Now showing items 1-20 of 9441

    • Hypothalamic Rax+ tanycytes contribute to tissue repair and tumorigenesis upon oncogene activation in mice

      Mu, W.; Li, S.; Guo, X.; Wu, H.; Chen, Z.; Qiao, L.; Helfer, Gisela; Lu, F.; Liu, C.; Wu, Q.-F. (2021-04-16)
      Hypothalamic tanycytes in median eminence (ME) are emerging as a crucial cell population that regulates endocrine output, energy balance and the diffusion of blood-born molecules. Tanycytes have recently been considered as potential somatic stem cells in the adult mammalian brain, but their regenerative and tumorigenic capacities are largely unknown. Here we found that Rax+ tanycytes in ME of mice are largely quiescent but quickly enter the cell cycle upon neural injury for self-renewal and regeneration. Mechanistically, Igf1r signaling in tanycytes is required for tissue repair under injury conditions. Furthermore, Braf oncogenic activation is sufficient to transform Rax+ tanycytes into actively dividing tumor cells that eventually develop into a papillary craniopharyngioma-like tumor. Together, these findings uncover the regenerative and tumorigenic potential of tanycytes. Our study offers insights into the properties of tanycytes, which may help to manipulate tanycyte biology for regulating hypothalamic function and investigate the pathogenesis of clinically relevant tumors.
    • Muscle deterioration due to rheumatoid arthritis: assessment by quantitative MRI and strength testing

      Farrow, Matthew; Biglands, J.; Tanner, S.; Hensor, E.M.A.; Buch, M.H.; Emery, P.; Tan, A.L. (2021-03-02)
      RA patients often present with low muscle mass and decreased strength. Quantitative MRI offers a non-invasive measurement of muscle status. This study assessed whether MRI-based measurements of T2, fat fraction, diffusion tensor imaging and muscle volume can detect differences between the thigh muscles of RA patients and healthy controls, and assessed the muscle phenotype of different disease stages. Thirty-nine RA patients (13 'new RA'-newly diagnosed, treatment naïve, 13 'active RA'-persistent DAS28 >3.2 for >1 year, 13 'remission RA'-persistent DAS28 1 year) and 13 age and gender directly matched healthy controls had an MRI scan of their dominant thigh. All participants had knee extension and flexion torque and grip strength measured. MRI T2 and fat fraction were higher in the three groups of RA patients compared with healthy controls in the thigh muscles. There were no clinically meaningful differences in the mean diffusivity. The muscle volume, handgrip strength, knee extension and flexion were lower in all three groups of RA patients compared with healthy controls. Quantitative MRI and muscle strength measurements can potentially detect differences within the muscles between RA patients and healthy controls. These differences may be seen in RA patients who are yet to start treatment, those with persistent active disease, and those who were in clinical remission. This suggests that the muscles in RA patients are affected in the early stages of the disease and that signs of muscle pathology and muscle weakness are still observed in clinical remission.
    • Quantitative MRI in myositis patients: comparison with healthy volunteers and radiological visual assessment

      Farrow, Matthew; Biglands, J.D.; Grainger, A.J.; O'Connor, P.; Hensor, E.M.A.; Ladas, A.; Tanner, S.F.; Emergy, P.; Tan, A.L. (2021-01-01)
      To assess whether magnetic resonance imaging (MRI)-based measurements of T2, fat fraction, diffusion tensor imaging, and muscle volume can detect differences between the muscles of myositis patients and healthy controls, and to identify how they compare with semi-quantitative MRI diagnosis. Sixteen myositis patients and 16 age- and gender-matched healthy controls underwent MRI of their thigh. Quantitative MRI measurements and radiologists' semi-quantitative scores were assessed. Strength was assessed using an isokinetic dynamometer. Fat fraction and T2 values were higher in myositis patients whereas muscle volume was lower compared to healthy controls. There was no difference in diffusion. Muscle strength was lower in myositis patients compared to healthy controls. In a subgroup of eight patients, scored as unaffected by radiologists, T2 values were still significantly higher in myositis patients. Quantitative MRI measurements can detect differences between myositis patients and healthy controls. Changes in the muscles of myositis patients, undetected by visual, semi-quantitative scoring, can be detected using quantitative T2 measurements. This suggests that MRI T2 values may be useful for the management of myositis patients.
    • Velocity Profile and Turbulence Structure Measurement Corrections for Sediment Transport-Induced Water-Worked Bed

