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Effects of glaucoma on detection and discrimination of image blur
Get PDFYesBlur is one of the most commonly reported visual symptoms of glaucoma, but it is not
directly measured by current clinical tests. We aimed to investigate the effects of
glaucoma on detection and discrimination of image blur.
People with glaucoma, separated into two groups with (n=15) or without (n=17)
central visual field defects measured by 10-2 perimetry, and an age-similar control
group (n=18) participated. First, we measured contrast detection thresholds centrally
using a 2-interval forced choice procedure. We then measured blur detection and
discrimination thresholds for the same stimuli (reference blurs 0, 1 arcmin
respectively) using a 2-alternative forced choice procedure under two contrast
conditions; 4x individual detection threshold for the low contrast condition, 95%
contrast for the high contrast condition. The stimulus was a horizontal edge bisecting
a hard-edged circle of 4.5° diameter. Data were analysed by linear mixed modelling.
Contrast detection thresholds for the glaucoma group with central visual field defects
were raised by 0.014 ± 0.004 (mean ± SE, Michelson units) (p=0.002) and by 0.011
± 0.004 (p=0.03) relative to control and glaucoma without central visual field defect
groups respectively. Blur detection and discrimination thresholds were similar
between groups, with small elevations in blur detection thresholds in the glaucoma
groups not reaching statistical significance (detection p=0.29, discrimination p=0.91).
The lower contrast level increased thresholds from the higher contrast level by 1.30
± 0.10 arcmin (p<0.001) and 1.05 ± 0.096 arcmin (p<0.001) for blur detection and
discrimination thresholds respectively.
Early-moderate glaucoma resulted in only minimal elevations of blur detection
thresholds that did not reach statistical significance in this study. Despite the
prevalence of blur as a visual symptom of glaucoma, psychophysical measurements
of blur detection or discrimination may not be good candidates for development as
clinical tests for glaucomaCollege of Optometrists PhD scholarshi
A whole system approach to increasing children's physical activity in a multi-ethnic UK city: a process evaluation protocol
Get PDFYesEngaging in regular physical activity requires continued complex decision-making in varied and dynamic individual, social and structural contexts. Widespread shortfalls of physical activity interventions suggests the complex underlying mechanisms of change are not yet fully understood. More insightful process evaluations are needed to design and implement more effective approaches. This paper describes the protocol for a process evaluation of the JU:MP programme, a whole systems approach to increasing physical activity in children and young people aged 5-14 years in North Bradford, UK.
This process evaluation, underpinned by realist philosophy, aims to understand the development and implementation of the JU:MP programme and the mechanisms by which JU:MP influences physical activity in children and young people. It also aims to explore behaviour change across wider policy, strategy and neighbourhood systems. A mixed method data collection approach will include semi-structured interview, observation, documentary analysis, surveys, and participatory evaluation methods including reflections and ripple effect mapping.
This protocol offers an innovative approach on the use of process evaluation feeding into an iterative programme intended to generate evidence-based practice and deliver practice-based evidence. This paper advances knowledge regarding the development of process evaluations for evaluating systems interventions, and emphasises the importance of process evaluation.Sport England's Local Delivery Pilot - Bradfor
Developing multifunctional/smart civil engineering materials to fight viruses
Get PDFYesThe on-going COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) has posed an extraordinary threat to global public health, wealth and well-being. As the carrier of human life and production, infrastructures need to be upgraded to mitigate and prevent the spread of viral diseases. Developing multifunctional/smart civil engineering materials to fight viruses is a promising approach to achieving this goal. In this perspective, the basic introduction on virus and its structure is provided. Then, the current design principles of antiviral materials and structures are examined. Subsequently, the possibility of developing active/passive antiviral civil engineering materials (including cementitious composites, ceramics, polymers and coatings) is proposed and envisaged. Finally, the future research needs and potential challenges to develop antiviral civil engineering materials are put forward. The proposed strategies to develop multifunctional/smart antiviral civil engineering materials will aid in the construction of smart infrastructures to prevent the spread viruses, thus improving human life and health as well as sustainability of human society.National Science Foundation of China (51978127, 52178188, and 51908103); Fundamental Research Funds for the Central Universities (DUT21RC(3)039
Integration of Hidden Markov Modelling and Bayesian Networks for fault analysis of complex systems. Development of a hybrid diagnostics methodology based on the integration of hidden Markov modelling and Bayesian networks for fault detection, prediction and isolation of complex automotive systems
No full textThe complexity of engineered systems has increased remarkably to meet customer needs. In the continuously growing global market, it is essential for engineered systems to keep their productivities which can be achieved by higher reliability and availability. Integrated health management based on diagnostics and prognostics provides significant benefits, which includes increasing system safety and operational reliability, with a significant impact on the life-cycle costs, reducing operating costs and increasing revenues. Characteristics of complex systems such as nonlinearity, dynamicity, non-stationarity, and non-Gaussianity make diagnostics and prognostics more challenging tasks and decrease the application of classic reliability methods remarkably – as they cannot address the dynamic behaviour of these systems.
