At a time when global debates about the movement of people have never been more heated, this book provides readers with an accessible, student-friendly guide to the subject of forced migration. Readers of this book will learn who forced migrants are, where they are and why international protection is critical in a world of increasingly restrictive legislation and policy. The book outlines key definitions, ideas, concepts, points for discussion, theories and case studies of the various forms of forced migration. In addition to this technical grounding, the book also signposts further reading and provides handy Key Thinker boxes to summarise the work of the field’s most influential academics. Drawing on decades of experience both in the classroom and in the field, this book invites readers to question how labels and definitions are used in legal, policy and practice responses, and to engage in a richer understanding of the lives and realities of forced migrants on the ground. Perfect for undergraduate and postgraduate teaching in courses related to migration and diaspora studies, Introducing Forced Migration will also be valuable to policy-makers, practitioners, journalists, volunteers and aid workers working with refugees, the internally displaced and those who have experienced trafficking.

Air traffic at many airports around the world is expected to grow, more often than not and at near capacity. Investing in new infrastructure is an option albeit relatively long-term but making a better use of existing facilities is an even better short and mid-term solution. Although Aircraft ground movement represents only a fraction of overall operations, optimal airport taxiing in terms of fuel burn and CO emission can contribute significantly to running costs and environment impact. Hence, with the view of optimising ground movement at busy airports, this research paper investigates a new framework for utilising model predictions to optimise the planning of taxiing operations of a BOEING-747 Aircraft. Research studies relating to how fuel consumption and emissions models (such as Carbon monoxide oxides of Nitrogen) are carried out. Specifically, the use of fuzzy-logic based models via quantitative data for the successful prediction of fuel consumption and CO emissions is explored in the paper. The fuzzy models are accurate, transparent but most importantly are capable of dealing with uncertainties, normally present in the system, intrinsically. These models and analyses will be integrated into a future study involving the development of optimal taxiing and navigation algorithms and to which the development of accurate models of aircraft fuel consumptions and emissions is crucial.

Laser interference patterning or lithography has been used in variety of the applications using, patterning, masking and processing structures at top of material. It offers fast processing over as large areas can be processed simultaneously. Additionally, fine patterns are possible to achieve both in micro and sub-micro scale. In this manuscript is presented novel concept to combine interference patterning and high-pressure processing environment. With aid of high-pressure system, it is possible to control processing environment and add co-solvents in desired state (liquid, gas, supercritical) and use developed system as controlled reactive environment in the future studies. Two systems were developed and assembled for testing and proofing the concept. The results of the two 4-beam interference systems (lens- and mirror-based) are presented and compared.

The financial crisis and increasing concerns around climate change and global warming have combined to shatter societal trust in the banking sector worldwide. Consequently, there is an urgent need for banks to rebuild trust among their stakeholders and enhance their reputations. This paper contributes to a growing literature in sustainable and green banking by exploring the views of senior banking representatives towards the implementation of sustainability initiatives through extensive interview research. We explore the extent to which such initiatives are embedded within the banking industry, whether they represent risk management mechanisms and whether they are imbued with reputational risk management rather than a genuine response to ethical societal concerns. The interviewees’ utterances are interpreted through a sociological theoretical lens derived from the work of Giddens and Beck, allowing us to conclude that external initiatives such as the Equator Principles seem to be adopted as re-embedding mechanisms that can rebuild societal trust, as well as representing mechanisms of reputational risk management. Further, the analysis suggested that internal sustainability initiatives were interpreted as coping mechanisms whereby bank employees can recreate their protective cocoon, reinstating their ontological security in response to the high consequence risks of climate change and other related systemic factors that create overwhelming feelings of engulfment.

The purpose of this study was to investigate the effects of a competitive soccer match on jump performance and interlimb asymmetries over incremental time points during a 72-hour period. Fourteen elite adolescent players from a professional English category 3 academy performed single-leg countermovement jumps pre, post, 24-, 48-, and 72-hour post-match on a single force platform. Eccentric impulse, concentric impulse, peak propulsive force, jump height, peak landing force, and landing impulse were monitored throughout. Interlimb asymmetries were also calculated for each metric as the percentage difference between limbs. Significant negative changes (p < 0.05) in jump performance were noted for all metrics at all time points, with the exception of jump height. Interlimb asymmetries were metric-dependent and showed very large increases, specifically post-match, with a trend to reduce back toward baseline values at the 48-hour time point for propulsive-based metrics. Asymmetries for landing metrics did not peak until the 24-hour time point and again reduced toward baseline at 48-hour time point. This study highlights the importance of monitoring distinct jump metrics, as jump height alone was not sensitive enough to show significant changes in jump performance. However, interlimb asymmetries were sensitive to fatigue with very large increases post-match. More frequent monitoring of asymmetries could enable practitioners to determine whether existing imbalances are also associated with reductions in physical performance or increased injury risk.

