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The automotive industry is evolving at a rapid pace, new technologies and techniques are being introduced in order to make the driving experience more pleasant and safer as compared to a few decades ago. But as with any new technology and methodology, there will always be new challenges to overcome. Advanced Driver Assistance systems has attracted a considerable amount of interest in the research community over the past few decades. This research dives into greater depths of how synthetic world simulations can be used to train the next generation of Advanced Driver Assistance Systems in order to detect and alert the driver of any possible risks and dangers during autonomous driving sessions. As Autonomous driving is still in the process of rolling out, we are far away from the point where Cars can truly be autonomous in any given environment and scenario and there are still quite a fair number of challenges to overcome. A number of semi autonomous cars are already on the road for a number of years. These include likes of Tesla, BMW \& Mercedes. But even more recently some of these cars have been involved in accidents which could have been avoided if a driver had control of the vehicle instead of the autonomous systems. This raises the question why are these cars of the future so prone to accidents and whats the best way to over come this problem. The answer lies in the use of synthetic worlds for designing more efficient ADAS in the least amount of time for the automobile of the future. This thesis explores a number of research areas starting from the development of an open source driver simulator that when compared to the state-of-the art is cheaper and efficient to deploy at almost any location. A typical driver simulator can cost between £10,000 to as much as £500,000. Our approach has brought this cost down to less than £2,000 while providing the same visual fidelity and accuracy of the more expensive simulators in the market. On the hardware side, our simulator consist of only 4 main components namely, CPU case, monitors Steering/pedal and webcams. This allows the simulator to be shipped to any location without the need of any complicated setup. When compared to other state-of-the-art simulators \cite{carla}, the setup and programming time is quite low, if a PRT based setup requires 10 days on state-of-the-art simulators then the same aspect can be programmed on our simulator in as little as 15 minutes as the simulator is designed from the ground up to be able to record accurate PRT. The simulator is then successfully used to record accurate Perception Reaction Times among 40 subjects under different driving conditions. The results highlight the fact that not all secondary tasks result in higher reaction times. Moreover, the overall reaction times for hands were recorded at 3.51 seconds whereas the feet were recorded at 2.47 seconds. The study highlights the importance of mental workloads during autonomous driving which is a vastly important aspect for designing ADAS. The novelty from this study resulted in the generation of a new dataset comprising of 1.44 million images targeted at driver vehicular interactions that can be used by researchers and engineers to develop advanced driver assistance systems. The simulator is then further modified to generate hi fidelity weather simulations which when compared to simulators like CARLA provide more control over how the cloud formations giving the researchers more variables to test during simulations and image generation. The resulting synthetic weather dataset called Weather Drive Dataset is unique and novel in nature as its the largest synthetic weather dataset currently available to researchers comprising of 108,333 images with varying weather conditions. Most of the state-of-the-art datasets only have non automotive based images or is not synthetic at all. The proposed dataset has been evaluated against Berkeley Deep Drive dataset which resulted in 74\% accuracy. This proved that synthetic nature of datasets are valid in training the next generation of vision based weather classifiers for autonomous driving. The studies performed will prove to be vital in progressing the Advanced Driver Assistance systems research forward in a number of different ways. The experiments take into account the necessary state of the art methods to compare and differentiate between the proposed methodologies. Most efficient approaches and best practices are also explained in detail which can provide the necessary support to other researchers to set up similar systems to aid in designing synthetic simulations for other research areas.