This research has focused on detecting, predicting and isolating faults in engineered systems, using operational data with multifarious data characteristics. Complexities in the data, including non-Gaussianity and high nonlinearity, impose stringent challenges on fault analysis. To deal with these challenges, this research proposed an integrated data-driven methodology in which hidden Markov modelling (HMM) and Bayesian network (BN) were employed to detect, predict and isolate faults in a system. The fault detection and prediction were based on comparing and exploiting pattern similarity in the data via the loglikelihood values generated through HMM training. To identify the root cause of the faults, the probability values obtained from updating the BN were used which were based on the virtual evidence provided by HMM training and log-likelihood values. To set up a more accurate data-driven model – particularly BN structure – engineering analyses were employed in a structured way to explore the causal relationships in the system which is essential for reliability analysis of complex engineered systems.
The automotive exhaust gas Aftertreatment system is a complex engineered system consisting of several subsystems working interdependently to meet emission legislations. The Aftertreatment system is a highly nonlinear, dynamic and non-stationary system. Consequently, it has multifarious data characteristics, where these characteristics raise the challenges of diagnostics and prognostics for this system, compared to some of the references systems, such as the Tennessee Eastman process or rolling bearings. The feasibility and effectiveness of the presented framework were discussed in conjunction with the application to a real-world case study of an exhaust gas Aftertreatment system which provided good validation of the methodology, proving feasibility to detect, predict, and isolate unidentified faults in dynamic processes
Numerical study of the dam-break waves and Favre waves down sloped wet rigid-bed at laboratory scale
No full textYesThe bed slope and the tailwater depth are two important ones among the factors that affect the propagation of the dam-break flood and Favre waves. Most previous studies have only focused on the macroscopic characteristics of the dam-break flows or Favre waves under the condition of horizontal bed, rather than the internal movement characteristics in sloped channel. The present study applies two numerical models, namely, large eddy simulation (LES) and shallow water equations (SWEs) models embedded in the CFD software package FLOW-3D to analyze the internal movement characteristics of the dam-break flows and Favre waves, such as water level, the velocity distribution, the fluid particles acceleration and the bed shear stress, under the different bed slopes and water depth ratios. The results under the conditions considered in this study show that there is a flow state transition in the flow evolution for the steep bed slope even in water depth ratio α = 0.1 (α is the ratio of the tailwater depth to the reservoir water depth). The flow state transition shows that the wavefront changes from a breaking state to undular. Such flow transition is not observed for the horizontal slope and mild bed slope. The existence of the Favre waves leads to a significant increase of the vertical velocity and the vertical acceleration. In this situation, the SWEs model has poor prediction. Analysis reveals that the variation of the maximum bed shear stress is affected by both the bed slope and tailwater depth. Under the same bed slope (e.g., S0 = 0.02), the maximum bed shear stress position develops downstream of the dam when α = 0.1, while it develops towards the end of the reservoir when α = 0.7. For the same water depth ratio (e.g., α = 0.7), the maximum bed shear stress position always locates within the reservoir at S0 = 0.02, while it appears in the downstream of the dam for S0 = 0 and 0.003 after the flow evolves for a while. The comparison between the numerical simulation and experimental measurements shows that the LES model can predict the internal movement characteristics with satisfactory accuracy. This study improves the understanding of the effect of both the bed slope and the tailwater depth on the internal movement characteristics of the dam-break flows and Favre waves, which also provides a valuable reference for determining the flood embankment height and designing the channel bed anti-scouring facility.National Natural Science Foundation of China (Grant No: 51879179, 52079081), the Open Fund from the State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University (SKHL1809) and the Sichuan Science and Technology Program (No. 2019JDTD0007
Two-dimensional turbulent burst examination and angle ratio utilization to detect scouring/sedimentation around mid-channel bar
No full textyesRiver morphological dynamics are complex phenomena in natural and environmental flows. In particular, the sediment transport around braid mid-channel bars has not gained enough understanding from previous research. The effect of submergence ratio on the turbulence behavior in the proximity of the bar has been investigated in this study. The spatial distribution of turbulent flow in the proximity of bar has been studied by plotting the depth-averaged two-dimensional contours of turbulent kinetic energy. The high value of TKE has been observed in regions just downstream from the bar. It is due to the vortex shedding occurring in that region. The interaction of sweep and ejection events have been analyzed using the parameter Dominance Function obtained from the ratio of occurrence probability of ejection events to the occurrence probability of sweep events. This outcome indicates that the depth averaged parameter Dominance Function has successfully predicted the high scouring region which makes it an ideal parameter for analyzing the scour phenomena in real-world water management projects. The high scouring zone lies in the close proximity of the bar. This shows that the scouring effect from the bar is limited to its close region. The magnitude of scouring occurring at the upstream region of the bar also increases with the increment of submergence ratio. The relationship of quadrant event inclination angles with the sediment transport occurring in the proximity of bar has been also studied, where an Angle Ratio parameter has been utilized for linking the bed elevation change with the inclination angle. The results indicate that the AR parameter has been successfully tested in this study to show its competence to represent the turbulent burst-induced bed sedimentation and scouring.The author has confirmed that no changes were made to the content of this proof on publication, although the paper is watermarked uncorrected proof
