Dimensionality reduction in complex models

As a part of the Managing Uncertainty in Complex Models (MUCM) project, research at Aston University will develop methods for dimensionality reduction of the input and/or output spaces of models, as seen within the emulator framework. Towards this end this report describes a framework for generating toy datasets, whose underlying structure is understood, to facilitate early investigations of dimensionality reduction methods and to gain a deeper understanding of the algorithms employed, both in terms of how effective they are for given types of models / situations, and also their speed in applications and how this scales with various factors. The framework, which allows the evaluation of both screening and projection approaches to dimensionality reduction, is described. We also describe the screening and projection methods currently under consideration and present some preliminary results. The aim of this draft of the report is to solicit feedback from the project team on the dataset generation framework, the methods we propose to use, and suggestions for extensions that should be considered.

A pre-post test evaluation of the impact of the PELICAN MDT-TME development programme on the working lives of colorectal cancer team members

Background - The PELICAN Multidisciplinary Team Total Mesorectal Excision (MDT-TME) Development Programme aimed to improve clinical outcomes for rectal cancer by educating colorectal cancer teams in precision surgery and related aspects of multidisciplinary care. The Programme reached almost all colorectal cancer teams across England. We took the opportunity to assess the impact of participating in this novel team-based Development Programme on the working lives of colorectal cancer team members. Methods - The impact of participating in the programme on team members' self-reported job stress, job satisfaction and team performance was assessed in a pre-post course study. 333/568 (59%) team members, from the 75 multidisciplinary teams who attended the final year of the Programme, completed questionnaires pre-course, and 6-8 weeks post-course. Results - Across all team members, the main sources of job satisfaction related to working in multidisciplinary teams; whilst feeling overloaded was the main source of job stress. Surgeons and clinical nurse specialists reported higher levels of job satisfaction than team members who do not provide direct patient care, whilst MDT coordinators reported the lowest levels of job satisfaction and job stress. Both job stress and satisfaction decreased after participating in the Programme for all team members. There was a small improvement in team performance. Conclusions - Participation in the Development Programme had a mixed impact on the working lives of team members in the immediate aftermath of attending. The decrease in team members' job stress may reflect the improved knowledge and skills conferred by the Programme. The decrease in job satisfaction may be the consequence of being unable to apply these skills immediately in clinical practice because of a lack of required infrastructure and/or equipment. In addition, whilst the Programme raised awareness of the challenges of teamworking, a greater focus on tackling these issues may have improved working lives further.

Development and psychometric evaluation of a new team effectiveness scale for all types of community adult mental health teams:a mixed-methods approach

Defining 'effectiveness' in the context of community mental health teams (CMHTs) has become increasingly difficult under the current pattern of provision required in National Health Service mental health services in England. The aim of this study was to establish the characteristics of multi-professional team working effectiveness in adult CMHTs to develop a new measure of CMHT effectiveness. The study was conducted between May and November 2010 and comprised two stages. Stage 1 used a formative evaluative approach based on the Productivity Measurement and Enhancement System to develop the scale with multiple stakeholder groups over a series of qualitative workshops held in various locations across England. Stage 2 analysed responses from a cross-sectional survey of 1500 members in 135 CMHTs from 11 Mental Health Trusts in England to determine the scale's psychometric properties. Based on an analysis of its structural validity and reliability, the resultant 20-item scale demonstrated good psychometric properties and captured one overall latent factor of CMHT effectiveness comprising seven dimensions: improved service user well-being, creative problem-solving, continuous care, inter-team working, respect between professionals, engagement with carers and therapeutic relationships with service users. The scale will be of significant value to CMHTs and healthcare commissioners both nationally and internationally for monitoring, evaluating and improving team functioning in practice.

Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

2000 Mathematics Subject Classification: 62H12, 62P99

High frequency electric machine models for the evaluation of operational impacts in integrated drives

