Now showing items 1-20 of 1483

    • Proteomic Investigation of Endocrine Therapy Resistance in Breast Cancer Investigating the Molecular Mechanisms for SERM Resistant Cell Lines Using SILAC-Based Proteomic Approach

      Sutton, Chris W.; Shnyder, Steven D.; Al-Kabariti, Aya Y. (University of BradfordSchool of Pharmacy. Faculty of Life Sciences, 2022)
      Introduction: Breast cancer is the second highest cause of cancer mortality in women worldwide. Hormonal therapy is considered one of the most effective therapies and is used against luminal-type malignancies. However, 40-50% of tumour cells can develop resistance, thereby limiting the success in breast cancer treatment. In this study, mechanisms of resistance were investigated using a novel multi-stable isotope labelled amino acids (SILAC) proteomics approach in phenotype-specific breast cancer cell lines resistant to endocrine treatment. Method: In vitro chemo-sensitivity (IC50) was determined for MCF7, T47D, MDA-MB-231, MDA-MB-468, MDA-MB-453, BT-20 and MCF-10A breast cell lines using four endocrine-based therapeutic agents (Tamoxifen, 4-Hydroxytamoxifen OHT, Raloxifene, Anastrozole) to select viable strains for resistance studies. MCF7 (luminal-type A) and MDA-MB-231 (triple negative breast cancer, TNBC) were selected and initially subject to OHT or raloxifene exposure with gradual increments for 10 months. WT cells were grown in the absence of drug in parallel as passage controls. Resistant cell lines were assessed by MTT and IF for comparison with parental cell lines. Resistant cell lines, along with the passage control and a SILAC control, were grown in “light” SILAC medium together with WT strains cultured in “heavy” SILAC medium. Proteins were extracted, concentrations determined and analysed by SDS PAGE for quality control. An aliquot of each “light” cell line (resistant, passage control or SILAC control) was combined with an equal amount of “heavy” WT, trypsin digested and analysed by nano-HPLC Orbitrap Fusion mass spectrometry (2D-LC MS/MS). Proteins were identified by database searching using MascotTM. Relative changes (resistant/WT ratio) in protein levels were determined and bioinformatics tools (STRING and UniProt) used to explore significantly changed pathways associated with resistance. Western blotting was used to verify selected target proteins. Results: Four consistently resistant sublines were generated MCF7 OHT Res (2.00-fold more resistant), MCF7 Ralx Res (2.00-fold), MDA-MB-231 OHT Res (1.90-fold change) and MDA-MB-231 Ralx Res (2.00-fold), in addition to two high passage controls. ER expression by IF was decreased in MCF7 OHT Res compared to the WT and MCF7 Ralx Res, whereas CD44 was increased. Proteomic analysis revealed 2247 and 2880 total proteins in MCF7 OHT Res and MCF7 Ralx Res whilst 3471 and 3495 total proteins were identified in MDA-MB-231 OHT Res and MDA-MB-231 Ralx Res, respectively. Bioinformatics tools identified significantly changed pathways included apoptosis, cytoskeleton, cell motility and redox cell homeostasis. Components of the MAPK-signalling cascade were consistently found to be upregulated in resistant cell lines. MAPK1 (ERK2), previously associated with tamoxifen resistance was increased in MDA-MB-231 Ralx Res cell lines by 4.45-fold and confirmed by Western blotting. Sorcin, which contributes to calcium homeostasis and is also linked to multidrug resistance was increased 4.11- and 2.35-fold in MCF7 OHT Res and Ralx Res sub cell lines, respectively. Some results, such as those for c-Jun, were inconsistent between proteomic analysis and Western blotting and require further investigation. Conclusion: The unique resistant cell lines generated here, as well the MCF7 OHT resistant line, provided novel data that give insights into the biological pathways involved in mechanisms of endocrine drug resistance in breast cancer. Proteomics analysis provided extensive data on common functionality and pathways across the resistant cell lines independent of phenotype or SERM. Overall, the results provided interesting targets for re-sensitising resistant breast cancer and the potential to investigate novel combination therapies in the future.
    • Proteomic profiling of matched normal and tumour tongue biopsies from smokers and non-smokers. Oncoproteomic applications for oral tongue squamous cell carcinoma biomarker discovery

