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Mortality, morbidity and educational outcomes in children of consanguineous parents in the Born in Bradford cohort
No full textYesBackground: Children of consanguineous parents have a higher risk of infant and childhood mortality, morbidity and intellectual and developmental disability.
Methods: Using a UK based longitudinal cohort study we quantify differences according to the consanguinity status of children from birth to 10 in mortality, health care usage, two health and three educational outcomes. The cohort comprises 13727 children; 35.7% White British, 43.7% Pakistani heritage, and 20.8% are from other ethnic groups.
Results: Compared to children whose parents were not related children whose parents were first cousins were more likely to die by age 10 (odds ratio 2.81, 95% CI 1.82-4.35) to have higher rates of primary care appointments (incident rate ratio 1.39, 95% CI 1.34-1.45) and more prescriptions (incident rate ratio 1.61, 95% CI 1.50-1.73). Rates of hospital accident and emergency attendance (incident rate ratio 1.21,95% CI 1.12-1.30) and hospital outpatients’ appointments (incident rate ratio 2.21,95% CI 1.90-2.56) are higher. Children of first cousins have higher rates of speech/ language development difficulties (odds ratio 1.63, 95% CI 1.36-1.96) and learning difficulties (odds ratio 1.89, 95% CI 1.28-2.81). When they begin school they are less likely to reach phonics standards (odds ratio 0.73, 95% CI 0.63-0.84) and less likely to show a good level of development (odds ratio 0.61, 95% CI 0.54-0.68). At age 10 there are higher numbers with special educational needs from first cousin unions compared to all children whose parents are not blood relations (odds ratio 1.38, 95% CI 1.20-1.58). Effect sizes for consanguinity status are similar in univariable and multivariable models where a range of control variables are added.
Conclusions: There is higher childhood mortality and greater use of health care as well as higher rates of learning difficulties, speech and language development challenges and substantive differences in education outcomes in children whose parents are first cousins.Born in Bradford is supported by Wellcome (223601) through the “Born in Bradford Age of Wonder” grant. DSM is supported by a Gates Cambridge Scholarship (OPP1144)
Financial literacy and investment behavior of individuals in Pakistan: Evidence from an Environment prone to religious sentiment
Get PDFYesWe explore the relationship dynamics between individual’s financial literacy and objective-oriented investment behaviour (OOIB) using the survey data from 686 investors in Pakistan. Drawing impetus from the social cognitive theory, we find that financial literacy significantly influences OOIB, which is subject to the individual’s belief in his/her capacity to manage their own investment portfolio (financial self-efficacy). However, we do not find the hypothesized moderating effect of financial risk attitude on the nexus between financial self-efficacy and OOIB. Our research indicates that factors such as gender, age, education, occupation, income level, and investment experience have a considerable impact on individual’s confidence and risk-taking propensity in
achieving financial goals. These findings provide valuable insights for policymakers and government bodies aiming to address financial concerns and develop prudent investment policies in an environment influenced by religious sentiments
A study of deep learning based face recognition models for addressing the interclass similarity challenges in face recognition systems
No full textPrecisely recognising siblings through facial recognition poses a significant challenge, primarily due to the pronounced similarities found in sibling’s faces. This research assesses the effectiveness of computational face recognition models in distinguishing between siblings, conducting a comprehensive analysis of both global facial features and specific attributes.
Leveraging datasets from SiblingDB, we have devised four customised frameworks aimed at discerning closely resembling sibling faces. This examination explores accuracy fluctuations across various facial regions.
The investigation starts with assessing sibling differentiation accuracy utilising state-of-the-art pre-trained face recognition models, incorporating diverse facial features and established similarity measures to predict the accuracy.
Second framework integrates an aggregate model, incorporating a custom object detector to identify facial parts. Informed by the first framework's analysis, this approach distinguishes between siblings using the optimal face recognition model and similarity measure.
Next framework adopts a fusion strategy, enhancing result robustness by amalgamating face recognition models and classifiers from prior experiments. This fusion approach addresses discrepancies, ensuring a robust outcome by considering various model combinations and similarity measures to discriminate between siblings. The research concludes by addressing threshold dependency through a fine-tuned framework, incorporating the Softmax activation function as the final layer in advanced face recognition models. This final layer predicts whether input images depict the same or different individuals, mitigating challenges associated with threshold variations.
