This research explores gender inequality in education, with a focus to examine the implications of gender disparities in schools on girls’ health and education. The study sought to investigate whether school management practices is a possible factor impacting the health behaviours of female students in senior secondary schools in Lagos, Nigeria. The study employed mixed methods design and gathered primary data in two consecutive phases, in line with sequential explanatory design. Data in Phase one was gathered through the use of questionnaire while phase 2 gathered primary data using semi-structured interviews to complement survey data. The sample frame included 2 public secondary schools, 42 students, 9 teachers, 1 vice principal and 2 principals. Quantitative data were analyzed using Statistical Package for Social Sciences (SPSS), while qualitative data were analyzed with help of ATLAS.ti. The findings of the study revealed school related barriers that influence high absenteeism and dropout among girls. Further findings also show the schools lack appropriate school management policies that promote healthful behaviours and encourage positive learning environment for girls. The researcher recommends leadership and school management training for school principals and their deputies, improving quality of health instruction in the curriculum, developing strict policy against school-related gender-based violence and adopting health-promoting policies.

The purpose of this research is to explore how Double Loop Learning (DLL) and Lean Six Sigma tool (i.e. DMAIC-Defined, Measure, Analysis, Improvement, and Control) can be used to reduce Food Waste and Loss (FWL) in the processing and distribution units of the Food Supply Chain (FSC) in the developing countries. This study is motivated base on the identified research problem of which about one-third of every food produce is wasted yearly, which equates to 1.3 billion tonnes of food throughout the entire food supply chain, with up to 50% of FWL occur at the pre-consumption stage of FSC in the developing countries. The economic values of FWL in Sub-Saharan Africa amount to $230 billion yearly. Therefore, the focus has been on how to reduce the magnitude of FWL at the pre-consumption stage of the FSC in the developing countries while promoting continuous improvement practices. Though technological, environmental, and Supply Chain Strategies (SCS) aimed at reducing FWL are effective in some parts of the world but the effectiveness of those strategies in some countries is hindered by poor supply chain activities. This research adopted a qualitative research method through the use of multiple case study strategies, with the aid of semi-structured interviews, observation, and documents to explore the perception, understanding, and experience of the FSC stakeholders on how DMAIC-DLL can be used to reduce FWL. The findings of this study show that with the DMAIC-DLL framework, the root causes of FWL at the pre-consumption stage were identified. The study found that some Lean tools, employee improvisation, learning practices are some of the strategies that could be used in reducing FWL. The findings suggest that experiential learning, collaborative learning, and on-job training are effective learning mechanisms that could be used to promote learning in the adoption of DMAIC-DLL in the FSC. Therefore, this research contributes towards the ongoing debate on how to reduce FWL as well as the wider debate learning mechanisms that support continuous improvement practices. Future research should explore how DMAIC-DLL can be extended to other settings other than the food industry.

The purpose of my research is to examine how copreneurial couples make sense of their lived experience of working in a copreneurial business and shape their mutual identity. The research context is copreneurs operating micro-businesses in the Greek leisure and tourism industry. Given the size of the tourism industry worldwide and the fact that many businesses within this sector are family-owned, this is an important area of inquiry. The aim is twofold: 1. To build theory in the field of entrepreneurship by focusing specifically on the undertheorized topic of how copreneurs understand and shape their identity and responsibilities within copreneurial businesses 2. To bring an under-utilized methodology to entrepreneurship studies, that of interpretive phenomenological analysis (IPA), as a means of enhancing the understanding of the lived experience of copreneurs. Drawing on phenomenological philosophy, IPA foregrounds the meanings research participants give to their experience and therefore offers rich interpretations from copreneurial couples While taking an idiographic approach, which focuses on the first-person experience of copreneurs in a particular context, the findings will resonate with other copreneurs. The contribution of this research therefore lies in advancing our understanding of copreneurship and familial entrepreneurship by elucidating the interrelationship between personal and business partnerships. The study makes visible the often invisible recursive links between paid work and family life for men and women

