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Research mini-projects : 1. Probabilistic forecasting of maximum wave height ; 2. Optimal sizing and operation of battery storage at ray wind farm
No full text1. Accurate forecasting provides a great deal of financial benefits and mitigation of risks in the shipping industry, as well as the operation and maintenance of marine energy systems. Forecasting maximum wave height over significant wave height gives a more thorough depiction of the sea state with respect to safety. Moreover, the probabilistic model's distribution illustrates the uncertainty in the forecast which allows for safer decision making. Linear models are produced and verified using continuous ranked probability score, mean absolute error and the pinball loss function. The data used to train the models consists of measured data, which is obtained from the FINO1 platform, and numerically forecast data from the Met Office database which is produced using the WAVEWATCH III R numerical model of the National Centres for Environmental Prediction. The models are trained to predict a mean value of the maximum wave height. The residuals are then used to calculate the variance and fit a distribution around the mean values that are predicted. The prediction performance of both linear models produced is compared and is found to be very similar. Further work is suggested in comparing the models to numerical weather predictions and considering other models for prediction.;2. This study provides an outline for the inclusion of a battery at a wind farm to offer flexible generation and allow for a higher fraction of distributed renewable energy on the grid. Many applications for batteries are considered, this study focuses specifically on the correction of forecast errors. Battery technologies are briefly discussed, particularly comparing the widespread Li-ion battery to the Vanadium Redox Flow Battery, which was chosen for this study. The strategy compromises on continuous error correction and designates the optimal times to correct forecast error based on price data. The assumption made with regards to the ability for battery charge/discharge from the grid is proven to be detrimental to the effective use of the battery. It is suggested that this assumption is omitted in further work and that ancillary service provision is considered as a revenue stream when the battery is not being used to correct forecast errors.1. Accurate forecasting provides a great deal of financial benefits and mitigation of risks in the shipping industry, as well as the operation and maintenance of marine energy systems. Forecasting maximum wave height over significant wave height gives a more thorough depiction of the sea state with respect to safety. Moreover, the probabilistic model's distribution illustrates the uncertainty in the forecast which allows for safer decision making. Linear models are produced and verified using continuous ranked probability score, mean absolute error and the pinball loss function. The data used to train the models consists of measured data, which is obtained from the FINO1 platform, and numerically forecast data from the Met Office database which is produced using the WAVEWATCH III R numerical model of the National Centres for Environmental Prediction. The models are trained to predict a mean value of the maximum wave height. The residuals are then used to calculate the variance and fit a distribution around the mean values that are predicted. The prediction performance of both linear models produced is compared and is found to be very similar. Further work is suggested in comparing the models to numerical weather predictions and considering other models for prediction.;2. This study provides an outline for the inclusion of a battery at a wind farm to offer flexible generation and allow for a higher fraction of distributed renewable energy on the grid. Many applications for batteries are considered, this study focuses specifically on the correction of forecast errors. Battery technologies are briefly discussed, particularly comparing the widespread Li-ion battery to the Vanadium Redox Flow Battery, which was chosen for this study. The strategy compromises on continuous error correction and designates the optimal times to correct forecast error based on price data. The assumption made with regards to the ability for battery charge/discharge from the grid is proven to be detrimental to the effective use of the battery. It is suggested that this assumption is omitted in further work and that ancillary service provision is considered as a revenue stream when the battery is not being used to correct forecast errors
Chemoselective reactions of organoboron compounds
No full textThe Suzuki-Miyaura reaction is a landmark discovery which has revolutionised the field of palladium catalysis. Since its inception, reaction development has not only progressed the range of electrophiles which can be adopted in this transformation but has significantly enhanced the scope of organoboron reagents which can be used, cementing the reaction as the most favoured method for C-C bond formation. Despite these advances, investigation around this key transformation is continuous. A key highlight of this reaction, which is desirable to the synthetic community, is the chemoselectivity shown between, competing electrophiles, through selective oxidative addition based on electronics and bond dissociation energies, and competing nucleophiles, through selective transmetalation using boron protecting groups. The use of boron protecting groups typically adds several steps to a synthetic sequence and, as such, is an aspect which this investigation looks to address by establishing chemoselectivity between ostensibly equivalent organoboron species. In order to probe this chemoselectivity a workhorse reaction was chosen: The Brown oxidation. This work describes the development of a chemoselective oxidation of competing organoboron species with a thorough investigation into the origin of this observed chemoselectivity. This study serves as a platform for chemoselectivity in other organoboron reactions without the necessity of protecting groups. A key mechanistic event in the SM reaction which has recently been disclosed in several mechanistic investigations, is the anion metathesis