky. Correction performance is found to be dependent on the atmospheric turbulence profile. If combined with ground layer adaptive optics, higher correction performance with a very high sky coverage may be achieved

Evolution of neural networks for the prediction of hydraulic conductivity as a function of borehole geophysical logs: Shobasama site, Japan.

This report describes the methodology and results of a project to develop a neural network for the prediction of the measured hydraulic conductivity or transmissivity in a series of boreholes at the Tono, Japan study site. Geophysical measurements were used as the input to EL feed-forward neural network. A simple genetic algorithm was used to evolve the architecture and parameters of the neural network in conjunction with an optimal subset of geophysical measurements for the prediction of hydraulic conductivity. The first attempt was focused on the estimation of the class of the hydraulic conductivity, high, medium or low, from the geophysical logs. This estimation was done while using the genetic algorithm to simultaneously determine which geophysical logs were the most important and optimizing the architecture of the neural network. Initial results showed that certain geophysical logs provided more information than others- most notably the 'short-normal', micro-resistivity, porosity and sonic logs provided the most information on hydraulic conductivity. The neural network produced excellent training results with accuracy of 90 percent or greater, but was unable to produce accurate predictions of the hydraulic conductivity class. The second attempt at prediction was done using a new methodology and a modified data set. The new methodology builds on the results of the first attempts at prediction by limiting the choices of geophysical logs to only those that provide significant information. Additionally, this second attempt uses a modified data set and predicts transmissivity instead of hydraulic conductivity. Results of these simulations indicate that the most informative geophysical measurements for the prediction of transmissivity are depth and sonic log. The long normal resistivity and self potential borehole logs are moderately informative. In addition, it was found that porosity and crack counts (clear, open, or hairline) do not inform predictions of hydraulic transmissivity

Prompt Problems: A New Programming Exercise for the Generative AI Era

Large Language Models (LLMs) are revolutionizing the field of computing education with their powerful code-generating capabilities. Traditional pedagogical practices have focused on code writing tasks, but there is now a shift in importance towards code reading, comprehension and evaluation of LLM-generated code. Alongside this shift, an important new skill is emerging -- the ability to solve programming tasks by constructing good prompts for code-generating models. In this work we introduce a new type of programming exercise to hone this nascent skill: 'Prompt Problems'. Prompt Problems are designed to help students learn how to write effective prompts for AI code generators. A student solves a Prompt Problem by crafting a natural language prompt which, when provided as input to an LLM, outputs code that successfully solves a specified programming task. We also present a new web-based tool called Promptly which hosts a repository of Prompt Problems and supports the automated evaluation of prompt-generated code. We deploy Promptly for the first time in one CS1 and one CS2 course and describe our experiences, which include student perceptions of this new type of activity and their interactions with the tool. We find that students are enthusiastic about Prompt Problems, and appreciate how the problems engage their computational thinking skills and expose them to new programming constructs. We discuss ideas for the future development of new variations of Prompt Problems, and the need to carefully study their integration into classroom practice.Comment: Accepted to SIGCSE'24. arXiv admin note: substantial text overlap with arXiv:2307.1636

"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmers

Recent developments in deep learning have resulted in code-generation models that produce source code from natural language and code-based prompts with high accuracy. This is likely to have profound effects in the classroom, where novices learning to code can now use free tools to automatically suggest solutions to programming exercises and assignments. However, little is currently known about how novices interact with these tools in practice. We present the first study that observes students at the introductory level using one such code auto-generating tool, Github Copilot, on a typical introductory programming (CS1) assignment. Through observations and interviews we explore student perceptions of the benefits and pitfalls of this technology for learning, present new observed interaction patterns, and discuss cognitive and metacognitive difficulties faced by students. We consider design implications of these findings, specifically in terms of how tools like Copilot can better support and scaffold the novice programming experience.Comment: 26 pages, 2 figures, TOCH

Trends and emissions of six perfluorocarbons in the Northern Hemisphere and Southern Hemisphere

Perfluorocarbons (PFCs) are potent greenhouse gases with global warming potentials up to several thousand times greater than CO2 on a 100-year time horizon. The lack of any significant sinks for PFCs means that they have long atmospheric lifetimes of the order of thousands of years. Anthropogenic production is thought to be the only source for most PFCs. Here we report an update on the global atmospheric abundances of the following PFCs, most of which have for the first time been analytically separated according to their isomers: c-octafluorobutane (c-C4F8), n-decafluorobutane (n-C4F10), n-dodecafluoropentane (n-C5F12), n-tetradecafluorohexane (n-C6F14), and n-hexadecafluoroheptane (n-C7F16). Additionally, we report the first data set on the atmospheric mixing ratios of perfluoro-2-methylpentane (i-C6F14). The existence and significance of PFC isomers have not been reported before, due to the analytical challenges of separating them. The time series spans a period from 1978 to the present. Several data sets are used to investigate temporal and spatial trends of these PFCs: time series of air samples collected at Cape Grim, Australia, from 1978 to the start of 2018; a time series of air samples collected between July 2015 and April 2017 at Tacolneston, UK; and intensive campaign-based sampling collections from Taiwan. Although the remote “background” Southern Hemispheric Cape Grim time series indicates that recent growth rates of most of these PFCs are lower than in the 1990s, we continue to see significantly increasing mixing ratios that are between 6 % and 27 % higher by the end of 2017 compared to abundances measured in 2010. Air samples from Tacolneston show a positive offset in PFC mixing ratios compared to the Southern Hemisphere baseline. The highest mixing ratios and variability are seen in air samples from Taiwan, which is therefore likely situated much closer to PFC sources, confirming predominantly Northern Hemispheric emissions for most PFCs. Even though these PFCs occur in the atmosphere at levels of parts per trillion molar or less, their total cumulative global emissions translate into 833 million metric tonnes of CO2 equivalent by the end of 2017, 23 % of which has been emitted since 2010. Almost two-thirds of the CO2 equivalent emissions within the last decade are attributable to c-C4F8, which currently also has the highest emission rates that continue to grow. Sources of all PFCs covered in this work remain poorly constrained and reported emissions in global databases do not account for the abundances found in the atmosphere