      Pu, Jaan H. (MDPI, 2021)
      When using point measurement for environmental or sediment laden flows, there is well-recognised risk for not having aligned measurements that causes misinterpretation of the measured velocity data. In reality, these kinds of mismeasurement mainly happen due to the misinterpretation of bed orientation caused by the complexity of its determination in natural flows, especially in bedload laden or rough bed flows. This study proposes a novel bed realignment method to improve the measured data benchmarking by three-dimensional (3D) bed profile orientation and implemented it into different sets of experimental data. More specifically, the effects of realignment on velocity profile and streamwise turbulence structure measurements were investigated. The proposed technique was tested against experimental data collected over a water-worked and an experimentally arranged well-packed beds. Different from the well-packed rough bed, the water-worked bed has been generated after long sediment transport and settling and hence can be used to verify the proposed bed-alignment technique thoroughly. During the flow analysis, the corrected velocity, turbulence intensity and Reynolds stress profiles were compared to the theoretical logarithmic law, exponential law and linear gravity (universal Reynolds stress distribution) profiles, respectively. It has been observed that the proposed method has improved the agreement of the measured velocity and turbulence structure data with their actual theoretical profiles, particularly in the near-bed region (where the ratio of the flow measurement vertical distance to the total water depth, z/h, is limited to ≤0.4).
    • Transcultural identity development among third generation minority consumers

      Takhar, A.; Jamal, A.; Kizgin, Hatice (2021-09)
      This study explores how global and local forces influence the processes of consumer re-acculturation amongst third-generation British Sikhs in the United Kingdom (U.K.). Data is collected over a three-year period using multiple methods that focus on the experiential consumption of by third-generation British-born Sikhs. Data is analysed using thematic analysis, and findings reveal three transcultural identity patterns: accommodating, re-acculturating, and resisting Sikh culture. We argue that the emergent identity patterns are fluid, as our participants feel neither wholly British, wholly Sikh, nor wholly British-Sikh, positioning themselves beyond, rather than against, Sikh or British culture. We uncover the connectedness between the traditional cultural practices of arranged marriages and the space of, a matrimonial website. We interpret this website as a medium through which transcultural identities are constructed. We contribute to theory by showing the development of transcultural patterns of consumption and consistent transcultural identity construction in non-migrating ethnic communities.
    • Security and Performance Engineering of Scalable Cognitive Radio Networks. Sensing, Performance and Security Modelling and Analysis of ’Optimal’ Trade-offs for Detection of Attacks and Congestion Control in Scalable Cognitive Radio Networks

      Kouvatsos, Demetres D.; Chuku, Ejike E. (University of BradfordSchool of Engineering and Informatics, 2019)
      A Cognitive Radio Network (CRN) is a technology that allows unlicensed users to utilise licensed spectrum by detecting an idle band through sensing. How- ever, most research studies on CRNs have been carried out without considering the impact of sensing on the performance and security of CRNs. Sensing is essential for secondary users (SUs) to get hold of free band without interfering with the signal generated by primary users (PUs). However, excessive sensing time for the detection of free spectrum for SUs as well as extended periods of CRNs in an insecure state have adverse effects on network performance. Moreover, a CRN is very vulnerable to attacks as a result of its wireless nature and other unique characteristics such as spectrum sensing and sharing. These attacks may attempt to eavesdrop or modify the contents of packets being transmitted and they could also deny legitimate users the opportunity to use the band, leading to underutilization of the spectrum space. In this context, it is often challenging to differentiate between networks under Denial of Service (DoS) attacks from those networks experiencing congestion. This thesis employs a novel Stochastic Activity Network (SAN) model as an effective analytic tool to represent and study sensing vs performance vs security trade-offs in CRNs. Specifically, an investigation is carried out focusing on sensing vs security vs performance trade-offs, leading to the optimization of the spectrum band’s usage. Moreover, consideration is given either when a CRN experiencing congestion and or it is under attack. Consequently, the data delivery ratio (PDR) is employed to determine if the network is under DoS attack or experiencing congestion. In this context, packet loss probability, queue length and throughput of the transmitter are often used to measure the PDR with reference to interarrival times of PUs. Furthermore, this thesis takes into consideration the impact of scalability on the performance of the CRN. Due to the unpredictable nature of PUsactivities on the spectrum, it is imperative for SUs to swiftly utilize the band as soon as it becomes available. Unfortunately, the CRN models proposed in literature are static and unable to respond effectively to changes in service demands. To this end, a numerical simulation experiment is carried out to determine the impact of scalability towards the enhancement of nodal CRN sensing, security and performance. Atthe instant the band becomes idle and there are requests by SUs waiting for encryption and transmission, additional resources are dynamically released in order to largely utilize the spectrum space before the reappearance of PUs. These additional resources make the same service provision, such as encryption and intrusion detection, as the initial resources. To this end,SAN model is proposed in order to investigate the impact of scalability on the performance of CRN. Typical numerical simulation experiments are carried out, based on the application of the Mobius Petri Net Package to determine the performance of scalable CRNs (SCRNs) in comparison with unscalable CRNs (UCRNs) and associated interpretations are made.
    • Contributions to evaluation of machine learning models. Applicability domain of classification models