step. Although this critical step has been suitably highlighted in these studies, we believe control of this event would provide a powerful, yet untapped, control vector in PdII catalysis. The following study highlights how an ion metathesis can be regulated to facilitate discrimination between competing Mizoroki-Heck and Suzuki-Miyaura pathways. To interrogate this vinyl BPin, a competent nucleophile in both cross-couplings, is employed as a bifunctional chemical probe. Ultimately, this thesis will discuss unexplored chemoselectivity of organoboron compounds and how this selectivity can be leveraged for the improvement of synthetic chemistry.The Suzuki-Miyaura reaction is a landmark discovery which has revolutionised the field of palladium catalysis. Since its inception, reaction development has not only progressed the range of electrophiles which can be adopted in this transformation but has significantly enhanced the scope of organoboron reagents which can be used, cementing the reaction as the most favoured method for C-C bond formation. Despite these advances, investigation around this key transformation is continuous. A key highlight of this reaction, which is desirable to the synthetic community, is the chemoselectivity shown between, competing electrophiles, through selective oxidative addition based on electronics and bond dissociation energies, and competing nucleophiles, through selective transmetalation using boron protecting groups. The use of boron protecting groups typically adds several steps to a synthetic sequence and, as such, is an aspect which this investigation looks to address by establishing chemoselectivity between ostensibly equivalent organoboron species. In order to probe this chemoselectivity a workhorse reaction was chosen: The Brown oxidation. This work describes the development of a chemoselective oxidation of competing organoboron species with a thorough investigation into the origin of this observed chemoselectivity. This study serves as a platform for chemoselectivity in other organoboron reactions without the necessity of protecting groups. A key mechanistic event in the SM reaction which has recently been disclosed in several mechanistic investigations, is the anion metathesis step. Although this critical step has been suitably highlighted in these studies, we believe control of this event would provide a powerful, yet untapped, control vector in PdII catalysis. The following study highlights how an ion metathesis can be regulated to facilitate discrimination between competing Mizoroki-Heck and Suzuki-Miyaura pathways. To interrogate this vinyl BPin, a competent nucleophile in both cross-couplings, is employed as a bifunctional chemical probe. Ultimately, this thesis will discuss unexplored chemoselectivity of organoboron compounds and how this selectivity can be leveraged for the improvement of synthetic chemistry
Modelling the distribution of mercury in oil and gas processing facilities
Get PDFMercury is not only considered a toxic pollutant in the environment but also a corrosive element in processing equipment. The presence of mercury in oil and gas can increase the exposure risk to field operators and can cause serious corrosion problems. Furthermore,it may cause catalyst poisoning and deactivation; these could lead to long,unplanned shutdowns which are neither operationally nor financially desirable as they negatively impacts the equipment life and profit. Therefore, producing oil and gas from reservoirs that contain mercury is a challenging task. This work is concerned with the thermodynamic modelling of mercury distribution in oil and gas process facilities. The main objectives of this research are to investigate the distribution of mercury in oil and gas process facilities in order to eliminate mercury impact and unplanned shutdowns.In addition it aims to identify the best location of mercury removal units in an effort to alleviate mercury exposure risks and damage. This work allows the prediction of the thermodynamic behavior of elemental mercury in a wide variety of solvents, hydrocarbon mixtures, and operating conditions where experimental data are unavailable.This was successfully achieved by using two approaches; introducing binary interaction parameters between mercury and other molecules, and modelling mercury atoms as an associating atoms. The effectiveness of the developed models is validated against experimental data.It has been observed that the process operating conditions play an important role in mercury distribution in various phases. Reducing the operating pressure and increasing operating temperature allows more heavy hydrocarbons to flash out carrying over more mercury to the gas stream. This increases the possibility of mercury accumulation in the gas processing units. The presence of heavy hydrocarbons in the produced water streams increases the solubility of elemental mercury in these streams. This negatively impacts the biosphere due to mercury pollution.Mercury is not only considered a toxic pollutant in the environment but also a corrosive element in processing equipment. The presence of mercury in oil and gas can increase the exposure risk to field operators and can cause serious corrosion problems. Furthermore,it may cause catalyst poisoning and deactivation; these could lead to long,unplanned shutdowns which are neither operationally nor financially desirable as they negatively impacts the equipment life and profit. Therefore, producing oil and gas from reservoirs that contain mercury is a challenging task. This work is concerned with the thermodynamic modelling of mercury distribution in oil and gas process facilities. The main objectives of this research are to investigate the distribution of mercury in oil and gas process facilities in order to eliminate mercury impact and unplanned shutdowns.In addition it aims to identify the best location of mercury removal units in an effort to alleviate mercury exposure risks and damage. This work allows the prediction of the thermodynamic behavior of elemental mercury in a wide variety of solvents, hydrocarbon mixtures, and operating conditions where experimental data are unavailable.This was successfully achieved by using two approaches; introducing binary interaction parameters between mercury and other molecules, and modelling mercury atoms as an associating atoms. The effectiveness of the developed models is validated against experimental data.It has been observed that the process operating conditions play an important role in mercury distribution in various phases. Reducing the operating pressure and increasing operating temperature allows more heavy hydrocarbons to flash out carrying over more mercury to the gas stream. This increases the possibility of mercury accumulation in the gas processing units. The presence of heavy hydrocarbons in the produced water streams increases the solubility of elemental mercury in these streams. This negatively impacts the biosphere due to mercury pollution
