College of Science, Engineering and Food Science - Masters by Research Theseshttps://hdl.handle.net/10468/98592024-03-29T14:31:54Z2024-03-29T14:31:54Z1051A case-study in the introduction of a digital-twin in a large-scale manufacturing facilityO'Sullivan, Jamiehttps://hdl.handle.net/10468/118672023-04-04T10:42:10Z2020-11-02T00:00:00Zdc.title: A case-study in the introduction of a digital-twin in a large-scale manufacturing facility
dc.contributor.author: O'Sullivan, Jamie
dc.description.abstract: The exponential increase in data produced in recent times has had a profound impact in all areas of society. In the field of industrial engineering, the knowledge produced by this newly obtained data is driving business forward. Automating the process of capturing data from industrial machines, analyzing it and using the knowledge gained to make better decisions for the machines is the crux of the digital twin.
Digital twins uncover a wealth of knowledge about the physical asset they duplicate. Sensor technology, Internet of Things platforms, information and communication technology and smart analytics allow the digital twin to transform a physical asset into a connected smart item that is now part of a cyber physical system and that is far more valuable than when it existed in isolation.
The digital twin can be adopted by the maintenance engineering industry to aid in the prediction of issues before they occur thus creating value for the business. This thesis discusses the introduction of a maintenance digital twin to a large-scale manufacturing facility. Issues that hamper such work are discovered and categorized to highlight the difficulty of the practical installation of this concept. The work here highlights the difficulties when working on digital systems in manufacturing facilities and how this isn’t discussed in journal articles and the disconnect between academia and industry on this topic.
To aid in the installation, a digital twin framework is created that simplifies the digital twin development process into steps that can be completed independently. Work on implementing this framework is commenced and early successes highlight the benefit of sensoring critical assets. The payback of the initial practical work is immediate, and it presents a promising outlook for the iterative development of a maintenance digital twin using the framework. The thesis’ work highlights the benefit in reducing project scale and complexity and hence risk for digital systems in manufacturing facilities by following the
framework developed. The later part of the thesis discusses machine learning and how this AI topic can be integrated into the digital twin to allow the digital asset to fulfill its potential.
2020-11-02T00:00:00ZA close knit complex network: statistical examination of board interlocks and their impact on financial resultsDave, Kirtivardhan Parantaphttps://hdl.handle.net/10468/119682023-04-04T10:54:20Z2021-01-01T00:00:00Zdc.title: A close knit complex network: statistical examination of board interlocks and their impact on financial results
dc.contributor.author: Dave, Kirtivardhan Parantap
dc.description.abstract: Board of directors are at the pinnacle of the corporate world, in any company they form the highest decision making authority. A position on the board of a company is one of immense privilege and power. Thus, making any individual who occupies such a position privy to information about the company which most people would not have. Even the shareholders who are the owners of the company are not privy to this information. In this study I look at complex networks formed by board interlocks in the United Kingdom. When one director sits on the board of two companies, it creates a board interlock, where he acts as a link between the two companies. The main aim of the study is to look at the relationship between the features of these networks and their impact on the financial results of public limited companies in the United Kingdom. The first part of this study looks at these corporate networks and how they have evolved over the past three decades. Using varied network analysis features, the board interlock network was studied from two different perspectives. First, as a dual mode network or a people to company network. In this kind of network edges are formed between a board member and the company on whose board she sits. Second, as a single mode network where common board members between two companies form an edge between those companies. We find that the corporate network has become denser over the years, exhibiting small world properties. Companies that did not share board members with any other company have nearly halved over the course of the three decades. There have been quite a few studies that have looked at the impact of network features on financial results from various academic perspectives be it financial, sociological, management, and more recently network analysis. I have used four different centrality measures and proposed a ranking based model. Which unlike any other existing study also goes deeper by incorporating different community sizes into the regression model. This allowed me to check whether network features of better connected companies or companies that are a part of larger communities are stronger predictors of financial performance. This study shows an upward trend with the regression fit improving over time.