Hypervalent iodine(III) compounds are attractive reagents in organic synthesis. The main advantages include their low cost and low toxicity. In particular, they have been used as atom-transfer reagents to introduce nucleophiles such as chloride and fluoride into organic compounds. In chapter two, a one-pot synthetic method was designed to introduce a variety of nucleophiles into the 2-position of 1,3-dicarbonyl compounds using fluoroiodane. Chloride, methoxy and ethoxy groups were introduced into a series of 1,3-dicarbonyl compounds in moderate to high yields (32-90 %). The advantage of this method is that only one hypervalent iodine(III) reagent is required to introduce a range of different nucleophiles into the 2-position of 1,3-dicarbonyl compounds, whereas previous methods required a different hypervalent iodine(III) reagent for each nucleophile. Unfortunately, the introduction of either a trifluoromethyl or a trifluoroethoxy group proved unsuccessful due to the low nucleophilicity and steric bulk of these nucleophiles. In chapter three a catalytic method was developed to introduce chlorine into 1,3-dicarbonyl compounds using 2-(2-iodophenyl)propan-2-ol under mild reaction conditions and in good yields (73-76 %). This methodology was applied to the tosyloxylation and fluorination of a β-ketoester with limited success. However, when hexafluoroisopropanol (HFIP) was employed as a solvent, the stoichiometric fluorination was possible. A range of 2-fluoro-1,3-dicarbonyl compounds was synthesised in good to excellent yields using fluoroiodane in HFIP, without the need for Et3N.3HF. 1H NMR studies provided evidence for the activation of fluoroiodane by hydrogen bonding, due to the formation of a hydrogen bonding adduct between fluoroiodane and HFIP. Finally, three chiral iodoarenes were synthesised in chapter four and investigated in the enantioselective chlorination of 1,3-dicarbonyl compounds. Only a small enantiomeric excess was obtained due to issues with background chlorination and hydroxylation. The Gilmour system, employing cesium choride and Selectfluor was explored and preliminary work showed no evidence of a competing background reaction.

With ever increasing data volumes and computing complexities, power-efficient alternatives, particularly Field Programmable Gate Arrays (FPGAs), need to be explored for industrial-scale data centres. Whilst FPGA device sizes have increased and associated design tools have matured, there are still challenges for their seamless integration model. This acts to hamper the abstraction of FPGA as a scalable, run-time programmable and high throughput resource, which can be designed from a high-level programming environment. This work contributes to the programming challenges in two domains; namely design process and the run-time programming. Firstly, it builds an integration stack that enables just-in-time compilation and runtime programmability for soft-cores in data centre environments, particularly for highly dynamic task queues. It enables remote access to an independent scalable FPGA accelerator in a similar manner to software-based systems whilst providing up to 10.7× greater energy efficiency. The work then proposes an abstracted platform-independent optimisation approach based on OpenCL for improving FPGA-based performance. Through the maximisation of resource utilisation via parallel workload balancing, the work is able to more fairly evaluate heterogeneous accelerators and show that FPGAs are capable of achieving better energy efficiency without requiring FPGA-specific language and skills. Finally, the work targets novel optimisation of throughput by both design and runtime techniques for area shared multi-task processing. It proposes a framework built on machine learning based characterisation and clustering of tasks. Integrated with static mapping of tasks, multi-task design space exploration and pre-emptive scheduling, the framework provides optimal spatial and temporal resource utilisation resulting in up to 2.8× and 2.3× higher throughput and energy efficiency compared to previous approaches.