      Neagu, Daniel; Rado, Omesaad A.M. (University of BradfordFaculty of Engineering and Informatics, 2019)
      Artificial intelligence (AI) and machine learning (ML) present some application opportunities and challenges that can be framed as learning problems. The performance of machine learning models depends on algorithms and the data. Moreover, learning algorithms create a model of reality through learning and testing with data processes, and their performance shows an agreement degree of their assumed model with reality. ML algorithms have been successfully used in numerous classification problems. With the developing popularity of using ML models for many purposes in different domains, the validation of such predictive models is currently required more formally. Traditionally, there are many studies related to model evaluation, robustness, reliability, and the quality of the data and the data-driven models. However, those studies do not consider the concept of the applicability domain (AD) yet. The issue is that the AD is not often well defined, or it is not defined at all in many fields. This work investigates the robustness of ML classification models from the applicability domain perspective. A standard definition of applicability domain regards the spaces in which the model provides results with specific reliability. The main aim of this study is to investigate the connection between the applicability domain approach and the classification model performance. We are examining the usefulness of assessing the AD for the classification model, i.e. reliability, reuse, robustness of classifiers. The work is implemented using three approaches, and these approaches are conducted in three various attempts: firstly, assessing the applicability domain for the classification model; secondly, investigating the robustness of the classification model based on the applicability domain approach; thirdly, selecting an optimal model using Pareto optimality. The experiments in this work are illustrated by considering different machine learning algorithms for binary and multi-class classifications for healthcare datasets from public benchmark data repositories. In the first approach, the decision trees algorithm (DT) is used for the classification of data in the classification stage. The feature selection method is applied to choose features for classification. The obtained classifiers are used in the third approach for selection of models using Pareto optimality. The second approach is implemented using three steps; namely, building classification model; generating synthetic data; and evaluating the obtained results. The results obtained from the study provide an understanding of how the proposed approach can help to define the model’s robustness and the applicability domain, for providing reliable outputs. These approaches open opportunities for classification data and model management. The proposed algorithms are implemented through a set of experiments on classification accuracy of instances, which fall in the domain of the model. For the first approach, by considering all the features, the highest accuracy obtained is 0.98, with thresholds average of 0.34 for Breast cancer dataset. After applying recursive feature elimination (RFE) method, the accuracy is 0.96% with 0.27 thresholds average. For the robustness of the classification model based on the applicability domain approach, the minimum accuracy is 0.62% for Indian Liver Patient data at r=0.10, and the maximum accuracy is 0.99% for Thyroid dataset at r=0.10. For the selection of an optimal model using Pareto optimality, the optimally selected classifier gives the accuracy of 0.94% with 0.35 thresholds average. This research investigates critical aspects of the applicability domain as related to the robustness of classification ML algorithms. However, the performance of machine learning techniques depends on the degree of reliable predictions of the model. In the literature, the robustness of the ML model can be defined as the ability of the model to provide the testing error close to the training error. Moreover, the properties can describe the stability of the model performance when being tested on the new datasets. Concluding, this thesis introduced the concept of applicability domain for classifiers and tested the use of this concept with some case studies on health-related public benchmark datasets.
    • Multiuser Multi Input Single Output (MU-MISO) Beamforming for 5G Wireless and Mobile Networks. A Road Map for Fast and Low Complexity User Selection, Beamforming Scheme Through a MU-MISO for 5G Wireless and Mobile Networks