Distributional fixed point equation model of island nucleation processes during submonolayer deposition
Get PDFIn this thesis, we look into the problem of finding an analytical model for the submonolayer nucleation processes on a substrate. More specically, we explore the Distributional Fixed Point Equation (DFPE) approach of modelling the size distribution of the gaps between nucleated islands (GSD) on a one dimensional substrate, and the size distribution of capture zones (CZD) around the islands (areas where a free monomer is more likely to be absorbed into the relevant island than to escape to the next one).;The DFPEs incorporate information about the critical island size, the nucleation mechanism (via diffusing monomers or through deposition) and the probability P(a) of a new island nucleation occurring at a position a inside a gap. The corresponding distribution Pz for the capture zones is derived from the fragmentation probability P for the gaps, so it cannot be directly observed.;We develop a strategy to solve the inverse problem of calculating the distribution P and Pz from the Integral Equation form of the DFPE, for a known GSD and CZD, in which we build P and Pz as a finite Fourier series. Additionally, we solve the inverse problem in another way: by using the Tikhonov regularisation method, and compare these results against each other and with the theoretical predictions. For the case of the gaps, we can directly measure P during the kinetic Monte Carlo simulations. We compare the results to the previously calculated P and find good consistency.;For the capture zones, we define an alternative distribution, one that can be measured: the probability of fragmenting a zone at a position a, Q(a). We then create an DFPE for this distribution Q, and we also use it to directly sample CZD. Since both approaches give promising results, we conclude our work by testing them on a two dimensional substrate, where we find that only the latter approach gives good results.In this thesis, we look into the problem of finding an analytical model for the submonolayer nucleation processes on a substrate. More specically, we explore the Distributional Fixed Point Equation (DFPE) approach of modelling the size distribution of the gaps between nucleated islands (GSD) on a one dimensional substrate, and the size distribution of capture zones (CZD) around the islands (areas where a free monomer is more likely to be absorbed into the relevant island than to escape to the next one).;The DFPEs incorporate information about the critical island size, the nucleation mechanism (via diffusing monomers or through deposition) and the probability P(a) of a new island nucleation occurring at a position a inside a gap. The corresponding distribution Pz for the capture zones is derived from the fragmentation probability P for the gaps, so it cannot be directly observed.;We develop a strategy to solve the inverse problem of calculating the distribution P and Pz from the Integral Equation form of the DFPE, for a known GSD and CZD, in which we build P and Pz as a finite Fourier series. Additionally, we solve the inverse problem in another way: by using the Tikhonov regularisation method, and compare these results against each other and with the theoretical predictions. For the case of the gaps, we can directly measure P during the kinetic Monte Carlo simulations. We compare the results to the previously calculated P and find good consistency.;For the capture zones, we define an alternative distribution, one that can be measured: the probability of fragmenting a zone at a position a, Q(a). We then create an DFPE for this distribution Q, and we also use it to directly sample CZD. Since both approaches give promising results, we conclude our work by testing them on a two dimensional substrate, where we find that only the latter approach gives good results
A study of small signal stability in power systems with converters
Get PDFFuture power systems will source much of their electrical power from converter-based generation,be it a large scale HVDC link or a smaller system such as the back-to-back converter systems found in modern, variable-speed wind turbines. This is in stark contrast to the original AC power systems which used directly-coupled synchronous generation. The transition from the past power system to the future power system will produce power systems that have both low inertia, which compromises angular and frequency stability, and low short-circuit ratios, which compromises voltage stability.In this thesis, the modelling and control of converter-based generation in low short-circuit ratio systems are investigated. For the modelling of AC power systems and the controllers being applied to the converter(s), the unified linear state-space approach is proposed. In this approach, linear state-space models of the electrical system are combined with linear state-space models in a manner which is highly scalable and sufficiently flexible to allow multiple control algorithms acting in a system instantaneously to be considered with relative ease. Three control algorithms are considered in single converter systems: dq-axis vector current control,proportional resonant control, and power synchronization control. By adopting dq-axis vector current control, the system becomes ill-conditioned at the current level, primarily due to the dynamics of the phase-locked loop, which then causes stability issues for outer feedback loops (for example DC voltage and AC voltage controllers) which accompany the current controller. Proportional resonant control, also employing a phase-locked loop, exhibits poor dynamics in the low