2021-01-01T00:00:00ZA comparison of the use of whole milk and fat-filled milk powders for production of heat-stable long-life beveragesCrotty, Aislinghttps://hdl.handle.net/10468/104972023-04-04T11:00:54Z2020-04-01T00:00:00Zdc.title: A comparison of the use of whole milk and fat-filled milk powders for production of heat-stable long-life beverages
dc.contributor.author: Crotty, Aisling
dc.description.abstract: Commercial bovine milk is 3.5% fat, the level of which is affected by seasonality, stage of lactation, feed, health, breed, and even the individual teat. Milk (and other liquid dairy products) are highly perishable due to their nutritional quality, as they are the sole source of nutrition for the neonate. As a result, milk is often dehydrated into powder form, which enhances its shelf life, its storage stability, and the convenience. Another way to enhance the shelf life of milk is to subject it to heat to destroy pathogenic bacteria, enzymes, spores, and to enhance the shelf life of the product. As most dairy products are subjected to some form of heat treatment, their heat stability is integral to the overall quality of the product. In Chapter 2, two reconstituted dairy powders (fat-filled milk powder (FFMP) and whole milk powder (WMP)) were compared under two heat treatments (UHT-processing and retort sterilisation), and three protein contents (2.3, 3.3, and 5%). These variables significantly affected the apparent viscosity, the pH, the colour, the emulsion stability, and the average particle size of the samples. Chapter 3 investigated the influence of calcium-chelating salts on heat stability. These salts are an often-used ingredient in dairy products, as they enhance the heat stability of the system by binding the calcium ions, which are important for casein micelle integrity. The influence of trisodium citrate (TSC), disodium hydrogen phosphate (DSHP), and sodium hexametaphosphate (SHMP) on heat stability, colour, and apparent viscosity was examined. SHMP had the most significant effect on heat stability, colour, and apparent viscosity due to its chelating capacity and its influence on cross-linking between the casein micelles. DSHP had no significant effect on viscosity or colour, whereas the addition of 20 mmol/L of TSC significantly affected the colour of the solution.
2020-04-01T00:00:00ZA drifter-based self-powered piezoelectric sensor for ocean wave measurementsKargar, Seyyed Masoudhttps://hdl.handle.net/10468/136882023-04-04T10:47:08Z2022-07-01T00:00:00Zdc.title: A drifter-based self-powered piezoelectric sensor for ocean wave measurements
dc.contributor.author: Kargar, Seyyed Masoud
dc.description.abstract: In the present research, a drifter-based piezoelectric sensor is proposed to measure ocean waves’ height and period. To analyze the motion principle and the working performance of the proposed drifter-based piezoelectric sensor, a dynamic model is developed. The developed dynamic model investigates the system’s response to an input of ocean waves and provides design insights into the geometrical and material parameters. Next, finite element analysis (FEA) simulations using the commercial software COMSOL-Multiphysics have been carried out with the help of a coupled physics analysis of Solid Mechanics and Electrostatics Modules to achieve the output voltages. An experimental prototype has been fabricated and tested to validate the results of the dynamic model and the FEA simulation. A slider-crank mechanism is used to mimic ocean waves throughout the experiment, and the results show a close match between the proposed dynamic modeling, FEA simulations, and experimental testing. In the end, a short discussion is devoted to interpreting the output results; comparing the results of the simulations and the experimental testing; the sensor’s resolution; and the self-powering functionality of the proposed drifter-based piezoelectric sensor.
2022-07-01T00:00:00ZA matter of time: assessing the biological functions of oscillating natural antisense
long non-coding RNA transcriptsvan Veen, Elizabethhttps://hdl.handle.net/10468/132202023-04-04T10:44:34Z2021-12-01T00:00:00Zdc.title: A matter of time: assessing the biological functions of oscillating natural antisense
long non-coding RNA transcripts
dc.contributor.author: van Veen, Elizabeth
dc.description.abstract: Circadian rhythms allow organisms to coordinate their metabolic and physiological responsesin accordance with Earth’s predictable daily, and yearly fluctuations in environmentalconditions. The roles of oscillating protein-coding transcripts have been well studied in theplant circadian clock, however recent research has identified that the transcription of long nonprotein coding RNAs can also oscillate in a diurnal manner. Here we document two circadianregulated lncRNAs that are natural antisense transcripts of two CDFs in the model plantArabidopsis thaliana.