      Sutton, Chris W.; Pors, Klaus; Saeed, Sidra (University of BradfordFaculty of Life Sciences. School of Pharmacy, 2021)
      Despite considerable development in the therapeutic repertoire for managing cancer-related malignancies, head and neck cancer mortality has not significantly improved. The burden of HNSCC fluctuates across countries and has been associated with exposure to tobacco-derived carcinogens, excessive alcohol consumption or combinations. Due to late detection, patients often present with oral pre-malignant lesions which have progressed to an advanced stage of HNSCC. In this study, the samples were from a male cohort as generally, men are at two to four-fold higher risk than women with over 90% of HNSCCs arising in the upper aerodigestive tract. Therefore, the purpose of this thesis was to identify HNSCC biomarkers in males associated within defined anatomical region (tongue) and causative agents, specific to smoking. An iTRAQ proteomic approach was used to profile protein changes in matched normal and tumour samples from male non-smoking (n=6) and smoking patients (n=6) with tongue carcinomas revealing identification of potential targets specific to cancer. Samples were subjected to liquid nitrogen cryo-pulverisation and protein determination. Protein extracts from the same category were pooled, trypsin digested and iTRAQ 4-plex labelled. Data was generated by 2D-LC/MS on an Orbitrap Fusion and significantly changed proteins (median ± SD) were subject to bioinformatics appraisal. A total of 3426 proteins were identified and quantified by proteomic analysis. Comparison of non-smoker tumour (NS:T) with smoker tumour (S:T) distinguished 64 proteins that were upregulated and 62 downregulated, S:T vs S:N categorised 349 proteins up- and 395 down-regulated respectively and NS:T vs NS:N identified 469 proteins up- and 431 down-regulated, respectively. Arginase-1 (ARG1), Keratin Type-2 Cytoskeletal 8 (KRT8), Lipocalin-1 (LCN1) and DNA replication licensing factor MCM2 (MCM2) were identified as biologically associated with smoking compared to non-smoking, providing viable targets for verification by immunochemical methods which further supported the proteomic data. Overall, the project demonstrated the importance of using matched biopsies with good clinicopathological data for experimental design and provided a set of unique targets for a more expanded verification study.
    • Time will tell: Material surface cues for the visual perception of material ageing Insights from psychophysics, online experiments, image processing and a science festival

      Bloj, Marina; Denniss, Jonathan; Logan, Andrew J.; De Korte, Elisabeth M. (University of BradfordSchool of Optometry and Vision Science. Faculty of Life Sciences, 2022)
      This thesis explores the visual perception of material change over time, a novel topic that has received little attention so far. We aimed to understand the material surface features and mental representations associated with material change over time by the human visual system, and possibly wider cognitive systems. To this end, we performed a series of experiments with varying methodologies. These included a psychophysics experiment, online experiments, and data collection during a science festival. The latter showed that the general public mentioned “Faded (colour)” most often to describe material change over time and that specific material surface change features clustered around specific materials. In another experiment, material type, but not colour or the geometrical distribution, had a significant effect on perceived material change. Other experiments partially contradicted this finding. It was found that perceived material type showed a significant, non-linear association with perceived material change, replicating earlier findings on the effect of material type. In contrast, material surface lightness, a constituent of colour, was associated with perceived material change. The same held for components of the geometrical distribution. They showed a minor contribution to the perception of material change, but a major one to perceived material type. Together, our findings suggest that the human visual system seems to use constituents of material surface colour as a cue to material change over time. The geometrical distribution seems to play a minor role. Although these contributions may vary with material type, as our findings showed that material type affected the perception of material change over time.
    • Online Anomaly Detection for Time Series. Towards Incorporating Feature Extraction, Model Uncertainty and Concept Drift Adaptation for Improving Anomaly Detection

      Neagu, Daniel; Gheorghe, Marian; Tambuwal, Ahmad I. (University of BradfordDepartment of Computer Science. Faculty of Engineering and Informatics, 2021)
      Time series anomaly detection receives increasing research interest given the growing number of data-rich application domains. Recent additions to anomaly detection methods in research literature include deep learning algorithms. The nature and performance of these algorithms in sequence analysis enable them to learn hierarchical discriminating features and time-series temporal nature. However, their performance is affected by the speed at which the time series arrives, the use of a fixed threshold, and the assumption of Gaussian distribution on the prediction error to identify anomalous values. An exact parametric distribution is often not directly relevant in many applications and it’s often difficult to select an appropriate threshold that will differentiate anomalies with noise. Thus, implementations need the Prediction Interval (PI) that quantifies the level of uncertainty associated with the Deep Neural Network (DNN) point forecasts, which helps in making a better-informed decision and mitigates against false anomaly alerts. To achieve this, a new anomaly detection method is proposed that computes the uncertainty in estimates using quantile regression and used the quantile interval to identify anomalies. Similarly, to handle the speed at which the data arrives, an online anomaly detection method is proposed where a model is trained incrementally to adapt to the concept drift that improves prediction. This is implemented using a window-based strategy, in which a time series is broken into sliding windows of sub-sequences as input to the model. To adapt to concept drift, the model is updated when changes occur in the new arrival instances. This is achieved by using anomaly likelihood which is computed using the Q-function to define the abnormal degree of the current data point based on the previous data points. Specifically, when concept drift occurs, the proposed method will mark the current data point as anomalous. However, when the abnormal behavior continues for a longer period of time, the abnormal degree of the current data point will be low compared to the previous data points using the likelihood. As such, the current data point is added to the previous data to retrain the model which will allow the model to learn the new characteristics of the data and hence adapt to the concept changes thereby redefining the abnormal behavior. The proposed method also incorporates feature extraction to capture structural patterns in the time series. This is especially significant for multivariate time-series data, for which there is a need to capture the complex temporal dependencies that may exist between the variables. In summary, this thesis contributes to the theory, design, and development of algorithms and models for the detection of anomalies in both static and evolving time series data. Several experiments were conducted, and the results obtained indicate the significance of this research on offline and online anomaly detection in both static and evolving time-series data. In chapter 3, the newly proposed method (Deep Quantile Regression Anomaly Detection Method) is evaluated and compared with six other prediction-based anomaly detection methods that assume a normal distribution of prediction or reconstruction error for the identification of anomalies. Results in the first part of the experiment indicate that DQR-AD obtained relatively better precision than all other methods which demonstrates the capability of the method in detecting a higher number of anomalous points with low false positive rates. Also, the results show that DQR-AD is approximately 2 – 3 times better than the DeepAnT which performs better than all the remaining methods on all domains in the NAB dataset. In the second part of the experiment, sMAP dataset is used with 4-dimensional features to demonstrate the method on multivariate time-series data. Experimental result shows DQR-AD have 10% better performance than AE on three datasets (SMAP1, SMAP3, and SMAP5) and equal performance on the remaining two datasets. In chapter 5, two levels of experiments were conducted basis of false-positive rate and concept drift adaptation. In the first level of the experiment, the result shows that online DQR-AD is 18% better than both DQR-AD and VAE-LSTM on five NAB datasets. Similarly, results in the second level of the experiment show that the online DQR-AD method has better performance than five counterpart methods with a relatively 10% margin on six out of the seven NAB datasets. This result demonstrates how concept drift adaptation strategies adopted in the proposed online DQR-AD improve the performance of anomaly detection in time series.
    • Physicochemical and biopharmaceutical characterization of novel derivatives of gallic acid