The developmental activities of skilled youth CONCACAF soccer players and the contribution of their development system

Small/er soccer nations rely strongly on developing youth athletes into experts in adulthood due to financial, logistical, and coach education constraints. One factor that contributes to this expertise is activities engaged in during childhood. Researchers have described these activities by focusing on larger, well-developed countries that often have larger participation rates and higher competition levels than their smaller counterparts. Therefore, to provide more specific information to support talent development in smaller soccer nations, a survey of the youth development system of a small soccer nation was conducted, alongside recording the developmental activities of skilled and less-skilled soccer players within this system. Key stakeholders (e.g., technical director) completed a youth development system survey. Skilled soccer players (n = 12) who were representing their country at U17 level and less-skilled players (n = 13) that had never played for their country completed a Participation History Questionnaire. Skilled players engaged in significantly higher amounts of individual practice in both childhood and early adolescence compared to less-skilled players. Survey data indicated that the greater amounts of individual practice for the skilled players stemmed from a lack of finances, playing facilities, and a formal coach education program. Results from this study may inform future practices and processes in the youth development systems of small/er soccer nations and their national associations

Heterogeneous N2O5 Uptake During Winter: Aircraft Measurements During the 2015 WINTER Campaign and Critical Evaluation of Current Parameterizations

Nocturnal dinitrogen pentoxide (N2O5) heterogeneous chemistry impacts regional air quality and the distribution and lifetime of tropospheric oxidants. Formed from the oxidation of nitrogen oxides, N2O5 is heterogeneously lost to aerosol with a highly variable reaction probability, γ(N2O5), dependent on aerosol composition and ambient conditions. Reaction products include soluble nitrate (HNO3 or NO3−) and nitryl chloride (ClNO2). We report the first‐ever derivations of γ(N2O5) from ambient wintertime aircraft measurements in the critically important nocturnal residual boundary layer. Box modeling of the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the eastern United States derived 2,876 individual γ(N2O5) values with a median value of 0.0143 and range of 2 × 10−5 to 0.1751. WINTER γ(N2O5) values exhibited the strongest correlation with aerosol water content, but weak correlations with other variables, such as aerosol nitrate and organics, suggesting a complex, nonlinear dependence on multiple factors, or an additional dependence on a nonobserved factor. This factor may be related to aerosol phase, morphology (i.e., core shell), or mixing state, none of which are commonly measured during aircraft field studies. Despite general agreement with previous laboratory observations, comparison of WINTER data with 14 literature parameterizations (used to predict γ(N2O5) in chemical transport models) confirms that none of the current methods reproduce the full range of γ(N2O5) values. Nine reproduce the WINTER median within a factor of 2. Presented here is the first field‐based, empirical parameterization of γ(N2O5), fit to WINTER data, based on the functional form of previous parameterizations

Patient acceptability of home monitoring for neovascular age-related macular degeneration reactivation:a qualitative study

Neovascular age-related macular degeneration (nAMD) is a chronic, progressive condition and the commonest cause of visual disability in older adults. This study formed part of a diagnostic test accuracy study to quantify the ability of three index home monitoring (HM) tests (one paper-based and two digital tests) to identify reactivation in nAMD. The aim of this qualitative research was to investigate patients’ or participants’ views about acceptability and explore adherence to weekly HM. Semi-structured interviews were held with 78/297 participants (26%), with close family members (n = 11) and with healthcare professionals involved in training participants in HM procedures (n = 9) (n = 98 in total). A directed thematic analytical approach was applied to the data using a deductive and inductive coding framework informed by theories of technology acceptance. Five themes emerged related to: 1. The role of HM; 2. Suitability of procedures and instruments; 3. Experience of HM; 4. Feasibility of HM in usual practice; and 5. Impediments to patient acceptability of HM. Various factors influenced acceptability including a patient’s understanding about the purpose of monitoring. While initial training and ongoing support were regarded as essential for overcoming unfamiliarity with use of digital technology, patients viewed HM as relatively straightforward and non-burdensome. There is a need for further research about how use of performance feedback, level of support and nature of tailoring might facilitate further the implementation of routinely conducted HM. Home monitoring was acceptable to patients and they recognised its potential to reduce clinic visits during non-active treatment phases. Findings have implications for implementation of digital HM in the care of older people with nAMD and other long-term conditions