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Ongoing Research Projects supported by Research IT

Listing of project codes and abstracts, describing work undertaken which use the resources of the compute clusters hosted by the Research IT team.

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Project Title Cortical surface reconstruction from MR data in The Irish Longitudinal Study on Ageing (TILDA)
Project Code HPC_17_00969
Principal Investigator Prof Rose Kenny
Start Date 2017-05-29
End Date 2018-05-28
Abstract Cortical surface reconstruction from MR data in The Irish Longitudinal Study on Ageing (TILDA): investigating cortical structure in older Irish adults. The human cortex displays remarkable profiles of change across the lifespan, both in health and disease. A unique challenge for research is to map brain structure changes with age onto the broader physical, cognitive, social, and economic factors that may be critical to healthy, successful ageing. The Irish Longitudinal Study on Ageing (TILDA) is the largest single-cohort study of older adults in Ireland, comprising a nationally representative sample of adults aged 50+. The goal of the current project is to explore cortical change in Irish adults aged 50+, by charting relationships between cortical structure and physical and cognitive health, alongside socio-demographic and economic factors. With the assistance of TCD TCHPC architectures, T1-w MR scans collected for a subset of TILDA participants allow the cortical surface (and a range of subcortical structures) to be reconstructed with FreeSurfer software. These reconstructed cortical surfaces enable investigations of cortical thickness, area, and curvature, as they relate to age, and to the detailed physical health assays available for TILDA participants (including cardiac, optical, orthopaedic, and ambulatory health). Moreover, such cortical metrics afford the opportunity to explore relationships between brain structure and the cognitive, social, environmental, and economic circumstances of older Irish adults. This project will provide a detailed exploration of the multi-faceted changes in brain structure with age, as they relate to factors that characterise growing older in Ireland.
Project Title Theoretical study on porphyrin/ guanidine conjugates as potential binders of Guanine-Quadruplexes
Project Code HPC_17_00968
Principal Investigator Prof Isabel Rozas
Start Date 2017-04-11
End Date 2018-05-31
Abstract Prof. Rozas’s group has been working in the design, synthesis and biological study of guanidinium derivatives as DNA minor groove binders during the last 15 years and these finding reveals very promising derivatives with activity as cell growth inhibitors.1-3 Continuing with our interest in the interactions established between guanidinium derivatives and Nucleic Acid structures, we have designed novel N-substituted porphyrins linked to DNA-binding small molecules such as guanidine-like systems to yield new dual-modality portmanteau binders to achieve selective GQ stabilization and enhanced detection. Porphyrins are an important class of compounds that has gained significant recognition as DNA binding agents. In particular, 5,10,15,20-tetrakis(N-methylpyridyl)porphyrins were found to bind to GQs through π–π-stacking but suffer from poor selectivity towards GQs.4,5 In context of interesting GQ binding properties of porphyrins and our onging work in the area of guanidines as DNA-minor groove binding agents, we propose now to study the conformation of a number of porphyrin/guanidine derivative conjugates and their potential interaction with known guanine quadruplexes structures, already reported in the RCSB PDB.6,7 This study will allow us to better understand the orientation of our compounds in the domain of GQ and important binding interactions with GQ. Moreover, the study also helps us to design new GQ-ligands in order to improve the GQ binding activity and selectivity over dsDNA.
Project Title Light field image processing
Project Code HPC_17_00967
Principal Investigator Prof Aljosa Smolic
Start Date 2017-04-10
End Date 2017-11-30
Abstract Light field imaging has been recently gaining a lot of attention in the image processing community, and as such a particular topic of interest in the V-SENSE project, lead by Prof. Aljosa Smolic. A light field captures light rays coming from different angles, and can be represented by a collection of 2D images arranged on a 2D grid, hence forming 4D visual data. Applications include post-capture refocusing, depth estimation, virtual viewpoint rendering, de-noising, super-resolution. Due to their very nature, processing light fields can require large memory amounts and high computational power. In this project we aim to investigate and evaluate novel methods for light field enhancement, including de-noising and super-resolution, as well as depth estimation.