Background: Cerebral Autoregulation (CA) is usually defined as the tendency of cerebral blood flow (CBF) to remain approximately constant despite changes in arterial blood pressure (BP) within the range of 50 to 170mmHg. Dynamic CA (dCA) can be estimated from the transient response of CBF to rapid changes in BP. Spontaneous acute intracerebral haemorrhage (ICH) presents a devastating cerebral event with high morbidity and mortality. The mainstay of treatment remains BP control, which relies on a functioning CA. CA has been shown to be impaired in acute ICH. Arterial partial pressure of carbon dioxide (PaCO2) has a strong influence on dCA and other cardio- and cerebro-vascular variables. Understanding the dynamic CA response to physiological manoeuvres, such as exercise and changes in respiratory patterns, has often been confounded by simultaneous changes in PaCO2. Hypercapnia leads to vasodilation of cerebral vessels and overall causes deterioration in CA. Conversely, hypocapnia has a vasoconstrictive effect, improving CA. Aim: The aim of this thesis is to comprehensively model the cerebral haemodynamic response to the entire physiological range of PaCO2 in order to safely permit the assessment of feasibility of clinical translation of a CO2-based intervention into a cohort of acute ICH patients with impaired autoregulation. Objectives: This thesis objectives are to: i) determine the natural history and prognostic implications of CA impairment in acute ICH; ii) determine if the use of current CO2 measurement techniques leads to significant differences in CO2-related systemic and cerebrovascular parameters; iii) determine the most appropriate method of initiating and maintaining hypocapnia; iv) determine if key cerebral haemodynamic parameters including autoregulation index (ARI), arterial BP (BP), heart rate (HR), critical closing pressure (CrCP) and resistance-area product (RAP) follow a logistic non-linear model similar to those described for cerebral blood flow velocity (CBFV); v) investigate sex differences in cerebral haemodynamics across the physiological range of PaCO2 and vi) determine whether hypocapnia (via hyperventilation) in acute ICH may improve CA and consequently clinical outcome. Methods: CA was measured in healthy and acute ICH patients by transcranial Doppler ultrasound assessment of middle cerebral artery velocities alongside continuous non-invasive monitoring of BP. Results: 45 healthy volunteers underwent a multi-step protocol inducing hypo- and hyper-capnia and 12 acute ICH patients underwent a metronome based hypocapnic intervention at < 48 hours and 10-14 days. The thesis results demonstrated i) the aforementioned parameters follow a logistic curve relationship; ii) CBFV is lower and dCA is impaired in acute ICH as compared to healthy controls; iii) different EtCO2 measurement techniques do lead to physiological changes and differences in parameter values; iv) dysautoregulation can be minimised by continuous metronome use during hyperventilation-induced hypocapnia; v) logistic curve parameters are influenced by sex and vi) dCA can be improved in acute ICH using a CA targeted CO2-based interventional manoeuvre. Conclusion: This thesis presents a new paradigm for assessment of the interaction of CO2 and dCA and its potential clinical applications. In addition, original findings include improved understanding of CO2 focussed physiological measurement protocol design, comprehensive clarification of cerebral haemodynamics in ICH, optimisation of hypocapnia induction, demonstration of novel sex differences during PaCO2 change and via accumulation of the aforementioned knowledge, the safety and feasibility of a novel CA targeted CO2-based interventional manoeuvre in acute ICH.