short-circuit ratio power system. By mimicking the basic synchronization process of a synchronous generator, power synchronization control is able to perform satisfactorily in a low short-circuit ratio system, much as a synchronous generator can. Two algorithms are considered in the multi-converter, low short-circuit ratio systems: dq-axis vector current control and power synchronization control. Performance issues observed in single converter systems when dq-axis vector current control is applied are observed in the multi-converter systems. Additional sources of undesirable coupling between control loops at the current control level are observed, potentially placing more demands on the design of the outer control loops. Power synchronization control performs satisfactorily in the multi-converter systems; however, oscillatory behaviour does arise, which requires careful tuning of the controllers. In addition, it is shown that the introduction of converters using power synchronization control enables other converters (in the same system) using dq-axis vector current control to exhibit improved performance. This is due to power synchronization control causing a converter to act as an effective voltage source/regulator,and dq-axis vector current control relying on electrical proximity to a strong voltage source. This produces systems with improved conditioning, which will reduce the complexity of the design of outer controllers for dq-axis vector current controlled converters. Keywords: control, modelling, HVDC, power systems, stability, voltage-source converter, weak ACsystems, multiple-converter systems, power system planningFuture power systems will source much of their electrical power from converter-based generation,be it a large scale HVDC link or a smaller system such as the back-to-back converter systems found in modern, variable-speed wind turbines. This is in stark contrast to the original AC power systems which used directly-coupled synchronous generation. The transition from the past power system to the future power system will produce power systems that have both low inertia, which compromises angular and frequency stability, and low short-circuit ratios, which compromises voltage stability.In this thesis, the modelling and control of converter-based generation in low short-circuit ratio systems are investigated. For the modelling of AC power systems and the controllers being applied to the converter(s), the unified linear state-space approach is proposed. In this approach, linear state-space models of the electrical system are combined with linear state-space models in a manner which is highly scalable and sufficiently flexible to allow multiple control algorithms acting in a system instantaneously to be considered with relative ease. Three control algorithms are considered in single converter systems: dq-axis vector current control,proportional resonant control, and power synchronization control. By adopting dq-axis vector current control, the system becomes ill-conditioned at the current level, primarily due to the dynamics of the phase-locked loop, which then causes stability issues for outer feedback loops (for example DC voltage and AC voltage controllers) which accompany the current controller. Proportional resonant control, also employing a phase-locked loop, exhibits poor dynamics in the low short-circuit ratio power system. By mimicking the basic synchronization process of a synchronous generator, power synchronization control is able to perform satisfactorily in a low short-circuit ratio system, much as a synchronous generator can. Two algorithms are considered in the multi-converter, low short-circuit ratio systems: dq-axis vector current control and power synchronization control. Performance issues observed in single converter systems when dq-axis vector current control is applied are observed in the multi-converter systems. Additional sources of undesirable coupling between control loops at the current control level are observed, potentially placing more demands on the design of the outer control loops. Power synchronization control performs satisfactorily in the multi-converter systems; however, oscillatory behaviour does arise, which requires careful tuning of the controllers. In addition, it is shown that the introduction of converters using power synchronization control enables other converters (in the same system) using dq-axis vector current control to exhibit improved performance. This is due to power synchronization control causing a converter to act as an effective voltage source/regulator,and dq-axis vector current control relying on electrical proximity to a strong voltage source. This produces systems with improved conditioning, which will reduce the complexity of the design of outer controllers for dq-axis vector current controlled converters. Keywords: control, modelling, HVDC, power systems, stability, voltage-source converter, weak ACsystems, multiple-converter systems, power system plannin
Cognitive feature fusion for effective pattern recognition in multi-modal images and videos
Get PDFImage retrieval and object detection have been always popular topics in computer vision, wherein feature extraction and analysis plays an important role. Effective feature descriptors can represent the characteristics of the images and videos, however, for various images and videos, single feature can no longer meet the needs due to its limitations. Therefore, fusion of multiple feature descriptors is desired to extract the comprehensive information from the images, where statistical learning techniques can also be combined to improve the decision making for object detection and matching. In this thesis, three different topics are focused which include logo image retrieval, image saliency detection, and small object detection from videos. Trademark/logo image retrieval (TLIR) as a branch of content-based image retrieval (CBIR) has drawn wide attention for many years. However, most TLIR methods are derived from CBIR methods which are not designed for trademark and logo images, simply because trademark/logo images do not have rich colour and texture information as ordinary images. In the proposed TLIR method, the characteristic of the logo images is extracted by taking advantage of the color and spatial features. Furthermore, a