      Abd-Alhameed, Raed A.; Hameed, Khalid W.H. (University of BradfordFaculty of Engineering and Informatics, 2019)
      Multi-User Multi-Input Multi-Output (MU-MIMO) systems are considered to be the sustainable technologies of the current and future of the upcoming wireless and mobile networks generations. The perspectives of these technologies under several scenarios is the focus of the present thesis. The initial system model covers the MU-MIMO, especially in the massive form that is considered to be the promising ideas and pillars of the 5G network. It is observed that the optimal number of users should be served in the time-frequency resource even though the maximum limitation of the MU-MIMO is governed by the total receiving antennas (K) is less than or equal to the base station antennas (M). The system capacity of the massive MIMO (mMIMO) under perfect channel state information (CSI) of uncorrelated channel is investigated and studied. Two types of precoders were applied, one is directly based on channel inversion, and the other uses the Eigen decomposition that is derived subject to the signal to a leakage maximization problem. The two precoders show a degree of equivalency under certain assumptions for the number of antennas at the user end. The convex optimization of multi-antenna networks to achieve the design model of optimum beamformer (BF) based on the uniform linear array (ULA) is studied. The ULA is selected for its simplicity to analyse many scenarios and its importance to match the future network applied millimetre wave (mmWave) spectrum. The maximum beams generated by the ULA are explored in terms of several physical system parameters. The duality between the MU-MIMO and ULA and how they are related based on beamformer operation are detailed and discussed. Finally, two approaches for overloaded systems are presented when the availability of massive array that is not guaranteed due to physical restrictions since the existence of a large number of devices will result in breaking the dimension rule (i.e., K ≤ M). As a solution, a low complexity users selection algorithm is proposed. The channel considered is uncorrelated with full and perfect knowledge at the BS. In particular, these two channel conditions may not be available in all scenarios. The CSI may be imperfect, and even the instantaneous form does not exist. A hybrid precoder between the mixed CSI (includes imperfect and statistical) and rate splitting approach is proposed to deal with an overloaded system under a low number of BS antennas.
    • IPR Law Protection and Enforcement and the Effect on Horizontal Productivity Spillovers from Inward FDI to Domestic Firms: A Meta-Analysis

      Christopoulou, D.; Papageorgiadis, N.; Wang, Chengang; Magkonis, G. (2021)
      We study the role of the strength of Intellectual Property Rights (IPR) law protection and enforcement in influencing horizontal productivity spillovers from inward FDI to domestic firms in host countries. While most WTO countries adopted strong IPR legislation due to exogenous pressure resulting from the signing of the Trade-Related Aspects of IPR (TRIPS) agreement, public IPR enforcement strength continues to vary significantly between countries. We meta-analyse 49 studies and find that public IPR enforcement strength has a direct positive effect on horizontal productivity spillovers from inward FDI to domestic firms and a negative moderating effect on the relationship between IPR law protection strength and horizontal productivity spillovers from inward FDI to domestic firms.
    • Denial of service detection using dynamic time warping

      Diab, D.M.; AsSadhan, B.; Binsalleeh, H.; Lambotharan, S.; Kyriakopoulos, K.G.; Ghafir, Ibrahim (2021)
      With the rapid growth of security threats in computer networks, the need for developing efficient security‐warning systems is substantially increasing. Distributed denial‐of‐service (DDoS) and DoS attacks are still among the most effective and dreadful attacks that require robust detection. In this work, we propose a new method to detect TCP DoS/DDoS attacks. Since analyzing network traffic is a promising approach, our proposed method utilizes network traffic by decomposing the TCP traffic into control and data planes and exploiting the dynamic time warping (DTW) algorithm for aligning these two planes with respect to the minimum Euclidean distance. By demonstrating that the distance between the control and data planes is considerably small for benign traffic, we exploit this characteristic for detecting attacks as outliers. An adaptive thresholding scheme is implemented by adjusting the value of the threshold in accordance with the local statistics of the median absolute deviation (MAD) of the distances between the two planes. We demonstrate the efficacy of the proposed method for detecting DoS/DDoS attacks by analyzing traffic data obtained from publicly available datasets.
    • Lattice-Boltzmann coupled models for advection-diffusion flow on a wide range of Péclet numbers