The first lncRNA “FLORE” forms a natural antisense transcript pair with CDF5, and these
transcripts were shown to display antiphasic expression, reflecting a mutual inhibitory
relationship. By resorting to ChIRP-seq, a multitude of putative FLORE genomic targets were identified, and through the implementation of molecular and bioinformatics techniques, four genes of interested were selected. Three of these genes; CCL, XPB1, and SR45A, exhibited upregulated transcription in a FLORE over-expressor under LD conditions. The fourth gene, RH27, displayed altered expression patterns between biological replicates. Finally, SR45A and RH27 were shortlisted for in-depth analysis. Histochemical GUS staining revealed that RH27 is transcriptionally active in newly developing tissues, as well as root tips and reproductivetissues. Finally, we found that a depletion in a gene related to SR45A (SR45) was associatedwith marginal changes in FLORE alternative splicing patterns.
The second lncRNA “lncCDF1” is a natural antisense transcript of CDF1. Recent data have
identified the CDFs as regulators of abiotic stress responses, and previous unpublished
experiments have shown both CDF1 and lncCDF1 to be induced by drought. Here, we
recorded a decrease in ABA sensitivity during seed germination, in a lnccdf1 promoter TDNA insertion mutant. Additionally lncCDF1 promoter activity appeared to be induced by ABA in two day old seedlings. Contrastingly, modulation of lncCDF1 transcript levels was not associated with altered ABA-mediated responses in older seedlings. Finally, we observed that CDF1 transcription is reduced in response to lncCDF1 over-expression, suggesting lncCDF1 may act in cis to repress lncCDF1. Taken together, these findings highlight the diverse regulatory functions carried out by lncRNAs in plants, and our findings provide a basis for further study on these transcripts.
2021-12-01T00:00:00ZA methodology and trial implementation for digitising information on a factory floorDuffy, Anniehttps://hdl.handle.net/10468/100812023-04-04T10:44:53Z2019-10-04T00:00:00Zdc.title: A methodology and trial implementation for digitising information on a factory floor
dc.contributor.author: Duffy, Annie
dc.description.abstract: In recent years manufacturing industries have moved towards Smart Manufacturing, to achieve improved efficiency and production targets. Part of this innovation of current processes includes digitisation and improving access to machine information, usually through the introduction of new technology to assist with this transition. In order to maintain smooth processes and uninterrupted production, various information sources must be available on the factory floor. This project aims to provide a proof of concept for digitisation and access to necessary information during Pulse Walks. The methodology used to develop this tool is discussed. Observations during Pulse Walks were used to highlight the areas that this could be applied to, and a survey was used to determine the most useful information sources to include. Another aspect of this project is to introduce a method of digitally storing issues discussed during the Pulse Walk, to highlight recurring issues and problematic areas. This was developed to be used as part of the tool during Pulse Walks. This research will present a proof of concept for an app that will act as a digital information hub for accessing information and logging issues from the Pulse Walks. The use cases for this tool have been deliberated and the benefits clearly identified. This tool can assist with tracking recurring issues, using previously logged issues to create a historical database. The issue logging dashboard can be used for investigating reasons for machine downtime. This tool aims to improve production efficiency for a manufacturing line in a factory through issue tracking.
2019-10-04T00:00:00ZA microbiota-targeted strategy to attenuate antipsychotic-induced weight gainLipuma, Timothyhttps://hdl.handle.net/10468/150092023-09-21T02:04:37Z2023-01-01T00:00:00Zdc.title: A microbiota-targeted strategy to attenuate antipsychotic-induced weight gain
dc.contributor.author: Lipuma, Timothy
dc.description.abstract: Background: Atypical antipsychotics such as olanzapine are an essential treatment for psychotic-spectrum disorders, but their use is associated with significant weight gain and increased cardiometabolic disease risk. Attenuating these side effects could improve the tolerability and adherence to antipsychotic medications. Evidence suggests that the microbiome plays a role in antipsychotic-induced weight gain, thus targeting the microbiome may be a viable therapeutic strategy to attenuate the side effect profile of antipsychotics like olanzapine. Furthermore, metabolomics approaches are being increasingly employed to elucidate disease pathophysiology and potential therapeutic targets, but these strategies have not yet been applied to the problem of antipsychotic-induced obesity and hyperphagia.
Aims: The primary aims of this study are to (1) investigate if combined microbiome-targeted treatments (probiotic [APC1472], prebiotic [xanthohumol], and their combination) with olanzapine attenuate antipsychotic-induced obesity, metabolic dysfunction, and hyperphagia in female Sprague-Dawley rats, and (2) analyse blood plasma using discovery metabolomics to generate potential mechanistic and therapeutic targets related to the side effects of olanzapine.