      Paluch, Krzysztof J.; Sheldrake, Helen M.; Kantamneni, Sriharsha; Alhyari, Dania H. (University of BradfordSchool of Pharmacy and Medical Sciences. Faculty of Life Sciences, 2022)
      Gallic acid is a known antioxidant and has anti-inflammatory activity in addition to other biological activities, but GA efficiency is restricted due to low permeability and low oral bioavailability. This study was designed to investigate the solubility, permeability, oral bioavailability, enzymatic stability with cytochrome CYP2D6, antioxidant and anti-inflammatory activity of novel gallic acid sulfonamide derivatives; TMBS, and THBS. In addition, a novel in silico permeability model was designed to predict the permeability and bioavailability of eighty derivatives of GA. In sillico prediction of intestinal permeability of GA derivative indicated an increase in permeability with increased lipophilicity and decreased aqueous solubility, replacing the carboxylic group with sulfonamide group has increased intestinal permeability. A significant (P <0.01) increase was observed in the permeability of TMBS and THBS over GA, in both gastric fluids and HIEC cells. TMBS was O-demethylated by CYP2D6. TMBS had greater ROS scavenging activity than GA in HIEC-6 cells. There was a significant (P< 0.05) increase in anti-inflammatory activity of THBS, and TMBS compared to ibuprofen. TMBS, and THBS had better oral bioavailability than GA. This data suggests that the in silico permeability model can be used in the future to study new candidate of gallic acid, and further in vivo and clinical investigations are required to introduce TMBS and THBS as a new antioxidant and anti-inflammatory drugs.
    • Measuring The Information Literacy of School Stakeholders in Implementing Blended Learning in High Schools in The State of Kuwait to Propose a School Management System. Examining the level of information literacy of stakeholders in High schools and to propose a new school management system to achieve the best implementation of information literacy and blended learning practices

      Abd-Alhameed, Raed; Kamala, Mumtaz A.; Carruthers, Andrew; AlQaoud, Fatima N.H. (University of BradfordFaculty of Engineering and Informatics, 2022)
      Information Literacy (IL) has been implemented among workers in schools in recent years in order to enhance workers’ skills and competencies through the utilisation of technology in education. To implement a sustainable IL system, the building of an IT infrastructure is required including the provision of PCs and network access, enabling students to connect to the internet during class time in order to access educational web-based content as well as to share discussions about subjects with their peers in and out of the class. Assessing the level of information literacy (IL) of stakeholders will assist in creating a new proposed school management system (SMS) to be used among them in the future. This will encourage teachers to use blended learning approach for teaching their students. Therefore, it is important to examine the IL of stakeholders (principal, head of division, teacher) in Kuwait to increase their skills and competencies which will lead to greater innovation in future developments. This work aims at assessing information literacy level of stakeholders, their skills and competencies in utilising technology in a workplace environment, which will assist the researcher to create a new school system. In addition, this work presents a new proposed school management system (SMS) for stakeholders in the current educational system of high schools in Kuwait, therefore, applying the BL approach in order to achieve a high quality of students' learning outcomes.
    • Collision and Avoidance Modelling of Autonomous Vehicles using Genetic Algorithm and Neural Network