      Dapelo, Davide; Simonis, S.; Krause, J.J.; Bridgeman, John (Elsevier, 2021-04)
      Traditional Lattice-Boltzmann modelling of advection–diffusion flow is affected by numerical instability if the advective term becomes dominant over the diffusive (i.e., high-Péclet flow). To overcome the problem, two 3D one-way coupled models are proposed. In a traditional model, a Lattice-Boltzmann Navier–Stokes solver is coupled to a Lattice-Boltzmann advection–diffusion model. In a novel model, the Lattice-Boltzmann Navier–Stokes solver is coupled to an explicit finite-difference algorithm for advection–diffusion. The finite-difference algorithm also includes a novel approach to mitigate the numerical diffusivity connected with the upwind differentiation scheme.
    • A meta-analysis of the UTAUT model in the moblie banking literature: The moderating role of sample size and culture

      Jadil, Y.; Rana, Nripendra P.; Dwivedi, Y.K. (2021)
      In the last few years, several studies have examined the predictors of mobile banking (m-banking) adoption using the unified theory of acceptance and use of technology (UTAUT). However, contradictory results in some of the UTAUT relationships were found in the existing literature. Therefore, we aim to clarify and synthesize the empirical findings from the m-banking studies published since 2004 by conducting weight and meta-analysis with a focus on the UTAUT theory. We also seek to identify the roles of moderating variables on each UTAUT path. A total of 364 path coefficients from 127 studies were relevant for data analysis. CMA software V3 was employed to combine the effect sizes. All UTAUT relationships were found to be significant. Performance expectancy emerged as the strongest antecedent of usage intention. We also find that usage intention is the most critical predictor of use behavior. It was also revealed that sample size and culture significantly moderated the linkages between facilitating conditions and usage intention, effort expectancy and usage intention, and usage intention and use behavior. Theoretical contributions and managerial implications are also discussed toward the end.
    • A qualitative exploration of autism and transition into further and higher education

      Rogers, Chrissie; Simmons, Amy L. (University of BradfordFaculty of Management, Law and Social Sciences, School of Social Sciences, 2019)
      In this thesis, I explore 42 autistic individuals’ transitions into further and higher education (FHE) in England, drawing on personal experience as well as interview data. I was diagnosed with Asperger’s Syndrome in 1998 at the age of 13. At the age of 15, my mother introduced the topic to me, and autism soon became the foundation of my socio-political identity. The discussion is divided into three themes; stigma and perception management strategies, formal and informal support networks and the interplay of autism with institutional factors. I draw upon Tringo’s (1970) work on the hierarchy of impairment and Goffman’s (1963) work on stigma. Tringo’s (1970) hierarchy of impairment led me to my intra-communal hierarchy of impairment (perpetuated by autistic individuals against autistic individuals) and Goffman’s (1963) work on stigma led me to my four degrees of openness; autistic individuals can be indiscriminately open, or indiscriminately reticent, but openness if relevant, and openness if necessary, are more common strategies. UPIAS’ (1976) work on the social model of disability laid the foundation for my socio-political identity and this thesis. I argue autism has been largely absent from the political arena. I outline how there are four ideals; the ideals of self-regulation, normalcy, ability and independence. Eager to conform to these ideals, eager to self-present as ‘independent’, ‘self-regulating’, ‘normal’ or ‘capable’, some autistic students are reluctant to request support and accommodations, complicating the transition to FHE.
    • A study of the relationships of power between humanitarian workers and local leaders in Haiti