While rare, incidents of inappropriate and/or unnecessary surgery do occur, so effective surveillance of surgical practice is required to ensure patient safety. This article explores the case of Ian Paterson, a consultant surgeon who was sentenced to 20 years in prison in 2017 for wounding with intent and unlawful wounding, primarily by undertaking inappropriate or unnecessary mastectomies. The article details the main points of the Paterson case, with reference to the subsequent government-commissioned inquiry and its recommendations. It also outlines various strategies for enhancing patient safety, including applying human factors theory, improving auditing, and rationalising NHS and private healthcare. The author concludes that nurses have a crucial role in the surveillance of surgical practice and that combined reporting of surgeons' practice across NHS and private healthcare organisations is required.

Speciation not associated with morphological shifts is challenging to detect unless molecular data are employed. Using Sanger-sequencing approaches, the Lomatium packardiae/L. anomalum subcomplex within the larger Lomatium triternatum complex could not be resolved. Therefore, we attempt to resolve these boundaries here. The Angiosperms353 probe set was employed to resolve the ambiguity within Lomatium triternatum species complex using 48 accessions assigned to L. packardiae, L. anomalum, or L. triternatum. In addition to exon data, 54 nuclear introns were extracted and were complete for all samples. Three approaches were used to estimate evolutionary relationships and define species boundaries: STACEY, a Bayesian coalescent-based species tree analysis that takes incomplete lineage sorting into account; ASTRAL-III, another coalescent-based species tree analysis; and a concatenated approach using MrBayes. Climatic factors, morphological characters, and soil variables were measured and analyzed to provide additional support for recovered groups. The STACEY analysis recovered three major clades and seven subclades, all of which are geographically structured, and some correspond to previously named taxa. No other analysis had full agreement between recovered clades and other parameters. Climatic niche and leaflet width and length provide some predictive ability for the major clades. The results suggest that these groups are in the process of incipient speciation and incomplete lineage sorting has been a major barrier to resolving boundaries within this lineage previously. These results are hypothesized through sequencing of multiple loci and analyzing data using coalescent-based processes.

Machine learning is adopted widely in many sectors including healthcare, automotive and finance where machine learning use cases include disease detection, predictive maintenance, and fraud detection. During 2017/2018, around 40%(226,000) of the incidents attended by fire and rescue service were false alarms. Therefore, this thesis is focused towards the application of machine learning on fire alarm systems data to address the rising problem of false alarms. The fire alarm system on site gathers the data about different events which can be utilised to conduct the experiments with machine learning. Therefore , to address this problem five different classification machine learning models including Logistic Regression, Support Vector Machines, Naïve Bayes Classifier, Decision Trees and Random Forests have been used to experiment with data gathered from fire alarm system. The performance of the different machine learning models is evaluated using different methods such as precision, recall, f1- score, confusion matrix, k-fold cross validation and mean accuracy to find the best suited models for reducing false alarm rates. Experiments were conducted on data gathered from the fire alarm system, 10-fold cross validation results indicated Naïve Bayes Classifier detecting 51 out of 53 Fires correctly but with a high misclassification rate and low mean accuracy of 61%. The remaining four models failed in classifying any fires correctly with 0.00 recall, still achieving overall accuracy in the range of 97-98% due to high imbalance in the dataset. The Cohen Kappa value of 0.0 was achieved by models indicating poor agreement in the decisions made. Machine learning models exhibited better performance on the new test data with incorporated temperature data, models achieved higher recall in the range of 0.70 to 1.00 during 10-fold cross validation as well as higher Cohen Kappa scores in the range 0.73 to 0.88 indicating substantial agreement in the decisions made by the machine learning models. The results on fire system data indicated machine may not be that effective due to poor correlation between the features in the data and high imbalance in the data. However, much better results are achieved by incorporating some additional sensors such as temperature into the fire alarm system data.

