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Owing to the specific characteristics of unmanned aerial vehicles (UAVs), the demands and applications increase dramatically for them being deployed in extremely confined or closed space for surveying, inspection or detection to substitute human. However, global positioning system (GPS) may lose effectiveness or become unavailable due to the potential signal block or interference in such environments. Under such circumstances, an imperative requirement on new positioning technology for UAV has emerged. With the rapid development of radio frequency (RF) based localisation technologies, especially for the ultra-wideband (UWB) based localisation technology, leveraging small wireless sensor nodes for low cost, low latency, low energy consumption and accurate localisation on UAV has received significant attention. However, the research challenges and issues such as the unreasonable values within the UWB measurements, the geometry configurations of the anchor nodes in the extremely confined environments, the requirement of the prior information, the performance influence from the unpredictable propagation condition and the geomagnetic disturbances for inertial measurement unit (IMU) still exists which limit the applications on UAV. To avoid these aforementioned research challenges and issues, the researches in this thesis are carried out from different perspectives. Firstly, the maximum iii Chapter 0. Abstract likelihood estimation (MLE) based algorithm plus with the anchor distribution strategy is proposed focused on the development of the pure UWB based localisation system. With the proposed algorithm and strategy, the most suitable geometry configurations of the anchor node can be found to achieve the accurate and robust UAV positioning in focused environments. However, considering the unreasonable values within the UWB measurements still have the huge impact on the localisation performance for the pure UWB based localisation approach, according to the simulation and experiment, the investigation on the sensor fusion based approaches which integrated the IMU and UWB is carried out. To overcome the performance degradation and oscillation leads by the unreasonable values, the extended Kalman filter (EKF) based algorithm can be seen as the ideal candidate, owing to the implementation simplicity and acceptable accuracy. Yet, the unknown prior information about the noise covariance matrices still has the great impact on the localisation performance, especially for the applications in the extremely confined environment. To mitigate the effects, in this thesis, a high precision UAV positioning system which integrates the IMU and UWB with the adaptive extended Kalman filter (AEKF) is proposed. Compared with the traditional EKF based approach, the estimated and recorded information from previous processes is exploited to adaptively estimate and further control the estimation of the noise covariance matrices for performance improvement. Nevertheless, the proposed AEKF algorithm and system still suffer from the performance influence caused by the geomagnetic disturbances for the additional IMU. To remedy this for further performance improvement, in this thesis, the tightly coupled adaptive extended Kalman filter (TC-AEKF) based algorithm is proposed. With the additional angular rate in the state prediction process and iv Chapter 0. Abstract the adaptively estimated noise covariance matrices, the proposed algorithm can significantly improve the localisation performance in the focused environments, according to the simulations and experiments. Even the proposed AEKF and TC-AEKF based algorithm can attain the high accuracy and precision localisation performance of the UAV in focused environments, however, there is still limitation for the proposed algorithm. Due to the principal of the proposed algorithms, the additional linearisation process is required in the correction process. Currently, the first order Taylor expansion is utilised for the linearisation of the observation matrix. This may directly lead to the performance degradation and oscillation, owing to the neglected high order terms. To mitigate the effect, in this thesis, an adaptive square root cubature Kalman filter (ASRCKF) based sensor fusion algorithm is proposed. With the integration of the IMU and UWB, the utilisation of the cubature rule, the adaptively estimated noise covariance matrices and the added estimation weighting factors, the performance degradation and oscillation led by the unreasonable value within the ranging information, the linearisation of the observation matrix and the unknown and hard-to-adjust noise covariance matrices can all be resolved. Finally, from the numerical simulations, experiments and autonomous inspection flight test, it can be proved that the proposed algorithm and system can attain 0.081m median error, 0.172m 95th percentile error and 0.045m average standard deviation (STD), which is feasible for the autonomous inspection in the focused environments.

As a concept imported from the West during the Meiji period, the notion of 'public space' did not exist in Japan before. Besides, the cultural differences in understanding 'space' and 'form', resulted in the newly coined Japanese term '"public" space' - 'kōkyō kūkan'- and its spatial materiality with more complexity, ambiguity, and multiple meanings contained today, showing the uniqueness and geographical, historical, and socio-cultural differences in theorizing, and evaluating 'public space'. Hiroba is usually regarded as functionally equal to the Western plaza or square and the prototype of Japanese public space. A retrospective review of the typological evolution of hiroba in Japanese public space development is explored. The research resurrects the term of hiroba as a concept in Japanese-type hiroba or Japanese hiroba, instead of hiroba usually as a model through formal imitation imported from the Western-type hiroba and later be applied in Japan. It finds the changing notions of 'public' (and its physical form in the typology of hiroba) in Japan and the close relationship between place-making and hiroba-ka in open space, Japanese kōkyō kūkan and hiroba-ka open space generated through architectural design by Japanese architects. The research aims to understand the Japanese hiroba-ka open space within contemporary Japanese architecture and interpret its notions of 'public' behind it. Four case studies are chosen to explore the three main questions: typology, human behaviour, and their interaction and relation in generating hiroba and the notions of 'public' behind this process. The research finds that a series of spatial elements and attachment elements are conducive to the constitution of the physical setting of hiroba-ka open space. The spatial configuration of those elements is closely related to human behaviour. The open space typologies of those spatial elements in making hiroba in the four cases are extracted and analysed on their spatial meanings and characters. It argues that both typology and human behaviour are indispensable to the generation of hiroba-ka open space within Tokyo's contemporary architecture. The hiroba-ka open space, therefore, is socially constructed place-making open space through the interaction between people and space through time. The research concludes that different from the lament on the fall of public space in most Western cities, Japan, as a country that lacks the notion of 'public' and spatial conditions to provide public space in the Western sense, has made a considerable achievement today. Japan has developed its own interpretation of 'public' and unique 'public' space -kōkyō kūkan by synthesis and dialogue between Western public space and Japanese hiroba adapting to the changing society.

With the development of artificial intelligence, computer pattern recognition has also been applied in different scenarios. This thesis focuses on facial expression recognition to improve the generalisation ability of the model, and the accuracy of the facial expression recognition system. Various facial expression recognition models and systems have been proposed. However, when applied to other untrained datasets, the performance is often suboptimal. The innovation of this thesis lies in the processing of the dataset to improve the generalisation ability of the model by using local abstract features. By extracting the main local features, analysing the facial expression information contained in the local regions and sorting the local regions, better input data choices can be provided for other facial expression recognition systems. By using local binary patterns and support vector machine experiments, I found that the mouth contains more facial expression information. Local regions can effectively improve the generalisation ability of the model. The regions selected are the eyes and eyebrow region, the nose and mouth region and the mouth and chin region. The eyes region and the mouth and chin region seem to 'hold' most clues to a person's mood. Three local facial expression features were experimentally combined. When the features of the eyes, nose and mouth were combined, the recognition accuracy was 50.23%. This result indicates a significant improvement in recognition results compared with the crossdatabase FER results reported in the literature, and the 5.71% increase in recognition accuracy is a significant improvement. The results of three applied algorithms for local regions of different sizes are analysed. The general trend is that as facial expression information is lost in most regions, the recognition accuracy also decreases. For machine-based recognition systems, the eye region and mouth region carry most of the useful information about a person's emotional state. However, the relatively low importance of the nose region for the facial expression recognition task can sometimes interfere with the experimental results, particularly when the number of training images is limited. When the input data are improved without changing the research model and are preprocessed, the effective facial expression area is extracted instead of using the full face for input. This process can effectively improve the accuracy of facial expression recognition and improve the method ability of the model. That is, when using untrained data for testing, better effective results can be obtained, which is conducive to the use of the model in reality.

The dynamic capability theory, the advanced version of the Resource-based View and a classic theory in the strategic management field, provides academics with an evolutionary perspective to understand organisational resource management. The dominant take of dynamic capability studies tends to emphasise top managers and the firm's leading role in reconfiguring organisational resources and creating new competencies to react to environmental changes. Thus far, I have a majority of dynamic capability studies adopting an inward-looking view that highlights profound decisions and systematic activities solely dominated by the firm. Nevertheless, a limited outward-looking view is adopted to study the phenomenon of the opening ecosystem. As an emerging phenomenon, the opening digital platform ecosystem has been attracting the attention of strategic management scholars. The main characteristic that differentiates the opening digital platform organisation from traditional organisations is that it requires us to see things from an ecosystem level and discuss the profitability of a loosely organised community rather than an individual. The idea of an opening ecosystem highlights the distributed responsibility of innovation and seizing opportunities. The platform organisation can benefit from complementary contributions and co-evolve with external parties by engaging various cross-industry members in the ecosystem. In addition, the basic component of a digital platform organisation-generative technologies facilitates the organisation to leverage external innovations and create a wide range of unpredictable applications. Thus, making the evolutionary path of a digital platform less fixed and depending more on emerging solutions and situated capabilities. Therefore, I argue that the extant firm-level logic of the dynamic capability view is insufficient for explaining the unique strategy of an opening digital platform. I need to shift the view to outside the organisation and incorporate more focus on the efforts of external parties in the value-creating process. I, thus, decide to react to the growing callings of further exploring the orchestration of ecosystems through the dynamic capability theoretical lens. The primary purpose of my research is to understand what kinds of dynamic capabilities facilitate the growth of an opening platform ecosystem and how these dynamic capabilities sustain dynamism while encountering rapid growth and extreme uncertainties. My primary research questions are divided into two parts. First, I directly tackle how platform organisations build and sustain rapid growth. By road mapping the growing path of an opening digital platform, I tried to understand what dynamic capabilities allow the platform to incorporate external efforts and how it achieves fast growth. Second, I try to further unfold the internal process of a digital platform organisation by studying how middle managers' routines support the dynamic capability of a digital platform organisation. I further explore the internal activities that support the dynamism of an opening digital platform organisation. By trying to answer these two questions, I endeavour to unfold the mechanism of an opening digital platform ecosystem deeply. I take processual studies of one of the top Chinese digital platform organisations-Tencent and deeply unfold its growing path and resource reconfiguration processes. I aim to generate context-specific, detailed and holistic explanations that are impossible to develop by quantitative research. Through my inductive single case studies, I uncover complex interactions among elements such as the organisation, members of the organisation and the ecosystem, projects, culture and behaviours of different actors in the context of a digital platform organisation. I choose the single case study because it allows us to focus on an extreme sample and conduct historical case study to observe interplays among different constructions within the phenomenon. My findings are 19 process models, which reveal resource reconfiguration processes inside and outside the platform organisation. These process models show how resources are reconfigured during interactions among external parties, the platform organisation, managers and employees. I, therefore, contribute to the dynamic capability theory from the following perspectives. First, I submit that departing from the traditional firm-level logic, the value proposition of the digital platform organisation could be highly externalised. Rather than keeping the process controlled internally and relying on the knowledge and experiences of top managers, issues and understandings of the market would gradually emerge as the platform shares resources with externals and gains feedback from them. Then, the new understanding of the market would, in turn, guide resource reconfiguration activities and create new competencies. Thus, the growth of a digital platform organisation is not a unilateral manager-led process; it is a highly malleable and interactive process engaging both the platform leader and external parties. Second, the leadership of the digital platform and top managers have depreciated significantly. The platform no longer plays the role of a "broker" and dominate the design of organisation strategy. Despite that, extant dynamic capability studies emphasise the power and control of the firm and top managers; I highlight that platform users and complementors are not entirely under control. Complementors are the external actors who interact with the focal firm to generate and commercialise innovations that benefit the end customer. Complementors provide the platform organisation with their resources, capabilities, and innovations to enable customers to utilise the final product, rather than the firm itself (e.g., Adner 2012; Adner and Kapoor 2010; Kapoor and Lee 2013). Consequently, the concept of the ecosystem aims to capture the connection between a core product, its components, and its complementary products/services ("complements"), which collectively enhance the value for customers. Such a shifting leadership requires the managerial focus to shift from controlling the activities of complementors to providing resources and facilitating innovations. I find that platform evolution is not an isolated activity conducted by the organisation. Instead, the evolution is interconnected with a diverse range of stakeholders. The responsibility of an opening platform is to align internal and external value-creation activities and achieve continuous growth while helping external parties grow, develop products and conduct innovations. Finally, yet importantly, I emphasise resource versatility rather than resource control. The traditional resource-managing logic of dynamic capability studies still focuses on controlling resources and developing an "isolating mechanism". Instead, I argue that platform resources need to be shared around different actors in the ecosystem to facilitate the development of market understandings and the creation of multiple applications. Platform leaders should focus less on controlling and isolating their resources and try to stimulate more peripheral innovations and contributions by supporting different actors with platform resources. Thus, avoiding the sticky nature of organisational resources.