novel adaptive fusion strategy is proposed for feature matching and image retrieval. The experimental results have shown the promising results of the proposed approach, which outperforms three benchmarking methods. Image saliency detection is to simulate the human visual attention (i.e. bottom-up and top-down mechanisms) and to extract the region of attention in images, which has been widely applied in a number of applications such as image segmentation, object detection, classification, etc. However, image saliency detection under complex natural environment is always very challenging. Although different techniques have been proposed and produced good results in various cases, there is some lacking in modeling them in a more generic way under human perception mechanisms. Inspired by Gestalt laws, a novel unsupervised saliency detection framework is proposed, where both top-down and bottom-up perception mechanisms are used along with low level color and spatial features. By the guidance of several Gestalt laws, the proposed method can successfully suppress the backgroundness and highlight the region of interests. Comprehensive experiments on many popular large datasets have validated the superior performance of the proposed methodology in benchmarking with 8 unsupervised approaches. Pedestrian detection is always an important task in urban surveillance, which can be further applied for pedestrian tracking and recognition. In general, visible and thermal imagery are two popularly used data sources, though either of them has pros and cons. A novel approach is proposed to fuse the two data sources for effective pedestrian detection and tracking in videos. For the purpose of pedestrian detection, background subtraction is used, where an adaptive Gaussian mixture model (GMM) is employed to measure the distribution of color and intensity in multi-modality images (RGB images and thermal images). These are integrated to determine the background model where biologically knowledge is used to help refine the background subtraction results. In addition, a constrained mean-shift algorithm is proposed to detect individual persons from groups. Experiments have fully demonstrated the efficacy of the proposed approach in detecting the pedestrians and separating them from groups for successfully tracking in videos.Image retrieval and object detection have been always popular topics in computer vision, wherein feature extraction and analysis plays an important role. Effective feature descriptors can represent the characteristics of the images and videos, however, for various images and videos, single feature can no longer meet the needs due to its limitations. Therefore, fusion of multiple feature descriptors is desired to extract the comprehensive information from the images, where statistical learning techniques can also be combined to improve the decision making for object detection and matching. In this thesis, three different topics are focused which include logo image retrieval, image saliency detection, and small object detection from videos. Trademark/logo image retrieval (TLIR) as a branch of content-based image retrieval (CBIR) has drawn wide attention for many years. However, most TLIR methods are derived from CBIR methods which are not designed for trademark and logo images, simply because trademark/logo images do not have rich colour and texture information as ordinary images. In the proposed TLIR method, the characteristic of the logo images is extracted by taking advantage of the color and spatial features. Furthermore, a novel adaptive fusion strategy is proposed for feature matching and image retrieval. The experimental results have shown the promising results of the proposed approach, which outperforms three benchmarking methods. Image saliency detection is to simulate the human visual attention (i.e. bottom-up and top-down mechanisms) and to extract the region of attention in images, which has been widely applied in a number of applications such as image segmentation, object detection, classification, etc. However, image saliency detection under complex natural environment is always very challenging. Although different techniques have been proposed and produced good results in various cases, there is some lacking in modeling them in a more generic way under human perception mechanisms. Inspired by Gestalt laws, a novel unsupervised saliency detection framework is proposed, where both top-down and bottom-up perception mechanisms are used along with low level color and spatial features. By the guidance of several Gestalt laws, the proposed method can successfully suppress the backgroundness and highlight the region of interests. Comprehensive experiments on many popular large datasets have validated the superior performance of the proposed methodology in benchmarking with 8 unsupervised approaches. Pedestrian detection is always an important task in urban surveillance, which can be further applied for pedestrian tracking and recognition. In general, visible and thermal imagery are two popularly used data sources, though either of them has pros and cons. A novel approach is proposed to fuse the two data sources for effective pedestrian detection and tracking in videos. For the purpose of pedestrian detection, background subtraction is used, where an adaptive Gaussian mixture model (GMM) is employed to measure the distribution of color and intensity in multi-modality images (RGB images and thermal images). These are integrated to determine the background model where biologically knowledge is used to help refine the background subtraction results. In addition, a constrained mean-shift algorithm is proposed to detect individual persons from groups. Experiments have fully demonstrated the efficacy of the proposed approach in detecting the pedestrians and separating them from groups for successfully tracking in videos
Random rectangular networks : theory and applications