      Not named; Gadinaik, Yogesh Y. (University of BradfordFaculty of Engineering and Informatics, 2022)
      This thesis is to study the optimisation problems in autonomous vehicles, especially the modelling and optimisation of collision avoidance, and to develop some optimisation algorithms based on genetic algorithms and neural networks to operate autonomous vehicles without any collision. Autonomous vehicles, also called self-driving vehicles or driverless vehicles are completely robotised driving frameworks to allow the vehicle to react to outside conditions within a bunch of calculations to play out the undertakings. This thesis summarised artificial intelligence and optimisation techniques for autonomous driving systems in the literature. The optimisation problems related to autonomous vehicles are categorised into four groups: lane change, motion planner, collision avoidance, and artificial intelligence. A chart had been developed to summarise those research and related optimisation methods to help future researchers in the selection of optimisation methods Collision Avoidance is one of streamlining issues in autonomous vehicles. Several sensors had been used to identify position and dangers and collision avoidance algorithms had been developed to analyse the dangers and to use vehicles to avoid a collision. In this thesis, the current research on collision avoidance has been reviewed and some challenges and future works were presented to select the research direction of this thesis, the aim of this research will be the development of optimisation methods to avoid collisions in a predefined environment. The contributions of this thesis are that (1) a simulation model had been developed using Matlab for collision avoidance and serval scenarios were proposed and experimented with. The sensors are used as the inputs to determine collision in the learning preparation of the algorithm; (2) a neural network was used for collision avoidance of autonomous vehicles; (3) a new method was proposed with the combination of genetic algorithm and neural network. In the proposed frame, the neural network is used for decision making and a genetic algorithm is used for the training of the neural network. The results and experimentation show that the proposed strategies are well in the designed environment.
    • Pregnancy, Transition to Motherhood, Infant Feeding Attitudes and Health Locus of Control in Nigeria

      Johnson, Sally E.; Stewart-Knox, Barbara; Lesk, Valerie E.; Adegbayi, Adenike (University of BradfordDivision of Psychology Faculty of Management, Law and Social Sciences, 2022)
      Exclusive breastfeeding and holistic maternity care are strategic to improving maternal and infant health outcomes in Nigeria. This thesis aimed at informing policies and interventions to promote breastfeeding and to improve Nigerian mother’s experiences in antenatal and intrapartum care. The study in this research focused upon psychological dynamics underlying societal culture around maternity and breastfeeding. Using quantitative method, attitudes toward breastfeeding and health orientation were surveyed in 400 Nigerian men and women using the Iowa Infant Feeding Attitude Scale (IIFAS) and the Multidimensional Health Locus of Control Scale (MHLoC). There were more positive attitudes toward breastfeeding in males, participants in the 20-29-year-old age category, and in those who identified as single. Higher internal HLoC was associated with more positive attitudes to breastfeeding and higher EHLoC scores were associated with more negative attitudes to formula feeding. The second study explored the experience of pregnancy and childbirth in Nigerian women. Qualitative interviews with 12 women implied that Nigerian women perceive pregnancy and childbirth as a multidimensional experience comprising physiological and psychological elements and also as risky. Control mechanisms that reflected internal HLoC included choosing multiple antenatal care sources to obtain holistic care, adopting new technology in bridging perceived communication gaps with health care providers and adopting physical and mental strategies in controlling the somatic and sensory changes that accompany pregnancy. Pregnancy and childbirth were viewed through an external HLoC lens as spiritual, and reflected in an entrenched belief in the intervention of deity to mitigate pain and risk associated with childbirth. These results have implications for practice, intervention and policy to promote breastfeeding at the societal level and improve maternity services for the current and next child-bearing generation.
    • Intersections between culture, sociodemographic change and caring: a qualitative study of current and prospective family caregivers in mainland China.

      Oyebode, Jan; Quinn, Catherine; Breen, Liz; Bifarin, Oladayo O. (University of BradfordFaculty of Health Studies, 2022)
      Aim: As the ageing population in China increases, support required from family caregivers for older relatives living with long-term health conditions also increases. This being so, this thesis explored the experiences and perceptions of current and prospective family caregivers, under the culture of Xiao (孝; filial piety). Design and Methods: Phase 1 was conducted with 19 Chinese students using 3 focus groups to gain greater familiarity with the culture and inform the main study (Phase 2). Adopting a social constructivist philosophical position, data for Phase 2 were obtained from three generational sub-samples: only-children affected by the One-Child Policy (OCP), parents affected by OCP, and family caregivers in the workforce, totaling 23 participants through virtual in-depth interviews with participants in mainland China. Interviews were translated, transcribed, and analysed using reflective thematic analysis. Findings and Conclusion: Phase 1 confirmed the centrality of the concept of Xiao to attitudes and beliefs around future caregiving for parents. Phase 2 findings’ overarching theme was ‘Competing pressures’, which comprised of three inextricably linked themes: (i) Caregiving beliefs, (ii) Contextual factors, and (iii) Caregiving conditions. Participants expressed meaningful desires to fulfil obligations, reflecting value-based convictions, stemming from their socio-cultural environment. Stressors experienced reveals structural and personal barriers to seeking support. Ultimately, extensive demands and limited coping strategies could diminish meaning in caregiving. This thesis makes a novel contribution on perceptions and experiences of family caregivers of older relatives within China as a collectivist society. Findings have implications for research, policy, and practice, highlighting the need for culturally attuned services to build resilience.
    • Strategic Decision-making Process in the Qatari Public Sector. Relationship between the Decision-Making Process, Implementation, and Outcome