Natural products are acknowledged sources of novel compounds for use in the treatment of diseases such as cancer, malaria, and human African trypanosomiasis. However, health burdens of such diseases still remain high, with drug resistance leading to failure of current medication. Therefore, there is a need for new treatments, and this project considers the potential of Nigerian ethno-medicinal plants and their products. Firstly, the aims were to isolate cytotoxic compounds through bio-guided evaluation and fractionation from 3 medicinal plants; Vitellaria paradoxa, Cyperus articulatus and Securidaca longepedunculata used traditionally in the treatment of cancer in North-East Nigeria. Extracts from S. longepedunculata were the most active when assessed in a panel of cancer cell lines, with IC50 values below 10 µg/ml, whilst fractions isolated from V. paradoxa and C. articulatus were moderately cytotoxic and able to overcome drug resistance mechanisms in drug resistant cell lines. In the second part of the thesis, novel cryptolepine analogues were semi-synthesized using environmentally friendly methods and evaluated for cytotoxic, anti-plasmodial and anti-trypanosomal activity. The compounds were found to be highly cytotoxic in cancer cell lines with the ability to overcome drug resistant mechanisms, with sub-µM IC50 values, and were also active against drug resistant strains of Plasmodium parasites in addition to Trypanosoma brucei, with IC50 values below 500 nM, and 300 pM respectively.

Annually, about 80,000 people die in the United Kingdom due to myocardial infarction, congestive heart failure, stroke, or from other diseases related to blood vessels. The current gold standard treatment for replacing the damaged blood vessel is by autograft procedure, during which the internal mammary artery (IMA) graft or saphenous vein graft (SVG) are usually employed. However, some limitations are associated with this type of treatment, such as lack of donor site and post-surgery problems that could negatively affect the patient’s health. Therefore, this present work aims to fabricate a synthetic blood vessel that mimics the natural arteries and to be used as an alternative method for blood vessel replacement. Polymeric materials intended to be used for this purpose must possess several characteristics including: (1) Polymers must be biocompatible; (2) Biodegradable with adequate degradation rate; (3) Must maintain its structural integrity throughout intended use; (4) Must have ideal mechanical properties; and (5) Must encourage and enhance the proliferation of the cells. The feasibility of using synthetic biodegradable polymers such as poly (ε- caprolactone) (PCL) and poly (lactide-co-glycolic acid) (PLGA) for fabricating tubular vascular grafts was extensively investigated in this work. Many fundamental experiments were performed to develop porous tissue- engineered polymeric membranes for vascular graft purposes through electrospinning technique to achieve the main aim. Electrospinning was selected since the scaffolds produced by this method usually resemble structural morphology similar to the extracellular matrix (ECM). Hence, four 6mm in diameter tubular shape vascular grafts PCL only, PLGA only, coaxial (core-PCL and shell-PLGA), and bilayer (inner layer-PCL and outer layer-PLGA) was designed and fabricated successfully. The structure and properties of each scaffold membrane were observed by scanning electron microscopy (SEM), and these scaffolds were fully characterized by Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), water contact angle measurements, mechanical tensile test, as well as cell culture studies were carried out by seeding human umbilical vein cells (HUVEC) and human vascular Fibroblast cells (HVF). Moreover, all polymeric grafts underwent degradation process, and the change in their morphological structure properties was studied over 12 weeks at room temperature. All scaffolds were also exposed to a controlled temperature of 37°C for four weeks, in phosphate-buffered saline solution (pH, 7.3). It was found that all scaffolds displayed exceptional fibre structure and excellent degradability with adequate steady weight-loss confirming the suitability of the fabricated scaffolds for tissue engineering applications. The coaxial and bilayer scaffolds degraded at a much slower (and steadier) rate than the singular PCL and PLGA tubular scaffolds. Coaxial grafts fabricated via coaxial needle showed an increase in their fibre diameter and pore size volume than other membranes, but also showed to have significant tensile strength, elongation at fracture, and Young’s modulus. To conclude, all scaffolds have demonstrated to be reliable to adhere and proliferate HUVEC, and HVF cells, but these cells were attracted to the PLGA membrane more than other fabricated membranes.

