Advanced informatics for event detection and temporal localization

PhD ThesisThe primary objective of a Sound Event Detection (SED) system is to detect the prescene of an acoustic event (i.e., audio tagging) and to return the onset and offset of the identified acoustic event within an audio clip (i.e., temporal localization). Such a system can be promising in wildlife and biodiversity monitoring, surveillance, and smart-home applications. However, developing a system to be adept at both subtasks is not a trivial task. It can be hindered by the need for a large amount of strongly labeled data, where the event tags and the corresponding onsets and offsets are known with certainty. This is a limiting factor as strongly labeled data is challenging to collect and is prone to annotation errors due to the ambiguity in the perception of onsets and offsets. In this thesis, we propose to address the lack of strongly labeled data by using pseudo strongly labeled data, where the event tags are known with certainty while the corresponding onsets and offsets are estimated. While Nonnegative Matrix Factorization can be used directly for SED but with limited accuracy, we show that it can be a useful tool for pseudo labeling. We further show that pseudo strongly labeled data estimated using our proposed methods can improve the accuracy of a SED system developed using deep learning approaches. Subsequent work then focused on improving a SED system as a whole rather than a single subtask. This leads to the proposal of a novel student-teacher training framework that incorporates a noise-robust loss function, a new cyclic training scheme, an improved depthwise separable convolution, a triple instance-level temporal pooling approach, and an improved Transformer encoding layer. Together with synthetic strongly labeled data and a large corpus of unlabeled data, we show that a SED system developed using our proposed method is capable of producing state-of-the-art performance

The Effects of Instrument Lubricants on the Physical and Mechanical Properties of Resin-Based Composites

Ph. D. ThesisUncured resin-based composites (RBCs) tend to stick to the placement instrument instead of cavity walls, potentially increasing void formation and margin discrepancy. Instrument lubricants (ILs) are used to overcome this problem, but they may affect the properties of RBC restorations. One hundred registered UK dentists were surveyed using a bespoke questionnaire to investigate their perspective on IL use and understand why and how they used them. Additionally, different laboratory investigations were conducted, based on the survey data, to test the effects of ILs on the physical and mechanical properties of RBCs. Two RBCs were treated with three classes of ILs —solvents, bonding agents and wetting resins —to investigate the effects different ILs have on the physical and mechanical properties of RBCs. Several areas were tested: degree of conversion, water uptake, Martens hardness, diametral tensile strength, microtensile bonding strength (μTBS), and the appearance of changes at the increment interface. The survey revealed that about 50% of the dentists used lubricants (32% response rate), of which bonding agents (67%) and wetting resins (33%) were most common. These were applied with microbrushes (47%) and by wiping the placement instruments (40%). The solvents, bonding agents and wetting resins created significant reductions in diametral tensile strength and Martens hardness, and increased water uptake compared to control groups fabricated without lubricants. The μTBS significantly reduced following treatment with solvents and bonding agents, but there was no reduction from the wetting resins. The respondents used lubricants to aid manipulation during placement. However, these materials have an impact upon physical and mechanical properties with solvents and bonding agents having the greater effect. Therefore, the use of ILs to manipulate the RBC should be limited or avoided.King Khalid Universit

Design, synthesis and SAR Evaluation of novel benzoxa-[2,1,3]-diazole amino acid hydrazides against my cobacterium tuberculosis

PhD ThesisThe major challenges of tuberculosis (TB) treatment are the emergence of the drug-resistant strains and the higher risk of hepatotoxicity with prolonged treatment. Therefore, efforts to effectively control TB require the discovery and development of new therapeutic options possessing new mechanisms of action. This project focused on the design and synthesis of novel agents targeting Mycobacterium tuberculosis (Mtb). We have successfully synthesised 170 hydrazides with 40 of those intermediates being converted to benzoxa-[2,1,3]- diazole substituted amino acid hydrazides 65. The resulting compounds were screened against susceptible and resistant Mtb strains utilising a Resazurin Microtiter Assay (REMA). A subsequent structure activity relationship (SAR) strategy investigated the structural modification of the benzo-[2,1,3]-diazole peptidomimetics architecture 65 as the main focus of the research presented in this thesis. The findings from this SAR study indicate that an increased size of the amino acid side chain, incorporation of heavy halogens at the meta position of the aryl hydrazine, the L-configuration of the amino acid and the benzoxa-[2,1,3]-diazole moiety each play a key role in improving the antitubercular activitySaudi Ministry of Education and Taibah Universit