      Kelly, Rhys H.S.; Quintiliani, Pierrette (University of BradfordFaculty of Social Sciences and Humanities, 2018)
      Like many former colonised countries, Haiti has been plagued by insecurity and conflicts caused by internal and external influences as well as natural disasters. In 1804, after a protracted conflict between slaves and French colonialists, Haiti became the first black country to gain its independence through a revolution. Today, Haiti is the poorest country in the Western hemisphere, ranking 153rd on the Human Development Index and a significant number of humanitarian organisations are present on the island aspiring at improving the standard of living of the population. The following study examines how the relationships of power emerging through the relationship between humanitarian and local leaders affect their perceptions of each other and identified the emotions emerging from these perceptions. The perceptions identified are the coloniality of power, corruption and distrust, the occurrence of conspiracy theories and the obstacles encountered in the implementation of a relief-development continuum model envisioned by general humanitarian policies. These perceptions create tensions between the humanitarian and local leaders, contributing to fuelling negative emotions such as regret, sadness, sense of failure, disappointment and anger. Negative emotions in this study affect the collaboration between humanitarians and local leaders, diminishing the positive influences and impact of humanitarian action on the well-being of the Haitian population. One of the components to increase these positive influences of humanitarian action is to lessen the asymmetricality of power between humanitarian and local leaders through the adoption of a Cultural Competence model by humanitarians.
    • Analytical model for the suspended sediment concentration in the ice-covered alluvial channels

      Wang, F.; Huai, W.; Guo, Yakun (Elsevier, 2021-06)
      Ice cover formed on an alluvial channel can significantly alter the flow characteristics, such as the vertical distributions of streamwise velocity and shear stress, and hence the water and sediment transport process. The vertical profile of the suspended sediment concentration in the ice-covered alluvial channels with steady uniform flows is investigated in this study. To calculate the suspended sediment concentration, we are based on the Schmidt O’Brien equation and deduce an analytical model that employs an existing eddy viscosity model and a modified formula of the sediment fall velocity considering the common effects of the upper and lower boundaries. The proposed analytical model is then validated by using available experimental data reported in the literature. The predicted accuracy of the proposed model is evaluated through error statistics by comparing to previous modeled results. The relative concentration profiles of the suspended sediment are subsequently simulated by applying the validated analytical model with different characteristic parameters. Results show that the relative concentration decreases with the increase of both the ice cover roughness and the sediment fall velocity. The uniformity of the relative concentration distribution is closely related to the value of the proportionality parameter σ, revealing the physical mechanism that the more prominent the turbulent diffusion effect is, the more uniform the relative concentration profile is.
    • Examining causal effects of Emotional Intelligence on human related challenges occurring in Agile managed Information Systems projects

      Sivarajah, Uthayasankar; Weerakkody, Vishanth J.P.; Luong, Tan T. (University of BradfordFaculty of Management and Law, 2020)
      Agile project management has become a widely implemented project management approach in Information Systems (IS). Yet, along with its growing popularity, the amount of concerns raised in regard to human related challenges is rapidly increasing. Nevertheless, the extant scholarly literature has neglected to identify the primary origins and reasons of these challenges. The purpose of this study is therefore to examine if these challenges are caused by a lack of Emotional Intelligence (EI) by means of a quantitative approach, which includes two main steps. Firstly, based on a sample of 447 IS-professionals, the psychometric properties of their EI in regard to their personal characteristics is examined. Secondly, based on the findings of the first analysis, the causal inference of EI on these challenges is computed using Propensity Score Matching based on a second sample of 194 agile practitioners. Different dimensions of EI were found to have a low to medium impact on human related challenges occurring in agile teams in regard to anxiety, motivation, mutual trust and communication competence. Hence, these findings offer important new knowledge for IS-scholars, project managers and human resource practitioners, about the vital role of EI for educating, staffing and training of IS-professionals working in agile teams.
    • Bond Performance between Corroded Steel and Recycled Aggregate Concrete Incorporating Nano Silica