Dense suspensions of solid particles immersed in a liquid are ubiquitous in industries. Understanding the rheology of dense suspensions plays an important role in improving industrial processes. In this thesis, the coupling of the Lattice Boltzmann Method (LBM), a class of computational fluid dynamics (CFD) methods for fluid simulation, and the Discrete Element Method (DEM), an effective numerical method in the analysis of granular systems, have been employed to simulate the non-Brownian dense suspensions. Such LBDEM simulations can capture the detailed flow field in the particle level and reveal the effect of the interactions between background fluid and particles. We conduct DEM simulations of a binary model system composed of frictional and frictionless particles (Chapter 4) and investigate the relationship between the jamming volume fraction of dense suspension and the fraction f of frictional contacts, which is determined by the fraction of frictional particles. By comparing our data with simulations of shear thickening suspensions, which introduce a transition between frictional and frictionless contacts by the Critical Load Model (CLM), we show that the Wyart-Cates model of shear thickening is incomplete. The shear-thickening behaviour is then successfully captured by LB-DEM simulations of dense suspensions under simple shear (Chapter 5). The difference between LBDEM and DEM simulations of suspensions can be minor in terms of the bulk rheology because the averaged velocity fields under simple shear are similar for these two simulation approaches. The third part is the LBDEM simulations of pressure-driven flow in the square channel (Chapter 6), where interactions between fluid and particles are not negligible and cannot be captured by DEM simulations. We capture the shear-induced migration of suspensions in the channel and look into the effect of friction in the migration process. With detailed information of the fluid phase from LBM and the solid phase from DEM, we examine the suspension balance model for different volume fractions and friction coefficients. These results can serve as a database for the further theoretical study of pressure-driven flow.

Silicon (Si) has become an attractive alternative to graphite (Gr) as an anode material for the next generation lithium-ion batteries (LIBs) due to its high theoretical capacity, natural abundance, and reasonable electrode potential. However, Si-based electrodes exhibit distinct electrochemical and thermal behaviors compared to traditionally used carbonaceous electrode, and there have been rare models tailored to the behaviors of Si-based electrodes. Therefore, this thesis aims to develop physics-based models able to describe and predict the electrochemical and thermal behaviors of Si-based electrodes, which can serve as important tools for understanding and designing LIBs with Si-based anodes. A mechanistic model of silicon anodes in LIBs is first developed to describe the unique voltage hysteresis phenomenon of silicon electrodes. The model correlates the voltage hysteresis of Si to its underlying phase transformation, crystallization and amorphization processes. The effects of crystallization rate and surface energy barriers are studied, unveiling the role of surface energy and particle size in determining the performance behaviors of Si. Subsequently, a multi-material model is developed for simulating Si/Gr composite electrodes, considering different behaviors of Gr and Si. Results show that silicon introduces voltage hysteresis to Si/Gr electrodes. The (de)lithiation sequence and competing processes between Si and Gr are comprehensively studied. A dimensionless competing factor is derived to quantify the active operating regions for each material, and demonstrates to be a useful indicator to design cycling protocols for mitigating the degradation of composite electrodes. The multi-material model is further coupled with a thermal submodel. By studying the respective heat contributions of each active material, the model reveals the origin of thermal peaks of Si/Gr composite electrodes, which are highly related to the phase transition processes of Gr. These thermal peaks can be potentially used to detect the ageing of Si-based batteries in service.

An effective and efficient CFD simulation is of high importance to accelerate the design activities of twin screw machines. However, mesh generation for screw machines with large helix angles can produce highly skewed numerical cells which can make simulation unreliable. From the established literature, the two main approachesto generate structured deforming mesh for CFD analysis of twin screw machines are algebraic and differential. The purpose of this thesis is to explore grid generation techniques suitable for 3D numerical modelling of rotatory positive displacement machines with large helix angles. Both cut-cell cartesian and body-fitted grid generation methods are investigated for analysis of machines with different profiles and helix angles. The conservation and simulation accuracy of cut-cell cartesian method was first evaluated using a simple piston cylinder example and a hook and claw rotor profile used in vacuum pump which is difficult to set by a body fitted mesh. It was shown that even with coarse initial mesh, such profiles could have been analysed using a cut-cell cartesian mesh, but it required special model to account for leakage flows. Secondly, screw machines with low helix angle are used to examine the capability of both grid generation methods. ANSYS CFX was used for analysis of body fitted mesh produced by SCORG grid generator, while ANSYS Forte was used for evaluation of cut-cell cartesian method. Thirdly, oil-injected twin screw compressor with intermediate helix angle was explored using body-fitted method. In addition, a case study of a twin-screw vacuum pump with higher helix angle of 62 degree was studied using SCORG and FLUENT to further explore the body-fitted method. Lastly, a twin-screw vacuum pump with variable pitch and cusp points was analysed using cut-cell cartesian method. These five case studies demonstrated advantages and disadvantages of body-fitted and cut-cell cartesian methods for low, intermediate, and large helix angles. This thesis then proposes development of an alternative method called a normal grid generation method which is expected to improve mesh quality of a body fitted mesh for screw machine with large helix angles and in turn could improve accuracy of flow calculation.

Chinese idioms comprise word strings of various lengths, ranging from three to eight characters (Luo, 2015). Four-character idioms (FCIs) constitute the largest group among all Chinese idioms. Different syntactic patterns have been identified among FCIs, namely, 1+1+1+1, 1+3, and 2+2, whereby each digit stands for the number of characters that constitute a syntactic unit. Among these, the 2+2 construction (henceforth, AABB) is found to be most widely distributed (Wang et al. 2013). Two types of 2+2 FCIs have been identified in the present study: (a) interchangeable 2+2 FCIs whose two units can replace each other (i.e., AABB or BBAA) and (b) non-interchangeable 2+2 FCIs whose two units cannot substitute each other (i.e., only AABB but not BBAA). For instance, 黑白混淆 (hēi-bái-hùn-xiáo: black-white-mix-confuse, "to garble things up like mixing black and white colours together") can be re-constructed as 混淆黑白 (hùn-xiáo-hēi-bái, mix-confuse-black-white), but 做贼心虚 (zuò-zéi-xīn-xū, become-thief-heart-empty, "to feel guilty like a thief having stolen something") cannot be re-constructed as 心虚做贼 (xīn-xū-zuò-zéi, heart-empty-become-thief). Prior studies (Chen 2001; Su 2002; Tao 2002; Zuo 2006; Nall 2008) have identified combinatory relationships in FCIs from a Construction Grammar perspective (Goldberg 1995, 2006). However, none has provided an in-depth diachronic account of the differences between interchangeable and non-interchangeable 2+2 FCIs in terms of internal constituency and propositional act functions (Croft, 2001). Similarly, structural mismatches between AABB and BBAA constructions in interchangeable FCIs have also not been adequately addressed in the literature. Finally, not much attention has been given to the partly schematic negative 2+2 construction [不 (bù, not) A 不 (bù, not) B] in terms of its functions. This thesis contains 8 chapters. Chapter 1 is the introduction which explains the aims and scope of this study. Chapter 2 is the literature review providing a description of idioms and idiomaticity. In particular, it deals with the basic concepts of Chinese idioms' classification and the research motivation for the Chinese FCIs. Chapter 3 is the literature review about the Construction Grammar and explains how construction grammar can be applied to Chinese FCI research. Chapter 4 is devoted to data collection and methodology. Chapter 5 makes a comparison between interchangeable and non-interchangeable 2+2 FCIs, while Chapter 6 is centred on AABB and BBAA patterns of interchangeable FCIs. Chapter 7 gives an account of the 2+2 [bù A bù B] construction in terms of internal constituency, propositional act function, and semantic prosody. Finally, chapter 8 is for the findings and conclusion. The present thesis argues that the internal constituency of Chinese 2+2 FCIs may affect their propositional act functions (cf. Croft 2001) in context and further lead a diachronic differentiation of interchangeable idioms vs non-interchangeable idioms. The former will appear to follow a directional path of constructional change, while the latter a non-directional one. This research also shows that three different mechanisms (attraction, differentiation, and substitution) may dictate the diachronic change between AABB and BBAA. This work aims to make a valuable contribution to the study of FCI constructions as it sets to explain (a) how interchangeable and non-interchangeable idioms evolve over time and (b) how the 2+2 [bù A bù B] construction shows a different behaviour than the general 2+2 constructions in terms of internal constituency, propositional act functions, and semantic prosody. Finally, the present analysis sheds new theoretical light not only on the linguistic representation of Chinese FCIs based on constructional schematicity, but also on the diachronic relationship between idiomaticity and creativity. Corpus data were obtained from Xinhua Dictionary of Idioms (Xu, 2002), the BLCU Corpus Center (BCC), zhTenTen Corpus and the Centre for Chinese Linguistics, PKU (CCL) and data manipulation and analysis of FCIs was implemented with Rstudio.

Crystallization is an essential unit operation for separating and purifying Active Pharmaceutical Ingredients (APIs) in pharmaceutical industry. Conventionally, crystallizers with moving parts such as stirred vessels are always used for crystallization operation. However, their applications are limited by relatively low heat and mass transfer efficiency as well as difficulty of scale-up. In recent years, there has been a growing interest in using fluidic devices without moving parts for crystallization since they can offer better mixing performance, scale-up capability, and small equipment footprint. Meanwhile, continuous operation is preferred for its unique features such as better control of crystal attributes, higher productivity, and lower operating costs. However, one of the main challenges for the fluidic devices applied in continuous crystallization domains is the limited residence time. The residence time cannot be augmented due to adverse influence of mixing intensity. In the experimental work of present research, a recently optimized design of fluidic oscillator along with two other fluidic devices namely helical coil and coiled flow inverter was used for continuous antisolvent crystallization of paracetamol from methanol-water solution. A loop configuration was designed to realize a higher residence time up to ~13.5 min without jeopardizing mixing in the fluidic devices. An offline imaging method using microscope, digital camera, and ImageJ software was employed to measure particle size distribution (PSD) of manufactured crystals. The lognormal distribution was then used to characterize the experimentally observed PSD. The impact of key operating conditions such as operational mode, configuration of the fluidic devices and residence time on PSD of produced paracetamol crystals was evaluated. Population balance equation (PBE) based model as an effective tool is always used for better insight of crystallization process. In the modelling work of present research, a population balance model coupling with conservation equations and crystallization kinetics was established to computationally interpret mixed semi-batch and batch as well as continuous antisolvent crystallization experiments under consideration. Standard method of moment and lognormal distribution with moments-related parameters σ and µ was utilized to simulate PSD. A lumped parameter, namely mixing coefficient C_mix was proposed to characterize the influence of non-ideal mixing on effective supersaturation and consequently PSD of produced crystals. The effectiveness of C_mix was examined in mixed semi-batch and batch operation under a short residence time of the loop (~200 s) as well as continuous operation under relatively large residence times of the loop (~6.5 and ~13.5 min). An effort was made to develop a relation between mixing coefficient C_mix with other process parameters such as residence time, degree of supersaturation, configurations of devices as well as seeds attributes. This thesis performed experimental and computational investigations of antisolvent crystallization of paracetamol in methanol-water solution using fluidic devices without moving parts. Two key points were observed from this research. Firstly, it was found that designed loop setup with the fluidic oscillator exhibited good mixing performance in continuous antisolvent crystallization. In addition, it was observed that established PBE-based models coupling with mixing coefficient C_mix can simulate PSD of manufactured paracetamol crystals in mixed semi-batch and batch as well as continuous crystallization experiments under different operating conditions. The presented experimental setup, approach, results, and computational models will be useful for expanding applications of fluidic devices without moving parts in antisolvent crystallization domains.