Advances in transportation and communication have resulted in the ease of migration of people across transnational borders and the internationalisation of business organisations. These events have brought about changing workforce demographics, intense global competition, and the quest for talents across the world. These trends have made workforce diversity inevitable for transnational companies (TNCs). TNCs operating in Nigeria face a peculiar problem as there are two layers of ethnic diversity created by the country’s enormous diversity. The task of managing the layers of diversity is complicated by the weak legal and institutional provisions for the management of diversity in public and private firms. Also, there is a general lack of awareness about diversity and inclusion (D&I) in Nigeria; hence, the field has received scant attention from academics and practitioners. This study explored the D&I policies and strategies adopted by selected subsidiaries of TNCs in Nigeria and describes ethnic minority employee perception of D&I policies and the effects these policies have on performance at the individual and team levels. To achieve these objectives, it aims to provide answers to two research questions: “What are the organisational policies and strategies that enhance diversity and the inclusion of ethnic minority employees in TNCs; and how do D&I policies and strategies impact the performance of individuals and groups within the organisation?” The study adopted the exploratory mixed-methods design to collect qualitative and quantitative data for analysis. The qualitative data included the primary and secondary sources; and involved semi-structured interviews with six senior managers in four subsidiaries of TNCs and documentary analysis. While the quantitative data involved a survey of 133 employees across the four participating companies. The reflexive thematic analysis method was used to analyse the qualitative data, leading to the generation of themes; while the quantitative data were analysed using the descriptive statistical technique. Findings reveal the presence of varying degrees of D&I initiatives among the participating organisations, ranging from well-articulated and established programmes in one company to medium range policies in two companies, and no initiatives in one company. Findings also suggest a high level of inclusion of ethnic minority employees at the group or team level and a low inclusion at the top management level. Also, participants generally report a positive perception of the relationship between workforce D&I and performance at both the individual and team level. Some of the variables used to indicate inclusion are access to information, participation in group activities, membership of informal networks, participation in decision-making and participation in meeting with supervisor and senior management. Similarly, some of the performance variables include creativity, innovation, timely completion of tasks and quality of work output. Finally, the findings from the study contributed to filling the gap in the literature as well as empirically highlighting the D&I policies operational in TNCs in Nigeria. The study recommends that diversity policy-makers pay attention to the additional layer of diversity while developing global policies for a more inclusive organisational environment. This study has provided valuable insights into the policies and practices as well as employee perception of diversity in light of the dearth of studies from the Nigerian context. Despite some inherent limitations, it serves as a starting point that could ignite the interest of other researchers and practitioners in the fields of diversity.

The operations efficiency, service quality and resources productivity, are the core aspects of the call centres competitive advantage in massive market competition. Thus, subjective evaluation is the leniency, perception and bias in performance evaluation which impact the efficiency of the operations and leads to frustrated customers. The study aims to determine the subjective performance evaluation in call centres to get a more objective measurement. It can be achieved by identifying factors affecting resources performance evaluation through the development of a conceptual model to reduce or eliminate the effect of subjective factors contained in the performance evaluation. The research approach is based on quantitative methodology through cross-sectional self-reports for 224 participants’ work in eight outsource call centres located in Egypt. The research aims to determine the subjective evaluation factors biases the true performance. It is followed by a machine learning practical application using neural networks for auto-detection the subjective context in the recorded calls to be considered through the evaluation process. The key findings of the study are nine subjective factors out of fifteen that have a direct influence on subjective performance evaluation. The actual performance is the performance evaluation after eliminating the subjective performance. Two different methods have concluded the actual performance. The first method excludes the subjective factors from the resulting evaluation to determine the actual performance. The second method is a prediction model defining subjectivity percent as a call centre baseline for future performance evaluation. Furthermore, the study highlights the potential subjective variables and the degree of influence for each variable. The theoretical contribution is determining the subjective factor and proposing the model to measure and predict the subjectivity in the call centre. The study recommended a restatement for the resource-based theory considering the subjective evaluation effect on performance evaluation. The practical application contribution is based on automating the detection and prediction of subjectivity using a machine learning approach through cascaded Convolutional Neural Networks, which achieved 75% accuracy in classifying the subjectivity for two study constructs: agents and customer behaviour.