      Ashour, Ashraf F.; Alhawat, Musab M. (University of BradfordFaculty of Engineering and Informatics, 2020)
      The current research project mainly aims to investigate the corrosion resistance and bond performance of steel reinforced recycled aggregate concrete incorporating nano-silica under both normal and corrosive environmental conditions. The experimental part includes testing of 180 pull-out specimens prepared from 12 different mixtures. The main parameters studied were the amount of recycled aggregate (RCA) (i.e. 0%, 25%, 50% and 100%), nano silica (1.5% and 3%), steel embedment length as well as steel bar diameter (12 and 20mm). Different levels of corrosion were electrochemically induced by applying impressed voltage technique for 2, 5, 10 and 15 days. The experimental observations mainly focused on the corrosion level in addition to the ultimate bond, failure modes and slips occurred. Experimental results showed that the bond performance between un-corroded steel and recycled aggregate concrete slightly reduced, while a significant degradation was observed after being exposed to corrosive conditions, in comparison to normal concrete. On the other hand, the use of nano silica (NS) showed a reasonable bond enhancement with both normal and RCA concretes under normal conditions. However, much better influence in terms of bond and corrosion resistance was observed under advancing levels of corrosion exposure, reflecting the improvement in corrosion resistance. Therefore, NS was superbly effective in recovering the poor performance in bond for RCA concretes. More efficiency was reported with RCA concretes compared to the conventional concrete. The bond resistance slightly with a small amount of corrosion (almost 2% weight loss), then a significant bond degradation occurs with further corrosion. The influence of specific surface area and amount of nano silica on the performance of concrete with different water/binder (w/b) ratios has been also studied, using 63 different mixtures produced with three different types of colloidal NS having various surface areas and particle sizes. The results showed that the performance of concrete is heavily influenced by changing the surface area of nano silica. Amongst the three used types of nano silica, NS with SSA of 250 m2 /g achieved the highest enhancement rate in terms of compressive strength, water absorption and microstructure analysis, followed by NS with SSA of 500 m2/g, whilst NS with SSA of 51.4 m2 /g was less advantageous for all mixtures. The optimum nano silica ratio in concrete is affected by its particle size as well as water to binder ratio. The feasibility of the impact-echo method for identifying the corrosion was evaluated and compared to the corrosion obtained by mass loss method. The results showed that the impact-echo testing can be effectively used to qualitatively detect the damage caused by corrosion in reinforced concrete structures. A significant difference in the dominant frequencies response was observed after exposure to the high and moderate levels of corrosion, whilst no clear trend was observed at the initial stage of corrosion. Artificial neural network models were also developed to predict bond strength for corroded/uncorroded steel bars in concrete using the main influencing parameters (i.e., concrete strength, concrete cover, bar diameter, embedment length and corrosion rate). The developed models were able to predict the bond strength with a high level of accuracy, which was confirmed by conducting a parametric study.
    • The Construction of Care in Computed Tomography. Exploring Care from the Perspective of Patients and Radiographers

      Not given; Forton, Rachael K. (University of BradfordFaculty of Health Studies, 2019)
      Purpose: Patient centred care and the ‘patient voice’ are core components of UK healthcare policy and practice guidance. This study explores how care is perceived and experienced within the high technology environment of CT. Methods and Materials: A two-phase approach of Critical Discourse Analysis (CDA) and adapted Grounded Theory (GT) methodology using semi structured interviews, was used to obtain primary data from CT radiographers and patients. Recruitment and data collection were performed at a 1200 bed teaching hospital over a 6-month period. Results: The radiographer patient relationship and the radiographer’s role in providing care within CT are complex and multifaceted. Both patients and radiographer’s perceive CT imaging to be an integral part of the overall patient care and treatment pathway. As such, the act of being imaged is perceived as a care process and while image acquisition is recognised as a task orientated and technical process, the human element of providing care is cognitive, dynamic and responsive to individual need. Importantly, patient confidence in the care received was influenced by the radiographer’s ability to build a trusting relationship and display technical competence and this in turn facilitated active compliance resulting in a technically accurate examination. Despite previous literature suggesting that the technical environment created a barrier to patient care, patients within this study confirmed that radiographers provide care commensurate to the nursing ideals represented by the 6C’s (Care; Compassion; Competence; Communication; Courage; Commitment). Conclusions: A co-constructed model of care encompassing both technical components and patient-centeredness has been identified. This model promotes a new vision of patient centred care based on care perceptions within the high technology environment of CT.
    • Investigation of Integrated Decoupling Methods for MIMO Antenna Systems. Design, Modelling and Implementation of MIMO Antenna Systems for Different Spectrum Applications with High Port-to-Port Isolation Using Different Decoupling Techniques

