Negative ion measurements in RF and DC temporally modulated hydrogen volume ion sources

Negative ion research is stimulated by the need for high power and high density neutral beams for neutral beam heating systems to be used in proposed nuclear fusion reactors. Extensive research has been carried out on the enhancement of the production of negative ions from hydrogen/deuterium discharges. The negative ion sources used at present are being investigated in order to optimise current densities of H7D' for future fusion machines. In this thesis low pressure radio frequency (RF) hydrogen plasmas are investigated and compared to filament driven hydrogen plasmas to understand further the physics in the two different modes, and to investigate the proposal of the utilisation of an RF volume ion source in he application of neutral beam injection (NBI) systems for the proposed nuclear fusion reactors of the future. Tuned Langmuir probes are used as a diagnostic method to measure different plasma parameters as a function of pressure and power. The spatial variations of these parameters are examined within the bulk plasma, and the effect of an applied magnetic field investigated. The temporal filter concept is examined with a view to enhancing negative ion generation in the afterglow of an RF temporally modulated discharge. It is proposed that by modulating the RF discharge, the dominant destructive mechanism, collisional detachment (CD), will become negligible and the dominant production mechanism, dissociative attachment (DA), will be optimised, hence allowing optimum production of negative ions in the volume ion source. A laser photodetachment technique was used to determine negative ion densities in temporally resolved filament generated and radio frequency powered hydrogen plasmas, and experimental data compared to theoretically modelled results. In an effort to enhance negative ion production, the addition of argon to the hydrogen discharge was examined. All plasma parameters were investigated and an increase in negative ion density observed. A model of the reaction rates for production and destruction in the discharge lead to a possible explanation for the increase detected. Langmuir probe measurements and laser photodetachment results are presented which show that the enhanced production of H' density which is achieved with a temporally modulated filament driven discharge is also achievable in a temporally modulated radio frequency hydrogen plasma

Automation by PC interface of a multicusp volume ion source, Denise

DENISE is an acronym for Deuterium Negative Ion Source Experiment and originated in FOM the Institute for Atomic and Molecular Physics in DCU where it is being recommissioned as a test bed for the production and extraction of negative hydrogen ion for use in proposed nuclear fusion reactors. These reactors require the neutralisation of particle beams of up to hundreds of amps and energies of about IMeV for use in Neutral Beam Injection (N.B.I.). The objective of this project was to automate the multicusp volume ion source called DENISE. Automation is the technology concerned with the application of mechanical, electronic, and computer-based systems in the operation and control of production. This process of technological development lends real-time monitoring and quick error detection and correction to parameters and components that need to be controlled. Another feature is the ease of use and the attraction of the safety features that are inherent in this technology. The parameters and components that are to be controlled are decided upon and the methods in which this is to be achieved discussed. The control system consists of a software/hardware interface to the pressure system, the cooling system and the pumping system. The Windows software monitors and displays the status of the physical system. An optoisolated electronic interface circuit allows control of the physical processes

Research, Design, and Development Needed to Realise a Neutral Beam Injection System for a Fusion Reactor

The ion temperature in the plasma in a fusion reactor must be sufficiently high that the fusion reaction (probably between D+ and T+) will need to be high to ensure that the reaction rate is as high as is required. The plasma will be heated by the energetic alpha particle created in the fusion reaction, but it is widely accepted that additional (externally supplied) heating will also be required to ensure a sustained “burn” and, perhaps, to control the reaction rate. A reactor based on the tokamak confinement system requires a toroidal current to flow in the plasma. Most of that current will be created by the “bootstrap” effect, but an external method of driving current in the poloidal centre of the plasma is needed as the bootstrap current will be low, or zero in that region. Neutral beam injection is an efficient heating mechanism and it has the current drive efficiency required in a reactor. In this chapter the R&D required for an NBI system for a reactor, is considered against the background of the ITER NBI system design as the ITER beam energy and operating environment are reactor relevant. In addition the elements requiring most development are identified

Validation of a screening instrument for autism spectrum disorders among primary school children in Ireland

Objectives The European Autism Information Systems Project (Posada & Ramirez, 2008) highlighted the lack of systematic and reliable data on the prevalence of autism spectrum disorders in Europe. The EAIS project designed a protocol for the study of ASD prevalence at European level to facilitate a common format for screening and diagnosing children across the EU. This is the first study to operationalise the screening phase of the protocol and validate the use of a screening instrument the Social Communication Questionnaire (SCQ: Rutter et al., 2003) as a primary screener for ASDs among national school children. Methods A study booklet completed by the parents of eligible children aged 6-11 years was returned to the teacher for collection by the study team. There were (n = 7,951) primary school children screened males 54% (n =4,268) females 46% (n = 3,683), special education school children (n = 189) males 66% (n = 125) females 34% (n = 64), in three regions: Galway, Waterford and Cork. Participation rates for parents of eligible children were 69% (n=5,457) for national schools, 36% (n=69) for special education schools. Results The distribution of SCQ total scores for the national school sample were strongly skewed towards lower scores 4.65 ± 4.75, range 0-36. The majority of children (92%) scored in the normal range (0 to11) (n = 5002), moderate (12-14) (n = 225) 4%, high (>15) score range 4% (n = 230). An optimal cut off score (>13) differentiated ASD from other diagnosis sensitivity 0.90, specificity 0.81, positive predictive value 0.43, and negative predictive value 0.98. Test re test reliability mean interval: 15 months, Pearson’s r of 0.77, df = 499, p < 0.001. Conclusions The feasibility of screening children for ASDs with the EAIS protocol, using the SCQ in a non-clinical setting of Irish primary and special schools was demonstrated