Project Title Frustrating Chemistry – Towards a Quantitative Model for Lewis Pair Association and Reactivity
Project Code HPC_17_00966
Principal Investigator Dr Carl Poree
Start Date 2017-04-10
End Date 2018-12-24
Abstract The formation of covalently-bound adducts between Lewis acids and Lewis bases has long been known – the archetype (ammonia borane, NH3∙BH3) was first prepared in the 1920s,[1] and its structure established in 1955.[2] These adducts are generally relatively unreactive, in marked contrast to their components. However, in recent years, the existence of so-called frustrated Lewis pairs (FLPs) – in which adduct formation does not occur – has been noted. This would arguably be of only marginal interest, if it were not for the remarkable ability of FLPs to activate relatively inert molecules such as hydrogen (H2) and carbon dioxide (CO2).[3] Previously, such modes of reactivity were available only to (often expensive) transition metal-based catalysts. Despite this considerable and growing interest in the field, a key, fundamental deficiency remains. The definition of a Lewis pair as ‘frustrated’ is primarily based on structure, and the inability of a given pair of Lewis acids and bases to form an adduct is generally considered to be due to the steric bulk of one or both partners. However, neither clear structural criteria nor guiding principles for the design of FLPs have emerged to date. Given the challenges inherent in handling the components required to form an FLP – they are often air- and moisture-sensitive – the design of more robust catalysts is of considerable interest. The prevailing mechanistic paradigm for H2 activation by FLPs is formally termolecular (i.e. requiring the encounter of three molecules in the rate-determining transition state), which is statistically highly improbable, absent the formation of a presumably weakly-bound bimolecular acid-base encounter complex. Computational studies to date have been predicated on the formation of such an encounter complex, but have not addressed the general questions of structure relevant to the formation of such species. Limited spectroscopic evidence for weak Lewis acid – Lewis base interactions in solution has also been reported, but is limited to two FLP systems (either tBu3P or Mes3P with B(C6F5)3).[4] The aim of the proposed work is to develop a model for the formation of traditional Lewis adducts or FLPs from pairwise combinations of phosphines and boranes, and to evaluate their abilities to activate small molecules (in the first instance, H2). This will involve quantum chemical calculations (predominantly employing density functional theory methods) in combination with statistical analysis with the overriding aim of determining key structure-activity relationships, allowing for the informed design of improved catalysts. In the longer term, experimental validation of the predictions generated by this study is envisaged. [1] A. Stock, E. Pohland, Ber. Dtsch. Chem. Ges. A/B 1925, 58, 657-661. [2] S. G. Shore, R. W. Parry, J. Am. Chem. Soc. 1955, 77, 6084-6085. [3] D. Stephan, G. Erker, Angew. Chem. Int. Ed. 2015, 54, 6400-6441 and references therein. [4] L. Rocchigiani, G. Ciancaleoni, C. Zuccaccia, A. Macchioni, J. Am. Chem. Soc. 2014, 136, 112-115.
Project Title Reproducible prediction for large imaging data
Project Code HPC_17_00965
Principal Investigator Dr Robert Whelan
Start Date 2017-03-06
End Date 2018-03-05
Abstract Overestimation of effect sizes and lack of reproducibility is a problem endemic to all medical and psychological research (Ioannidis, 2005a/b, 2008; Open Science Collaboration, 2015; Ware & Munafo, 2014), and has become increasingly addressed in the field of neuroimaging in recent years (see Pernet & Poline, 2015; Poldrack & Poline, 2015; Ioannidis et al., 2014). With the move toward Big Data in neuroscience the field has taken an important step towards addressing this reproducibility crisis. However, the availability of large imaging datasets also calls for the use of truly robust analysis methods (see also Fritsch et al., 2015). In order for neuroimaging research to advance clinical practice and scientific inquiry it is therefore necessary to adopt truth-supporting analysis approaches developed for data science (Iniesta, Stahl, & McGuffin, 2016; Yarkoni & Westfall, n.p.; Jollans & Whelan, 2016). Machine Learning algorithms such as Support Vector Machines, Random Forests, or Naïve Bayes classifiers have become standard tools for regression and classification analyses in the neuroimaging community. However, the majority of these tools were not developed with imaging data in mind, and neither the ability of these methods to deal with the inherent small effect sizes and multicollinearity of imaging data, nor how data dimensionality affects performance of these algorithms has been established in the neuroimaging literature. In this project we intend to empirically evaluated the efficacy of some of these approaches for 2nd level between-subject regression analysis with high-dimensional neuroimaging data, and how sample size and number of input variables (i.e. features) interact with elements of machine learning protocols.