      Abd-Alhameed, Raed A.; Excell, Peter S.; McEwan, Neil J.; Noras, James M.; Salah, Adham M.S. (University of BradfordFaculty of Engineering and Informatics, 2019)
      Multiple-Input-Multiple-Output (MIMO) antenna technology refers to an antenna with multiple radiators at both transmitter and receiver ends. It is designed to increase the data rate in wireless communication systems by achieving multiple channels occupying the same bandwidth in a multipath environment. The main drawback associated with this technology is the coupling between the radiating elements. A MIMO antenna system merely acts as an antenna array if the coupling between the radiating elements is high. For this reason, strong decoupling between the radiating elements should be achieved, in order to utilize the benefits of MIMO technology. The main objectives of this thesis are to investigate and implement several printed MIMO antenna geometries with integrated decoupling approaches for WLAN, WiMAX, and 5G applications. The characteristics of MIMO antenna performance have been reported in terms of scattering parameters, envelope correlation coefficient (ECC), total active reflection coefficient (TARC), channel capacity loss (CCL), diversity gain (DG), antenna efficiency, antenna peak gain and antenna radiation patterns. Three new 2×2 MIMO array antennas are proposed, covering dual and multiple spectrum bandwidths for WLAN (2.4/5.2/5.8 GHz) and WiMAX (3.5 GHz) applications. These designs employ a combination of DGS and neutralization line methods to reduce the coupling caused by the surface current in the ground plane and between the radiating antenna elements. The minimum achieved isolation between the MIMO antennas is found to be better than 15 dB and in some bands exceeds 30 dB. The matching impedance is improved and the correlation coefficient values achieved for all three antennas are very low. In addition, the diversity gains over all spectrum bands are very close to the ideal value (DG = 10 dB). The forth proposed MIMO antenna is a compact dual-band MIMO antenna operating at WLAN bands (2.4/5.2/5.8 GHz). The antenna structure consists of two concentric double square rings radiating elements printed symmetrically. A new method is applied which combines the defected ground structure (DGS) decoupling method with five parasitic elements to reduce the coupling between the radiating antennas in the two required bands. A metamaterial-based isolation enhancement structure is investigated in the fifth proposed MIMO antenna design. This MIMO antenna consists of two dual-band arc-shaped radiating elements working in WLAN and Sub-6 GHz 5th generation (5G) bands. The antenna placement and orientation decoupling method is applied to improve the isolation in the second band while four split-ring resonators (SRRs) are added between the radiating elements to enhance the isolation in the first band. All the designs presented in this thesis have been fabricated and measured, with the simulated and measured results agreeing well in most cases.
    • A planar dual-polarized phased array with broad bandwidth and quasi end-fire radiation for 5G mobile handsets

      Ojaroudi Parchin, Naser; Zhang, J.; Abd-Alhameed, Raed A.; Pedersen, G.F.; Zhang, S. (IEEE, 2021)
      A planar dual-polarized phased array is proposed for 5G cellular communications. The array has the properties of dual-polarization, wideband and quasi end-fire radiation, which is printed on one side of a single-layer substrate. The design contains two 8-element sub-arrays including horizontally polarized end-fire dipole antennas and vertically polarized end-fire periodic slot antennas, employed on the PCB ground plane of the 5G mobile platform. Both sub-arrays provide wide bandwidth to cover 28 and 38 GHz (promising 5G candidate bands). The -10 dB impedance bandwidth of the proposed CPW-fed dipole and slot antennas are 26.5-39.5 GHz and 27.1-45.5 GHz, respectively. Moreover, for -6 dB impedance bandwidth, these values could be more than 20 GHz (24.4-46.4 GHz for the dipole antenna) and 70 GHz (22.3-95 GHz for the slot antenna). The fundamental characteristics of the proposed dual-polarized 5G antenna array in terms of the impedance bandwidth, realized gain, polarization, radiation pattern, and beam steering are investigated and good results are obtained. The clearance of the proposed dual-polarized 5G antenna array is less than 4.5 mm which is sufficient for cellular applications.