In England and Wales, the 'war on terror' has been argued to impact adversely on existing race relations policies. Recent research has suggested that changes in legislation (such as wide discretionary powers of stop and search) and counter-terrorism measures (such as arrest and the extension of pre-charge detention of 28 days under the Terrorism Act [2006], and the use of control orders to detain without trial) may have contributed to the construction and reinforcement of the Muslim community as a 'suspect', which, in turn, may result in a police bias towards members of the Muslim community. Research showed that such police bias had contributed to the grave violations of human rights with appalling consequences that involved miscarriages of justice. This thesis focuses on an under-researched aspect of police investigative and interviewing processes, namely, the influence of prejudicial stereotyping on criminal investigations when investigating the suspects from a 'suspect' community. This thesis examined the influence of prejudicial stereotyping (within the context of criminal investigations) and originally contributed to the existing knowledge through the course of five studies. The first study focused on the role of prejudicial stereotyping in stop and search practices. This first study examined more than 2,100 stop and search records of the provincial police force in England and Wales, as well as 20 semi-structured interviews which were conducted with serving police officers (from the same force) to examine whether police officers use prejudicial stereotypes to inform suspicions in their day to day policing. This first study ascertained that officers rely on certain types of stereotypes (e.g. people's age, race, appearance, location, and social class) to inform their suspicions. In order to examine how such prejudicial stereotyping may affect criminal investigations, the second study in this thesis utilised a novel approach. In this second study, an innovative instrument 'the Minhas Investigative Interviewing Prejudicial Stereotyping Scale' (MIIPSS) was developed and used to assess the apparent level of interviewers' prejudicial stereotyping towards suspects from certain stigmatised groups. This study involved semi-structured interviews with twenty people, who had previously been interviewed as suspects in England and also eight very experienced lawyers. Both their views were measured using the MIIPSS before being subjected to a Guttman analysis. Statistical analyses showed that the MIIPSS satisfies the criteria for classification as a valid unidimensional and cumulative scale. It was found that the MIIPSS could be used as a tool to measure prejudicial stereotyping in investigative interviews towards suspects from stigmatised groups or individuals suspected of different types of crimes. The third study focused on the role of prejudicial stereotyping within the context of a 'suspect' community and investigative interviewing practices. As far as it is known, this is the first study that has obtained views from twenty-two real-life Asian Muslim suspects' and explored their perceptions to examine whether prejudicial stereotypes could influence investigative interviews. Thematic analysis of interviews revealed that around two-thirds of the suspects reported perceiving the demonstration of various stereotyping by police officers during interviews, half of whom indicated that the interviewers demonstrated racial/religious stereotypes via discriminatory behaviour. The fourth study in this thesis broke new ground by examining the perceptions of fifteen very experienced legal representatives who had represented suspects in the police interviews. Thematic analysis of interview transcripts revealed that one-third of the legal representatives reported that they witnessed instances (in what these legal representatives described as a reckoned comparable case) when a white suspect was released whereas a charge was sought against an Asian Muslim suspect. Additionally, a quarter of these legal representatives mentioned instances of perceived police interviewers' hostile and discriminatory behaviour towards their Muslim clients, also reporting that they felt such hostility was due to their client's Muslim background. The final study in this thesis is novel and groundbreaking to have analysed the influence of prejudicial stereotyping on real-life police interviewers' investigative decision-making within the context of the 'suspect' community. In order to explore whether a 'suspect' community stereotyping could influence police officers' instigative decision-making, the fifth study utilised information gathered via semi-structured interviews, conducted individually with twenty serving police officers from a single police organisation in England. During these interviews the same scenario was put to each police officer in turn, only differing in the name of the suspect (which for one half of the sample referred to an indigenous person from the UK, while the other half was referred to a suspect with obvious Muslim name). As a result of crisp-set qualitative comparative analysis (csQCA), it was found that when the 'Muslim suspect condition' was applied, six times as many officers stated that they would charge him with possession and intent to supply class A drugs than did those in the indigenous suspect condition. These results triangulated with those of the suspects and legal representatives' perceptions that the ethnicity and religious background may have played a role and influenced the outcome of investigations. In conclusion, findings from this thesis are not only consistent with the Hillyard's study (i.e. the 'suspect' community stereotyping may result in a police bias against members of the 'suspects' community) but the findings also suggest that perceived prejudicial stereotypes (based on a suspect's group membership) indeed may influence the outcome(s) of the criminal investigations.

Owing to a recent online trend of web 2.0, societies have emerged not only culturally but also technologically/virtually. This coupled with semantic web and Web Services have provided end-users with more opportunities to contribute to the web and consequentially have also multiplied their digital needs. One such requirement of a modern-day end-user is to combine the data, view and/or process presented across the web to suit his/her ephemeral needs by developing a novel application known as a service mashup. The end user development of mashup poses significant challenges to the end users. First challenge addressed in this thesis is the scope vs complexity challenge which refers to the impossibility of fully eliminating the technical barrier between a tool and the end user due to the corresponding complexity creeping in while developing new features in tool and extending its scope to provide added functionality. The second challenge arises from the utility=value/effort equation which implies that effort required in developing a mashup decreases the value and hence neutralizes the utility. Given these challenges and the related issues, I made three contributions. The central theme of my proposed approach - for managing these inherent challenges - is that the end user must be integrated into the process of a service composition application. My approach - A Goal-Oriented Mashup Development (GO-MaDe) framework defines, organizes and addresses the problems faced by end-users while composing their applications by proposing a new style of development in the mashup area in a bid to render irrelevant the underlying inherent tensions of the paradigm. My first contribution in this regard is a classification model that takes into account end user centered usability criteria for calibrating mashup tools efforts. Secondly, this research is the pioneer study about the integration of an agile-style analysis-cum-design phase into the mashup development process. Hence, it presents a redefined process of service-based applications development by introducing a spiral process model that introduces a phased, incremental concept of mashup development lifecycle. Based on the spiral model, I have presented a method (KAReM) annotated with domain theory for better acquisition and representation of user requirements encompassed by the APIs or Web Services that are composed to develop a mashup by incorporating the dynamics of goal decompositions using goal based templates. It serves to enhance the end-user experience by facilitating them to explore the problem space and helping them derive the visual representations of their requirements which can then be translated into service compositions. To evaluate my contributions qualitatively and quantitatively I conducted literature reviews, and validated my framework by scenarios and a controlled experiment.