A high frequency physical phase variable electric machine model was developed using FE analysis. The model was implemented in a machine drive environment with hardware-in-the-loop. The novelty of the proposed model is that it is derived based on the actual geometrical and other physical information of the motor, considering each individual turn in the winding. This is the first attempt to develop such a model to obtain high frequency machine parameters without resorting to expensive experimental procedures currently in use. The model was used in a dynamic simulation environment to predict inverter-motor interaction. This includes motor terminal overvoltage, current spikes, as well as switching effects. In addition, a complete drive model was developed for electromagnetic interference (EMI) analysis and evaluation. This consists of the lumped parameter models of different system components, such as cable, inverter, and motor. The lumped parameter models enable faster simulations. The results obtained were verified by experimental measurements and excellent agreements were obtained. A change in the winding arrangement and its influence on the motor high frequency behavior has also been investigated. This was shown to have a little effect on the parameter values and in the motor high frequency behavior for equal number of turns. An accurate prediction of overvoltage and EMI in the design stages of the drive system would reduce the time required for the design modifications as well as for the evaluation of EMC compliance issues. The model can be utilized in the design optimization and insulation selection for motors. Use of this procedure could prove economical, as it would help designers develop and test new motor designs for the evaluation of operational impacts in various motor drive applications.

An evaluation of home range models for marine fish tracking and fine scale habitat use and movement patterns of age 1 Greenland cod (Gadus macrocephalus ogac)

My thesis examines fine-scale habitat use and movement patterns of age 1 Greenland cod (Gadus macrocephalus ogac) tracked using acoustic telemetry. Recent advances in tracking technologies such as GPS and acoustic telemetry have led to increasingly large and detailed datasets that present new opportunities for researchers to address fine-scale ecological questions regarding animal movement and spatial distribution. There is a growing demand for home range models that will not only work with massive quantities of autocorrelated data, but that can also exploit the added detail inherent in these high-resolution datasets. Most published home range studies use radio-telemetry or satellite data from terrestrial mammals or avian species, and most studies that evaluate the relative performance of home range models use simulated data. In Chapter 2, I used actual field-collected data from age-1 Greenland cod tracked with acoustic telemetry to evaluate the accuracy and precision of six home range models: minimum convex polygons, kernel densities with plug-in bandwidth selection and the reference bandwidth, adaptive local convex hulls, Brownian bridges, and dynamic Brownian bridges. I then applied the most appropriate model to two years (2010-2012) of tracking data collected from 82 tagged Greenland cod tracked in Newman Sound, Newfoundland, Canada, to determine diel and seasonal differences in habitat use and movement patterns (Chapter 3). Little is known of juvenile cod ecology, so resolving these relationships will provide valuable insight into activity patterns, habitat use, and predator-prey dynamics, while filling a knowledge gap regarding the use of space by age 1 Greenland cod in a coastal nursery habitat. By doing so, my thesis demonstrates an appropriate technique for modelling the spatial use of fish from acoustic telemetry data that can be applied to high-resolution, high-frequency tracking datasets collected from mobile organisms in any environment.

Midwifery-led antenatal care models: mapping a systematic review to an evidence-based quality framework to identify key components and characteristics of care

Background: Implementing effective antenatal care models is a key global policy goal. However, the mechanisms of action of these multi-faceted models that would allow widespread implementation are seldom examined and poorly understood. In existing care model analyses there is little distinction between what is done, how it is done, and who does it. A new evidence-informed quality maternal and newborn care (QMNC) framework identifies key characteristics of quality care. This offers the opportunity to identify systematically the characteristics of care delivery that may be generalizable across contexts, thereby enhancing implementation. Our objective was to map the characteristics of antenatal care models tested in Randomised Controlled Trials (RCTs) to a new evidence-based framework for quality maternal and newborn care; thus facilitating the identification of characteristics of effective care.

Methods: A systematic review of RCTs of midwifery-led antenatal care models. Mapping and evaluation of these models’ characteristics to the QMNC framework using data extraction and scoring forms derived from the five framework components. Paired team members independently extracted data and conducted quality assessment using the QMNC framework and standard RCT criteria.

Results: From 13,050 citations initially retrieved we identified 17 RCTs of midwifery-led antenatal care models from Australia (7), the UK (4), China (2), and Sweden, Ireland, Mexico and Canada (1 each). QMNC framework scores ranged from 9 to 25 (possible range 0–32), with most models reporting fewer than half the characteristics associated with quality maternity care. Description of care model characteristics was lacking in many studies, but was better reported for the intervention arms. Organisation of care was the best-described component. Underlying values and philosophy of care were poorly reported.

Conclusions: The QMNC framework facilitates assessment of the characteristics of antenatal care models. It is vital to understand all the characteristics of multi-faceted interventions such as care models; not only what is done but why it is done, by whom, and how this differed from the standard care package. By applying the QMNC framework we have established a foundation for future reports of intervention studies so that the characteristics of individual models can be evaluated, and the impact of any differences appraised.