Applications of Non-Orthogonal Waveforms and Artificial Neural Networks in Wireless Vehicular Communications

Ph. D. ThesisWe live in an ever increasing world of connectivity. The need for highly robust, highly efficient wireless communication has never been greater. As we seek to squeeze better and better performance from our systems, we must remember; even though our computing devices are increasing in power and efficiency, our wireless spectrum remains limited. Recently there has been an increasing trend towards the implementation of machine learning based systems in wireless communications. By taking advantage of a neural networks powerful non-linear computational capability, communication systems have been shown to achieve reliable error free transmission over even the most dispersive of channels. Furthermore, in an attempt to make better use of the available spectrum, more spectrally efficient physical layer waveforms are gathering attention that trade increased interference for lower bandwidth requirements. In this thesis, the performance of neural networks that utilise spectrally efficient waveforms within harsh transmission environments are assessed. Firstly, we investigate and generate a novel neural network for use within a standards compliant vehicular network for vehicle-to-vehicle communication, and assess its performance practically in several of the harshest recorded empirical channel models using a hardware-in-the-loop testing methodology. The results demonstrate the strength of the proposed receiver, achieving a bit-error rate below 10−3 at a signal-to-noise ratio (SNR) of 6dB. Secondly, this is then further extended to utilise spectrally efficient frequency division multiplexing (SEFDM), where we note a break away from the 802.11p vehicular communication standard in exchange for a more efficient use of the available spectrum that can then be utilised to service more users or achieve a higher data throughput. It is demonstrated that the proposed neural network system is able to act as a joint channel equaliser and symbol receiver with bandwidth compression of up to 60% when compared to orthogonal frequency division multiplexing (OFDM). The effect of overfitting to the training environment is also tested, and the proposed system is shown to generalise well to unseen vehicular environments with no notable impact on the bit-error rate performance. Thirdly, methods for generating inputs and outputs of neural networks from complex constellation points are investigated, and it is reasoned that creating ‘split complex’ neural networks should not be preferred over ‘contatenated complex’ neural networks in most settings. A new and novel loss function, namely error vector magnitude (EVM) loss, is then created for the purposes of training neural networks in a communications setting that tightly couples the objective function of a neural network during training to the performance metrics of transmission when deployed practically. This loss function is used to train neural networks in complex environments and is then compared to popular methods from the literature where it is demonstrated that EVM loss translates better into practical applications. It achieved the lowest EVM error, thus bit-error rate, across all experiments by a margin of 3dB when compared to its closest achieving alternative. The results continue and show how in the experiment EVM loss was able to improve spectral efficiency by 67% over the baseline without affecting performance. Finally, neural networks combined with the new EVM loss function are further tested in wider communication settings such as visible light communication (VLC) to validate the efficacy and flexibility of the proposed system. The results show that neural networks are capable of overcoming significant challenges in wireless environments, and when paired with efficient physical layer waveforms like SEFDM and an appropriate loss function such as EVM loss are able to make good use of a congested spectrum. The authors demonstrated for the first time in practical experimentation with SEFDM that spectral efficiency gains of up to 50% are achievable, and that previous SEFDM limitations from the literature with regards to number of subcarriers and size of the transmit constellation are alleviated via the use of neural networksEPSRC, Newcastle Universit