Financial fraud rampages onwards seemingly uncontained. The annual cost of fraud in the UK is estimated to be as high as £193bn a year [1] . From a data science perspective and hitherto less explored this thesis demonstrates how the use of linguistic features to drive data mining algorithms can aid in unravelling fraud. To this end, the spotlight is turned on Financial Statement Fraud (FSF), known to be the costliest type of fraud [2]. A new corpus of 6.3 million words is composed of102 annual reports/10-K (narrative sections) from firms formally indicted for FSF juxtaposed with 306 non-fraud firms of similar size and industrial grouping. Differently from other similar studies, this thesis uniquely takes a wide angled view and extracts a range of features of different categories from the corpus. These linguistic correlates of deception are uncovered using a variety of techniques and tools. Corpus linguistics methodology is applied to extract keywords and to examine linguistic structure. N-grams are extracted to draw out collocations. Readability measurement in financial text is advanced through the extraction of new indices that probe the text at a deeper level. Cognitive and perceptual processes are also picked out. Tone, intention and liquidity are gauged using customised word lists. Linguistic ratios are derived from grammatical constructs and word categories. An attempt is also made to determine ‘what’ was said as opposed to ‘how’. Further a new module is developed to condense synonyms into concepts. Lastly frequency counts from keywords unearthed from a previous content analysis study on financial narrative are also used. These features are then used to drive machine learning based classification and clustering algorithms to determine if they aid in discriminating a fraud from a non-fraud firm. The results derived from the battery of models built typically exceed classification accuracy of 70%. The above process is amalgamated into a framework. The process outlined, driven by empirical data demonstrates in a practical way how linguistic analysis could aid in fraud detection and also constitutes a unique contribution made to deception detection studies.

Functional and degenerative damage to regions of the limbic system are often associated with cognitive impairments in different aspects of memory. Neuroimaging studies in post-traumatic stress disorder (PTSD) and Alzheimer's disease (AD) have reported selective hippocampal atrophy. Neuroimaging studies in panic disorder have also suggested reduced functional activity in the right parahippocampal gyrus. It is unclear whether this hippocampal damage is responsible for the emergence of selective neuropsychological deficits. Abnormal activity in limbic structures has also been reported in PTSD patients exposed to trauma-related stimuli. This thesis was concerned with examining the effects of structural and functional damage to the limbic system on selective cognitive abilities. The limbic structures under investigation included the hippocampus, parahippocampal gyrus, anterior cingulate cortex and amygdala. In order to investigate this issue, a series of neuropsychological and neuroimaging experiments were carried out using groups of patient populations, such as panic disorder, PTSD and AD, known to exhibit abnormalities to the limbic structures. An fMRI study, using the Color Stroop and Emotional Stroop task was also administered to PTSD patients and healthy controls. Results from the neuropsychological studies showed greater impairments in topographical/spatial memory compared to verbal memory in all groups of patients. In addition, voxel-based correlation analyses found that both PTSD and AD are associated with neuropsychological deficits in the area of visuo-spatial and topographical memory that may be explained by the regional brain atrophy in limbic structures. Abnormalities of the parahippocampal gyri and cingulate cortex and possibly the amygdalae in the fMRI study also suggested a dysregulation in limbic-cortical networks in PTSD. This thesis has demonstrated that damage to limbic structures might contribute to the cognitive abnormalities of panic disorder, PTSD and AD.