Methods: Animals were treated with olanzapine (2 mg/kg body weight) alone (n=12), olanzapine with probiotic (n=11), olanzapine with prebiotic (n=11), olanzapine with probiotic and prebiotic (n=12) or control vehicle (n=12) twice a day via intraperitoneal injection for 31 days. Changes in body weight, adiposity, glucose metabolism, dietary intake, anxiety-like behaviour, plasma biomarkers (corticosterone, insulin, ghrelin), and hypothalamic and hepatic gene expression were examined. Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) and subsequent metabolomic analysis using Progensis QI and Metaboanalyst were used to characterise plasma differences between the olanzapine treatment group and controls.
Results: After the study conclusion, quality control issues with the probiotic formulation were discovered, limiting the interpretability of the data from those treatment groups. However, the olanzapine treatment displayed increased weight gain, dietary intake, and hypothalamic genes related to ghrelinergic signalling. Olanzapine did not increase adiposity, change hepatic gene expression, plasma biomarkers, or hypothalamic genes related to anorexigenic signalling. No treatments attenuated olanzapine-induced weight gain. There were no observed differences in anxiety-like behaviour between any groups. Lastly, the metabolomics investigation revealed several highly differentially expressed metabolites; two androstanoids and one endocannabinoid (oleamide).
Conclusion: These findings indicate that olanzapine-associated increases in hypothalamic ghrelinergic signalling can occur before or without the onset of peripheral changes in metabolic health. Although the attenuation of olanzapine-associated increases in hypothalamic ghrelinergic signalling could not be assessed due to the quality control issues with the probiotic, targeting ghrelinergic signalling via microbiome-targeted approaches warrants further research. Additionally, the metabolomics analyses highlight oleamide as a novel metabolite that is potentially at the intersection of the endocannabinoid system, the microbiota, and olanzapine treatment, but further research is needed to clarify if the observed increase in oleamide is due to changes in host and/or microbial metabolism.
2023-01-01T00:00:00ZA seismic study on the structural evolution of the North Celtic Sea Basin, offshore IrelandByrne, Keith B.https://hdl.handle.net/10468/113062023-03-31T07:10:28Z2020-01-01T00:00:00Zdc.title: A seismic study on the structural evolution of the North Celtic Sea Basin, offshore Ireland
dc.contributor.author: Byrne, Keith B.
dc.description.abstract: The North Celtic Sea Basin (NCSB) is one of a number of basins related to regional Mesozoic extension across north-west Europe. Previous authors have described the NCSB as having a conventional “steer’s head” geometry or alternatively a half graben geometry. Modern 2D and 3D seismic data has now allowed interpretation of faulting at depth within the NCSB. In particular it has demonstrated the importance of intra-basinal faulting and results in a robust updated structural evolution of the NCSB. Rifting is believed to have commenced in the Triassic with the development of an asymmetric simple shear rift. Extension was accommodated by several reactivated Variscan thrust faults with a detachment between the upper and lower crust at 18-20 km (11-12.5 miles) depth. Rifting continued through the Lower Jurassic and extension was accommodated primarily on the most northern of the reactivated Variscan thrusts, the Morrigan Fault. A deep extension of the Morrigan Fault has been mapped by previous authors on deep refraction seismic data as a south -easterly dipping low angle detachment. The other Variscan thrusts became locked, possibly against the granites within the Labadie Bank High – Pembrokeshire Ridge to the south. Halokinesis initiated within the Lower Jurassic, caused by movement on underlying faults and differential loading of the overburden. Renewed rifting in the Upper Jurassic and Lower Cretaceous was accommodated by a symmetric pure shear rift as extension was accommodated on the Morrigan Fault and new mid-basinal normal faults, antithetic to the Morrigan Fault, resulting in a conventional full graben geometry. These antithetic faults (Dagda, Brigit and Aonghus Faults) detach in the underlying Triassic halites. The post rift sag phase in the Upper Cretaceous yielded thick deep marine deposits which overstepped the basin bounding faults to yield a classic “steer’s head” geometry. Subsequent Alpine compression in the Oligo-Miocene and uplift in the Paleocene reactivated and reversed the mid-basin antithetic faults, creating broad mid-basinal anticlines and flower structures. These faults were preferentially reactivated as they detached in Triassic halites. Recognition of this revised structural evolution of the NCSB is critical to predicting the spatial distribution of sedimentary facies and de-risking hydrocarbon prospectivity of the basin.