Targeting Kinases with Small Molecule Covalent Inhibitors

PhD ThesisProtein kinases are considered the largest and most functionally diverseenzymesuperfamily critically involved in the regulation of almost all cellular process. Theyareone of the most intensively pursued targets, particularly in cancer drugdiscoveryprograms. In the case of cancer therapy, covalent inhibitors have proven to be better than reversible inhibitors and several kinases targeted covalent inhibitors are in clinical use. In this thesis, irreversible inhibition of NF-κB inducing kinase(NIK) and Epidermal growth factor receptor (EGFR) is investigated. NIK is an essential upstream kinase, which regulates activation of the noncanonical NF-κB pathway involved in lymphoid organ development and adaptive immune responses. Numerous genetic studies demonstrated that the aberrant expression or regulation of NIK is associated with several disease states including cancers. The NIK kinase has been targeted for drug therapy by small molecule reversible inhibitors,but many of them were impractical for in-vivo administration due to poor selectivity or pharmacokinetic properties. Achieving potency and selectivity in NIK inhibitors is particularly challenging due to its constitutive activity, high ATP affinity (Km4µM) and relatively shallow binding pocket. Developing an irreversible inhibitor of NIK that targets active site Cys-444, which is unique to NIK, is expected to deliver greatly improved selectivity and superior efficacy. Extensive structure-activity relationshipstudies (SARs) based on literature NIK inhibitors have led to lead benzimidazole28. Benzimidazole 28 exhibits NIK potency of 0.18 µM and has been confirmed to bind covalently to NIK Cys-444, but has poor selectivity profile inhibiting both NIK dependent and independent cell lines. Co-crystallisation studies using28werecarried out to understand the binding mode in NIK and identify structural features to exploit to achieve better potency and selectivity in future analogues. SAR studies around the hinge binding motif, benzimidazole core structure, and covalent warhead were investigated, and a number of analogues were designed and synthesised. A scaffold hopping approach based on recently published NIK inhibitors was also carried out with the aim of improving the compound potency and selectivity. EGFR is critically involved in cell signalling pathways that control cell growth, proliferation, and survival. Multiple generations of EGFR TKIs have been approved for clinical use. Mutations or over-expression of EGFR have been discovered in association with many types of cancers providing a rationale for efforts to inhibit EGFR. Multiple generation of EGFR TKIs have been developed and approved for clinical use. Despite the documented efficacy of FDA approved third generation EGFR TKIs, new EGFR mutations and other drug resistance mechanisms emerge rapidly after treatment leaving patient without further therapeutic options other than chemotherapy and local ablative therapy. Multiple mechanisms of resistance were detected in clinical trials with tertiary C797S mutation accounting for more than20%incidence rate and the most difficult to deal with. It was proposed that developing an irreversible inhibitor of EGFR by targeting Cys-775 would deliver a new therapeutic option for patient who develop resistance to third generation EGFR TKIs. Extensive structure-activity relationship studies were conducted based on literature compounds have led to lead pyrimidopyridone 128. Pyrimidopyridone 128 exhibits a potency of 107 nM in the TMTR-FRET assay and has been confirmed to be a covalent inhibitor of EGFR targeting Cys-775. Co-crystallisation studies using 128 were carried out to understand the binding mode in EGFR, and to help in identifying structural features to exploit to achieve better potency. Further SARs studies to improve the compound potency were conducted in which SARs around the phenyl ring were undertaken. Compounds with electron rich phenyl ring were more potent than compounds with electron deficient phenyl ring. AQSAR study revealed that compounds with electron donating substituents were more potent regardless of the position of the substituents, but no obvious relationship was observed with the lipophilicity. The outlier of this was compound 151, which was the most potent compound in this series, though not the one with the most electron rich phenyl ring suggesting that the sulphonamide group at the para-position was making an additional interaction within the sugar pocket. Modelling of compound151withdouble mutant EGFR revealed the proximity of several functional groups that may act as H-bonding partners to the sulphonamide moiety in compound 151 (Ser-797intriple mutant EGFR, Asn-842 and Ser-720). TJordan University of Science and Technolog

Realistic evacuation simulation through micro and macro scale agent-based modelling including demographics, agent patience and evacuation route capacities