Overall, this study contributes innovative approaches and insights, advancing the realism of discriminating siblings based on diverse facial features and unravelling the complexities of face recognition in differentiating individuals with high facial similarity
Spatial distribution of corrosion products from a bridge pier
Get PDFYesThis paper studies the spatial distribution of corrosion by-products by a bridge pier within a conductive medium. An electrochemical impedance spectroscopy (EIS) technique was used to investigate an uncoated metallic bridge pier submerged in static distilled water. An equivalent circuit model, derived from EIS results, served as the foundation for the study. Further, the role of diffusion was analysed, considering its significance in characterising the transfer of particles from the pier into the surrounding water. This exploration revealed the complex interaction between the diffusion processes of various corrosion by-products as a function of distance. In addition, by evaluating the spatial distribution of iron (II) corrosion by-products and modelling nanoparticle diffusion, the research examined the impact of diffusion and concentration on corrosion particle transmission. The findings, analysed via Nyquist and Bode plots, demonstrate significant differences between theoretical and empirical diffusion coefficients. Results indicated that under natural corrosion conditions, the primary product of the corrosion reaction, iron (II), disperses into the medium when oxidation occurs. The elevated resistivity due to the presence of iron (II) underscores the diffusion effect, leading to corrosion product precipitation and reaching saturation level. Additionally, the results demonstrated ideal values for the diffusion coefficient, which are crucial for advanced corrosion modelling. The results emphasised the need for empirical data to improve corrosion prediction models and informed maintenance strategies for submerged structures
Development of a Dignity Experience Scale in Mental Healthcare. Co-creating Empirical Measures with Service Users and Healthcare Professionals
Get PDFDignity is enshrined in statute, healthcare professional (HCP) ethics and policy, yet worldwide, mental healthcare violates service user dignity. Dignity lacks empirical definition as an operational concept. The aim of this study is to operationalize dignity in mental healthcare service user experience, to inform service design and delivery.
This thesis addresses concepts of dignity within a theoretical framework of service experience and proposes a new paradigm for understanding dignity which emphasizes the dynamic co-production of dignity experiences. It proposes a consensus model for the mechanisms of dignity co-production and the first Dignity Experience Scale found in mental healthcare, co-created with service users (SUs) and HCPs.
The study uses a sequential mixed methods approach to knowledge co-creation which privileges SU perspectives, comprising: 1. a literature meta-synthesis to specify an initial scale; 2. 17 experiential narratives to develop the scale and a Delphi panel of 11 HCPs to refine it; 3. quantitative research with 160 SUs and HCPs to test the scale; 4. Exploratory Factor Analysis (EFA) to identify latent factors.
Study findings show the importance of dignity co-production in rights-based, person-centred, recovery-oriented mental healthcare across 3 domains: Relationships, Environment and Confidentiality. EFA proposes an internally consistent 25-item, 5-factor scale. The primary factor, Empowering Empathy, emphasizes collaborative therapeutic relationships in which SUs are met with understanding and empowered with information and choice for recovery beyond symptom reduction. Other factors emphasize Respect for Equal Humanity, No Informal Coercion and creating Safe Space for Difference within relationships; and developing Comfortable, Confidential Environments
Perspectives of minority ethnic caregivers of people with dementia interviewed as part of the IDEAL programme
Get PDFYesPostwar migrants from the Caribbean and Indian subcontinent (Bangladesh, India, and Pakistan) to the UK are now experiencing the onset of age-related diseases such as dementia. Our evidence base, both quantitative and qualitative, documenting the experiences of family caregivers of people with dementia is largely drawn from studies undertaken with white European, North American, and Australasian populations. Consequently, there is a need for research in the field of dementia caregiving to reflect the increasing diversity in ethnic identities of the older adult population of the UK. Using semistructured interviews, we investigated the experiences of 18 caregivers of people with dementia in Black Caribbean, Black African, and South Asian (Indian, Pakistani, and Bangladeshi) communities in England. Participants were recruited from the Join Dementia Research platform and were predominantly female intergenerational carers. We identified the following three themes: motivation to care (spending time with the care recipient and reciprocity), positive and negative consequences of caregiving (rewards and consequences), and the cultural context of caregiving (cultural norms and values supporting caregiving and negative attitudes towards dementia). Our findings develop existing literature by identifying (a) the importance of spending time with the person they care for, (b) the absence of faith as a caregiving driver, and (c) the challenge of watching the declining health of a parent. We highlight how the different motivations to care are intertwined and dynamic. This is illustrated by the linking of obligation and reciprocity in our dataset and positive and negative experiences of caregiving.Alzheimer's Society. Grant Numbers: 348, AS-PR2-16-001. National Institute for Health Researc
Smart decision support system for keratoconus severity staging using corneal curvature and thinnest pachymetry indices
Get PDFYesBackground: This study proposes a decision support system created in collaboration with machine learning experts and ophthalmologists for detecting keratoconus (KC) severity. The system employs an ensemble machine model and minimal corneal measurements.