Extensive attention has been given to the effects of individual stress on employee work performance in both psychology and business literature. Recent work stress research has been shifting focus to team processes and performance. Nevertheless, several questions have not yet been fully addressed: (1) how does team stress impact new product development (NPD) team performance? (2) does stress chronicity, the persistency of NPD teams' stress experience, change the effects of work stress? (3) what team processes can explain the underlying relationship between team stress and NPD team performance? (4) how do slack resources affect the NPD process and performance? By integrating the cognitive activation theory of stress (CATS) and the challenge-hindrance stressor framework (CHSF), this study attempts to investigate challenge stress intensity and hindrance stress intensity as important antecedents of NPD team performance with the team adaptation temporal framework as the explanatory mechanism, and how stress chronicity affects their effects. Based on the data from 112 Chinese NPD teams (i.e. 112 team leaders and 242 team members), results revealed that although challenge stress intensity promotes team performance by boosting both team improvised adaptation and team preemptive adaptation, high stress chronicity attenuates the positive effects of challenge stress intensity. Hindrance stress intensity, on the contrary, has negative associations with team adaptations and team performance. As stress chronicity increases, these associations are weakened. Moreover, slack financial resources are found to have both adaptive and maladaptive characteristics, namely, a high level of slack resources weakens the positive association between team improvised adaptation and NPD team performance but strengthens the positive association between team preemptive adaptation and NPD team performance. This study contributes to theory by capturing the role time plays in the stress-performance relationship and contribute to practice by giving important recommendations regarding stress management and resource allocation.

This thesis is an empirical study on UK CPI price quote data (Mar 1988-Dec 2019) provided by the Office for National Statistics. It extends the study by Zhou and Dixon (2018). I follow Dixon and Grimme (2022) to divide price spells into four subsets which are (+, +), (+, -), (-, -), and (-, +) spells. A (+, +) spell is a price spell that started with a price increase then ended with another price increase. The questions that have been answered in this thesis are first how each type of price spell behaves over time? Second, have prices become more flexible since the 2008 financial crisis? Third, what are the determinants of nominal rigidity? I first used the crosssection method developed by Dixon (2012), then I did some non-parametric and semi-parametric analysis (Cox proportional hazard model). Finally, I used panel regression with fixed and random effects to find the determinants of size of price changes. Here are some stylized facts on the UK CPI data: 1: The average price spell in the UK is about 10 months, and (+, +) spells have the longest average duration while (+, -) spells have the shortest average duration. 2: The proportion of (+, +) spells is the biggest, and more than 50% of the spells are (+, +) spells in the services sector. 3: The average frequency of price changes, which is defined as the percentage of price quotes that changed in each month, is about 21.42%. 4: The 12-month spike pattern that was widely seen in previous literature was only found in (+, +) spells. 5: Prices have become more rigid since the 2008 financial crisis. 5: Heterogeneity can be found among the 11 COICOP divisions. 6: Macro factors matter in the price setting process, and it takes about 3 months for them to have significant effects on nominal rigidity. 7: Monthly effects and regional variations are significant. 8: Our model is good in terms of goodness of fit for the goods sector.

This thesis addresses guided deep learning, a new perspective for dealing with the real-world challenges of deep learning applications such as animal analysis. The proposed methods seek guidance from various sources in data such as spatiotemporal context, visual coherence, temporal correspondence, and dynamic learning policies to facilitate learning. The results are demonstrated on various computer vision tasks including animal detection, animal behaviour understanding, action recognition, video representation learning, and generic object detection. First, this thesis explores a context-guided detection model. It leverages spatiotemporal context with the attention mechanism, building a spatio-local correlation and a long-range temporal dependency to boost animal detection in the camera trap. The proposed method outperforms state-of-the-art frame-based detection baselines on the PanAfrica Dataset, a dataset of Great Apes filmed by camera traps in their natural habitats. Extensive experimental results show the effectiveness of the proposed context guidance in scenarios where motion blur, major occlusion, and camouflage effects etc. occur whereas the state-of-the-art detectors fail. This thesis also offers insight into how to leverage visual coherence and temporal correspondence in a video to guide visual representation learning without labels. The proposed self-guided temporal learning model performs forward-backward cycle predictions in time and then guides the predicted cycles to be coherent (smoothly varying) and correspondent (circularly consistent). It shows competitive experimental results for action recognition on UCF101 and HMDB51. Also, self-guided learning demonstrates the potential in animal analysis where a large amount of unlabelled animal videos can be exploited in a meaningful way. Inspired by the success of semi-supervised learning using large quantities of unlabelled data in other research fields, this thesis final argues that semi-supervised approaches can benefit animal analysis to address the lack of data labels in animal datasets. However, the current pseudo-label-based semi-supervised detection models that simultaneously utilise labelled and unlabelled data suffer from potential learning collapse. Herein, a policy-guided semi-supervised model is proposed. The proposed curriculum learning policies can steer learning towards a self-reinforced virtuous learning cycle that benefits the learning process and improves model performance. Experiments on PanAfrica and Bee datasets demonstrate the superior performance of policy guidance compared with state-of-the-art semi-supervised detection. It also achieves state-of-the-art performance on MS-COCO and PASCAL VOC 2007 under a low-data regime. This thesis concludes that the proposed guided deep learning approaches benefit animal analysis in tackling the real-world challenges.

The thesis analyses transparency and competition in the procurement process using interdisciplinary studies in diverse fields of the European Union (EU) legal framework for systematic coherence and economic theories and models. The thesis views debriefing as an ideal device for observing those tensions. The main question that this thesis addresses is whether debriefing enhances the effectiveness of the EU public procurement system? The EU Parliament and Council's 2014 public procurement package devoted to increasing transparency throughout procedures for higher efficiency and effectiveness and accordingly debriefing is a process meant to lead towards a fair, transparent, and efficient public procurement system. Debriefing is a procurement process designed to provide participants with access to a review of the contract award decision or the way to apply for effective remedies before a contract concludes. There is, however, a consensus that the EU Parliament and Council's 2014 public procurement package has endorsed debriefing with overload transparency compliance by the PSD while producing adverse effects on fairness competition. In view of that, this thesis provides a critical enquiry into debriefing by investigating EU public procurement, administrative procedure, competition, and data protection law. In the dealing with those tensions, thesis takes an objective-oriented approach by designing a specialised coordinate system to observe three objectives for regulating debriefing - integrity, fairness, and economic efficiency. This thesis identifies these objectives by exploring the legal effectiveness of the PSD and the RD where debriefing placed in and explains their concept by breaking them down into elements, components, and criteria for measurement for further discussion. Align to these objectives, its investigation into economic theories behind debriefing, such as the game, social welfare, auction, and oligopoly, is necessary to develop a combination of economic positivism and legal positivism analysis. In view of this, the thesis explains the principal-agency problem a priori detrimental to integrity for a public procurement system, measures the social cost of the procedure in reducing the cost of error and in enforcing substantive rules and, furthermore, forewarns the risk of collusive oligopoly when market players strategically use debriefing for repeated coordination. In addition, this thesis provides that coordinate system by empowering interdisciplinary studies, including the regulatory debriefing integrating the integrity tools of transparency and a monitoring system, a uniform judgement system for developing procedural rights such as of the rights to good administration and effective remedies in debriefing, the role of the principle of fairness connecting and formulating the data subject rights, confidentiality and trade secrets, the drawbacks of the principle of competition in controlling debriefing and the effectiveness of behavioural competition instruments. These are the main areas of focus for this thesis, which explores how they have and should been managed by using EU legal instruments, such as general principles, fundamental rights, and the Court of Justice of the European Union (CJEU)'s precedents.

Ice accretion often posed serious operational and safety challenges in a wide range of industries, such as aircraft, wind turbines, power transmission cables, oil field exploration and production and marine transport. Great efforts had been expended to research and develop viable solutions for both active and passive ice prevention. Effective ice protection techniques, however, had yet to be developed due to their deficiencies, such as significant consumption of de-icing chemicals or energy for active methods and poor balance among durable icephobic performance, good environmental resistances, and good mechanical and chemical properties for passive methods. Thus, with the specific surface microstructure design and the deployment of interdisciplinary techniques, this PhD project aimed to research and develop highly efficient ice mitigating strategies. The outcomes of this project committed to widening the vision of the ice mitigating field and minimising the gap between lab research and practical application. Before the experimental work, a fundamental literature review was conducted about the intrinsic background of ice crystals and iced surfaces, the relationship between hydrophobicity and icephobicity, the current research status of ice mitigation, and the commonly used characterisation and evaluation of icephobicity. Inspired by the talent ideas from literature, the interdisciplinary techniques, powder metallurgy and surface acoustic wave (SAW), were chosen to develop new strategies that covered from dry passive textured surfaces and wet passive icephobic structures to active ice protection with high efficiency. Through a simple stamping method and chemical vapour deposition, the textured polydimethylsiloxane-184 (PDMS) and 1H,1H,2H,2H-perfluorooctyltriethoxysilane (POTS) -coated coatings with fine and regular texture patterns were developed successfully. The evaluations of surface wettability, water droplet icing, environmental scanning electron microscope (ESEM) icing, and ice adhesion strength demonstrated the good anti/de-icing performance of the prepared coatings. The roles of lowering surface energy and surface texturing for the improvement of hydrophobicity and icephobicity were also discussed and verified accordingly. The relationship between the ice adhesion strength and surface wetting factors gave poor correlations which indicated that the icephobic mechanisms of textured surfaces could not be correlated with single surface wetting parameters or by linear fitting. With the application of solid sintering, surface functionalisation, and liquid impregnation, two new wet strategies, liquid-impregnated porous metallic structure (LIPMS) and phase change materials (PCM)-impregnation porous metallic structures (PIPMSs), were proposed and fabricated with gradient porosity and hydrophobic/oleophilic guarding design. The evaluation of mechanical properties and repeated anti/de-icing performance showed effective icing delay, good humidity resistance, ultra-low ice adhesion strength (less than 1 kPa), good mechanical properties, durable icephobicity, and improved liquid-maintaining capacity for both LIPMS and PIPMS. Due to the solid properties of PCMs at subzero temperatures, PIPMS had better durable performance and impregnated-material maintaining capacity than LIPMSs. The surface localised acoustic waves and the acoustic thermal effect of the thin film zinc oxide (ZnO) surface acoustic wave devices demonstrated their excellent potential for active ice mitigations. With the specific surface design, SAW devices were proven to have good anti/de-icing performance with high energy efficiency in a series of active anti/de-icing experiments. The sensitive monitoring of the resonant frequency shifts and their good ice repellency proved SAW devices can be used to design an effective ice monitoring-removing autonomous system. The anti/de-icing work with rime icing on SAW devices revealed the dynamic interfacial behaviour of SAW that the hybrid effect of acoustic waves and the acoustic thermal effect led to the effective anti/de-icing performance.