Get PDFThe world is full of complex systems, with many interconnected parts interacting in some way, and the whole system cannot be understood simply by looking at each part individually. Instead, it is necessary to consider the system as a whole, which may exhibit emergent behaviour as a result of the many interconnections. Network theory is a very powerful tool for analysing complex systems, and has been applied to a wide range of phenomena with great success.This work is concerned with spatial networks, which are the ones that are naturally embedded in physical space in some way. For example, wireless sensor networks in a geographical region such as a city where the flow of information is essential, or plant populations in a crop field where it is important to understand and try to limit the spread of diseases. Another example is the rocks found deep underground in the Gulf of Mexico that are highly fractured; these fractures can clearly be thought of as spatially embedded networks through which fluids such as oil and gas can flow. There is great commercial interest in efficiently extracting the oil and gas from the rocks, and there are also serious efforts to use the depleted rocks as a means of carbon sequestration to help combat the problem of greenhouse gases. Therefore, it is clearly important to understand the nature of the structure and dynamical properties of these real-world networks.It is intuitive that the topological and dynamical properties of spatial networks depend on the shape of the space in which they are embedded. In this work we discuss the generalisation of two spatially-defined random graph models to consider nodes located in a unit rectangle. We generalise the random geometric graph (RGG) to the random rectangular graph (RRG), and the relative neighbourhood graph (RNG) to the rectangular relative neighbourhood graph (RRNG).We found an analytic expression for the expected value of the average node degree of RRGs, as well as useful bounds for the diameter, the average path length, and the algebraic connectivity, and approximations to the degree distribution, connectivity, and clustering coefficient. For the RRNGs we found an approximation to the average node degree and a bound on the diameter and algebraic connectivity.Using this generalisation, we examine the behaviour of diffusion in RRGs and find that increasing the elongation causes diffusive particles to spread more slowly. We also discuss some results relating to epidemics in crop fields, where we show that elongating the field makes it more difficult for a disease to become epidemic. Finally, we find that the relative neighbourhood graphs work well to mimic the properties of the rock fracture networks compared to other null models, and we are able to optimise the value of the elongation in the model for each fracture network.The world is full of complex systems, with many interconnected parts interacting in some way, and the whole system cannot be understood simply by looking at each part individually. Instead, it is necessary to consider the system as a whole, which may exhibit emergent behaviour as a result of the many interconnections. Network theory is a very powerful tool for analysing complex systems, and has been applied to a wide range of phenomena with great success.This work is concerned with spatial networks, which are the ones that are naturally embedded in physical space in some way. For example, wireless sensor networks in a geographical region such as a city where the flow of information is essential, or plant populations in a crop field where it is important to understand and try to limit the spread of diseases. Another example is the rocks found deep underground in the Gulf of Mexico that are highly fractured; these fractures can clearly be thought of as spatially embedded networks through which fluids such as oil and gas can flow. There is great commercial interest in efficiently extracting the oil and gas from the rocks, and there are also serious efforts to use the depleted rocks as a means of carbon sequestration to help combat the problem of greenhouse gases. Therefore, it is clearly important to understand the nature of the structure and dynamical properties of these real-world networks.It is intuitive that the topological and dynamical properties of spatial networks depend on the shape of the space in which they are embedded. In this work we discuss the generalisation of two spatially-defined random graph models to consider nodes located in a unit rectangle. We generalise the random geometric graph (RGG) to the random rectangular graph (RRG), and the relative neighbourhood graph (RNG) to the rectangular relative neighbourhood graph (RRNG).We found an analytic expression for the expected value of the average node degree of RRGs, as well as useful bounds for the diameter, the average path length, and the algebraic connectivity, and approximations to the degree distribution, connectivity, and clustering coefficient. For the RRNGs we found an approximation to the average node degree and a bound on the diameter and algebraic connectivity.Using this generalisation, we examine the behaviour of diffusion in RRGs and find that increasing the elongation causes diffusive particles to spread more slowly. We also discuss some results relating to epidemics in crop fields, where we show that elongating the field makes it more difficult for a disease to become epidemic. Finally, we find that the relative neighbourhood graphs work well to mimic the properties of the rock fracture networks compared to other null models, and we are able to optimise the value of the elongation in the model for each fracture network
The evaluation of targeted radionuclide therapies and radio sensitising agents in malignant melanoma