2020-01-01T00:00:00ZA study of airline route dataYu, Xiaochenhttps://hdl.handle.net/10468/113292023-04-04T10:57:45Z2020-01-01T00:00:00Zdc.title: A study of airline route data
dc.contributor.author: Yu, Xiaochen
dc.description.abstract: For decades, with the advancement of airline information system construction, the aviation industry has successfully built a number of information systems. An enormous amount of data has been accumulated through the successful operation of these systems for the aviation sector. The effective use of these invaluable data assets has increasingly become a requirement for the relevant airline departments, and the focus of aviation industry. Revenue management is crucial for measuring the operational success of the airlines. However, the traditional forecasting methods cannot support processing of the underlying data that keeps changing over time, which have impaired the accuracy of the forecast, and thus, the credibility. The new airline passenger ticket revenue pricing methods proposed in this thesis have explored the possibility of solving the existing problems through advanced modeling techniques, and thus provide a view for better airline route planning and optimisation. First of all, the airline data is classified in a targeted manner. The factors of available seat kilometers, revenue passenger kilometers, load factors, total number of passengers, average fares, etc. collected from different time periods were used to establish a multiple linear regression model in the statistical software, R. Through empirical analysis it is found that the factors affecting the passenger ticket revenue, over different time periods of the same company, are different. Therefore, a multivariate linear regression model was established which was based on the data of different airlines in one specific time period. It was empirically found through this approach that different airlines had different factors affecting ticket revenue in the same time period. A multivariate linear regression model was established for analysing the data of the head office and the various branches at the same time period and through this it was found that the factors affecting the passenger ticket revenue of the head office and the branches at the same time period were different. The research results of this dissertation can provide scientific evidence that airlines should consider analysing real-time ticket data for ticket price and flight plan collected from the IT system to maximise the revenue.
2020-01-01T00:00:00ZActivity profiles of adults aged 50 - 70 years: functional data analysisWeedle, Richardhttps://hdl.handle.net/10468/99772023-04-04T10:56:20Z2019-10-01T00:00:00Zdc.title: Activity profiles of adults aged 50 - 70 years: functional data analysis
dc.contributor.author: Weedle, Richard
dc.description.abstract: Physical activity has a major impact on health. Questionnaires are the most
common method of physical activity assessment. While cost effective, these are
subjective and can correlate poorly with actual activity levels. Accelerometers
have gained popularity given their accuracy, objectivity and ability to capture
large amounts of data. Simple summary measures such as the total or average
activity over the day are often used. However, these fail to exploit the
longitudinal nature of the data and do not capture the variation in activity
levels throughout the day. This study intends to capitalise on this nature by
implementing a functional data analysis approach. Activity data was collected from a cohort of 475 people in Mitchelstown in 2011. The individuals wore wrist worn accelerometers in a free living environment for a week. This data was collapsed into 1 minute epochs and each epoch was then aggregated over the week to get an estimate of daily circadian activity. The discrete wavelet transform was chosen as the smoothing technique to reveal the underlying functional nature of the data. This allows every individual in the cohort to be represented by a smooth activity profile. This study aimed to
identify and characterise subgroups within a cohort based on these activity
profiles. Functional principal component analysis was applied to these activity profiles in
order to explore the dominant patterns within the data. Each individual’s
profile was approximated by a weighted sum of profiles and these weights were
then used to perform a cluster analysis. Five distinct subgroups were identified.
These differed from each other in both the magnitude of the activity and the
times at which the activity occured. A more simplified approach, based purely
on the distance between profiles, was also implemented. Two distinct clustering
methods identified the exact same 5 subgroups in the cohort. To ensure their
robustness, these results were subject to a sensitivity analysis with respect to
the epoch length, smoothing technique and number of functional components
utilised in the clustering. Other studies have clustered accelerometer data in terms of absolute activity volume, as in high or low activity groups. However, they do not place too much value in using the granularity of the data to determine what time of day people
are active. In addition to the high, moderate and low activity subgroups, our
analysis revealed two subgroups which have a propensity to be active in either
the morning or evening. It is suggested that these are indicative of an
individual’s biological rhythm or chronotype. The Mitchelstown cohort was
re-screened 5 years later in 2016, which presents an exciting opportunity to
examine changes in these profiles over time.
2019-10-01T00:00:00Z