      Weerakkody, Vishanth J.P.; Sivarajah, Uthayasankar; Al-Hashimi, Khalid M.I.A. (University of BradfordSchool of Management. Faculty of Management, Law, and Social Science, 2022)
      Although several multi-dimensional models of strategic decision-making processes (SDMPs) have been examined in the literature, these studies have paid insufficient attention to the public sector context and Gulf Cooperation Council (GCC) region. SDMP in the public sector and the State of Qatar can vary to SDMP in the private sector due to institutional and socio-cultural differences respectively. Therefore, more research is urgently needed to better understand SDPM within this context. To contribute to filling this void, this study develops and tests a multi-dimensional SDMP model including SDMP dimensions, implementation, and outcome. The study model examines (𝑖) the impact of four SDMP dimensions—procedural rationality, intuition, constructive politics, and participation—on the implementation success of the strategic decision; (𝑖𝑖) the impact of the successful implementation of SD over the SD quality; (𝑖𝑖𝑖) the mediation role of the implementation success of SD; (𝑖𝑣) the moderation effect of stakeholder uncertainty. The model was analysed using Partial Least Square Structural Equation Modelling (PLS-SEM) and tested using data from multiple informants on 170 strategic decisions in 38 Qatari public organisations. The study finds that procedural rationality, constructive politics, participations, and the implementation Success of SD plays a significant and positive role on SDMP and its overall outcome. Finally, the study provides substantial and original contributions to the knowledge of SDMP in the public sector; implications for decision-makers and directions for future research.
    • The Impact of AI on Online Customer Experience and Consumer Behaviour. An Empirical Investigation of the Impact of Artificial Intelligence on Online Customer Experience and Consumer Behaviour in a Digital Marketing and Online Retail Context

      Mahroof, Kamran; Rana, Nripendra P.; Weerakkody, Vishanth J.P.; Kronemann, Bianca (University of BradfordFaculty of Management, Law and Social Science, 2022)
      Artificial Intelligence (AI) is adopted fast and wide across consumer industries and digital marketing. This new technology has the potential to enhance online customer experience and outcomes of customer experience. However, research relating to the impact of AI is still developing and empirical evidence sparse. Taking a consumercentred approach and by adopting Social Response Theory as theoretical lens, this research addresses an overall research question pertaining to the implications of online customer experience with AI on consumer behaviour. A quantitative research strategy with positivist approach is adopted to gather a large sample (n= 489) of online consumers who have previously interacted with AI-enabled technology. The collected data is analysed statistically utilising Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM). Empirical findings show strong positive effects of anthropomorphism of AI, para-social interaction with AI, and performance expectancy of AI on all three customer experience dimensions of informativeness, entertainment and social presence. Additionally, there is strong statistical support for the positive effect of informativeness and social presence on continued purchase intentions (β= .379 and β= .315), while the effects of entertainment are less strong. The mediating effects of customer experience have been assessed, highlighting social presence as most important mediator. This research contributes to knowledge by extending previous customer experience theory and quantifying the influence of online customer experience with AI on purchase intentions and eWOM. The theoretical insights also translate into direct implications for marketing practice relating to the design, integration, and implementation of more consumer- and outcome-oriented AI applications.
    • Social Protection for Well-Being. The effectiveness of social protection programmes in Bangladesh

      Arora, Rashmi; Ambituuni, A.; Analoui, Farhad; Morvaridi, Behrooz; Salam, Mohammad A. (University of BradfordDepartment of Peace Studies and International Development. Faculty of Management, Law and Social Sciences, 2022)
      Well-being is the ultimate goal of social protection that integrates both material and social aspects. Most studies focus on material dimensions, and little attention has been given to the social aspects of well-being. Further, outputs are commonly used to assess the effectiveness of social protection, while insufficient attention has been given to the outcomes and process evaluation. This study aims to assess the effectiveness of social protection in ensuring well-being, comprising human development and social cohesion. It adopts a result-oriented framework that considers both outcome and process evaluation. The study follows sequential mixed methods for assessing the effectiveness of social protection programmes. Using a secondary dataset of six developing countries (including Bangladesh) from 2002 to 2019 and employing a pooled OLS model, this study shows that social protection expenditure increases the primary (education) completion rate and reduces the child (under 5) mortality rate in developing countries. It also reveals that the effect of social protection on education and health outcomes improves with governance efficacy and operational competency. Using primary data collected through a quantitative survey (n=400) from four districts of Bangladesh and employing the OLR model, this study shows that social protection benefits positively affect informal and formal networks and institutional trust and norms of behaviour. It also reveals that the educational status of beneficiaries can mediate informal and formal networks, interpersonal trust, and norms of reciprocity. The process evaluation has done through 24 in-depth qualitative interviews with key stakeholders. By using content analysis, this study recognises five "governance" and six "operational" issues that can limit the effectiveness of social protection programmes. It also proposes a model for the effective functioning of social protection programmes based on empirical findings and justified by prevailing literature. The study shows how effectively programmes are executed and how programmes can be improved to achieve the goal. These findings have significant implications for enhancing the development effectiveness of social protection programmes. The policy directions can assist policymakers and development partners in taking suitable policies to ensure the well-being of the poor and vulnerable people of developing countries.
    • Breast cancer, medical imaging, and cancer genetics. A new genetic concept regarding the causes and prevention strategies of cancer is presented