No full textIntroduction: Malignant melanoma is highly resistant to conventional cancer therapies, characterised by a broad spectrum of radio resistance combined with a low response to chemotherapeutics. This state is compounded by inadequate dose delivery of conventional radiotherapy options. A targeted approach to radiotherapy exploiting native features of the melanoma cells such as melanin may in combination with radiosensitizing agents may improve the effectiveness of therapy towards the disease. Aims: The aims of this study were three-fold: • To assess the effectiveness of the melanin binding radionuclide [131I]MIP1145 in the treatment of malignant melanoma in vitro and in vivo. • To investigate whether malignant melanoma cell lines and xenografts can berendered susceptible to [131I]MIBG radionuclide therapy via transfection invitro with noradrenaline transporter (NAT) and via gene delivery in vivo withthe HSV1716/NAT vector. • To screen novel DNA repair and IKKβ Inhibitors in combination with X-Ray radiation to determine suitability for future targeted radiotherapy/drug combination therapy approaches. Results: [131I]MIP1145 demonstrated accumulation and retention accompanied by considerable reductions in cell survival and tumour burden in melanotic melanomacell lines and tumour Xenografts. Additionally, a modest uptake and cytotoxic effect of [131I]MIBG was observed following transfection with the noradrenaline transporter in vitro. Xenografts bearing NAT transfected melanoma cells demonstrated tumour growth delay when treated with [131I]MIBG. HSV1716/NAT Successfully delivered the NAT gene to melanoma tumours in vivo demonstrated high tumour specificity and tumour growth delay. The MRE11 inhibitor Mirin produced cytoxicity in vitro but not in vivo when combined with 2Gy X-ray radiation, reducing but not inhibiting γH2AX foci clearance post radiation treatment. The novel IKKβ Inhibitors SU567 and SU182 produce effects consistent with IKKβ inhibition and are cytotoxic to melanoma celllines, enhancing 1Gy X-ray induced DNA damage and produce marked alterations in the cell cycle of treated cells. Conclusions: Melanoma tumours can be successfully targeted both endogenously and exogenously with radionuclide therapy. Investigations with novel radiosensitising agents identified that the MRE11 inhibitor Mirin produced a mild reduction in cell survival at drug concentrations as both as a single treatment and as a pre-treatment to 2Gy X-ray irradiation. Novel IKKβ inhibitors induce cytotoxity and enhance 1GY Xr-ray [sic] toxicity compared to X-ray treatment alone.Introduction: Malignant melanoma is highly resistant to conventional cancer therapies, characterised by a broad spectrum of radio resistance combined with a low response to chemotherapeutics. This state is compounded by inadequate dose delivery of conventional radiotherapy options. A targeted approach to radiotherapy exploiting native features of the melanoma cells such as melanin may in combination with radiosensitizing agents may improve the effectiveness of therapy towards the disease. Aims: The aims of this study were three-fold: • To assess the effectiveness of the melanin binding radionuclide [131I]MIP1145 in the treatment of malignant melanoma in vitro and in vivo. • To investigate whether malignant melanoma cell lines and xenografts can berendered susceptible to [131I]MIBG radionuclide therapy via transfection invitro with noradrenaline transporter (NAT) and via gene delivery in vivo withthe HSV1716/NAT vector. • To screen novel DNA repair and IKKβ Inhibitors in combination with X-Ray radiation to determine suitability for future targeted radiotherapy/drug combination therapy approaches. Results: [131I]MIP1145 demonstrated accumulation and retention accompanied by considerable reductions in cell survival and tumour burden in melanotic melanomacell lines and tumour Xenografts. Additionally, a modest uptake and cytotoxic effect of [131I]MIBG was observed following transfection with the noradrenaline transporter in vitro. Xenografts bearing NAT transfected melanoma cells demonstrated tumour growth delay when treated with [131I]MIBG. HSV1716/NAT Successfully delivered the NAT gene to melanoma tumours in vivo demonstrated high tumour specificity and tumour growth delay. The MRE11 inhibitor Mirin produced cytoxicity in vitro but not in vivo when combined with 2Gy X-ray radiation, reducing but not inhibiting γH2AX foci clearance post radiation treatment. The novel IKKβ Inhibitors SU567 and SU182 produce effects consistent with IKKβ inhibition and are cytotoxic to melanoma celllines, enhancing 1Gy X-ray induced DNA damage and produce marked alterations in the cell cycle of treated cells. Conclusions: Melanoma tumours can be successfully targeted both endogenously and exogenously with radionuclide therapy. Investigations with novel radiosensitising agents identified that the MRE11 inhibitor Mirin produced a mild reduction in cell survival at drug concentrations as both as a single treatment and as a pre-treatment to 2Gy X-ray irradiation. Novel IKKβ inhibitors induce cytotoxity and enhance 1GY Xr-ray [sic] toxicity compared to X-ray treatment alone
From Pittsburgh to Pressburg : the transatlantic Slovak national movement, 1880-1920
Get PDFBetween 1870 and 1920, half a million Slovak-speaking migrants left the Kingdom of Hungary for the United States of America. They represented one fifth of the world's Slovak-speaking population. During this mass, transatlantic Slovak migration, Slovak nationalism in Hungary was transformed from a fringe idea into a serious political goal. The resulting Slovak national movement helped create the First Czechoslovak Republic (1918-1938), a state whose mostly Czech leaders pledged to support Slovak national rights. The multilingual region known as 'Upper Hungary' from which Slovak-speakers had left was given a new, ethnically-based name: Slovakia, which was imagined as a national, territorial homeland for Slovak speakers, and still in existence today.This critical period of change in Slovak nationalist thought has yet to be properly understood. This is because scholarship on Slovak nationalism in the new world has been artificially separated from research into Slovak nationalism in the old country. Although the role played by the emerging Slovak American community in campaigning for a Czecho-Slovak state during the First World War has been recognised, the wider significance of Slovak American political institutions, fraternal organisations and the Slovak migrant press in shaping Slovak nationalist activism has not. Historians of the Slovak-American community, on the other hand, have yet to influence debates on Slovak political nationalism. By combining two historiographical traditions that largely talk past one another, this study uncovers the transatlantic Slovak national movement that formed between nationalist leaders in Upper Hungary and the migrant colony in the United States. Based on extensive research in Slovak and Slovak-American archives in both the USA and Slovakia, this dissertation demonstrates that a transatlantic Slovak political movement in the late nineteenth century brought about the creation of a Slovak national homeland in the twentieth.Between 1870 and 1920, half a million