PhD ThesisDisasters affect millions of people annually, causing large social impacts, and detrimental economic impacts. Emergency professionals recurrently tackle these impacts, therefore they require assessment methods to understand potential consequences and enable the delivery of resilient resolutions. One method of achieving this is through numerical modelling, specifically agent-based modelling. However, current models simulating human behaviours and movement are bespoke in nature and non-transferable. It has also been found that current modelling tools have either focused on the microscale (e.g. individual confined spaces) or macroscale (e.g. city scale), without considering how the two scales may be interlinked. Further to this, the inclusion of human behaviour has been over-simplified and generic, lacking the inclusion of unique populations with varied characteristics. The aim of this research is to develop a modelling framework, utilising agent-based modelling, to form a more robust representation of human behaviour within an enhanced evacuation model environment. This will allow emergency planners to be better prepared, reduce the interruption after an event (thereby reducing social and economic impacts) and potentially reduce the mitigation required beforehand. The individual agents within the framework capture a range of robust human behaviour indicators (e.g. walking speed, obedience, and patience), allowing the accurate replication of an emergence scenario response. Initially, the research focused on creating a macroscale evacuation model for a test city, to assess whether the inclusion of varied population characteristics and groups of people affected evacuation time. The varied characteristics included a range of ages, gender, and mobility in the form of walking speed. It was then possible to compare this with the parameters of existing evacuation models. This research has found that by enhancing the representation of human behaviour within a model environment more accurate predictions of evacuation time can be produced. To produce more robust human behaviour, models must include a range of population characteristics (such as age, gender and mobility), the grouping of agents and walking speed ratio. When all the variables are included in the model, there is an average increase of 70% in the time to evacuate Newcastle city centre. Even with less variables, i.e. only considering population characteristics, there has been an average increase of 45% in the time to evacuate Newcastle city centre compared with existing models. To further examine human behaviour and the more intricate and detailed behaviours such as patience, a microscale model was created to consider the capacity of the pathways and to introduce congestion. The two microscale models were created of a pavement and a crossroads, ii to replicate people passing and waiting behind slower people, whilst still including the varied population characteristics. When capacity is captured at the microscale, there is an average 61% increase in the time to exit the pavement and when on a crossroads there is an average 87% increase in the time to exit compared to 1.34m/s (3mph) models. Overall, this research has found that there is a need to provide more robust representation of human behaviour characteristics within evacuation models. This must be carried out not only at the macroscale in terms of enhancing population demographics but also at the microscale by capturing intricate behaviours such as taking over and giving way. Without an ability to exhibit these characteristics evacuation simulations cannot effectively capture human behaviour and therefore produce robust simulation times. The inclusion of more representative human behaviour in simulations and the continual need to improve provides the opportunity to reduce the likelihood of increased fatalities and injuries caused by those unable to evacuate in time due to current underestimations. The improvement of computational simulation of evacuations alongside existing simulation techniques allows emergency professionals to plan and prepare better for a range of events to protect global communities

The role of expectations on affective sound processing: behavioural and neural correlates