Transforming Health through Big Data: Challenges and Considerations

Modern healthcare is increasingly dependent on good data, and effective information systems, for care delivery, and to develop and evaluate health policy. The context of big data differs in significant ways from traditional types of health data, while the use of big data for epidemiology and public health is becoming more common, the use of these tools for health service planning and health policy making lags behind. A large EU funded project (titled MIDAS) that focuses on merging, analysing and visualising data from heterogeneous sources to support health policy makers work in using and accessing health data across EU countries is underway. This paper briefly describes the key challenges that must be met to access, use and make sense of this big data in healthcare, focusing on legal, governance and ethical issues. Unless these issues are dealt with, the promise of Big Data for health, will never be fulfilled

Impact Evaluation of an Emerging European Health Project – the MIDAS Model

Background: This paper describes the impact evaluation of a large big data platform initiative that is being undertaken in order to increase the probability of its success. The initiative, MIDAS (Meaningful Integration of Data Analytics and Services), is a European health-based Horizon 2020 project comprising a consortium of members from various universities, research institutions, and government agencies. Objectives: The purpose of the paper is to present a pioneering platform that will support healthcare policymakers in their decision-making by enabling greater and more efficient use of their data. The goal is to present and evaluate the results of the MIDAS project across four countries. Methods/Approach: The literature is replete with examples of worthwhile technology projects that have failed due to user resistance. In order to avoid such failure, and ensure the success of the final MIDAS platform, a detailed impact evaluation is being undertaken at timed periods of development. Results: This paper describes the impact evaluation process, outlining the use of Q-methodology and the development of a 36-item concourse using the HTMLQ system for that purpose. Conclusions: This research contributes to the overall understanding of how impact evaluation can be undertaken at timed periods during the development of an innovative technology for organisational purposes

Evaluating Impact of an Emerging Big Health Data Platform: A Logic Model and Q-Methodology Approach

Despite advances in technology and medical science, modern health-based projects are open to systemic failure due to many factors. These include I.T. developer’s lack of awareness with regard to end-user needs, poor communication amongst all parties concerned and inappropriate or inadequate tests of the emerging system. Other issues may be external (e.g. political and legal) such as sharing of patient data and issues surrounding consent. The goal of this paper is to take a major health-based European model in current development and explore how it addresses the needs of four institutions in four different countries, and how it will meet their respective needs. The evaluation was designed within a Logic Model, and uses the Framework approach, and Q-Methodology to assess both impact and evaluation. Data will be collected through longitudinal semi-structured interviews and Q-scoring with principal stakeholders and developers at each stage of the project. This approach, recurring interviews with the same key players in the project, will help ensure that there is mutual understanding between I.T. developers and end-users of the system. The final system is meant to provide effective health-based decision support systems for policy makers. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Evaluating Impact of an Emerging Big Health Data Platform: A Logic Model and Q-Methodology Approach

Despite advances in technology and medical science, modern health-based projects are open to systemic failure due to many factors. These include I.T. developer’s lack of awareness with regard to end-user needs, poor communication amongst all parties concerned and inappropriate or inadequate tests of the emerging system. Other issues may be external (e.g. political and legal) such as sharing of patient data and issues surrounding consent. The goal of this paper is to take a major health-based European model in current development and explore how it addresses the needs of four institutions in four different countries, and how it will meet their respective needs. The evaluation was designed within a Logic Model, and uses the Framework approach, and Q-Methodology to assess both impact and evaluation. Data will be collected through longitudinal semi-structured interviews and Q-scoring with principal stakeholders and developers at each stage of the project. This approach, recurring interviews with the same key players in the project, will help ensure that there is mutual understanding between I.T. developers and end-users of the system. The final system is meant to provide effective health-based decision support systems for policy makers. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Logic Model Early Stage Evaluation of a European Public Health Data Analytic Framework

The multi-national MIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to facilitate utilisation of a wide range of health and social care data to enable integration of heterogeneous data sources, providing analytics, forecasting tools and bespoke visualisations of actionable epidemiological data. An evaluation framework starting with a logic model and semi-structured interviews using the principles of realist evaluation was developed working with end users and software developers. Parallel case studies were used to address the requirements of stakeholders at critical time points during the project. The objective was to ensure IT systems development is in line with end user requirements. Overall, the early stage interviews findings indicated the logic model is an effective framework for the evaluation of the project

Q-Method Evaluation of a European Health Data Analytic End User Framework

MIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to facilitate the utilisation of a wide range of health and social care data to support better policy making. Our aim is to explore the use of Q-methodology as part of the evaluation of the implementation of the MIDAS project. Q-methodology is used to identify perspectives and viewpoints on a particular topic. In our case, we defined a concourse of statements relevant to project implementation and goals, by working from a logic model previously developed for the evaluation, and structured interviews with project participants. A 36-item concourse was delivered to participants, using the HTMLQ system. Analysis was done in the qmethod package. Participants had a range of professional backgrounds, and a range of roles in the project, including developers, end-users, policy staff, and health professionals. The q-sort is carried out at 14 months into the project, a few months before the intended first release of the software being developed. Sixteen people took part, 6 developers, 5 managers, 2 health professionals and 3 others. Three factors (distinct perspectives) were identified in the data. These were tentatively labelled ‘Technical optimism’, ‘End-user focus’ and ‘End-user optimism’. These loaded well onto individuals, and there were few consensus statements. Analysis of these factors loaded well onto individuals with a significant number of consensus statements identified. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p