Methods: A clinical dataset is initially obtained from Pentacam corneal tomography imaging devices, which undergoes pre-processing and addresses imbalanced sampling through the application of an oversampling technique for minority classes. Subsequently, a combination of statistical methods, visual analysis, and expert input is employed to identify Pentacam indices most correlated with severity class labels. These selected features are then utilized to develop and validate three distinct machine learning models. The model exhibiting the most effective classification performance is integrated into a real-world web-based application and deployed on a web application server. This deployment facilitates evaluation of the proposed system, incorporating new data and considering relevant human factors related to the user experience.
Results: The performance of the developed system is experimentally evaluated, and the results revealed an overall accuracy of 98.62%, precision of 98.70%, recall of 98.62%, F1-score of 98.66%, and F2-score of 98.64%. The application's deployment also demonstrated precise and smooth end-to-end functionality.
Conclusion: The developed decision support system establishes a robust basis for subsequent assessment by ophthalmologists before potential deployment as a screening tool for keratoconus severity detection in a clinical setting
Machine learning predictions for bending capacity of ECC-concrete composite beams hybrid reinforced with steel and FRP bars
Get PDFYesThis paper explores the development of the most suitable machine learning models for predicting the bending capacity of steel and FRP (Fiber Reinforced Ploymer) bars hybrid reinforced ECC (Engineered Cementitious Composites)-concrete composite beams. Five different machine learning models, namely Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), Multilayer Perceptron (MLP), Random Forest (RF), and Extremely Randomized Trees (ERT), were employed. To train and evaluate these predictive models, the study utilized a database comprising 150 experimental data points from the literature on steel and FRP bars hybrid reinforced ECC-concrete composite beams. Additionally, Shapley Additive Explanations (SHAP) analysis was employed to assess the impact of input features on the prediction outcomes. Furthermore, based on the optimal model identified in the research, a graphical user interface (GUI) was designed to facilitate the analysis of the bending capacity of hybrid reinforced ECC-concrete composite beams in practical applications. The results indicate that the XGBoost algorithm exhibits high accuracy in predicting bending capacity, demonstrating the lowest root mean square error, mean absolute error, and mean absolute percentage error, as well as the highest coefficient of determination on the testing dataset among all models. SHAP analysis indicates that the equivalent reinforcement ratio, design strength of FRP bars, and height of beam cross-section are significant feature parameters, while the influence of the compressive strength of concrete is minimal. The predictive models and graphical user interface (GUI) developed can offer engineers and researchers with a reliable predictive method for the bending capacity of steel and FRP bars hybrid reinforced ECC-concrete composite beams
DEM simulation of a single screw granulator: The effect of liquid binder on granule properties
No full textYesThe Caleva UK single-screw Variable Density Extruder (VDE) is a continuous powder processing equipment known for spheronization and extrusion. Its suitability for granulation remains uncertain, a common challenge in powder processing industries that deal with granules, pellets, and tablets. This study investigates the VDE's potential for granulation, using 65 µm CaCO3 powder and PEG 4000 as a liquid binder. In order to replicate several experimental setups with varying binder concentrations and liquid-to-solid ratios (L/S) of 0.1 and 0.15, eight DEM simulations were run. Our results indicate that higher binder concentrations yield more consistent products with fewer fines, while lower concentrations result in inconsistent products with increased fines. Low L/S ratios produce fragile, fine-sized products with a broad particle size distribution (PSD). DEM simulations reveal a direct relationship between liquid binder content and contact forces. Analysis of bonds formed, and particle counts in simulations corroborates experimental observations of fines production. Additionally, granule strength appears to be directly proportional to contact force.Special gratitude is given to Ghana Scholarship Secretariat for providing the necessary funding for this research
Understanding underdog brand positioning effects among emerging market consumers: A moderated mediation approach
Get PDFYesThis study explores the underdog brand biography dimensions that emerging-country consumers identify with (Study 1) and attempts to uncover the effects of these dimensions on brand affinity and purchase intention moderated by self-identity and brand trust (Study 2). Study 1, using data from 359 young Indians, reveals three underlying dimensions integral to underdog brand biography in emerging markets. Study 2 employs an experimental setup with a single-factorial design among 332 young Mexican consumers to investigate the direct effects of three identified underdog brand biography dimensions on purchase intention, mediated by brand affinity and moderated by consumer self-identity and brand trust. Study 1 reveals three dimensions underlying underdog brand biographies: unfavorable circumstances, striving in adversities and passion, and persistent will to succeed. Study 2 reveals that consumers with higher self-identity demonstrate greater purchase intentions for an underdog brand than a top dog one. This study delineates the link between different dimensions of underdog brand biographies with brand affinity and purchase intention in emerging countries and builds on the understanding of the moderating role played by self-identity and brand trust. The results indicate that marketers can successfully use underdog narratives to influence consumer decision-making, thereby increasing brand affinity and purchase intention