Objectives: The objective of this study was to verify if 3D reconstruction is feasible to assess maxillary impacted canines from a 2D panoramic X-ray.Methods: Pre-treatment CBCT data for 74 patients with impacted canines were collected. A dataset containing paired 2D panoramic X-rays and pseudo 3D images were converted from all 74 subjects. This pseudo 3D image contained information related to depth, as well as the location of the impacted canine in the buccal/lingual, mesial/distal, and apical/coronal position. These data were used to train a deep-learning reconstruction algorithm. The location of the maxillary impacted canine was determined from the output of the algorithm. The reconstruction was evaluated using structure similarity index measure (SSIM) as a metric to indicate the reconstruction quality. Additionally, the accuracy of the impacted canine location was calculated.Results: The reconstruction algorithm predicts the position of the impacted canine in the buccal, middle, or lingual position with a 41% accuracy. The mesial and distal positions are predicted with 55% accuracy. The mean SSIM for the output is 0.71 with a range of 0.63 - 0.84. Conclusions: Although our SSIM values were equivalent to the values reconstructed by other deep-learning algorithms in the dental field, we found that our 3D reconstruction had less than 50% accuracy in determination of the impacted canine location. Further development of deep learning algorithms is needed to increase the robustness in dental reconstruction applications.

The motivation of this work is to present an energy cost reduction concept in a home area power network (HAPN) with intelligent generation and flexible load demands. This study endeavors to address the energy management system (EMS) and layout-design challenges faced by HAPN through a systematic design approach. The growing demand for electricity has become a significant burden on traditional power networks, prompting power engineers to seek ways to improve their efficiency. One such solution is to integrate dispersed generation sources, such as photovoltaic (PV) and storage systems, with an appropriate control mechanism at the distribution level. In recent years, there has been a significant increase in interest in the installation of PV-Battery systems, due to their potential to reduce carbon emissions and lower energy costs. This research proposes an optimal economic power dispatch strategy using Model Predictive Control (MPC) to enhance the overall performance of HAPN. A hybrid AC/DC microgrid concept is proposed to address the control choices made by the appliance scheduling and hybrid switching approaches based on a linear programming optimization framework. The suggested optimization criteria improve consumer satisfaction, minimize grid disconnections, and lower overall energy costs by deploying inexpensive clean energy generation and control. Various examples from actual case study demonstrate the use of the established EMS and design methodology.

Infertility is an emotionally devastating condition for a couple. It is defined as the inability to conceive following 1 year of regular unprotected intercourse. Infertility affects 15% of couples with nearly 50% of cases due to poor sperm quality in the male partner. i.e. 'male factor infertility'. There are currently no approved pharmacological therapies to directly stimulate spermatogenesis; anti-oestrogens and aromatase inhibitors have limited effectiveness for the treatment of oligospermia and their usage is not supported by current clinical guidelines. Consequently, the only therapeutic option for male factor infertility is assisted reproductive technologies (ART), such as intra-cytoplasmic sperm injection (ICSI) which although effective are resource limiting and unaffordable for many couples worldwide. Therefore, there exists an important and unmet need to develop practical and cost-effective therapies for male factor infertility. Over the last 50 years, whilst sperm quality has declined, obesity has doubled in prevalence. Evidence suggests an association between obesity and male infertility, which makes weight loss a plausible answer to this rising endemic problem. Currently, bariatric surgery is the most effective treatment for obesity leading to major weight loss. However, effects on semen parameters are controversial, with some studies suggesting that the acute starvation-like state induced by bariatric surgery paradoxically reduces sperm function. Recent observational reports have suggested that milder dietary weight loss is associated with improved semen quality and DNA fragmentation index (DFI) in men with obesity and infertility. Low energy diet (LED) is a safe, well-tolerated and established method of achieving modest weight loss which could therefore provide a novel, non-pharmacological therapy for men with obesity-related male factor infertility. However to date, there are currently no prospective randomised controlled studies investigating whether weight loss via LED can improve sperm quality in obese men. Additionally, it is unclear what level of weight loss would be ideal to optimise sperm quality in obese men. This thesis outlines the first ever three randomised controlled studies investigating the physiological effects of weight loss by LED on sperm quality in obese fertile (study 1 and 2) and infertile men (study 3) respectively. I hypothesized that some, but not all, degrees of weight loss would significantly improve sperm concentration in men with obesity, with a potential threshold of weight loss in men leading to improvements 3 in sperm quality. I have measured novel molecular markers, such as seminal reactive oxygen species (ROS) and DFI, associated with male infertility in obese men undergoing weight loss. Collectively, these results will extend our understanding of the physiological effects of weight loss on sperm quality in obese men. This could potentially lead to larger studies determining the effect of weight loss on live birth rates in couples affected by obesity-related male infertility.