      Youseffi, Mansour; Rasheed, Mohammed E.H. (University of BradfordBiomedical and Electronics Engineering Department. Faculty of Engineering and Informatics, 2021)
      Breast cancer is the most common cancer type in the United Kingdom. Many women with breast cancer do not show any noticeable symptoms in their early stages, hence regular breast screening is important. In this research focus is on medical imaging and its role in breast cancer screening, diagnosis, and treatment monitoring. Around 10% of all cancers are caused by inherited gene mutations which may cause cancer to run in families. Though, majority of cancer cases (up to 90%) are caused by acquired gene mutations which may also appear to run in families when family members share a particular environment or exposure. Genetic testing is conducted in this research on a number of participants to investigate the cancer cases found among their families. The findings of this research show that significant improvements have taken place in the emergence of hybrid imaging modalities used for breast imaging, through the fusion of different imaging techniques. The findings also provide evidence that similar to cancers caused by inherited gene mutations, cancers caused by non-inherited gene mutations may also appear to run in families when family members share certain environments and exposures or lifestyle behaviours. As a result, a new genetic concept of cancer essential to understand and control the disease is presented in this work which links between the human population origins and migrations, environmental factors and gene mutations, and the development of cancer. Furthermore, a number of cancer prevention strategies are recommended in this study to prevent people from getting the disease.
    • Talking Trains, Planes and Automobiles: Machine Anthropomorphism in Children’s Fiction

      Goodall, Mark D.; Roberts, Benjamin L.; Thornton, Karen D.; Godfrey, William I.C. (University of BradfordDepartment of Media, Design and Technology. Faculty of Engineering and Informatics, 2021)
      Machine anthropomorphism is the reification of technology in representation, giving machines human features, qualities, and motivations. This study aims to investigate the origins and functions of machine anthropomorphism and the impact that it has on readers in a technic society as part of an ideological apparatus. It looks at how machine anthropomorphism creates a social imaginaire for technology and how animist representations of machines have shifted from adult culture to children’s fiction. Working from the premise that children identify with childlike machines such as Thomas the Tank Engine this study examines how the relationships between machines and humans are used to model relationships between children and adults. These fall into three modes of representation: the promethean machine, the fraternal machine, and the dominant machine. Each mode functions as an ideological apparatus to either support the promethean ideology, provide a counter discourse, or turn it on its head completely. The case studies focus on promethean representations in The Railway Series/Thomas and Friends and Bob the Builder; on fraternal representations in Ivor the Engine and WALL·E; and on reverse promethean representations in The Transformers franchise and Pixar’s Cars films. Machine anthropomorphism is an important mode of representation not only in children’s entertainment but increasingly in adult culture as well, functioning as part of an ideological apparatus to reproduce consumer power in a post-technic society. As technology becomes more human-like machine anthropomorphism functions to create a new social imaginaire, preparing society for the technical disruption of increased automation, robotics, cybernetics, and artificial intelligence.
    • An Investigation into the Relationship Between Economic Growth, Energy Consumption, and the Environment: Evidence from Nigeria

      Arora, Rashmi; Anand, Prathivadi B.; Ahmad, Ahmad (University of BradfordFaculty of Law, Management and Social Sciences, 2023)
      This thesis employs the Autoregressive Distributed Lag model (ARDL), Toda-Yamamoto causality analysis, and ordinary least square (OLS for robust estimation) techniques to empirically investigate the impact of economic growth and energy consumption on the environment in Nigeria from 1980 to 2020. The results of cointegration demonstrate a long-term link between the model's input variables. The outcome of the first objective of the study shows that trade and economic development in Nigeria worsen the state of the environment. Environmental quality is accelerated by financial development; nevertheless, FDI is proven to be insignificant in predicting environmental quality. The result demonstrates that FDI and energy use both have the potential to significantly speed up the rate of environmental degradation. Nevertheless, trade has a negligible impact on the environment in the country, and financial development slows down environmental deterioration. The study also finds that the combination between energy and economic development improves Nigeria's environmental quality. The outcome of the fourth objective shows that economic expansion and energy consumption have a favorable impact on the environment. Additionally, environmental degradation, energy use, and economic growth are all causally related. Moreover, the outcome of the robust estimation reveals a positive and significant relationship between economic growth and energy consumption in the environment. Therefore, the study suggests economic policies with environmental control measures. This could be through an emphasis on the use of other alternatives of low-emission energy, that will mitigate the level of C02 and enhance energy utilization for a better environment in the nation.
    • Non-Invasive Techniques for the Detection and Diagnosis of Dementia