Ph. D. Thesis.Theoretical frameworks and empirical evidence in the last two decades have shown that prior expectations about the upcoming stimulus can shape the perception when the stimulus arrives. How expectations influence emotional responses to the stimulus is, however, relatively less understood. In this thesis, using behavioural and neural measures of electroencephalography (EEG) and intracranially recorded local field potentials (LFPs) from human subjects, I explore the role of expectations on the processing of affective sounds. In Chapter 2, the neural basis of expectation is first established using EEG. Two visual cues were used to elicit the expectation of either neutral or aversive sounds. An event related potential just before the onset of upcoming stimuli, called Stimulus Preceding Negativity (SPN), is measured to index the expectation of an upcoming stimulus. Although a robust measure of SPN could be observed for the expectation of both aversive and neutral sounds, no difference between the two was observed indicating no relation between the magnitude of SPN and valence of sounds. Source localization of SPN, using multiple sparse priors algorithm revealed a network of brain areas including the anterior insula, inferior frontal gyrus, temporal cortex, supplementary motor area (SMA) and thalamus. A limitation of the first experiment was that no behavioural measure of expectation of valence was recorded. It is likely that there is variation across subjects in the expectation and perceived valence after the stimulus onset. The second experiment (Chapter 3), also a cued paradigm as above, addressed this limitation by using subjective measures of expectations before the sound onset and aversive ratings after sound offset as reported by the subjects. Mediation analysis between perceived ratings following sound onset and expectation ratings confirmed a mediator role of expectation/predictions in the aversive experience – an expectation for aversive sounds translated into a more aversive experience, and an expectation for less aversive sounds translated into a less aversive experience once the sound was heard. Exploratory analyses showed that subjects whose perceived aversiveness shifted in the direction of expectation displayed a stronger SPN. Moreover, this effect was seen for aversive but not for neutral sounds. Additionally, activity in the alpha-beta band during encoding of the predictive cues was associated with the precision of subjective expectancy. In summary, the data highlight the importance of measuring behavioural/subjective correlates of expectation and perceived aversiveness. This may be particularly important when the cues-contingencies are not explicitly disclosed and when using emotional (subjective) stimuli, as there is bound to be high inter-individual variability both in learning rates and stimulus appraisal. Expectations about the upcoming stimulus can be formed based on different sources. For example, it could be based on information from other people (that is, social source) or expectations can be formed based on personal experiences with the world (conditioned source). In the third and last experiment (Chapter 4), the behavioural, physiological and neural basis of social and conditioned expectations are measured. Using a cued paradigm, subjects formed expectations of the upcoming stimulus either based on social information or their own conditioning experiences. As in the experiment in Chapter 3, subjects rated their expectation prior to the stimulus onset and their perceived aversiveness following the onset of the stimulus. The data again show that the perceived aversiveness shifted in the direction of expectations for both the social and conditioned cues. Further, physiological and autonomic responses also shifted in the direction of expectations. Recordings from LFPs in a group of epileptic patients undergoing neurosurgical evaluations for the locations of their seizure foci show expectation-based changes during sound perception in a widespread network including temporal cortex, anterior cingulate and orbitofrontal cortices, inferior frontal gyrus, and insula. Collectively, the research presented in this doctoral thesis show expectations can and do alter the processing of aversive sounds at the behavioural, somatic, and neural levels.Newcastle Universit

Bond graph modelling of exergy in integrated energy systems

Ph. D. Thesis.Integrated municipal or district energy systems are one facet of the effort to support sustainable energy systems that work towards reducing anthropogenic climate change emissions. Current energy systems — including electricity, heat, and cooling — operate mostly independently, under the control of domain-distinct industries and regulatory bodies. Operating these separate systems in a cooperative or integrated manner promises improvements in efficiency, the ability of networks to absorb renewable energy sources and storage, emissions reductions and community-based benefits. The nature of district energy systems is that they cannot easily be modified or built upon without severe disruption to the communities they serve, so assessments of their behaviour and performance caused by potential changes must be modelled. This thesis investigates what methods can model integrated energy systems and develops a bond graph-based approach to constructing a fully-integrated system model. Although energy based methods for integrated energy system modelling exist, this thesis demonstrates that exergy can form the basis of integrated energy system models. Exergy being a measure of the usefulness of energy allows the equivalence of energy domains in a single model form, permitting development of a genuine, physically-founded integrated energy system model. An integrated model of a residential district supplied by heat and electrical networks, based on a real UK urban area, is demonstrated in OpenModelica using the developed modelling approach. The concept of an exergy storage device is introduced to provide a mechanism for mediating energy flows between the networks. The model is used to evaluate the performance of the test network, using trial cases to investigate how transferring exergy between energy domains through the mediating storage affects the overall system energy and exergy efficiencies. Operational regimes that transfer energy from the electrical to the thermal sub-system using the mediating storage are found to improve the exergy efficiency of the system.Newcastle University, Siemen