Stability and consolidation of sediment tailings incorporating unsaturated soil mechanics
No full textYesTailing dams are commonly used to safely store tailings without damaging the environment. Sand tailings (also called Sediment tailings) usually have a high water content and hence undergo consolidation during their placement. As the sediment tailings are usually placed above the ground water level, the degree of saturation and permeability of the sediment tailing is associated with the unsaturated condition due to the presence of negative pore-water pressure or suction. Current practices normally focus on the analyses saturated conditions. However, this consolidation process requires the flow of water between saturated and unsaturated zones to be considered. The objective of this study is to investigate the stability and consolidation of sediment tailings for the construction of road pillars considering the water flow between saturated and unsaturated zones. The scope of this study includes the unsaturated laboratory testing of sediments and numerical analyses of the road pillar. The results show that the analyses based on saturated conditions overestimate the time required to achieve a 90% degree of consolidation. The incorporation of the unsaturated soil properties is able to optimize the design of slopes for road pillars into steeper slope angles
What Are the Barriers and Enablers to the Implementation of Pharmacogenetic Testing in Mental Health Care Settings?
No full textYesIn psychiatry, the selection of antipsychotics and antidepressants is generally led by a trial-and-error approach. The prescribing of these medications is complicated by sub-optimal efficacy and high rates of adverse drug reactions (ADRs). These both contribute to poor levels of adherence. Pharmacogenetics (PGx) considers how genetic variation can influence an individual’s response to a drug. Pharmacogenetic testing is a tool that could aid clinicians when selecting psychotropic medications, as part of a more personalized approach to prescribing. This may improve the use of and adherence to these medications. Yet to date, the implementation of PGx in mental health environments in the United Kingdom has been slow. This review aims to identify the current barriers and enablers to the implementation of PGx in psychiatry and determine how this can be applied to the uptake of PGx by NHS mental health providers. A systematic searching strategy was developed, and searches were carried out on the PsychInfo, EmBase, and PubMed databases, yielding 11 appropriate papers. Common barriers to the implementation of PGx included cost, concerns over incorporation into current workflow and a lack of knowledge about PGx; whilst frequent enablers included optimism that PGx could lead to precision medicine, reduce ADRs and become a more routine part of psychiatric clinical care. The uptake of PGx in psychiatric care settings in the NHS should consider and overcome these barriers, while looking to capitalize on the enablers identified in this review.Bradford District Care NHS Foundation Trust in partnership with the University of Bradford; National Institute for Health Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre (NIHR Yorkshire and Humber PSTRC); National Institute for Health Research Leeds in vitro Diagnostics Co-operative
Defect prediction on production line
No full textYesQuality control has long been one of the most challenging fields of manufacturing. The development of advanced sensors and the easier collection of high amounts of data designate the machine learning techniques as a timely natural step forward to leverage quality decision support and manufacturing challenges. This paper introduces an original dataset provided by the automotive supplier company VALEO, coming from a production line, and hosted by the École Normale Supérieure (ENS) Data Challenge to predict defects using non-anonymised features, without access to final test results, to validate the part status (defective or not). We propose in this paper a complete workflow from data exploration to the modelling phase while addressing at each stage challenges and techniques to solve them, as a benchmark reference. The proposed workflow is validated in series of experiments that demonstrate the benefits, challenges and impact of data science adoption in manufacturing
Performance of Multimodal Biometric Systems Using Face and Fingerprint (Short Survey)
No full textYesBiometric authentication is the science and engineering of assessing and evaluating bioinformatics from the human body in order to increase system security by providing reliable and accurate behaviors and classifiers for personal identification and authentication. Its solutions are widely used in industries, governments, and the military. This paper reviews the multimodal biometric systems that integrated both faces and fingerprints as well as shows which one has the best accuracy and hardware complexity with the methods and databases. Several methods have been used in multimodal biometric systems such as KNN (K-Nearest Neighbor), CNN (Convolutional Neural Network), PCA (Principal Component Analysis), and so on. A multimodal biometric system for face and fingerprints that uses an FoM (Figure of Merit) to compare and show between the articles the best accuracy that have used multimodal biometric system face and fingerprints methods. The best performance has been found is 99.43% by using the cascade multimodal method.Horizon-MSCA-RISE-2019-2023, Marie Sklodowska-Curi