Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing.

BACKGROUND: Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. RESULTS: Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. CONCLUSIONS: By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies

Micropower Generation using Buckling Piezoelectric Elements

In recent years, piezoelectric materials and structures have gained significant attention for energy harvesting purposes. This attention can be attributed to the enhancement of low-power electronics and the high energy density of piezoelectric materials compared to other forms of energy conversion and transduction. This work explores the recent contributions to the field of piezoelectric energy harvesting, contributing two novel methods that can be implemented to improve the power output and efficiency of a single piezoelectric element. The methods that have been investigated in this thesis are based on the buckling of piezoelectric material. The initial method examines a diaphragm preformed piezoelectric element, where numerical and simulation model has been carried out. This work has then been validated through experimentation, where empirical data has been collected verifying the COMSOL model and future optimising the manufacturing process of the diaphragm. This work contributes to a peer-reviewed paper “Powering lights with Piezoelectric energy-harvesting floors” published in the journal Energy Technology. This work shows that employed a diaphragm structure can increase both efficiency and power output with an increase of efficiency from 0.522% to 3.765%. The observed power output increase from 191.686µJ to 644.16µJ. The second method investigates a preloaded piezoelectric curved structure with elastic walls. The use of nonlinear materials is critical to the development of a buckling structure, allowing energy to be stored upon actuation while reducing input stresses. The result of this is a reduced buckling force, with an increased energy output and efficiency for the whole system. The findings of this work demonstrate that efficiency can be increase from 0.522% to 16.813% while achieving a greater power output from 191.686µJ to 208.577µJ. Furthermore, this work identifies that a monostable structure as opposed to a bi or multi-stable structure can significantly produce higher power outputs than conventional methods, whilst achieving long life within a small compact area. A COMSOL simulation of the mechanical behaviour coupled with the constitutive equations has been developed to enable future optimises to structure and design and validated using the empirical data. In additional, two equations have been developed using empirical data to aid in selection of buckling force and power output for an energy harvester. This is to enable developers of low-power electronics to select the optimised system for their application reducing the need for primary batteries within electrical devices

Editorial

20th International Conference on Evaluation and Assessment in Software Engineering, EASE 2016; University of Limerick, Limerick; Ireland; 1 - 3 June 201