This thesis examines the role of exhibitionary spaces during a period that spans the Tokyo artistic milieu's localisation of Western European and Northern American concepts of fine art, museum and exhibition, and the establishment of a modern art system. Whereas existing scholarship on these has primarily concentrated on art historical and museological analysis of artists and collections, this thesis demonstrates the need to study exhibitionary spaces, their histories, and the shifting terminology used to describe and define them. Grounded by extensive archival research, this thesis addresses the use of temples, bijutsukan (art-prioritising institutions) and alternative spaces by artists and other key agents who occupied central, peripheral and intermediate positions within the artistic milieu. Drawing from Reiko Tomii's collectivism and the Deleuzoguattarian concept of 'territory', this thesis analyses the exhibitionary operations that these agents deployed, in relation to specific spaces, one another, and the shifting geopolitical dynamics of the specified historical period. It contends that exhibitionary spaces functioned as a physical ground for the artistic milieu's localisation of new concepts in the pre-modern period (1868-1907), the establishment of a mainstream institutional system and independent models in the modern period (1907-1945), and the deterritorialisation of artistic and exhibitionary borders during the contemporary period (1945-1970s).

Polyphenism is the ability of an organism's genotype to produce multiple discrete phenotypes when exposed to environmental stress. Polyphenism is very important to organisms as it allows them to react quickly to changes in environmental stress and therefore increase their chance of survival in the changing environment. There are many different types of polyphenism, including phase polyphenism, wing polyphenism and others. Aphids are one of the key model organisms used in studying polyphenism. Under normal conditions, aphids reproduce asexually and all the offsprings are essentially clones of the mother. However, upon exposure to environmental stress such as crowding, predation, and depletion of food resources, aphids exhibit wing polyphenism whereby the offspring from the next generation will develop wings, which allows them to escape from poor environmental conditions. Even though the aphid model has been used to investigate polyphenism, the underlying mechanisms in regulating such wing polyphenism remain unclear. The main experiment in this thesis involved exposing two different aphid genotypes (N116 and N127) to crowding conditions to trigger alternative morph production and the degree and number of adult alternative morphs were recorded (mesocosm experiment). Next, we carried out two transfer experiments to investigate the possibility of trade-offs between dispersal and reproduction. At the end of this mesocosm experiment, five 4th instar nymphs of each morph were transferred to individual plants to allow them to reproduce for another 12 days (Transfer experiment 1). The total number of offspring produced by each morph was recorded. At the end of transfer experiment 1, five 4th instar nymphs produced by each morph were transferred to another individual plant and allowed to reproduce for another 12 days and the total number of the population was recorded. The adult morphs collected from the mesocosm experiment were used to investigate the underlying mechanisms of wing polyphenism in aphids and the role of epigenetics mechanisms in regulating pea aphid wing polyphenisms through different techniques: qPCR, RNA-seq, MBD-seq, pyrosequencing and mIRNA-seq. 25 The two aphid genotypes reacted very differently to starvation conditions with N116 producing winged offspring in the next generation while N127 changed their body colour from red to pale. In addition, N127 also produced a higher percentage of alternative morphs compared to N116. We found that in both transfer experiments the dispersal morphs have lower reproduction compared to the wild type. This suggests a possible trade-off between dispersal and reproduction and such a trade-off could last for more than one generation. Our RNA-seq and qPCR identify several genes that could be involved in regulating wing development, reproduction and stress response in the pea aphid. Pyrosequencing revealed that among the genes that were differentially expressed between morphs only a few were differentially methylated. Further, our MBD-seq shows that the pea aphid has the highest methylation in the gene body region. However, integrating the MBD-seq and RNA-seq suggests that there was no clear correlation between DNA methylation and gene expression but some genotypes and morphs show stronger positive trends. In addition, we found that many conserved and some novel miRNAs were differentially expressed between the aphid morphs. Target gene prediction results from these miRNAs suggest that they target many genes that were involved in wing development, reproduction and wing development. Together the results from this thesis provide insight into genes that could be regulating wing polyphenism, stress response and reproduction in pea aphids and the role of different epigenetic mechanisms in regulating this polyphenism.

This thesis reports studies of systems containing actinide (An) and noble gas (Ng) elements, in both the nuclear materials and coordination chemistry fields. Among nuclear fuel fission products, noble gases (especially Kr and Xe) have low solubility and may release to the fuel-clad gap, which will lead to fuel swelling and thermal conductivity degradation. For the safe and efficient use of nuclear fuel, it is important to have a comprehensive understanding of fission gas release behaviours. However, the fission gas release model in actinide nitrides, promising candidates for use as a fuel in Generation IV reactors, is rudimentary. Chapter 3 studies the effect of non-stoichiometry of UN on point defect formation energy and Ng solution energy. The most stable defect types and the preferred trap sites of Ng under different stoichiometric conditions are reported. Chapter 4 investigates the diffusion of Ng in UN, and finds that the Ng diffusion is governed by the U vacancy-assisted mechanism. The calculated diffusion coefficients are in good agreement with the experiments. Chapter 5 extends the binary UN work to ternary (U, Pu)N. Actinide vacancy formation energy and Ng incorporation energy are found to be highly dependent on the chemical environment around the defects (i.e., the number of U atoms in the first (NU(1NN)) and second (NU(2NN)) nearest-neighbour shell), which increase as NU(1NN) increases while decrease as NU(2NN) increases. In coordination chemistry, An-Ng (especially He) complexes are candidate molecules for achieving high coordination numbers. Chapter 6 investigates the geometries, electronic structures, and bond properties of early An-Ng complexes, reporting 18-coordinate Th3+-He and Th4+-He systems for the first time. The covalency of the An-He bond in the group valent AnHe17q+ (An = Ac-U) species increases from AcHe173+ to UHe176+, while Ac-Ng bond covalency in AcNg123+ increases as the Ng gets heavier.

The past decades have seen the rise of studies on masculinity and language; however, there is very little empirical research given on the topic of men's talk in contemporary China. With empirical evidence collected from two male friendship groups, this thesis explores how Chinese men construct friendships and gender identities in their spontaneous talk. The findings of this thesis contribute to gender and language studies with ethnography-informed discourse analysis and sociocultural linguistics. The empirical evidence from the participants' friendship talks offers insights into intersectional identities and masculinities in the Chinese context. The other original contribution to knowledge of this research is closing a gap in the existing study of Chinese masculinity, which does not yet offer extensive conclusions in terms of a linguistic perspective on men's lived experiences. My study adds to the literature on Chinese masculinity by enhancing two underexplored topics: male homosociality in contemporary China and sexual experiences as a retold narrative practice. This thesis explores both the style and discourse of the narratives, conversational humour and personal talk that frequently emerge from men's talk. Various emerging social constructs, including locality, social class and age, interact to construct participants' intersectional identities and masculinities. Chinese men in this research still associate with a dominant masculinist discourse that devalues women and femininity. Further, they align themselves with success- and wealth-based hegemonic masculinity. They use their personal talk to define their understanding of male friendship, which suggests that 'male friendship as a virtue' has its contemporary expressions. Even though they show a desire to disclose their feelings, their personal and even emotional talk is still a site to lecture, police and reinforce hegemonic gender norms and expectations.

This thesis investigates the advancement of Acoustic emission (AE) monitoring techniques and analysis methods that could be applied in the field of Structural Health Monitoring (SHM), with an emphasis on the use of advanced AE techniques to detect and locate damage and their application on the monitoring of corrosion and Stress corrosion cracking (SCC) in complex metallic structures. The work was divided into three main areas of research, which are an investigation into using FE (Finite Element) generated delta-T mapping to locate experimental AE signals on complex structures, source location of AE signals generated by corrosion and an experimental investigation into SCC damage locations on a metallic specimen.

Interstrand crosslink (ICL) is a highly deleterious form of DNA damage as crosslinked DNA double strands block DNA replication, transcription machinery and prevent chromosome segregation. One of the major pathways for resolving DNA ICL damage is the Fanconi anaemia (FA) pathway, of which recruitment of the FANCD2/FANCI complex to sites of ICL damage is crucial for its repair by the FA pathway. The activity of FANCD2/FANCI complex is tightly regulated by post-translational modifications. Monoubiquitination of the FANCD2/FANCI complex lead to their retention on chromatin, which is essential for subsequent repair events to occur. However, it is believed that ubiquitination takes place after the recruitment of the FANCD2/FANCI complex to DNA, thus how recruitment of the complex is regulated still remains to be investigated. Our group reported a previously unknown kinase CK2 dependent phosphorylation event on FANCD2 at a six-residue cluster spanning from residue 882-898, which reduces the activity of FANCD2/FANCI complex, hence blocking subsequent events in the FA pathway. Phosphorylation of FANCD2 by CK2 restrains not only recruitment of FANCD2/FANCI complex to DNA but also FANCD2 monoubiquitination, pointing to an inhibitory effect on the function of the complex to prevent cells from spurious activation of repair in unperturbed conditions. We speculated that an unknown phosphatase may antagonize the effect of CK2 and promote the repairing function of FANCD2/FANCI complex during ICL repair. Here we identified one of the members belonging to the protein serine/threonine phosphatase PP2A family, PPP2R3A/PP2A, as the major phosphatase that specifically dephosphorylates and therefore activates CK2-phosphorylated FANCD2 during ICL repair. Silencing the catalytic activity of PPP2R3A/PP2A led to reduced recruitment and ubiquitination of FANCD2 upon induction of ICL damage. Importantly, cells lacking active PPP2R3A/PP2A displayed a deficient activation of the FA pathway, including increased sensitivity to ICL inducing reagent MMC. Our results describe a novel regulatory mechanism in which the function of FANCD2/FANCI complex is tightly regulated by the dynamic phosphorylation and dephosphorylation events mediated by CK2 and PP2A. In addition, PPP2R3A/PP2A that activates FANCD2 could serve as a potential druggable target to overcome chemotherapy resistance to ICL inducing reagents such as cisplatin, as the major mechanism of developing drug resistance is via an over-activated FA pathway.