Reliability assessment of a peer evaluation instrument in a team-based learning course

Objective: To evaluate the reliability of a peer evaluation instrument in a longitudinal team-based learning setting. Methods: Student pharmacists were instructed to evaluate the contributions of their peers. Evaluations were analyzed for the variance of the scores by identifying low, medium, and high scores. Agreement between performance ratings within each group of students was assessed via intra-class correlation coefficient (ICC). Results: We found little variation in the standard deviation (SD) based on the score means among the high, medium, and low scores within each group. The lack of variation in SD of results between groups suggests that the peer evaluation instrument produces precise results. The ICC showed strong concordance among raters. Conclusions: Findings suggest that our student peer evaluation instrument provides a reliable method for peer assessment in team-based learning settings.

Introducing a pilot data collection model for real-time evaluation of data redundancy

In order to reduce serious health incidents, individuals with high risks need to be identified as early as possible so that effective intervention and preventive care can be provided. This requires regular and efficient assessments of risk within communities that are the first point of contacts for individuals. Clinical Decision Support Systems CDSSs have been developed to help with the task of risk assessment, however such systems and their underpinning classification models are tailored towards those with clinical expertise. Communities where regular risk assessments are required lack such expertise. This paper presents the continuation of GRiST research team efforts to disseminate clinical expertise to communities. Based on our earlier published findings, this paper introduces the framework and skeleton for a data collection and risk classification model that evaluates data redundancy in real-time, detects the risk-informative data and guides the risk assessors towards collecting those data. By doing so, it enables non-experts within the communities to conduct reliable Mental Health risk triage.

Deep learning models for the automatic analysis of volleyball plays

Collecting and analysing data is an important element in any field of human activity and research. Even in sports, collecting and analyzing statistical data is attracting a growing interest. Some exemplar use cases are: improvement of technical/tactical aspects for team coaches, definition of game strategies based on the opposite team play or evaluation of the performance of players. Other advantages are related to taking more precise and impartial judgment in referee decisions: a wrong decision can change the outcomes of important matches. Finally, it can be useful to provide better representations and graphic effects that make the game more engaging for the audience during the match. Nowadays it is possible to delegate this type of task to automatic software systems that can use cameras or even hardware sensors to collect images or data and process them. One of the most efficient methods to collect data is to process the video images of the sporting event through mixed techniques concerning machine learning applied to computer vision. As in other domains in which computer vision can be applied, the main tasks in sports are related to object detection, player tracking, and to the pose estimation of athletes. The goal of the present thesis is to apply different models of CNNs to analyze volleyball matches. Starting from video frames of a volleyball match, we reproduce a bird's eye view of the playing court where all the players are projected, reporting also for each player the type of action she/he is performing.

Development of a porcine lactation model for the evaluation of mammary transfer of exogenous molecules - A contribution from the conception project

Around 5 million women give birth each year in Europe and, while breastfeeding, the majority of them may need to take medications, either occasionally or continuously. Unfortunately, there is often scarce evidence of trustworthy information about how a specific molecule might affect the physiology of lactation. This is the reason that brought a European public-private partnership to fund the development of a reliable platform to provide women and health-care professionals a helpful instrument to reduce uncertainty about the effects of medication used during breastfeeding. On April 1st 2019, the ConcePTION project (Grant Agreement n°821520) started to develop such envisaged platform. The 3rd Work Package was in charge of the validation of in vitro, in vivo and in silico lactation models. Between the numerous species currently used in preclinical studies, pigs’ similarities with humans’ anatomy, physiology and genomics make them extremely useful as translational models, when proper veterinary expertise is applied. The ASA team from the University of Bologna, went first to characterize the translational lactation model using the swine species, chosen upon literature review. The aim of this work was to lay the foundations of a porcine lactation model that could be suitable for application within pharmaceutical tests, to study drug transfer through milk prior approval and commercialization. The obtained results highlighted both strengths and critical points of the study design, allowing a significant improvement in the knowledge of pharmacokinetic physiology in lactating mammals. Lastly, this project allowed the assessment of microbial changes in gut resident bacteria of newborns through an innovative in vitro colonic model. Indeed, even if there were no evident adverse effects determined by drug residues in milk, possible alterations in the delicate microbial ecology of newborns’ gastrointestinal tract was considered pivotal, giving its possible impact on the individual health and growth.