Higher derivative terms and their influence on N=2 supersymmetric systems

This thesis is concerned with so-called higher derivative terms which arise in low energy approximations to certain physical models. In particular, the aim is to investigate the role that such terms play in low energy N=2 supersymmetric gauge theories in 4 dimensions, with gauge group SU(2).Chapter one serves as an introduction to the notions of supersymmetry and superfields. The problem of constructing an effective action which describes the low energy dynamics is introduced, and the construction of the Wilsonian action in terms of light and heavy modes is developed. The concept on a derivative expansion is also described. Chapter two introduces N=2 supersymmetric gauge theories with spontaneous symmetry breaking. It is observed that such systems always have a Bogomolnyi bound, and the consequences are discussed. We then develop a derivative expansion of this system in terms of N=2 superfields, drawing particular attention to the next-to- leading order derivative term (that is, those with 4 derivatives/8 fermions). The duality properties of such a term are reviewed, and their impact on the mass formula discussed. Conclusions are drawn as to their influence on the results of Seiberg and Witten. Chapter three deals with a non-renormalisation theorem for the next-to-leading order higher derivative term proposed by Dine and Seiberg. This states that instanton contributions to such a term in massless N=2 SU(N(_c)) gauge theories vanish when the number of flavours N(_f) = 2N(_c). We prove this result using the ADHM formalism for multi-instantons in the case N(_c) = 2

Performance effects of appointing other firms' executive directors

This paper studies the relationship between directors’ human capital and the company’s performance. In particular, we focus on the effect on performance of non-executive directors who are also executive directors in other firms. We find a positive relationship between the presence of these non-executive directors and the accounting performance of the appointing company. The effect is stronger if these directors are also executive directors at companies that are performing well. Additionally, the similarity of industry plays a role. The results support the view that appointing firms benefit from the human capital of the appointee

Accuracy and feasibility of an android-based digital assessment tool for post stroke visual disorders - The StrokeVision App

Background: Visual impairment affects up to 70% of stroke survivors. We designed an app (StrokeVision) to facilitate screening for common post stroke visual issues (acuity, visual fields and visual inattention). We sought to describe the test-time, feasibility, acceptability and accuracy of our app based digital visual assessments against a) current methods used for bedside screening, and b) gold standard measures. Methods: Patients were prospectively recruited from acute stroke settings. Index tests were app based assessments of fields and inattention performed by a trained researcher. We compared against usual clinical screening practice of visual fields to confrontation including inattention assessment (simultaneous stimuli). We also compared app to gold standard assessments of formal kinetic perimetry (Goldman or Octopus Visual Field Assessment); and pencil and paper based tests of inattention (Albert’s, Star Cancellation, and Line Bisection). Results of inattention and field tests were adjudicated by a specialist Neuro-Ophthalmologist. All assessors were masked to each other’s results. Participants and assessors graded acceptability using a bespoke scale that ranged from 0 (completely unacceptable) to 10 (perfect acceptability). Results: Of 48 stroke survivors recruited, the complete battery of index and reference tests for fields was successfully completed in 45. Similar acceptability scores were observed for app-based (assessor median score 10 [IQR:9-10]; patient 9 [IQR:8-10]) and traditional bedside testing (assessor 10 [IQR:9-10; patient 10 [IQR:9-10]). Median test time was longer for app-based testing (combined time-to-completion of all digital tests 420 seconds [IQR:390-588]) when compared with conventional bedside testing (70 seconds, [IQR:40-70]) but shorter than gold standard testing (1260 seconds, [IQR:1005-1620]). Compared with gold standard assessments, usual screening practice demonstrated 79% sensitivity and 82% specificity for detection of a stroke-related field defect. This compares with 79% sensitivity and 88% specificity for StrokeVision digital assessment. Conclusion: StrokeVision shows promise as a screening tool for visual complications in the acute phase of stroke. The app is at least as good as usual screening and offers other functionality that may make it attractive for use in acute stroke

Channel characterisation and modelling for transcranial Doppler ultrasound.