Infertility is defined as the inability to become pregnant following one year of practicing regular and unprotected sexual intercourse and is estimated to affect 72.4 million people globally. Within the U.K., infertility has been estimated to affect 14% of couples. In 50% of cases of infertility the cause will be attributable to poor sperm quality and the main treatment is assisted reproductive technologies (ART) such as in-vitro fertilisation (IVF). However, ART is resource limited and IVF has an estimated success rate of 29%. Thus, there is an urgent need to improve our understanding of the pathophysiological mechanisms that underpin male infertility to help develop more cost-effective therapies. Recent studies have highlighted the effects of oxidative stress (including seminal reactive oxygen species (ROS) and sperm DNA fragmentation (SDF)) in sperm dysfunction. Furthermore, there is limited data showing differences in seminal microbiome in infertile compared to fertile men. However, it is unclear from the literature how oxidative stress and the seminal microbiome correlate with semen analysis. This is pertinent given that semen analysis is the gold standard investigation for diagnosing male infertility. Non obstructive azoospermia (NOA) is the absence of sperm in the ejaculate due to impaired spermatogenesis. The only method for men with NOA to conceive biological children is through sperm retrieval surgery combined with ART. However, the success rate of testicular sperm extraction in men with NOA is only 50%. In half of all cases of NOA the cause is unknown but there is emerging data showing that genetic mutations may be contributory. This knowledge is helpful in both patient counselling and clinical management. For example, men with NOA who have either Azoospermia factor A or B gene deletions have a lower likelihood of testicular tissue containing sperm and should be counselled against sperm retrieval surgery. There is emerging data showing that in some cases of idiopathic NOA, a genetic mutation may be causal. Further genetic studies are needed to help improve our understanding of the aetiology of NOA and this may help identify future therapeutic targets for men with infertility. Spermatogenesis is stimulated by gonadotropins and intratesticular testosterone. Some clinicians have trialed hormone stimulation therapy to improve sperm retrieval rates in men with NOA. However, no study has critically evaluated the literature regarding the effects of hormone stimulation therapy in improving sperm retrieval rates and also the potential adverse events. This thesis includes the first study investigating how oxidative stress markers and seminal microbiome differ in different cohorts of male infertility and fertile controls. Furthermore, I performed the first meta-analysis investigating the effects of hormone stimulation therapy on surgical sperm retrieval rates in men with NOA. I have also investigated for novel genetic mutations in a cohort of infertile men with idiopathic NOA. Collectively, the results from this thesis will improve our understanding on the aetiological factors, pathophysiological mechanisms and management of male infertility.

Abstract: In order to assess the effectiveness of public policy interventions (or lack of) aimed at food insecure households, an individual’s socio-economic and demographic status, energy adequacy, and healthy food diversity need to be better understood. Through a cross-country comparison (Canada, US and India) of the determinants of dietary adequacy and diversity, with different policy programs aimed at enhancing food security in place, we can provide recommendations for effective strategies aimed at reducing food insecurity, in different contexts. Results suggest that multiple indicators need to be assessed to understand the multi-faceted nature of a household’s food security status. Income plays a significant role in energy adequacy, while respondent age and family size play an important role in healthy food diversity. Assessing policy programs by effectiveness suggests that India may benefit from a cash transfer program instead of the traditional TPDS.

