Gram-negative bacteria cause a high global case burden of infectious disease. The characteristic double membrane distinguishing the Gram-negative wall confers resistance to different antibiotics, which limits clinical treatment options in these infections. A perplexing feature of the Gram-negative cell wall is the strikingly thin peptidoglycan layer, which can be up to ten times thinner than that in Gram-positive organisms. Peptidoglycan contributes structural rigidity and resistance to turgor pressure to bacteria; its hydrolysis promotes cell lysis and can contribute to bacteriophage infection of bacteria.

Lysozymes are peptidoglycan hydrolases, ubiquitous in most mammalian secretions, which form the first line of host innate immunity against bacteria. Gram-negative bacteria are known to resist degradation by lysozymes through endogenous expression of chromosomally encoded lysozyme inhibitor proteins. Genes encoding lysozyme inhibitor proteins are widespread in Gram-negative organisms; expression of these proteins may contribute to Gram-negative pathogenicity in host organisms.

This work studies the lysozyme-inhibitory characteristics of Ivy proteins from Escherichia coli and Pseudomonas aeruginosa, establishing the mechanism underpinning their inhibition of lysozymes.

This thesis investigates the impact of lactoferrin, another host innate immunity protein, on permeabilization of the Gram-negative cell wall. Species-specific synergy profiles of lactoferrin with lysozyme or antibiotic drugs were established, in hopes of advancing clinical efforts to sensitise pathogens to antibiotic treatments.

In silico modelling of lysozyme inhibitor protein complexed with hen egg white lysozyme, human lysozyme, the type III secretion system hydrolase EtgA, and bacteriophage T4 endolysin was performed and contributes structural information of these complexes which is hoped to expand current research on lysozyme inhibitor proteins.

In silico modelling of lysozyme inhibitor protein complexes with sperm acrosome associated proteins 3 and 5 suggests a putative sui generis mechanism for bacterial-associated infertility, the first suggestion of such an interaction. It is hoped that this work will advance research in reproductive medicine.

China's growing engagement in Africa has led to a new form of workplace engagement for the African context – interaction between Chinese entrepreneurs and local African business people. Its investment in Africa has attracted numerous controversial state-level debates around political motivations, colonialism, Chinese loans etc., (Peng, 2021). However, these discussions mostly concern the political, economic and employment intentions behind the expansion of Chinese companies. There has been very limited research into relationship management between Chinese and Africans as individuals in shaping the company dynamic (Anderson, 2010 Brautigam, 2009; Chang, 2013).

Recent politeness research has started to shift its focus towards the process of relationship management and evaluations. Specifically, Spencer-Oatey and Kádár (2021) have mapped out the steps of the evaluation process to help reveal how people evaluate each other. This thesis applies this framework to the intercultural workplace experiences of Kenyans and Chinese as they relate to each other in Chinese-owned companies in Kenya.

The thesis presents findings from 25 in-depth qualitative interviews with Chinese and Kenyans working in Chinese companies in Kenya. 162 short stories have been extracted from the interviews for analysis, using Barkhuizen's (2019) perspective on narrative inquiries to better capture the factors outlined in Spencer-Oatey and Kádár's (2021) Rapport Evaluation Model. The story data were analysed in MAXQDA 22 to identify the themes of the interviewees' experiences of relating and the criteria they used for evaluative judgements.

The findings reveal two main things: (a) relationship management is affected by a complex range of factors, including power dynamics, goals, and rights and obligations, (b) Analysis of the evaluation criteria used by the participants revealed that it was a complex process, with the criteria interpreted differently by the various participants. Theoretically, the thesis proposes some modifications to Spencer-Oatey and Kádár's (2021) Rapport Evaluation Model and empirically, it uncovers a wide range of interculturally sensitive areas that warrant practical attention.

To achieve significant energy savings in air and water supply systems, variable frequency induction motor drives are employed to power centrifugal fans and pumps. The cost of implementing closed loop control for energy savings can be reduced by replacing expensive flow rate or pressure sensors with estimators that are based on monitored variables from the drives and are embedded into their software. Existing estimation techniques rely on quasi-steady modelling of fans and pumps using data from steady state experiments or data sheets. However, this approach faces challenges during transients, which are addressed in the present thesis. This research proposes quasi-steady and dynamical estimators for the flow rate and pressure of a centrifugal fan with an induction motor drive, based on neural networks trained using both steady state and transient experimental data. The thesis describes a test rig designed specifically for this purpose, which utilizes an industrial centrifugal fan from Nicotra- Gebhardt equipped with a three-phase induction motor. Additionally, the thesis presents a detailed procedure for designing the estimators.

The use of electrical drives for controlling centrifugal fans and pumps is a wellestablished practice that can lead to significant energy savings. However, this requires electrical and automation engineers to possess knowledge relevant to the modelling of fans and pumps in relation to drives. Existing approaches rely heavily on quasisteady modelling, which is widely used by drives application experts, but there is limited adoption of dynamical modelling that is integrated with AC drives.

This thesis aims to enhance existing dynamical models by employing neural network estimation to calculate the overall efficiency of the fan/pump. The model separates the fan/pump's own efficiency for the computation of motor load torque to reflect accurately the power balance. The developed model is designed to be suitable for control design applications. Additionally, this research verifies the dynamical model experimentally, which supports the necessity of incorporating a first-order nonlinear differential equation to model the flow rate dynamics.

A linearized mathematical model of a centrifugal fan powered by a Squirrel Cage Induction Motor has been developed and validated through experimental and simulation data. Furthermore, a H mixed sensitivity approach has been employed to design a controller for a system that aims to achieve performance objectives such as stability, disturbance rejection, and reference tracking. The proposed H mixed sensitivity controller meets the necessary requirements for optimal performance, offering a promising solution for control system design.