This thesis reviews the national climate commitments from an economic efficiency perspective, aiming to better track national climate efforts and facilitate more ambitious climate commitments. This research contributes to the United Nations Climate Change Conference (COP) by enabling collective action on Carbon Dioxide Removal (CDR) and motivating more ambitious mitigation targets by acknowledging the corresponding benefits. It is crucial to track the results of national CDR liabilities and guide future development efforts. At present, effort sharing is still the best way to determine national responsibilities for negative emissions. This thesis allocates cost-effective global CDR pathways to countries using the principle of Common but Differentiated Responsibilities and Respective Capabilities (CBDR-RC). As the biophysical endowment and physical storage capability are constraining countries from deploying CDR, the equitable liability is further compared with national cost-effective CDR capability (including land-used CDR capability and geophysical storage capability). Equitable allocations of CDR, in many cases, exceed implied land and carbon storage capacities. This mismatch between CDR liability and capability thus highlights the need for a more diverse set of CDR technologies and mechanisms to facilitate the equitable international distribution of CDR. In light of the increasing recognition of mitigation benefits, this thesis developed a solely economic approach to review both the first and post-2020 updated NDCs from a cost-benefit-efficient perspective. Climate change mitigation is treated as solely economic behaviour motivated by avoiding future climate damage. The results show that countries from the US, the EU, China, and Japan have proposed more ambitious NDCs that are consistent with 1.5℃ in the post-2020 NDCs. Other developing countries, such as Brazil, South Africa, and Other Asian countries, are lagging behind in ratcheting up ambitions, with their NDCs less ambitious than the first NDCs. The evaluation reveals an increasing differentiation of national climate efforts, which opens up opportunities for leadership effects and climate clubbing in future climate negotiations. With uncertainty in national emission accounting, the author estimates the social cost of carbon as an indicator to track national climate policies and informs further action beyond emission control. While the social cost of carbon used in current policy appraisals satisfies national cost-benefit efficiency, they are significantly lower than the Paris consistent level. This thesis generally reinforces the recognition of economic efficiency in the Paris discussion. The proposed solely economic strategy motivates climate actions with the avoided climate damage and provides associated policy indicators to track national efforts. The results of the analysis of the economic tradeoffs justify more ambitious NDCs and point to the urgent need for clear CDR development goals.

Can machines optimally take sequential decisions over time? Since decades, researchers have been seeking an answer to this question, with the ultimate goal of unlocking the potential of artificial general intelligence (AGI) for a better and sustainable society. Many are the sectors that would be boosted by machines being able to take efficient sequential decisions over time. Let think at real-world applications such as personalized systems in entertainment (content systems) but also in healthcare (personalized therapy), smart cities (traffic control, flooding prevention), robots (control and planning), etc. However, letting machines taking proper decisions in real-life is a highly challenging task. This is caused by the uncertainty behind such decisions (uncertainty on the actual reward, on the context, on the environment, etc.). A viable solution is to learn by experience (i.e., by trial and error), letting the machines uncover the uncertainty while taking decisions, and refining its strategy accordingly. However, such refinement is usually highly data-hungry (data-inefficiency), requiring a large amount of application specified data, leading to very slow learning processes -- hence very slow convergence to optimal strategies (curse of dimensionality). Luckily, data is usually intrinsically structured. Identifying and exploiting such structure substantially improves the data-efficiency of sequential learning algorithms. This is the key hypothesis underpinning the research in this thesis, in which novel structural learning methodologies are proposed for decision-making strategies problems such as Recommendation System (RS), Multi-armed Bandit (MAB) and Reinforcement Learning (RL), with the ultimate goal of making the learning process more (data)-efficient. Specifically, we tackle such goal from the perspective of modelling the problem structure as graphs, embedding tools from graph signal processing into decision learning theory. As the first step, we study the application of graph-clustering techniques for RS, in which the curse of dimensionality is addressed by grouping data into clusters via graph-clustering techniques. Next, we exploit spectral graph structure for MAB problems, representing online learning problems. A key challenge is to learn sequentially the unknown bandit vector. Exploiting the smoothness-prior (i.e., bandit vector smooth on a given underpinning graph), we study theoretically the Laplacian-regularized estimator and provide both empirical evidences and theoretical analysis on the benefits of exploiting the graph structure in MABs. Then, we focus on the theoretical understanding of the Laplacian-regularized estimator. To this end, we derive a theoretical error upper bound on the estimator, which illustrates the impact of the alignment between the data and the graph structure as well as the graph spectrum on the estimation accuracy. We then move to RL problems, focusing on the specific problem of learning a proper representation of the state-action (representation learning problem). Motivated by the fact that a good representation should be informative of the value function, we seek a learning algorithm able to preserve continuity between the value function and the representation space. Showing that state values are intrinsically correlated to the state transition dynamic structure and the diffusion of the reward on the MDP graph, we build a new loss function based on the newly defined diffusion distance and we propose a novel method to learn state representation with such desirable property. In summary, in this thesis we address both theoretically and empirically important online sequential learning problems leveraging on the intrinsic data structure, showing the gain of the proposed solutions toward more data-efficient sequential learning strategies.

Compared to the last century, research and development of smart materials are receiving more attention due to their ability to change shape in response to specific environmental conditions. Although the development of shape memory natural rubber is motivated by the higher recovery strain, low trigger temperature leads to poor shape memory performance typically when the surrounding temperature is increased. A new shape memory natural rubber fabrication method, prevulcanisation is proposed to maintain the crystalline structure of the rubber molecule at elevated temperature. The low molar fatty acid which is palmitic acid involves in the prevulcanisation process to increase the trigger temperature of shape memory natural rubber. The prevulcanised rubber is fabricated with various amount of palmitic acid and sulphur to evaluate its shape memory capability under different temperature conditions (various programming temperatures and recovery temperatures). A custom-made stretching apparatus is developed to measure the shape memory parameters (shape fixity and shape recovery) under strain-control mode. The shape memory experimental settings (200% deformation strain for the shape memory natural rubber with less than 60% palmitic acid loading) are determined from the swollen shape memory natural rubber experiment. According to the shape memory experiment of prevulcanised rubber, the outstanding shape fixity and shape recovery are found when the temperature is closer to the melting temperature of the palmitic acid during the programming and recovery process. A similar trend is observed when palmitic acid content is increased. However, the sulphur content (>1.0pphr) has a reverse effect, causing the prevulcanised rubber to behave like elastic rubber and immediately recover its shape after unloading. Apart from the shape memory experiment, other material properties such as rubber strength and stress relaxation are also investigated. Furthermore, a shape memory behaviours prediction model is adopted to model the shape memory responses by using a standard linear solid model with Kelvin-Voigt element and a thermal strain model. The prediction model captured the shape memory behaviours appropriately and provided some insights on the stress-strain response of the respective segment phases for the shape memory process.

The increase of energy cost and usage in worldwide chemical industries leads to rising awareness for incorporating economic-efficient ways of saving energy. Heat exchanger networks (HEN) are important in process industries since they can improve energy efficiency and reduce 'greenhouse' gas emissions by heat integration. The benefits can be attributed into HEN for achieving energy saving, but heat exchangers require significant capital cost at the same time and need to be allocated across an efficient network configuration for massive process streams, which leads to the HEN design becoming a complex optimization problem. Therefore, a systematic methodology for HEN synthesis is necessary to investigate these design issues for achieving a trade-off between energy and capital costs. This thesis develops a systematic optimization-based approach to achieve realistic and economic-efficient HEN synthesis with detailed heat exchanger sizing, which aims to overcome the drawbacks in existing methods associated with the application of short-cut HEN model using constant heat transfer coefficients and simplified exchanger capital cost calculation. This approach further presents how these exchanger details from the exchanger sizing can be employed to guide the HEN superstructure towards generating more economic efficient solutions, rather than a HEN with the individual unit designs. Three innovations are presented in this work. In the first innovation, a generalized disjunctive programming model for STHE sizing is proposed to improve the time-consuming design procedures and varied solution qualities caused by extensive user manipulation and fine-tuning of widely accepted commercial software. The model is formulated as a mixed-integer nonlinear programming (MINLP) problem, involving a selection of 12 technology combinations. Both global and local optimization solvers are tested. The results show the developed STHE sizing method can provide better design solutions compared with conventional design procedures. Secondly, approaches to obtain optimal HEN solutions can be based on deterministic and stochastic algorithms, but it is still challenging to tackle the large-scale HEN synthesis problems due to the complexities arisen from nonlinearities. An enhanced deterministic approach using stage-wise superstructure is also presented to support the network searching. The present model is extended to allow a flexible requirement of stream splitting for practical application. The deterministic-based solver (BARON) shows better performance by comparing the results with existing works using stochastic algorithms. Furthermore, unlike conventional methods of allocating utilities to achieve target temperatures at the end of streams, efficient utilization of waste heat in heat sources and intermediate placements of low-level hot utilities in heat sinks can dramatically improve the process energy efficiency. An enhanced stage-wise superstructure is presented to automatically optimize selections of stages covering waste heat recovery and multiple hot utilities. Grand composite curve (GCC) is adopted to implement preliminary simplifications for the superstructure, by cutting the inappropriate utilities according to the pinch method and minimum temperature driving force to eliminate redundant combinations. Finally, by integrating the presented HEN superstructure approach with heat exchanger design, a novel iterative-based decomposition approach is proposed to synthesize the HEN considering exchanger geometrical details. Fouled individual stream heat transfer coefficients and corrected total process cost are updated iteratively between the HEN superstructure and STHE design model. In each iterative procedure, exchanger geometrical details are optimized to achieve optimal thermodynamic performance for the current HEN configuration. Global optimization for heat exchangers is achieved to reduce the network investment cost and improve the unstable iteration process caused by local optimums. Consequently, the proposed approach can time-efficiently address the HEN synthesis by incorporating heat exchanger details and provide economic-efficient solutions.

This thesis investigates the relevance of real options to corporate shareholders in three aspects, as presented in three self-contained chapters as follows. Chapter 2 studies a novel mechanism through which real options play a prominent role in inducing the skewness of stock returns. Building on the investment-based asset pricing framework, we show that firms' real options to contract (expand) their businesses when productivity is low (high) can increase return skewness. Consequently, return skewness represents a U-shaped function of firm productivity. Furthermore, the real-options effect is stronger for more flexible firms, characterized by lower scale-adjustment frictions. Employing a large sample of U.S. firms during 1972-2018, we provide a battery of robust empirical evidence consistent with the model predictions. Chapter 3 demonstrates that contraction options help reduce crash risk. This effect is stronger for firms with lower productivity, lower profitability or higher operating leverage. Using U.S. data between 1962 and 2019, we find strong empirical evidence supporting the model's predictions. Our work suggests that firms' investment and operation decisions affect their stock price crash risk without appealing to more widely recognized information asymmetry arguments in the crash risk literature. Chapter 4 shows that real flexibility curbs losses in firm value and reduces return volatility, especially for firms with high book-to-market or high COVID-19 exposure, consistent with the idea that the benefits of real flexibility are associated primarily with contraction options, rather than expansion options, during the COVID-19 crisis. Our analysis shows that real flexibility provides incremental and complementary protection beyond financial flexibility. Besides its impact on stock prices, real flexibility also helps firms sustain earnings, especially during 2020 compared with 2019 when the pandemic had not struck. Our work demonstrates that real flexibility is an important tool for corporate managers in navigating episodes of disasters.

The fact that artists struggle financially and affectively might not surprise many people in the UK, but what is less known is how they put up with those struggles and why they struggle. To explore these issues, this thesis presents an in-depth ethnographic analysis of the struggle, endurance and affect of visual and performing art practitioners in the UK. The ethnographic data are collected through both shadowing ten UK-based visual and performing art practitioners as well as participating in and observing art events during fourteen-months fieldwork between May 2018 and September 2019. This thesis challenges two established explanations of artists' struggles: struggles are the only thing that people should know about artists; struggles might actually be what artists want, given that art is the thing they want to live for and die for. Instead, I argue that UK-based artists' struggles can be understood as an integral part of "the 'terms' of being an artist in the early 21st century". That is, these artists model themselves on historical artist figures, the terms of which are freeing themselves from the domination of "Enlightenment-modernity-capitalism" but entailing economic and affective struggles. They sometimes also follow two alternative imperatives (pro-lifestyle and pro-equality), but the more they try to follow two or more contradictory imperatives, the more their efforts come to nothing. By examining themes such as poverty, meritocracy, unconscious bias, relationality and spontaneity, this thesis further contributes to the comparative studies and the interdisciplinary discussions of endurance, affect, inequality, art and human feelings under liberal capitalism.