Infertility is the inability to achieve pregnancy after 12 months of regular intercourse and is associated with male factors in 40% of couples. Currently, the diagnosis of male infertility is based on conventional semen analysis and management options involve assisted reproduction therapies for the female partner. The regulation of male fertility therefore remains under investigated. Recurrent pregnancy loss is the loss of 3 or more pregnancies before the 24th week of gestation. As half of the female partners have normal investigations, their male partners may be contributing to a significant extent, but male partners are not commonly investigated. By using a direct chemiluminescence assay to measure semen oxidative stress, my data showed markedly elevated oxidative stress in the semen of male partners affected by recurrent pregnancy loss. The main source of semen oxidative stress is leucocytes derived myeloperoxidase, a hyperactivated enzyme in chronic inflammatory states such as obesity. I have performed an in vivo study investigating the effect of a novel myeloperoxidase inhibitor on reproductive function in mice with diet-induced obesity. Having established that obesity has detrimental effects on male fertility from previously published studies, I investigated the effects of weight loss on obese male. Caloric restriction for weight loss was given to obese men over a period of two months and their semen parameters were compared to a control group who received simple observations over the same time period. In summary, I have identified a novel diagnostic marker for male partners of women with recurrent pregnancy loss. My weight loss study was the first randomised controlled study to identify the effects of caloric restriction in sperm function of obese men. These data have important implications for the diagnosis of male infertility and could provide an effective intervention for couples with male factor infertility associated with obesity.

Asthma is a chronic disease of the lungs and respiratory passages. Hallmarks of asthma exacerbation, commonly referred to as an “asthma attack,” are bronchoconstriction, inflammation, and airway remodeling. Millions of people worldwide have asthma, with both children and adults affected by the disease. Asthma prevalence in the United States has been increasing on a yearly basis, and thus asthma is a serious health threat to people of all ages. Asthma can be controlled with short term bronchodilatory drugs and inhaled corticosteroids for long-term inflammation management. Pediatric asthma is particularly taxing, however, as it can cause numerous absences from school, frequent hospitalizations, and can be difficult for children to manage without close supervision. Many of these pediatric patients present in emergency departments, and are given oral or IV steroids to treat the asthma exacerbation. We specifically want to assess the effect of early administration of these steroids on the patient outcomes of admission rate and length of stay. We hypothesize that patients given steroids sooner rather than later are less likely to be admitted to inpatient status and will have a shorter stay in the emergency department. To test our hypotheses, we conducted a retrospective study in which we gathered pediatric patient data from August, 2011, to April, 2012. We included patients that presented with asthma exacerbation and recorded a number of metrics and variables for each patient, including time of steroid administration, admission status, and total length of stay in the emergency department. Steroid administration time was separated into two categories: administration pre or post-30 minutes of triage, and administration pre or post-60 minutes of triage. This data was logged, reviewed, and finally analyzed for statistical significance. Results of the study showed that there is no statistically significant association between time of steroid administration on admission rates. To assess the relationship of steroid administration time and length of stay in the emergency department, patients with the same admission status were compared against one another in order to eliminate potential confounding (i.e. length of stay for admitted patients who received steroids within 30 minutes was compared to that of admitted patients receiving steroids post-30 minutes, and so on). Overall, those patients receiving steroids tended to have a shorter mean length of stay in the emergency department. This finding was statistically significant for only one subset of the patient sample, however: discharged patients who received their steroids pre-60 minutes as opposed to post-60 minutes. While the data that we analyzed did not depict many statistically significant associations, it did reveal trends in outcomes that are associated with timing of steroid administration. With further study and an expanded sample size, these associations may prove to be of significance. From a clinical perspective, such findings could impact emergency asthma care, with early steroid administration becoming more of a priority in treatment protocols.

This study is an exploratory study, descriptive in nature and investigates the familiarity and practices of midwives and women with regard to complementary therapies during pregnancy and labour. The study was conducted in four major hospitals in Western Sydney, namely Nepean, Jamieson, Blue Mountains Anzac Memorial and Hawkesbury hospitals. The findings showed that in the main the midwives and women were familiar and made use of four therapies, ie. aromatherapy, massage, music and hydrotherapy. The midwives practiced without any significant training in these therapies. Hospital policies were almost non existant in relation to the practice of complementary therapies and nurses often felt frustrated at not being able to implement complementary therapies. The main issues that emerged from the study were the need for education for the midwives related to specific complementary therapies, hospital policies conducive to the practice of complementary therapies and research into the efficacy of the different complementary therapies. The women need further exposure to complementary therapies and education in the respective therapies if they are to feel empowered in dealing with the stress of their daily lives