Drilling is one of the important aspects in the oil and gas industry due to the high demand for energy worldwide. Drilling time is considered as the major part of the operations time where the penetration rate (ROP) remains as the main factor for reducing the time. Maximizing ROP to lower the drilling cost is the main aim of operators. However, high ROP if not controlled may impact on the well geometry in terms of wellbore instability, cavities, and hole diameter restrictions. Accordingly, more time is needed for the other operations that follow such as: pool out of hole (POOH), casing running, and cementing. Bit wear is considered as the essential issue that influences in direct way on the bit performance and reduce ROP. Predicting the abrasive bit wear is required to estimate the right time when to POOH to prevent any costly job to fish any junk out to the surface. The two-common types of bits are considered in the research, rock bits (roller cone bits) and Polycrystalline Diamond Compact bits (PDC). This study focuses more on PDC bits because about 60% of the total footage drilled in wells worldwide were drilled by PDC bits and this is expected to reach 80% in 2020. The contribution of this research is to help reducing the drilling cost by developing new tools not to estimating the time when to POOH to surface but also to measure the wear and enhance the accuracy of prediction the bit efficiency. The work is broken down into four main stages or models to achieve the objective: The first stage; estimating of the rock abrasiveness and calculate the dynamic dulling rate of the rock bit while drilling. The second stage; estimating the PDC abrasive cutters wear by driving a new model to determine the mechanical specific energy (MSE), torque, and depth of cut (DOC) as a function of effective blades (EB). The accuracy of the predicted wear achieves 88% compared to the actual dull grading as an average for bits used in five wells. The third stage; modifying the previous MSE tool to develop a more accurate approach; effective mechanical specific energy (EMSE), to predict the PDC bit efficiency in both the inner and outer cone to match the standard bit dulling. The fourth stage; predicting ROP while PDC drilling in hole by accounting three parts of the process: rock drillability, hole cleaning, and cutters wear. The results achieve an enhancement of about 40% as compared to the available previous models. Consequently, the developed models in this study provide a novelty on understanding in more details the bit rock interface process and gain an idea of the relationship between the drilling parameters to enhance the bit performance and avoid damaging the bit. This is basically about optimisation the controllable factors such as: weight on bit (WOB), rotary speed (RPM), and flow rate. The result is the reduction in time losses and the operations cost. To ensure reliability and consistency of the proposed models, they were validated with several vertical oil wells drilled in Libya. The results from the validation of the models are consistent with the real field data. The research concludes that the developed models are reliable and applicable tool for both: to assist decision-makers to know when to pull the bit out to surface, and also to estimate the bit performance and wear.

Faces are among the most complex stimuli that the human visual system processes. Growing commercial interest in face recognition is encouraging, but it also turns out to be a challenging endeavour. These challenges arise when the situations are complex and cause varied facial appearance due to e.g., occlusion, low-resolution, and ageing. The problem of computer-based face recognition using partial facial data is still largely an unexplored area of research and how does computer interpret various parts of the face. Another challenge is age progression and regression, which is considered to be the most revealing topic for understanding the human face changes during life. In this research, the various computational face recognition models are investigated to overcome the challenges posed by ageing and occlusions/partial faces. For partial face-based face recognition, a pre-trained VGGF model is employed for feature extraction and then followed by popular classifiers such as SVMs and Cosine Similarity CS for classification. In this framework, parts of faces such as eyes, nose, forehead, are used individually for training and testing. The results showing that there is an improvement in recognition in small parts, such as recognition rate in forehead enhanced form about 0% to nearly 35%, eyes from about 22% to approximately 65%. In the second framework, five sub-models were built based on Convolutional Neural Networks (CNNs) and those models are named Eyes-CNNs, Nose-CNNs, Mouth-CNNs, Forehead-CNNs, and combined EyesNose-CNNs. The experimental results illustrate a high recognition rate when it comes to small parts, for example, eyes increased up to about 90.83% and forehead reached about 44.5%. Furthermore, the challenge of face ageing is also approached by proposing an age-template based framework, generating an age-based face template for enhanced face generation and recognition. The results showing that generated new aged faces are more reliable comparing with state-of-the-art.

Due to the result of the sudden fossil fuels over-night price rises of 1973/1974, coupled with the depletion of the traditional energy resources, many initiatives globally have addressed the efficient use of these resources. Since then, several renewable energy sources have been introduced as alternatives to traditional resources to protect environmental resources and to improve quality of life. Globally, there are more than a quarter of the human population experiencing an energy crisis, particularly those living in the rural areas of developing countries. One typical example of this is Nigeria. This is a country with approximately 80% of her population consistently relying on combustible biomass from wood and its charcoal derivative. Nigeria has an abundant amount of both renewable and fossil fuel resources, but due to the lack of a reasonable energy policy (until recently), it has concentrated on traditional fossil fuels alone. Renewable energy is now Globally considered as a solution for mitigating climate change and environmental pollution. To assess the sustainability of renewable energy systems, the use of sustainability indicators is often necessary. These indicators are not only able to evaluate all the sustainability criteria of the renewable energy sources,1 but also can provide numerical results of sustainability assessment for different objective systems.