Efficient landing is a key component of improving air transport, both for passengers' experience and fuel consumption. With just two runways, Heathrow airport was running at 98% capacity before the pandemic. The existing queuing system allows buffer time for the aircraft to land on one runway, but this can add delays to journeys and be fuel inefficient. With the recovery of the travel industry after the 2020 pandemic, improving landing procedures remains a pertinent problem to NATS (who manages all the air traffic in UK airspace). In this thesis, we develop alternative methods to sequence aircraft as they approach for landing at Heathrow. In the first part of this thesis, we cast the arrival management problem in a reinforcement learning framework. We design a basic air traffic model and apply both table representation methods and nonlinear approximation with a neural network. Specifically, we compare the performance of Q-learning, SARSA, and DDPG on this environment. Further we explore dimension reduction/feature representation through path signatures. Finally we design multi-grid inspired neural network structures and see that these lead to faster training but ultimately comparable performance. For the second part, we look at the problem from a different perspective. We take inspiration from the theory of optimal transport and formulate an entropy-regularised optimisation problem. We design an algorithm with block gradient descent-like steps and note that the conflicts in the set-up of our problem introduces non-convexity even when working in the (convex) space of distributions over arrival times. By adding an additional 'considerate' cost, akin to a Pigouvian tax, the performance of the algorithm is enhanced. Finally, the last part of this thesis shows the flexibility of our approach. We adapt our work to apply to a new air traffic design concept being researched at NATS.

The aim of this research is to develop a smart textile system based on multifunctional input and output electronic fibre devices. Unlike planar/rigid display devices, this research proposes not only a novel device architecture but also its integration into a textile system by using conventional yarn-to-textile methodologies, such as weaving and knitting. Smart lighting/display textile with multifunctional fibre devices has great potential in numerous areas, including lighting, display, smart home and Internet of Thing (IoT). This thesis first introduces the existing technology in textile engineering, including conventional fibre material and textile fabrication technology followed by the latest development in smart textile, which covers topics of functional fibre materials and devices. Conductive yarn is the fundamental for fibre-electronics and smart textile. The developed silver-polyamide (Ag-PA) conductive fibre shows an excellent electrical conductivity and mechanical robustness up to 35% strain. The F-touch and F-RF fabricated from Ag-PA also exhibits an excellent bending durability. The Field- effect transistor (FET) based F-biosensor shows a threshold voltage V_TH of 0.9 V, an ON/OFF ratio of 10⁸, and a saturation mobility μ_sat of 8 cm²/V·s which is comparable to the state-of-the-art flexible transistors. The F-temperature and F- energy demonstrated the viability of true core-shell cylindrical structure device for temperature measurement and energy storage that could withstand more than 900 bending cycles. As an output component, F-LEDs (fibre light-emitting diode) embedded 34-inch 6536-pixel full colour large area display represents the highest resolution full colour textile display reported to the date. The integrated smart textile has functions including touch detection, electrocardiogram (ECG) bio-signal measurement, temperature monitoring, far- field ultraviolet (UV) detection, wireless power transmission with RF signal, energy storage and video/image/information displaying. To further improve the display unit, a quantum dot light-emitting diode (QDLED) based textile display was developed. The electrode with lab synthesized silver nanowire (AgNW) shows a figure of merit (FoM) of 0.0014. The optimised MoO₃/Au electrode exhibits a transmittance of T₅₅₀= 81%, sheet resistance of Rs = 17.92 and a FoM of 0.0077. Both electrodes show a superior mechanical bending durability beyond the indium tin oxide (ITO) electrode. The optimisation was carried out on QDLED devices to ensure their performance meets the requirements for smart textile. The reduced phosphomolybdic acid hole injection layer (PMA-r HIL) based device exhibits a luminance that is comparable to the poly(3,4- ethylenedioxythiophene) with poly(4-sulfonate) (PEDOT:PSS) HIL based device and an even higher external quantum efficiency (EQE). The novel double layer PMA-r/PEDOT:PSS HIL device shows a remarkable 11.33% EQE. A remarkable lifetime of T₇₅ = 1019 h is achieved using MoO₃/Au/PMA-r device. The bending test also shows such device is able to maintain its luminance over 15000 cd/m² after 500 bending cycles at a bending radius of 5 mm. On the system level, a novel lateral driving architecture for smart textile display was developed and examined. The innovative architecture greatly simplifies the interconnection and tackles the resolution and stability issue encountered by other textile display architecture. The woven textile display is the world's first full color QDLED textile display with high pixels per inch (PPI) scalability.

This thesis investigates the effects of CEO home bias on corporate actions through three individual but interweaved essays. Specifically, the first essay studies whether social trust sourced from CEOs' birthplaces affects corporate social responsibility decisions. Using a sample of US public firms, this essay finds that CEOs who manage firms headquartered in their birth states engage in more corporate social responsibility (CSR) activities. The results suggest that the idiosyncratic styles of managers impact corporate policies in the form of CSR decisions. The second essay examines the effect of CEO home bias on accrual-based earnings management activities. Consistent with the view that home CEOs care more about their reputational capital, this essay finds that home CEOs are associated with significantly less accrual-based earnings management in their firms than non-home CEOs. Overall, the evidence suggests that CEO reputational capital affects earnings management activities within firms. The third essay examines whether CEO home bias affects acquisition deterrence. This essay finds that firms with home CEOs are less likely to receive a takeover bid but more prone to adopt antitakeover provisions. This finding is consistent with the birthplace attachment explanation, which indicates CEOs' reluctance to lose hometown jobs. This essay also shows that target firms with home CEOs are more likely to withdraw deals during the M&A process but are more willing to complete deals if the acquirer comes from the same state. The findings suggest that having a home CEO on board in the target firm acts as a "shield" against corporate takeovers.

Shannon and Weaver categorized communications into three levels of problems: the technical problem, which tries to answer the question "how accurately can the symbols of communication be transmitted?"; the semantic problem, which asks the question "how precisely do the transmitted symbols convey the desired meaning?"; the effectiveness problem, which strives to answer the question "how effectively does the received meaning affect conduct in the desired way?". Traditionally, communication technologies mainly addressed the technical problem, ignoring the semantics or the effectiveness problems. Recently, there has been increasing interest to address the higher level semantic and effectiveness problems, with proposals ranging from semantic to goal oriented communications. In this thesis, we propose to formulate the semantic problem as a joint source-channel coding (JSCC) problem and the effectiveness problem as a multi-agent partially observable Markov decision process (MA-POMDP). As such, for the semantic problem, we propose DeepWiVe, the first-ever end-to-end JSCC video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. We also further show that it is possible to use predefined constellation designs as well as secure the physical layer communication against eavesdroppers for deep learning (DL) driven JSCC schemes, making such schemes much more viable for deployment in the real world. For the effectiveness problem, we propose a novel formulation by considering multiple agents communicating over a noisy channel in order to achieve better coordination and cooperation in a multi-agent reinforcement learning (MARL) framework. Specifically, we consider a MA-POMDP, in which the agents, in addition to interacting with the environment, can also communicate with each other over a noisy communication channel. The noisy communication channel is considered explicitly as part of the dynamics of the environment, and the message each agent sends is part of the action that the agent can take. As a result, the agents learn not only to collaborate with each other but also to communicate "effectively'' over a noisy channel. Moreover, we show that this framework generalizes both the semantic and technical problems. In both instances, we show that the resultant communication scheme is superior to one where the communication is considered separately from the underlying semantic or goal of the problem.

The disruption to trains caused by rail maintenance commonly happens in operation. The stress state drives this issue as it causes damage to track. The longitudinal stress is induced by change in the temperature during extreme weather, especially in the widely used Continue Welded Rails (CWR) since there is no space for rail expansion. Existing stress measurement solutions to deal with this problem are either time/cost-consuming or destructive. Therefore, this project is aiming to develop a new non-destructive stress measurement device based on ultrasound, for rails, which is urgently needed and beneficial to the transportation industry. Previous researchers have shown the possibility of stress monitoring by using ultrasound and compared to other theories, this might be the best choice at the moment. The work in the PhD consists of five stages of testing. A pilot lab test for validating the ultrasonic stress measurement principle in small specimens, while, determining the most suitable transducer frequency and arrangement. After that, rail material study paralleled with validation testing of a removable transducer with rail specimens was conducted. Once the removable transducer-based system was built, laboratory testing with rail sections was performed to justify the versatility of the measurement system by testing it on different rails. In the real working condition, there are many random variables that must be assessed before a new system is turned into a commercial version, thus, field testing was critical in this work. Based on the performance from the field testing, an iteration can be delivered for improving accuracy and durability of the system. By using this rail stress monitoring system, the rail stress condition can be accessed without cutting the rail and closing the line from service, therefore, significant savings in operating and manpower costs can be achieved in the rail industry.

Holography is an advanced three-dimensional (3D) imaging and visualisation technology capable of reconstructing realistic 3D scenes. Despite decades of concentrated effort, holographic 3D displays are still struggling to meet the demands required for a consumer-ready solution. This thesis addresses technical challenges in the practical implementation and focuses specifically on potential image quality improvements based on algorithmic development. The thesis builds a holographic display system prototype and reconstructs established 3D scenes and real-world scenes using commercially available RGB-D cameras. By closely examining the reconstructed images, experimental reconstruction issues are evaluated. Given that image quality degradation is one of the significant issues in holographic displays, the gradient descent method is introduced to phase-only CGH optimisation. Contemporary image quality metrics (IQMs) considering human visual systems are employed as loss functions to improve the reconstructed image quality. Extensive objective and subjective assessment of experimentally reconstructed images reveal that the perceived quality improves considerably should the appropriate IQM loss be selected. Finally, the gradient descent method is extended to 3D hologram generation. While previous work optimises 3D CGH generation primarily on the in-focus region, this research further combines the method with an incoherent imaging module and a reformulated loss function to improve the defocus effect without sacrificing in-focus image quality. The experimentally acquired result demonstrates its effectiveness in reconstructing realistic 3D images beyond the capabilities of existing 3D hologram generation algorithms.

