The infrared imaging spectrograph (IRIS) for TMT: electronics-cable architecture

The InfraRed Imaging Spectrograph (IRIS) is a first-light instrument for the Thirty Meter Telescope (TMT). It combines a diffraction limited imager and an integral field spectrograph. This paper focuses on the electrical system of IRIS. With an instrument of the size and complexity of IRIS we face several electrical challenges. Many of the major controllers must be located directly on the cryostat to reduce cable lengths, and others require multiple bulkheads and must pass through a large cable wrap. Cooling and vibration due to the rotation of the instrument are also major challenges. We will present our selection of cables and connectors for both room temperature and cryogenic environments, packaging in the various cabinets and enclosures, and techniques for complex bulkheads including for large detectors at the cryostat wall

The InfraRed Imaging Spectrograph (IRIS) for TMT: photometric precision and ghost analysis

The InfraRed Imaging Spectrograph (IRIS) is a first-light instrument for the Thirty Meter Telescope (TMT) that will be used to sample the corrected adaptive optics field by NFIRAOS with a near-infrared (0.8 - 2.4 $\mu$m) imaging camera and Integral Field Spectrograph (IFS). In order to understand the science case specifications of the IRIS instrument, we use the IRIS data simulator to characterize photometric precision and accuracy of the IRIS imager. We present the results of investigation into the effects of potential ghosting in the IRIS optical design. Each source in the IRIS imager field of view results in ghost images on the detector from IRIS's wedge filters, entrance window, and Atmospheric Dispersion Corrector (ADC) prism. We incorporated each of these ghosts into the IRIS simulator by simulating an appropriate magnitude point source at a specified pixel distance, and for the case of the extended ghosts redistributing flux evenly over the area specified by IRIS's optical design. We simulate the ghosting impact on the photometric capabilities, and found that ghosts generally contribute negligible effects on the flux counts for point sources except for extreme cases where ghosts coalign with a star of $\Delta$m$>$2 fainter than the ghost source. Lastly, we explore the photometric precision and accuracy for single sources and crowded field photometry on the IRIS imager.Comment: SPIE 2018, 14 pages, 14 figures, 4 tables, Proceedings of SPIE 10702-373, Ground-based and Airborne Instrumentation for Astronomy VII, 10702A7 (16 July 2018

The infrared imaging spectrograph (IRIS) for TMT: electronics-cable architecture

The InfraRed Imaging Spectrograph (IRIS) is a first-light instrument for the Thirty Meter Telescope (TMT). It combines a diffraction limited imager and an integral field spectrograph. This paper focuses on the electrical system of IRIS. With an instrument of the size and complexity of IRIS we face several electrical challenges. Many of the major controllers must be located directly on the cryostat to reduce cable lengths, and others require multiple bulkheads and must pass through a large cable wrap. Cooling and vibration due to the rotation of the instrument are also major challenges. We will present our selection of cables and connectors for both room temperature and cryogenic environments, packaging in the various cabinets and enclosures, and techniques for complex bulkheads including for large detectors at the cryostat wall

Maternal communication style, problem-solving and dietary adherence in young children with type 1 diabetes

The incidence of type 1 diabetes (T1D) in young children is increasing markedly however young children have been overlooked in paediatric adherence research despite the unique challenges their care presents. We investigated the relation between maternal communication style and adherence to the dietary regimen in 40 children with T1D, aged 2-8 years, and their mothers. Mothers completed measures of children's sugar consumption, parent-child communication quality, and child psychological functioning. Mothers and children engaged in a videotaped problem-solving task related to the dietary regimen, with maternal utterances analysed for behavioural control style (e.g., commands versus suggestions) and cognitive complexity (e.g., provision of labels versus questions). Maternal communications which engaged children, behaviourally and cognitively, in the task were associated with better adherence, medical, communication quality, and child adjustment outcomes. We conclude that adherence and health (medical and psychological) are optimized when young children are given opportunities to participate in their care.casl16pub1774pub

How do frontline staff use patient experience data for service improvement? Findings from an ethnographic case study evaluation