The detection of micro-embolic signals (MES) is a mature application of transcranial Doppler (TCD) ultrasound. It involves the identification of abnormally highpitched signals within the arterial waveform as a method of diagnosis and prediction of embolic complications in stroke patients. More recently, algorithms have been developed to help characterise and classify MES using advanced signal processing techniques. These advances aim to improve our understanding of the causes of cereberovascular disease, helping to target the most appropriate interventions and quantifying the risk to patients of further stroke events. However, there are a number of limitations with current TCD systems which reduce their effectiveness. In particular, improvements in our understanding of the scattering effects in TCD ultrasound propagation channels will benefit our ability to develop algorithms that more robustly and reliably identify the consistency and material make-up of MES. This thesis explores TCD propagation channels in three related research areas. Firstly, a method of characterising TCD ultrasound propagation channels is proposed. Isotropic and non-isotropic three dimensional space (3-D) spherical scattering channel models are described in terms of theoretical reference models, simulation models, and sum of sinusoids (SoS) simulators, allowing the statistical properties to be analysed and reported. Secondly, a TCD ultrasound medical blood flow phantom is described. The phantom, designed to replicate blood flow in the middle cerebral arteries (MCA) for TCD ultrasound studies, is discussed in terms of material selection, physical construction and acoustic characteristics, including acoustic velocity, attenuation and backscatter coefficients. Finally, verification analysis is performed on the non-isotropic models against firstly, the blood flow phantom, and secondly, a patient recordings database. This analysis expands on areas of agreement and disagreement before assessing the usefulness of the models and describing their potential to improve signal processing approaches for detection of MES. The proposed non-isotropic channel reference model, simulation model, SoS simulator, and blood flow phantom are expected to contribute to improvements in the design, testing, and performance evaluation of future TCD ultrasound systems

The effect of co-trimoxazole on serum potassium concentration: safety evaluation of a randomized controlled trial

AIMS: Co-trimoxazole maintains a well-established role in the treatment of Pneumocystis jirovecii and Toxoplasma gondii, as well as urinary tract infections. Observational studies report hyperkalemia associated with co-trimoxazole which may stem from an amiloride-like potassium sparing effect. Our study reports on changes in serum potassium on patients without acute infections, and the influence of concomitant anti-kaliuretic drugs on this effect.  METHODS: Post-hoc analysis of a randomised controlled trial in patients with interstitial lung disease who were assigned to placebo or 960 mg twice daily co-trimoxazole. Serum potassium and creatinine were measured at baseline, six weeks, 6, 9 and 12 months. Primary outcome was difference in mean serum potassium concentrations between co-trimoxazole and placebo at six weeks.  RESULTS: Mean serum potassiums were similar at baseline, 4.24 (±0.44) mmol/L in the 87 co-trimoxazole group participants and 4.25 (±0.39) mmol/L in the 83 control participants. Co-trimoxazole significantly increased mean serum potassium at 6 weeks, difference between means compared to placebo of 0.21 mmol/L (95% Confidence Intervals [CI] 0.09-0.34; p = 0.001). This significant increase in serum potassium was detectable even after exclusion of patients on anti-kaliuretic drugs, difference between means for co-trimoxazole compared to placebo 0.23 mmol/L (95% CI 0.09-0.38, p = 0.002). There were 5/87 (5.7%) patients on co-trimoxazole whose serum potassium reached concentrations ≥5.5 mmol/L during the study period.  CONCLUSIONS: Co-trimoxazole significantly increases serum potassium concentration, even in participants not using anti-kaliuretic drugs. Whilst the magnitude of increase is often minor, a small proportion in our outpatient cohort developed hyperkalaemia of clinical importance

Location of Mach Discs and Diamonds Supersonic Air Jets

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77542/1/AIAA-3788-127.pd

Sheep as host species for zoonotic Babesia venatorum, United Kingdom

Babesia venatorum is an increasingly prominent zoonotic parasite that predominantly infects wild deer. Our molecular examination of Babesia infecting mammals in the United Kingdom identified 18S sequences in domestic sheep isolates identical to zoonotic B. venatorum. Identification of this parasite in livestock raises concerns for public health and farming policy in Europe

Survey: Leakage and Privacy at Inference Time

Leakage of data from publicly available Machine Learning (ML) models is an area of growing significance as commercial and government applications of ML can draw on multiple sources of data, potentially including users' and clients' sensitive data. We provide a comprehensive survey of contemporary advances on several fronts, covering involuntary data leakage which is natural to ML models, potential malevolent leakage which is caused by privacy attacks, and currently available defence mechanisms. We focus on inference-time leakage, as the most likely scenario for publicly available models. We first discuss what leakage is in the context of different data, tasks, and model architectures. We then propose a taxonomy across involuntary and malevolent leakage, available defences, followed by the currently available assessment metrics and applications. We conclude with outstanding challenges and open questions, outlining some promising directions for future research