The main research aim of this thesis was to establish routine and robust methods to sequentially characterise nuclear materials which are out of regulatory control, from the bulk to the micrometre scale, similar to standards set by nuclear forensics. The tools and techniques used were high precision gamma spectrometry, XRT, XRF, XRD, SEM, EDS, FIB, synchrotron μXRT, μXRF, μXANES and MC-ICP-MS. The nuclear materials surveyed was collected from both ends of the radioactive release spectrum; from the FDNPP accident with a massive fallout over a relatively short period versus the Winfrith ALES which had a slow chronic regulated discharge. The physical characteristics of material from the Winfrith ALES pipe matched those of iron pipe scale, closely resembling material found from drinking water systems. There were many variations in the external surfaces, internal morphology, elemental composition and chemical phases of the material at different sampling locations from the pipe. Most notable were samples collected from the Break Pressure Tank, the highest from sea level portion of the pipe. These samples had a heterogeneous density structure made up of partially cemented Fe oxides, Fe rich spheres and discrete ultra dense micrometre scale U rich particles distributed throughout the material. These samples also had environmentally significant concentrations of radionuclides (Co-60, Cs-137, Am-241), these uniquely radiaoctive pipe scale were found to be thermodynamically stable and would pose little environmental risk. Generally, the largest levels of radioactivity found in coastal sediments around the UK are associated with 'hot' particles, some of which are actinide (U, Pu) based. Since earlier bulk analysis of the Winfrith pipe scale indicated the presence of discrete U rich particles, this warranted further study beyond lab based x-ray systems. Therefore, these U particles were isolated and extracted from pipe scale and analysed using micrometre scale x-ray systems at the Diamond Light Source, Harwell, UK. The results indicated that the U particles were conclusively anthropogenic and ascribed to nuclear fuel processing. The U particles were primarily UO2, mostly co-associated with the magnetite phases of the Fe pipe scale structure. Fortunately, this implied that the overall mobility of the U particles was extremely low and thus, posing little radiological risk. The material collected from the Winfrith ALES pipeline was also analysed using MC-ICP- MS. This work exploited the well known U and Pu isotope pair radiotracers in order to make some qualitative assessments about the general movement of this nuclear material to the wider environment. U233/U236, 236U/238U, 240Pu/239Pu and 242Pu/239Pu atom ratios possessed characteristics that were clearly distinct from isotopic signatures present in Dounreay, Sellafield or La Hague. However, there was a large degree of internal variability which suggested that the nuclear material was derived from multiple sources of varying isotopic composition. This was not entirely unexpected as the Winfrith ALES pipeline serviced many different nuclear test reactors, testing many different types of fuel. In the context of Fukushima, Cs isotope activity ratios are useful for estimating source terms, reactor conditions and tracing. In this portion of the work, we focused on the Cs- 134/Cs-137 activity ratio. Instead of using the traditional calibration methods employed by the scientific community, such as using in house reference standards or a simple ratio-ing of the Cs-134/Cs-137 gamma peaks, this work has evaluated an intrinsic calibration method. This is particularly helpful when analysing a high volume of variable environmental samples which is usual for FDNPP sampling missions. We found that this intrinsic calibration method had excellent agreement with literature results with slightly better precision which was necessary to better discriminate between different Fukushima nuclear reactor units. This work then employed the intrinsic calibration method in order to exploit the Cs- 134/Cs-137 as a radiotracer in the environmental. Tracking this activity ratio, we were able to illustrate basic spatial variability of the Cs micro-particles from the different FDNPP reactor units. We have also established some important correlations between these ratios and temporal, terrain and material variations. Notably, we have found that material from Unit 1 has been preferentially mobilising much more than those from Units 2-3. This research project improved and validated new analytical methods predicted to have future utility for the nuclear forensics community. All the tools and techniques developed in this work were part of the usual complement of the nuclear forensics toolkit. Therefore, all developments studied in this work can apply or easily adapted to any nuclear forensics setting although the majority of work done in this project did not have a forensics element.

The aspiration of computer vision is to enable computers to make sense of a world, one that exists in a vast sea of colorful pixels reflecting what humans see every day. Central to this goal perhaps, is the discovery of object representations from these pixels: clusters of pixels representing the things from big to small that constitute our physical world and the interactions with which form our daily life. Visual object segmentation is a subject that deals with this task. It concerns the prediction of pixel-wise masks that delineate objects of interest from visual data. Different types of evidence have been leveraged for segmenting out objects (according to the application), e.g., contours, saliency, motion, extreme points, and pre-defined semantic categories, among others. In this thesis, we investigate the exploitation of temporal correspondences and natural language descriptions for visual object segmentation, motivated by their omnipresence and efficacy, and contribute new methods that improve the state of the art for the relevant applications. In the first part of the thesis, we consider the modeling of temporal dependencies for object segmentation in videos, where the continuous movement of an object offers natural correspondences in time. Conventional methods based on sequential modeling are ineffective at exploiting such cues, and they still perform on a par with static segmentation models. In this thesis, we address this issue by introducing a technique that learns dense correspondences between pixels of frames that can be arbitrarily far apart in time. This enables the learning of long-term dependencies without conditioning on intermediate frames, which significantly improves the (deep) representation consistency of the object over time and leads to accurate object segmentation in videos. In the second part, we explore the use of natural language for object segmentation in images, where an object that corresponds to a natural language description is segmented out. With the aim of aligning linguistic meanings and visual clues in a common feature space, previous methods adopt the paradigm of fusing visual and linguistic features after they have been independently extracted from a vision encoder and a language encoder, respectively. In this thesis, we introduce a new paradigm that relocates cross-modal feature alignment to an earlier phase, i.e., to be conducted jointly with image encoding. The main idea is to supplement linguistic features to multiple intermediate layers of a vision Transformer network, to have linguistic information embedded jointly with visual information by the Transformer layers during the forward pass. With this approach, we tap into the correlation modeling power of the Transformer model at an early stage, and can harvest segmentation with a lightweight mask predictor. In the last part, we investigate the joint utilization of temporal and linguistic cues for visual object segmentation in the task of video object segmentation from referring expressions. We show how appearance, language, and motion features can be simultaneously aligned in a single network that is end-to-end trainable by exploiting the hierarchical structure of convolutional neural networks. Compared with previous methods, the proposed method has a much-enhanced capability in representing multi-modal inputs at different semantic and spatial granularity levels while enjoying a much simpler design.

The Oxford Domed Lateral (ODL) mobile bearing Unicompartmental Knee Replacement (UKR) provides good clinical results, but the bearing dislocation rate is unacceptably high. A systematic review and meta-analysis found that changing the articulating surface on the tibial component from a flat to a domed shape reduced the overall bearing dislocation rate from 17% to 3.7%. The risk of anterior/posterior (AP) dislocations was reduced substantially. Most dislocations were found to occur medially and with the knee in a flexed position. Dislocations occur in flexion because when the knee is flexed, the lateral ligaments are lax. Therefore a mechanical rig, which allowed the relative position of components to be adjusted and the joint to be distracted, was used to determine the minimum Distraction required for a Dislocation (DD), which is related to the risk of dislocation. However, as testing with the rig was inefficient, a computational dislocation analysis tool based on the mechanical rig was developed and validated against results from the rig. The tool uses path planning algorithms from the field of robotics to allow the bearing to find a viable dislocation pathway. It was found that medial dislocations required a much lower DD than AP dislocations, which explains why medial dislocations are more common than AP dislocations. Further, changing the tibial surface from a flat to a dome increased the DD for AP dislocations substantially, which explains why this change primarily decreased AP dislocations. A series of potential implant design changes were studied to see if they would decrease the DD for medial dislocations to that of AP dislocations as the risk of AP dislocation was considered acceptable. The simplest change to achieve this was to increase the tibial wall height by 2 mm, but to avoid the femoral and tibial components hitting if there is bearing wear, the minimum bearing thickness would have to be 5 mm. Alternatively if the centre of the femoral component sphere was moved laterally, the bearing made wider laterally and the wall height increased, then an acceptable dislocation rate would be achieved with a minimum bearing thickness of 4 mm. For both these modifications to be successful, surgeons must ensure that the bearing is not more than 4 mm from the tibial wall. Cadaveric and clinical studies are required to assess the viability of the proposed changes. If the risk of dislocation can be minimised or reduced, more patients may benefit from the advantages of lateral mobile bearing UKRs.

The railway industry has seen significant innovation in intelligent maintenance systems leading to improvements in efficiency and reliability. However, ongoing challenges such as intensity of labour, hazardous environments, and operational inefficiency necessitate advancement in the deployment of Robotic and Autonomous Systems (RAS). Successful implementation of RAS in a railway context requires a comprehensive function allocation process. This thesis presents a novel function allocation framework for systematic task analysis and allocation. The framework includes comprehensive multi-stage evaluation criteria such as technical feasibility, overall system performance, and cost impact. Function allocation for each identified subtask is realised in an iterative manner to reach a final system design, and the structure and elements of the framework are supported by rigorous derivations and practical examples. The proposed framework has been successfully applied and thoroughly demonstrated through case studies based around the maintenance activities of wheelsets. The case studies demonstrate that the proposed framework is capable of providing guidance in system design at the preliminary stages of the introduction of automation into railway maintenance systems; also, can help to re-evaluate an already implemented system and thus propose guidance on whether the current allocation can be optimised.

The present research examines the effects of economic institutions under the broader context of the inequality-growth nexus. We are able to identify from fixed effects panel estimations that although both institutional quality and innovations can offer significant contributions towards economic growth, this progress is made at the expense of economic equality. The interactions of the two variables of interest are found to be negative in signs within the inequality and the growth model, meaning the marginal effects of both innovations and institutions on growth and inequality diminish in their potency as their interacting counterparts increase in value. This indicates that while institutions and innovations are shown to be inequalityinducing, their interaction dampens the effect at higher values. Similarly, while both variables contribute positively towards growth, their interactions also possess negative coefficients, reduces the overall impact on growth in a display of potential institutional inefficiency and diminishing return on innovation. Furthermore, we uncover a transitory institutional effect on growth, where the partial effects of property right protection gradually diminish as the economy develop and are eventually replaced by the broader institutional effects. Additional testing of the model uses GMM and IV estimations, as well as additional robustness tests, reinforce the findings. To develop policy implications from our hypotheses and the empirical findings, we construct a theoretical framework of a voter-driven political model where the balance of the inequality-growth trade-off is set by a redistributive policy tool, determined by a median voter through their utility consideration between inequality and economic growth. We estimate the structural model using the indirect inference technique on long data for the UK from 1870 to 2018. The empirical estimation is not rejected by the Wald test, suggesting that our theoretical model cannot be rejected and is a good fit for empirical data. Key words: inequality, economic growth, institutions, entrepreneurship, innovation, fixed effects, System- GMM, indirect inference, structural modelling, political economics.

Eukaryotic DNA polymerase δ plays a critical role in DNA replication and repair. At the replication fork, Pol δ carries out the bulk of lagging strand DNA synthesis and plays transient but crucial roles in leading strand DNA replication as well. Human Pol δ consists of a catalytic subunit (PolD1) and three accessory subunits (PolD2, PolD3 and PolD4). The regulated degradation of PolD4 in response to DNA damage reflects the important role of this protein, however, its precise function remains to be fully understood. Structural studies have located the PolD4 protein between PolD1 and PolD2, leading to the suggestion that PolD4 degradation is likely to bring about a subtle change in the three-dimensional architecture of Pol δ to modulate the enzyme's activity. This work used PolD4 proteins from fission yeast Schizosaccharomyces pombe and thermophilic fungus Chaetomium thermophilum (Ct) as models to explore the function and structure of PolD4. Overexpression of S. pombe PolD4 could supress mutations in genes encoding PolD1, PolD2 and PolD3. We investigated how the conserved residues at the C-terminal domain of PolD4 contribute to this function. We identified a PCNA interacting protein (PIP) motif in the N-terminal region of CtPolD4 and solved the crystal structure of CtPolD4 PIP peptide bound to CtPCNA. This structure reveals a non-canonical mode of binding that contrasts with the recently characterised human PolD4 (p12) PIP-PCNA interaction. As part of a wider study dissecting the structure and function of Pol δ, we developed protocols for expression and purification of CtPol δ and obtained its cryo-EM structure to near 4 Å. Our studies may provide insights on the role of PolD4 in contribution to Pol δ function, regulation of DNA replication and maintenance of genome stability.