Funding Information: The authors would like to thank the following: the ward teams and senior management teams at the six participating case study sites. Neil Churchill, Angela Coulter, Ray Fitzpatrick, Crispin Jenkinson, Trish Greenhalgh and Sian Rees who were co-investigators on the study, contributing to the original design and conduct of the study. Esther Ainley and Steve Sizmur from Picker Institute Europe, who contributed to data collection and analysis. Prof. John Gabbay and Prof. Andr? le May, University of Southampton, for facilitating the learning community meetings. The members of the lay advisory panel: Barbara Bass, Tina Lonhgurst, Georgina McMasters, Carol Munt, Gillian Richards, Tracey Richards, Gordon Sturmey, Karen Swaffield, Ann Tomlime and Paul Whitehouse. The external members of the Study Steering Committee: Joanna Foster, Tony Berendt, Caroline Shuldham, Joanna Goodrich, Leigh Kendall, Bernard Gudgin and Manoj Mistry. At the time of conducting the research LL and SP were employed by the University of Oxford. Preliminary findings from the study have been presented publicly at the following conferences: European Association for Communication in Healthcare 2016; The International Society for Quality in Healthcare 2017; Health Services Research UK 2017; Medical Sociology 2018. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Publisher Copyright: © The Author(s) 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Peer reviewedPublisher PD

Understanding how front-line staff use patient experience data for service improvement: an exploratory case study evaluation

Background and aim: The NHS collects a large number of data on patient experience, but there are concerns that it does not use this information to improve care. This study explored whether or not and how front-line staff use patient experience data for service improvement. Methods: Phase 1 – secondary analysis of existing national survey data, and a new survey of NHS trust patient experience leads. Phase 2 – case studies in six medical wards using ethnographic observations and interviews. A baseline and a follow-up patient experience survey were conducted on each ward, supplemented by in-depth interviews. Following an initial learning community to discuss approaches to learning from and improving patient experience, teams developed and implemented their own interventions. Emerging findings from the ethnographic research were shared formatively. Phase 3 – dissemination, including an online guide for NHS staff. Key findings: Phase 1 – an analysis of staff and inpatient survey results for all 153 acute trusts in England was undertaken, and 57 completed surveys were obtained from patient experience leads. The most commonly cited barrier to using patient experience data was a lack of staff time to examine the data (75%), followed by cost (35%), lack of staff interest/support (21%) and too many data (21%). Trusts were grouped in a matrix of high, medium and low performance across several indices to inform case study selection. Phase 2 – in every site, staff undertook quality improvement projects using a range of data sources. The number and scale of these varied, as did the extent to which they drew directly on patient experience data, and the extent of involvement of patients. Before-and-after surveys of patient experience showed little statistically significant change. Making sense of patient experience ‘data’ Staff were engaged in a process of sense-making from a range of formal and informal sources of intelligence. Survey data remain the most commonly recognised and used form of data. ‘Soft’ intelligence, such as patient stories, informal comments and daily ward experiences of staff, patients and family, also fed into staff’s improvement plans, but they and the wider organisation may not recognise these as ‘data’. Staff may lack confidence in using them for improvement. Staff could not always point to a specific source of patient experience ‘data’ that led to a particular project, and sometimes reported acting on what they felt they already knew needed changing. Staff experience as a route to improving patient experience Some sites focused on staff motivation and experience on the assumption that this would improve patient experience through indirect cultural and attitudinal change, and by making staff feel empowered and supported. Staff participants identified several potential interlinked mechanisms: (1) motivated staff provide better care, (2) staff who feel taken seriously are more likely to be motivated, (3) involvement in quality improvement is itself motivating and (4) improving patient experience can directly improve staff experience. ‘Team-based capital’ in NHS settings We propose ‘team-based capital’ in NHS settings as a key mechanism between the contexts in our case studies and observed outcomes. ‘Capital’ is the extent to which staff command varied practical, organisational and social resources that enable them to set agendas, drive process and implement change. These include not just material or economic resources, but also status, time, space, relational networks and influence. Teams involving a range of clinical and non-clinical staff from multiple disciplines and levels of seniority could assemble a greater range of capital; progress was generally greater when the team included individuals from the patient experience office. Phase 3 – an online guide for NHS staff was produced in collaboration with The Point of Care Foundation. Limitations: This was an ethnographic study of how and why NHS front-line staff do or do not use patient experience data for quality improvement. It was not designed to demonstrate whether particular types of patient experience data or quality improvement approaches are more effective than others. Future research: Developing and testing interventions focused specifically on staff but with patient experience as the outcome, with a health economics component. Studies focusing on the effect of team composition and diversity on the impact and scope of patient-centred quality improvement. Research into using unstructured feedback and soft intelligence

Can early weight loss, eating behaviors and socioeconomic factors predict successful weight loss at 12- and 24-months in adolescents with obesity and insulin resistance participating in a randomised controlled trial?