Project Title Omnidirectional video coding
Project Code HPC_17_00964
Principal Investigator Prof Aljosa Smolic
Start Date 2017-03-03
End Date 2018-05-11
Abstract 360-degree video is attracting an increasing amount of attention in the context of Virtual Reality (VR). Owing to its very high-resolution requirements, existing professional streaming services for 360-degree video suffer from severe drawbacks. This research introduces a novel method to encode 8K resolution 360-degree video and provide an enhanced VR experience using Head Mounted Displays (HMDs).
Project Title Service execution monitoring and prediction in dynamic IoT environments
Project Code HPC_17_00963
Principal Investigator Professor Siobhan Clarke
Start Date 2017-02-27
End Date 2019-08-27
Abstract IoT (Internet of Things) applications, are typically built from services provided by heterogeneous devices, which are potentially resource constrained and/or mobile. With the increase in popularity of these services, effective evaluation of user-side quality of service (QoS) becomes a critical research problem. To address this challenge we conduct an evaluation of existing QoS prediction approaches, which use adaptive matrix factorisation (AMF). These approaches derive from the collaborative filtering model used in recommender systems, which avoids the problems of many other QoS prediction approaches of requiring additional invoking of available IoT components on behalf of the user. We conduct comprehensive experiments based on a real-world large-scale QoS dataset as well as a transformation of this dataset to more closely estimate IoT services to show how these approaches differ when applied to a different dataset.
Project Title Mechanical, thermal and acoustic characterization of historical earthen structures.
Project Code HPC_17_00962
Principal Investigator Dr Dermot O'Dwyer
Start Date 2017-02-24
End Date 2020-02-24
Abstract The aim of this research is to study the mechanical, thermal and acoustic properties of historical earthen structures such as: cob, adobe, rammed earth, etc., as well as their environmental and economical implications. By correlating the results of the numerical simulations, performed in ANSYS, with those obtained by experimental procedures, performed at the Lab of Civil Engineering, an optimization of the thickness of a structural wall will be studied. Parallel to this, the dynamic behavior of traditional structures will be studied under seismic actions in order to study the efficiency of various retrofitting techniques and determine which ones are more efficient under certain influence parameters.
Project Title Diffusion in YSZ Surface Slabs
Project Code HPC_17_00961
Principal Investigator Prof Graeme Watson
Start Date 2017-02-27
End Date 2018-02-26
Abstract The study of ionic diffusion is important for the efficient construction of many devices, such as solid oxide fuel cells, oxygen sensors and lithium-ion batteries. While diffusion within bulk systems has been widely investigated, the impact of specific interfaces existing within the bulk, has been largely ignored, despite its critical impact on performance. The diffusion of O2- ions within specific yttria-stabilised zirconia (YSZ) surface slabs (the (100), (110), (111), (210), (221) and (310) ) will be investigated in order to determine whether the surface effects have a beneficial or detrimental effect on ionic conductivity, and to what extent.
Project Title Cortical surface reconstruction from MR data in The Irish Longitudinal Study on Ageing (TILDA)
Project Code HPC_17_00960
Principal Investigator Prof Rose Kenny
Start Date 2017-03-20
End Date 2018-03-19
Abstract Cortical surface reconstruction from MR data in The Irish Longitudinal Study on Ageing (TILDA): investigating cortical structure in older Irish adults. The human cortex displays remarkable profiles of change across the lifespan, both in health and disease. A unique challenge for research is to map brain structure changes with age onto the broader physical, cognitive, social, and economic factors that may be critical to healthy, successful ageing. The Irish Longitudinal Study on Ageing (TILDA) is the largest single-cohort study of older adults in Ireland, comprising a nationally representative sample of adults aged 50+. The goal of the current project is to explore cortical change in Irish adults aged 50+, by charting relationships between cortical structure and physical and cognitive health, alongside socio-demographic and economic factors. With the assistance of TCD TCHPC architectures, T1-w MR scans collected for a subset of TILDA participants allow the cortical surface (and a range of subcortical structures) to be reconstructed with FreeSurfer software. These reconstructed cortical surfaces enable investigations of cortical thickness, area, and curvature, as they relate to age, and to the detailed physical health assays available for TILDA participants (including cardiac, optical, orthopaedic, and ambulatory health). Moreover, such cortical metrics afford the opportunity to explore relationships between brain structure and the cognitive, social, environmental, and economic circumstances of older Irish adults. This project will provide a detailed exploration of the multi-faceted changes in brain structure with age, as they relate to factors that characterise growing older in Ireland.