      Ugail, Hassan; Lesk, Valerie E.; Blount, Joseph A. (University of BradfordFaculty of Engineering and Informatics, 2021)
      It is estimated that there are currently fifty million people living with dementia worldwide. An accurate and early diagnosis of dementia is important in order to initiate appropriate treatment programs as soon as possible. Common methods of neuropsychological assessment can be sensitive to external factors which may compromise accuracy. The aim of this thesis was to investigate techniques that have the potential for the detection of dementia that avoid some of the external influences. The thesis looked at measurements of (i) postural stability (ii) facial analysis and (iii) fully-immersive virtual reality in cognitively-healthy individuals. These techniques were chosen as postural stability and facial analysis change in dementia and whilst virtual reality has previously been used in dementia research, fully-immersive virtual reality measures have not been established. To see if the measurements were associated with cognitive function, participants completed a series of cognitive tests. Results indicate that all techniques explored shared a relationship with memory performance, with lower anteroposterior postural sway (F(1,22) = 17.76, p < 0.01), number of activities participated in that involve a posture element (F(2, 39) = 3.77, p < .05; Wilk's Λ = 0.84, partial η2 = 0.16), the greater the frequency of negative facial expressions (F(2, 18) = 4.49, p < .05; Wilk's Λ = 0.67, partial η2 = 0.33.), and low blink rate (t(11.02) = 2.62 p < .05) all showing better scores on memory tests. Moreover, better scores on the fullyimmersive virtual reality task predicted better scores on with short-term memory (F(1,22) = 20.20 p < 0.01), LTM (F(1,22) = 09.10 p < .01), associative learning (F(1,22) = 08.75 p < .01), and a dual–task test (F(1,22) = 04.64 p < .05). The novel findings that elements such as postural stability, participation in sports, facial expressions of emotion, blink rates, and spatial memory as assessed in fully-immersive virtual reality highlight that non-invasive techniques can provide measurements that correspond to cognitive ability. This may hold implications for dementia diagnoses. Future research should assess whether these relationships can also be found in an older adult population. If this relationship is found in older adults, it could justify further research into how these techniques could be applied in a clinical context.
    • Investigating The Relationship Between Surface Topology And Functional Characteristics For Injection Moulded Thermoplastic Components

      Whiteside, Benjamin R.; Katsikogianni, Maria G.; Sefat, Farshid; Snelling, Anna M.; Israr Raja, Tehmeena (University of BradfordFaculty of Engineering and Informatics, 2021)
      Bacteria are known to adhere to surfaces, which allows for the formation of biofilms, possibly causing a surge in hospital-offset infections, perilous diseases, and in some cases, death. Although certain bacteria are present in the natural flora of the human skin, some present extreme clinical significance due to the ability to transmit and adhere, and can be resistant to antibiotics. They also evolve over time to survive in harsh environmental conditions. Current research reveals that design of plastic surfaces containing submicron structures, is becoming a popular approach to tackle issues concerning infection transmission, with inspiration being derived from biomimetics and self-cleaning surfaces, such as the surface of a gecko skin, and the hydrophobic wax layer of forest leaves. Main barriers to adoption include that these surfaces alone are difficult to manufacture on 3D products, expensive to fabricate on a large scale and do not last long when subjected to environmental wear. Replication of nano-scale ridges was carried out using micro-injection, and the various samples were characterised using a range of tools to determine physical and biomechanical parameters. The sample surfaces were then cultured with the pathogenic bacterium Staphylococcus aureus under several environmental conditions, and the results were statistically analysed to reveal that anti-fouling LIPSS (laser induced periodic surface structures) ridges perform better to reduce bacteria cell-substrate adhesion, when compared to flat surfaces, or surfaces containing dual structures (anti-fouling ridges combined with anti-wear walls). It was therefore demonstrated that nanotextured polymeric surfaces with hydrophobic characteristics have exceptional non-fouling properties, preventing S. aureus, a very significant bacterial strain, from initial adhesion, a critical primary mechanism in its ability to proliferate. Collectively, the findings of this study strongly support the literature, suggesting that the bacteria struggle to adhere onto polymeric topography with increased water contact angles and simple nanostructures. However, the addition of certain anti-wear micro-features increased bacterial adhesion, reducing the efficacy of the non-fouling nanostructures from preventing biofilm formation.
    • A Framework for Digital Investigation of Peer-to-Peer (P2P) Networks. An Investigation into the Security Challenges and Vulnerabilities of Peer-to-Peer Networks and the Design of a Standard Validated Digital Forensic Model for Network Investigations