This study explores two craft movements in Japan and Taiwan in the first half of the twentieth century under the political structure of Japanese imperialism. The thesis is organised into four chapters, the first two focusing on the Japanese Mingei Movement and the last two on the Taiwanese artist Yen Shui-long's craft practice in forms of design. With the frame of the 'International Arts and Crafts' perpetuating in the legacy of the British Arts and Crafts Movement, I argue that these local responses should be seen as an art-historical process of displacement and replacement, rather than mere transmission or absolute subversion. Craft has been made to play the role of a negative in the construction of art's history. Reconsidering the concept of craft, which has been previously explored by identifying its 'non-art' properties, this research re-engages with the art-versus-craft debate to reveal imperialism within European art history's narratives of Others and its influence in non-European cultures' acquirement of 'art'. In searching for alternative aesthetic value for shaping Japanese art history, Yanagi Sōetsu's mingei theory problematised the dualistic structure of the art-craft category, interrogating the hegemony within the modernist idea of 'fine art'. Meanwhile, mingei aesthetics' nuance in Taiwan extends the story to re-examine mingei theory's own nationalist ideology. I analyse this movement as forms of cultural resistance, challenging the myths of originality, authenticity and other artificial substances used to frame the boundary of cultural identity, highlighting the ways in which 'craft' played a significant role in processing local mobilities and autonomies. These two cases give evidence for craft's dialectical tension in relation to art, open a post-colonial view onto art history's Eurocentrism and re-examine pervasive imperialism in forms of Japanese colonialism in the early twentieth century.

This thesis consists of three essays about the role of corporate innovation strategy in corporate disclosure. Innovation is crucial in helping firms gain a competitive edge and sustainable growth. While firms increasingly and continuously invest more resources into innovative activities, their innovation strategies exhibit substantial variations. Innovation strategy is a significant way to guide firms' innovation efforts and facilitate trade-off decisionmaking. There are two types of corporate innovation strategy: exploration and exploitation. Exploration innovation strategy emphasises the exploration of new possibilities, whereas exploitation innovation strategy focuses on the exploitation of existing certainties. Given that the difference between exploration and exploitation is connected with firm behaviour that significantly influences firms' underlying earnings stream and disclosure environment (He and Wong, 2004; March, 1991), this thesis examines how firms' choice of innovation strategy impacts corporate disclosure. Specifically, the thesis contains three empirical studies about the impact of innovation strategy on the characteristics of financial reporting, earnings, and voluntary disclosure, respectively. The first empirical work studies the impact of innovation strategy on accounting conservatism. The results show that exploration-oriented firms report more conservatively than exploitation-oriented firms. Cross-sectional tests indicate that the positive relationship between exploration innovation strategy and accounting conservatism is statistically significant only for firms with greater information asymmetry, higher stock price crash risk, a higher failure-to-success ratio and higher managers' litigation risk. The evidence supports that accounting conservatism in exploration-oriented firms can be explained as a rational response to uncertainty. The second empirical work studies the impact of innovation strategy on income smoothing and the magnitude of accruals. Income smoothing and the magnitude of accruals present two important properties of earnings. Using a composite measure of income smoothing and accruals, this study suggests a positive (negative) relationship between exploration (exploitation) innovation strategy and income smoothing and the magnitude of accruals. Evidence suggests that income smoothing and the magnitude of accruals in exploratoryoriented firms are beneficial from the perspective of improving firm value and earnings informativeness. Cross-sectional tests indicate that the positive relationship is statistically significant for firms with more analyst coverage. The findings of this study shed light on the role of innovation strategy in shaping earnings properties of income smoothing and the magnitude of accruals. The third empirical work studies the impact of innovation strategy on non-GAAP earnings. The baseline results suggest that firms pursuing an exploitation-oriented (explorationoriented) innovation strategy are positively (negatively) associated with the likelihood and magnitude of non-GAAP exclusions. The study also provides insight that exploitation innovation strategy affects the likelihood and magnitude of non-GAAP exclusions in the form of other exclusions. Moreover, the cross-sectional tests show that exploitation-oriented firms report more aggressive non-GAAP earnings when firms have a higher information asymmetry environment. This study also tests the quality of non-GAAP exclusions and finds that non-GAAP exclusions defined by exploitative firms are persistent and, thus, low-quality. The findings of this study advance our understanding of how a public company's choice of innovation strategy affects its disclosure practice of non-GAAP earnings.

This dissertation is concerned with folding rigid panels of uniform thickness into a compact volume and deploying it back to a continuous and flat surface in a predictable manner afterwards. This was achieved by either forming an assembly with a single degree-of-freedom (DoF) through special geometric designs of thick-panel kirigami or ensuring a collision-free deployment of a multiple-DoFs system through dynamics simulations. Four major findings of this dissertation were as follows. First, kirigami patterns were investigated to enable the folding of a chessboard-like array with identical panels into two stacks without any voids. Revolute joints (also known as hinges or rotational joints) and slits are placed to connect or disconnect panels according to a Hamiltonian circuit (HC) (Hamilton, 1856) that was drawn over the array. If multiple HCs were found, a method was proposed to select the ones that could be folded into two stacks. Physical prototypes were made to validate the designs. Secondly, simple spring-loaded hinges were used to synchronise the deployment of a multiple-DoF assembly resulting from the HC approach. An optimisation method was proposed to select the stiffness of hinges to ensure a collision-free deployment. Dynamic simulation of the deployment and collision detection method were incorporated into the optimisation process. By this approach, the trajectories of panels were sequenced to avoid collisions during the deployment, and the array was always deployed to a flat surface from packaged stacks, which were further validated by experiments. Thirdly, through special geometric designs, interlinked regular flat rigid panels of uniform thickness were folded into compact stacks with a single DoF. Kinematically the deployable structure is an assembly of several 8R closed chains. Although such a chain with eight rigid bodies and eight revolute joints would have two DoFs in general, a single-DoF assembly was created by combining them in a particular way. The bi-directional folding concept can be extended to fold an assembly consisting of an infinite number of panels. Not only can this work be directly applied to the design of future flat arrays, but is also important in the theory of mechanisms as the proposed assemblies are rare examples where a kinematic loop consisting of linkages of multiple DoFs possesses single mobility. Finally, a modular approach was proposed to fold arrays composing squares or the combination of squares and half-square triangles into a compact volume that is conforming to the shape of a CubeSat. The obtained arrays could possess a single DoF or a small number of DoFs.

Graphene, Mxene and related 2D materials have the potential to open new engineering opportunities in a wide range of technological applications. In particular, 2D materials could provide an alternative to conventional electrode materials by improving the storage capacity and lifetimes of energy storage devices. However, the practical application of these materials in energy will require assembly into 3D structures with tuned architectures to truly maximise their available surface area for reactions, fluid transport or the distribution of functional sites. This research project focuses on the development of novel electrode materials with multi-scale architectures via advanced manufacturing approaches such as 3D printing, freeze casting and tape casting. Overall, the study will comprise the following endeavours: 1) fundamental research on the synthesis, chemical stability, and rheological properties of 2D materials: MXene; 2) Design of novel inks with optimized viscoelastic performance for freeze casting, tape casting and extrusion-based printing; 3) Investigate the structure-property evolution of the material during and after manufacturing via advanced characterization techniques; 4) Study of the electrochemical performance of relevant electrodes in energy storage devices (supercapacitor).

This project investigates the migration/penetration of ionic species within organic coatings using ion-selective electrodes. Chloride and chromate are chosen to be studied for three reasons. Firstly, chloride is a very common aggressive specie and its movement from the external environment to the substrate is often the first step to the start of under-film corrosion. Secondly, chromate is a common and traditional species that acts as an effective corrosion inhibitor in coatings. Thirdly, both species can be determined, in principle, using the same method of a silver/silver chloride (or chromate) electrode. Solvent-free epoxy resin, waterborne epoxy resin and solvent-borne polyester resin were selected as three common types of coating. The overall objectives of this project are to prove that ions are detectable using this method, to measure the chemical influence (activity) of chloride and chromate in different organic coatings at the substrate after migration and to determine the influence of pigment amount in coatings on the migration of ions. Unfortunately, the last of these was not possible as a consequence of COVID. Ion-selective electrodes were manufactured using thin silver wire, thicker rod and flat plate with coating application by dipping (wire and rod) and spin/bar coating (plate). Any difference of reproducibility in the ion-selective electrodes of different shapes is not apparent. However, coatings applied on wire and rod electrodes are not uniform due to a retained droplet at the bottom of sample resulting in a difficulty in the measurement of actual coating thickness. Thus, flat plate samples were predominantly used with coating thickness measured by eddy-current electronic gauge. Before measurement of potential in ionic solutions of various concentrations, coating integrity was checked using electrochemical impedance. This is to avoid any errors in measurements caused by ion migration through pores and other small defects rather than through the bulk of the polymer coating. If the coating impedance was more than 10⁶ ohm.cm² (water-borne coating) or 10⁷ ohm.cm² (solvent borne coating) and maintained this value over the time of the experiment then it was assumed that the coating had no defects. The impedance of solvent-free epoxy resin coated electrodes was generally too high for the electrochemical potential of the electrode to be measured due to the insufficient input impedance (10¹⁴ ohm) of the potentiostat/voltmeter. Therefore, work using the solvent-free system was abandoned. For waterborne epoxy resin on the chloride electrode, generally high impedance values (> 10⁶ ohm.cm²) were measured showed intact coatings. Moreover, the potentials measured for these coated electrodes are similar to those on uncoated electrodes and this indicates that the chloride was detected after migration through the coating and it was in thermodynamic equilibrium with the external chloride value. Changing the chloride value produced a relatively rapid change in potential on the coated electrode which was too fast for migration throughout the body of the coating. Therefore, it was interpreted as a short-circuit diffusion along the hydrophilic boundaries between the coalesced particles that comprised the coating. For the solvent polyester system, the coating impedance was often found to be too high for consistent measurement of potential and this may be due to a higher cross-link density or as the polymer coating is more homogeneous. However, there is evidence that if the coating is not too thin (so has holes) and is not too thick (so not a massive high resistance) that the electrode coating will respond to external chloride but over a longer time. For chromate detection the waterborne system was used as this seemed to have the greatest chance of success. The uncoated electrodes did not show expected straight line responses to logarithm of chromate concentration but with predicted slopes after linear fitting. However, a suitable reference electrode and test solution are crucial to obtain the expected results. Also the chromate solution, which was oxidising and alkaline, accelerated the degradation of the waterborne system which made obtained good data hard. Nonetheless, there is evidence that chromate is detectable using this method under paint coatings.

This thesis focuses on new techniques in synthesis, design, and fabrication for microwave diplexers and multiplexers. Coupling matrix theories are employed with design knowledge to guide computational intelligent techniques to realize complex microwave multiplexers. To achieve compact size and lightweight multiplexers, novel design concepts and emerging fabrication technologies are proposed and implemented. The main contributions of the thesis are: 1) A general all-resonator diplexer/multiplexer coupling matrix synthesis method (GACMS) is presented. Classic filter design knowledge and advanced optimisation techniques are combined to generate high-quality coupling matrices for diplexers/multiplexers with complex topologies. 2) A novel electromagnetic (EM) optimisation method is presented for diplexers. A systematic physical dimensioning method is proposed for a high-quality initial design. A key performance-based objective function is proposed. Together with a powerful optimizer, the diplexer optimisation can achieve a high success rate in a fully automatic process. 3) A resonant manifold multiplexer is proposed based on an all-resonator structure. Different from the traditional transmission line-based manifold-junction, coupled-resonators constitute the manifold-junction. Tailored methods are proposed to synthesis and optimize the multiplexers. The new multiplexer structure offers a more compact footprint. 4) A D-band diplexer is designed based on all-resonator structure. Two commercial fabrication techniques, high-resolution micro laser sintering 3D printing and high precision CNC milling, are employed to the same diplexer design, respectively. Comprehensive measurements and comparisons are conducted for the fabricated diplexers.