Alzheimer’s disease (AD) is a rapidly progressive chronic neurodegenerative disease, which eventually leads to brain damage. Despite combined efforts of the research community, no fully effective treatment has been identified yet. Drug delivery is a major issue in neurodegenerative diseases due to the complexity of the diseases but the difficulty in accessing targets. A medicine is only effective if it reaches its target. As such, while some active molecules can be demonstrated very efficiently in vitro, side effects and unreachable targets bring delivery at the forefront of drug efficiency. Rivastigmine is one of the reversible Acetylcholinesterase (AChE) Inhibitors, which is used for the treatment of mild to moderate dementia of either AD or Parkinson’s disease (PD). As a cholinesterase inhibitor, its role is to inhibit AChE activity to maintain ACh level by decreasing its breakdown rate, therefore boosting cholinergic neurotransmission in forebrain regions and compensate for the loss of functioning brain cells Rivastigmine has shown some success in improving ACh level in AD patients and also inhibiting amyloid plaques deposition in the brain. It is commercially available in different forms including oral solutions, tablets, and patches but therapeutic regimens require frequent dosing causing fluctuations is the plasma level. Whereas the oral form has been associated with a high incidence of gastrointestinal side effects, the transdermal patch formulation has been shown to have a better tolerability profile but adverse dermatologic reactions remain a concern. In addition, an important safety concern persists with dermal application with the risk of treatment overdose by administering multiple patches at the same time, potentially leading to fatal outcomes. Therefore, the oral form could be safer if its side effects could be controlled. Following initial uptake, crossing the blood-­‐brain barrier (BBB) is another major obstacle to be considered. Due to its hydrophilic nature, rivastigmine efficacy is also restricted by its poor ability to cross BBB. Its bioavailability is reported to be only up to 35%. To overcome these issues, this work has focused on the delivery of rivastigmine, particularly its uptake with nanoparticle-­‐based formulations that can facilitate uptake, protect the active molecule from early degradation, and provide targeted delivery while preventing side effects due to unwanted interactions. Rivastigmine loaded nanoparticles have previously been designed and proven to have numerous fundamental properties that assist their effectiveness such as biocompatibility, lack of toxicity, reduced side effects, and increased tolerated dose of the drug but not effective enough for the treatment. Their enhanced retention time within the systemic circulation and their ability to cross BBB still remains challenging. The novel formulations designed in this study were designed for slow release to prevent cytotoxicity while providing stability and high uptake in GI tract to reach the systemic circulation. Biodegradable composition of these formulations will prevent the risks that may contribute to accumulation of inorganic material inside the brain. As the aim of the research is the successful targeted delivery of Rivastigmine, the first objective of this study was to design an efficient method to monitor and analyse delivery, using UPLC in an analytical set up standardised using in house developed standard solutions. In the second part of this study, several formulations were designed and investigated to improve rivastigmine intestinal uptake, where both negatively and positively charges drug loaded nanoparticles were formulated. In the third part of this work ,a Caco-­‐2 cell duodenal model was used to assess membrane permeability, uptake, and intake of Rivastigmine. Cytotoxicity of nanoformulations was determined by MTT assay showing low toxicity in the case of rivastigmine-­‐loaded nanoparticles. The final results of this study demonstrate that nanoparticle formulations provide a slower stable release of rivastigmine from nanoparticles than previously designed nanoformulations. I addition, some of these formulations provide high bioavailability over both apical and basal membrane, therefore, providing higher intake to target the BBB, with limited unwanted interaction in the intestine therefore limiting the major concern about side effects

Child Sexual Abuse (CSA) is global problem that is found in all societies and cultures. Although there is research exploring CSA in western countries, the literature shows that there is limited CSA research on developing countries, like South Africa which is the focus of this thesis. Incidence and prevalence rates are substantially higher in South Africa when compared to other countries and for that reason, further research is needed for the context of that region. The literature shows that ‘coping’ from CSA plays a significant role in survivors’ lives but it is an area that has not been explored sufficiently in South Africa. To this end, the subject of this thesis is to explore ‘coping’ from CSA in South Africa and to explore ways in which CSA survivors cope with their experiences of abuse. This has been achieved through outlining the existing research on CSA coping in the region with the aim to identify studies that are related with topic; to understand the main learnings for that specific population; and to compare these findings to the strategies of other western countries. The study identifies a number of coping strategies that have been adopted by CSA survivors in South Africa to cope with the abuse. It is also shown that similar strategies have been used by CSA survivors in western countries. The link between coping strategies in the area and the specific cultural characteristics is discussed as well. This thesis makes knowledge around coping strategies in South Africa available, and identifies areas for further research.