Multi-objective torque control of switched reluctance machine

PhD ThesisThe recent growing interest in Switched Reluctance Drives (SRD) is due to the electrification of many products in industries including electric/hybrid electric vehicles, more-electric aircrafts, white-goods, and healthcare, in which the Switched Reluctance Machine (SRM) has potential prospects in satisfying the respective requirements of these applications. Its main merits are robust structure, suitability for harsh environments, fault-tolerance, low cost, and ability to operate over a wide speed range. Nevertheless, the SRM has limitations such as large torque ripple, high acoustic noise, and low torque density. This research focuses on the torque control of the SRD with the objectives of achieving zero torque error, minimal torque ripple, high reliability and robustness, and lower size, weight, and cost of implementation. Direct Torque Control and Direct Instantaneous Torque Control are the most common methods used to obtain desired torque characteristics including optimal torque density and minimized torque ripple in SRD. However, these torque control methods, compared to conventional hysteresis current control, require the use of power devices with a higher rating of about 150% to achieve the desired superior performance. These requirements add extra cost, conduction loss, and stress on the drive’s semiconductors and machine winding. To overcome these drawbacks, a simple and intuitive torque control method based on a novel adaptive quasi sliding mode control is developed in this study. The proposed torque control approach is designed considering the findings of an investigation performed in this thesis of the existing widely used control techniques for SRD based on information flow complexity. A test rig comprising a magnet assisted SRM driven by an asymmetric converter is constructed to validate the proposed torque control method and to compare its performance with that of direct instantaneous torque control, and current hysteresis control methods. The simulation and experimental results show that the proposed torque control reduces the torque ripple over a wide speed range without demanding a high current and/or a high switching frequency. In addition, It has been shown that the proposed method is superior to current hysteresis control method in the sensorless operation of the machine. Furthermore, the sensorless performance of the proposed method is investigated with the lower component count R-Dump converter. The simulation results have also demonstrated the excellent controller response using the standard R-Dump converter and also with its novel version developed in this thesis that needs only one current sensor

Microbial interactions in tomato solanum iycopersicum for health, growth, and pathogen defence

PhD ThesisSolanum lycopersicum is an important vegetable high in vitamin A and C and minerals such as phosphorus, iron and high in lycopene and beta-carotene. It is considered the favourite in the food processing and cosmetics industries. S. lycopersicum current global production is concentrated in the United States of America, China, and India. The production of S. lycopersicum depends on the application of chemical fertiliser; however, ecological damages caused by chemical fertiliser far outweigh its benefits. Thus, there is a need to initiate and adopt eco-friendly cultivation of S. lycopersicum using vertically transmitted endophytes. In this study, different strains of vertically transmitted endophytic bacteria were isolated from eight different cultivars of S. lycopersicum. The findings show that vertically transmitted endophytes are host specific and display various phenotypes that produce diverse metabolites with different concentrations. It also demonstrated that treated S. lycopersicum under fertilised microbial communities performed significantly better than those under the manure microbial community, untreated microbial community, and the control tank. The finding also shows that vertically transmitted endophytes in the S. lycopersicum failed to stimulate interaction between S. lycopersicum and its surrounding soil microbial communities, which promotes plant growth, increase chlorophyll content, increase fresh and dried biomass of the plant. Our result further demonstrated no significant difference when the isolated vertically transmitted endophytes Bb-B-1 was inoculated on S. lycopersicum under the optimum nutrient condition and deprived nutrient condition. Finally, the study demonstrates that microbial communities from fertilised treated soil, manure treated soil, and untreated microbial communities are not involved in inducing or suppressing Auxin, LelRT1, FER, FROS2 and LeNRT2;3 genes in S. lycopersicum. It further shows that the S. lycopersicum vertically transmitted endophytes are not involved in regulating these genes. Whilst no significant result to demonstrate the possible role of vertically transmitted endophytes the study demonstrated that S. lycopersicum vertically transmitted endophytes are host specific and display various phenotypes that produce diverse metabolites with different concentrations. Further investigation is required to focus on the isolated vertically transmitted endophytes precisely to understand their possible roles in the plant host. Additional studies investigating the role of different microbial communities on the host plant required more time to monitor the suitable duration needed by the microbial communities to be established in the new environment.PTDF Nigeri