© 2016 Gow et al.Background: Lifestyle interventions in adolescents with obesity can result in weight loss following active intervention but individual responses vary widely. This study aimed to identify predictors of weight loss at 12- and 24-months in adolescents with obesity and clinical features of insulin resistance. Methods: Adolescents (n = 111, 66 girls, aged 10-17 years) were participants in a randomised controlled trial, the RESIST study, examining the effects of two diets differing in macronutrient content on insulin sensitivity. Eighty-five completed the 12-month program and 24-month follow-up data were available for 42 adolescents. Change in weight was determined by BMI expressed as a percentage of the 95th percentile (BMI95). The study physician collected socioeconomic data at baseline. Physical activity and screen time, and psychological dimensions of eating behavior were self-reported using the validated CLASS and EPI-C questionnaires, respectively. Stepwise multiple regressions were conducted to identify models that best predicted change in BMI95 at 12- and 24-months. Results: Mean BMI95 was reduced at 12-months compared with baseline (mean difference [MD] ± SE: -6.9 ± 1.0, P < 0.001) but adolescents had significant re-gain from 12- to 24-months (MD ± SE: 3.7 ± 1.5, P = 0.017). Participants who achieved greater 12-month weight loss had: greater 3-month weight loss, a father with a higher education, lower baseline external eating and parental pressure to eat scores and two parents living at home. Participants who achieved greater 24-month weight loss had: greater 12-month weight loss and a lower baseline emotional eating score. Conclusions: Early weight loss is consistently identified as a strong predictor of long-term weight loss. This could be because early weight loss identifies those more motivated and engaged individuals. Patients who have baseline factors predictive of long-term weight loss failure may benefit from additional support during the intervention. Additionally, if a patient does not achieve early weight loss, further support or transition to an alternate intervention where they may have increased success may be considered. Trial registration: Australian New Zealand Clinical Trial Registration Number (ACTRN) 12608000416392 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=83071Link_to_subscribed_fulltex

The infrared imaging spectrograph (IRIS) for TMT: electronics-cable architecture

The InfraRed Imaging Spectrograph (IRIS) is a first-light instrument for the Thirty Meter Telescope (TMT). It combines a diffraction limited imager and an integral field spectrograph. This paper focuses on the electrical system of IRIS. With an instrument of the size and complexity of IRIS we face several electrical challenges. Many of the major controllers must be located directly on the cryostat to reduce cable lengths, and others require multiple bulkheads and must pass through a large cable wrap. Cooling and vibration due to the rotation of the instrument are also major challenges. We will present our selection of cables and connectors for both room temperature and cryogenic environments, packaging in the various cabinets and enclosures, and techniques for complex bulkheads including for large detectors at the cryostat wall

The InfraRed Imaging Spectrograph (IRIS) for TMT: photometric characterization of anisoplanatic PSFs and testing of PSF-Reconstruction via AIROPA

The InfraRed Imaging Spectrograph (IRIS) is a first-light instrument for the Thirty Meter Telescope (TMT) that will be used to sample the corrected adaptive optics field by the Narrow-Field Infrared Adaptive Optics System (NFIRAOS) with a near-infrared (0.8 - 2.4 µm) imaging camera and integral field spectrograph. To better understand IRIS science specifications we use the IRIS data simulator to characterize relative photometric precision and accuracy across the IRIS imaging camera 34”x34” field of view. Because the Point Spread Function (PSF) varies due to the effects of anisoplanatism, we use the Anisoplanatic and Instrumental Reconstruction of Off-axis PSFs for AO (AIROPA) software package to conduct photometric measurements on simulated frames using PSF-fitting as the PSF varies in single-source, binary, and crowded field use cases. We report photometric performance of the imaging camera as a function of the instrumental noise properties including dark current and read noise. Using the same methods, we conduct comparisons of photometric performance with reconstructed PSFs, in order to test the veracity of the current PSF-Reconstruction algorithms for IRIS/TMT