      Awan, Irfan U.; Musa, Ahmad S. (University of BradfordDepartment of Computer Science. Faculty of Engineering and Informatics, 2022)
      Peer-to-Peer (P2P) Networks have been presenting many fascinating capabilities to the internet since their inception, which has made and is still gathering so much interest. As a result, it is being used in many domains, particularly in transferring a large amount of data, which is essential for modern computing needs. A P2P network contains many independent nodes to form a highly distributed system. These nodes are used to exchange all kinds of files without using a single server as in a Client-Server architecture. Such types of files make the network highly vulnerable to malicious attackers. Nevertheless, P2P systems have become susceptible to different malicious attacks due to their widespread usage, including the threat of sharing malware and other dangerous programs, which can be significantly damaging and harmful. A significant obstacle with the current P2P network traffic monitoring and analysis involves many newly emerging P2P architectures possessing more intricate communication structures and traffic patterns than the traditional client-server architectures. The traffic volume generated by these networks, such as uTorrent, Gnutella, Ares, etc., was once well over half of the total internet traffic. The dynamic use of port numbers, multiple sessions, and other smart features of these applications complicate the characterization of current P2P traffic. Transport-level traffic identification is a preliminary but required step towards traffic characterization, which this thesis addresses. Therefore, a novel detection mechanism that relies on transport-level traffic characterization has been presented for P2P network investigation The importance of the investigation necessitates the formalization of frameworks to leverage the integration of forensics standards and accuracy to provide integrity to P2P networks. We employed the standard Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model to aid a credible digital investigation. We considered the ADDIE model for validation as a standard digital forensic model for P2P network investigations using the United States’ Daubert Standard, the United Kingdom's Forensic Science Regulator Guidance – 218 (FSR-G-218), and Forensic Science Regulator Guidance – 201 (FSR-G-201) methodologies. The solution was evaluated using a realistic P2P investigation and showed accurate load distribution and reliable digital evidence.
    • Impacts of dried Athel leaves and silica fume as eco-friendly wastes on behaviour of lime-treated heavy clay

      Mohamed, Mostafa H.A.; Muhmed, Asma A.B. (University of BradfordFaculty of Engineering and Informatics, 2021)
      Construction on problematic soils is challenging owing to the potential of volume changes due to variation of moisture content. Lime stabilisation can be used to treat problematic soils. The main drawbacks of lime addition to the clayey soils are the need for lengthy curing periods and relatively large quantities of lime for significant improvement and also loss in ductility. Using eco-friendly agricultural and industrial wastes, that can partially be substituted by the material responsible for greenhouse gases such as lime, can overcome these drawbacks and decrease global warming. In the current study, variables controlling the unconfined compressive strength of lime treated clay with a focus on assessing the effects of moisture content were investigated. Furthermore, the effects of adding agricultural waste (Dried Athel Leaves (DAL)) and industrial waste (Silica Fume (SF)) on hydromechanical properties of lime treated clay were assessed. The performance of the treated mixtures was examined based on results attained from unconfined compressive strength, swelling pressure and permeability. Specimens were treated with deferent percentages of lime and cured at different periods and temperatures to observe the strength behaviour. In oedometer tests, the specimens were prepared and tested immediately after compaction. The failure patterns were also studied to better understand the ultimate behaviour of lime stabilised clays. The appearance and presence of cementitious products were identified by using the scanning electron microscope and energy dispersive X-ray spectrometer techniques to elucidate their strength development. The findings indicated that the effect of moisture content is controlled by the clay content and unit weight. The addition of 7% lime to clay caused a remarkable increase in the unconfined compressive strength by 363%. The incorporation of 2% DAL and 5% SF within lime treated clay further increased the strength by 6% and 33% respectively after curing of 28 days at 20 °c in comparison with those attained by lime treatment only. The improvement of the strength of the lime­ treated clay augmented with both wastes continued in long term. Temperature and lime content have positive effects on the improvement of strength, however, increasing lime content to 11% negatively affected the strength of lime treated specimens with 2% DAL. The formation of cementitious products was observed in SEM images and detected quantitatively through EDS analysis. The results of the recorded oedometric tests for lime-DAL and lime-SF mixtures revealed that incorporation of the 2% DAL and 5% SF reduced the clay swelling pressures by 25% and 10% compared to that attained by lime treatment only resulting in total reductions of 93.6% and 68% from that recorded on untreated clay. In addition, the impermeable clay transformed into permeable material by adding DAL and SF. Of the two types of wastes considered in this research, DAL demonstrated more superior improving capability. A further study was conducted to develop ANN model based on collated laboratory data for the prediction of the UCS values of lime treated soils. The promising outcomes of this research suggest that the drawbacks of lime stabilisation can be overcome by the addition of agricultural and industrial wastes. Consequently, the findings attained could be considered in future practice standards with regards to the requirement of lime stabilisation.