Slovak-speaking migrants left the Kingdom of Hungary for the United States of America. They represented one fifth of the world's Slovak-speaking population. During this mass, transatlantic Slovak migration, Slovak nationalism in Hungary was transformed from a fringe idea into a serious political goal. The resulting Slovak national movement helped create the First Czechoslovak Republic (1918-1938), a state whose mostly Czech leaders pledged to support Slovak national rights. The multilingual region known as 'Upper Hungary' from which Slovak-speakers had left was given a new, ethnically-based name: Slovakia, which was imagined as a national, territorial homeland for Slovak speakers, and still in existence today.This critical period of change in Slovak nationalist thought has yet to be properly understood. This is because scholarship on Slovak nationalism in the new world has been artificially separated from research into Slovak nationalism in the old country. Although the role played by the emerging Slovak American community in campaigning for a Czecho-Slovak state during the First World War has been recognised, the wider significance of Slovak American political institutions, fraternal organisations and the Slovak migrant press in shaping Slovak nationalist activism has not. Historians of the Slovak-American community, on the other hand, have yet to influence debates on Slovak political nationalism. By combining two historiographical traditions that largely talk past one another, this study uncovers the transatlantic Slovak national movement that formed between nationalist leaders in Upper Hungary and the migrant colony in the United States. Based on extensive research in Slovak and Slovak-American archives in both the USA and Slovakia, this dissertation demonstrates that a transatlantic Slovak political movement in the late nineteenth century brought about the creation of a Slovak national homeland in the twentieth
Partial discharge behaviour under AC and DC conditions including novel manufacture techniques for void-type dielectric samples
Get PDFThe move from centralised electricity generation, near centres of demand, to distributed generation has brought justification for the use of high voltage direct current (HVDC) transmission techniques. One key application is the transmission of power from offshore wind farms, there is a breakeven distance where conventional high voltage alternating current (HVAC) transmission is less cost effective than HVDC transmission.;The condition monitoring of HVDC transmission networks will be paramount to minimise any unnecessary system downtime. The primary method to monitor the condition of an insulation system is the measurement of partial discharge (PD). This thesis develops the understanding around sensor installation, sample behaviour under DC conditions and novel manufacture methods for void type dielectric samples.;The first area of interest to this thesis was the development of a method to assess the effect of the electromagnetic field emissions from HVDC converter station on the behaviour of high frequency current transformers (HFCT). A range of sensors of different constructions were tested in a controlled electromagnetic field environment. The relative immunity of the sensors to the incident field was derived using the method.;The second phase of this work investigated the behaviour of a range of dielectric samples under AC and DC conditions. Existing analysis techniques were explored based on recommendations in IEC 60270 and literature to date. The behaviour of a void type sample was explored further through the variation of test history such as; grounding period, DC polarity and AC/DC variation.;The final section of research focused on the development of novel manufacturing techniques and the behaviour of void type samples under AC and DC conditions. The proposed techniques made use of two very different manufacturing approaches; 3D printing and subsurface laser etching (SSLE). In this study, 3D printing was found to be more successful in enabling void type PD behaviour. Initial explorations were made of AC/DC PD behaviour of multiple void samples and thermally aged samples.The move from centralised electricity generation, near centres of demand, to distributed generation has brought justification for the use of high voltage direct current (HVDC) transmission techniques. One key application is the transmission of power from offshore wind farms, there is a breakeven distance where conventional high voltage alternating current (HVAC) transmission is less cost effective than HVDC transmission.;The condition monitoring of HVDC transmission networks will be paramount to minimise any unnecessary system downtime. The primary method to monitor the condition of an insulation system is the measurement of partial discharge (PD). This thesis develops the understanding around sensor installation, sample behaviour under DC conditions and novel manufacture methods for void type dielectric samples.;The first area of interest to this thesis was the development of a method to assess the effect of the electromagnetic field emissions from HVDC converter station on the behaviour of high frequency current transformers (HFCT). A range of sensors of different constructions were tested in a controlled electromagnetic field environment. The relative immunity of the sensors to the incident field was derived using the method.;The second phase of this work investigated the behaviour of a range of dielectric samples under AC and DC conditions. Existing analysis techniques were explored based on recommendations in IEC 60270 and literature to date. The behaviour of a void type sample was explored further through the variation of test history such as; grounding period, DC polarity and AC/DC variation.;The final section of research focused on the development of novel manufacturing techniques and the behaviour of void type samples under AC and DC conditions. The proposed techniques made use of two very different manufacturing approaches; 3D printing and subsurface laser etching (SSLE). In this study, 3D printing was found to be more successful in enabling void type PD behaviour. Initial explorations were made of AC/DC PD behaviour of multiple void samples and thermally aged samples
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