The role of Optical Coherence Tomography (OCT) for the diagnosis, monitoring, and guiding of treatment for neovascular Age-related Macular Degeneration (nAMD): an evidence synthesis study

Purpose:To determine the optimal role of OCT in diagnosing and monitoring nAMD (detecting disease activity and the need for further anti-VEGF treatment).
Methods:Systematic review. Major electronic databases and websites were searched. Studies were included if they reported the diagnostic performance of time domain or spectral domain OCT (or selected other tests) against a reference standard of ophthalmologist-interpreted fluorescein angiography in people with newly suspected or previously diagnosed nAMD. Risk of bias was assessed by two independent investigators using QUADAS-2. Summary receiver operating characteristic (SROC) curves were produced for each test given sufficient data.
Results:3700 titles/abstracts were screened, and 120 (3.2%) were selected for full-text assessment. A total of 22 studies were included (17 on diagnosis, 7 monitoring, and 3 both). From 15 studies reporting OCT data, sensitivity and specificity ranged from 59% to 100% and 27% to 100%, respectively.
Conclusions:The reported diagnostic performance of OCT showed large variability. The methodological quality of most studies was sub-optimal.

A multi-capability sensor for hydrocarbons, synthetic-based fluids and heavy metals:Applications for environmental monitoring during removal of drill cuttings piles

As part of any drilling cuttings pile removal process the requirement for monitoring the release of contaminants into the marine environment will be critical. Traditional methods for such monitoring involve taking samples for laboratory analysis. This process is time consuming and only provides data on spot samples taken from a limited number of locations and time frames. Such processes, therefore, offer very restricted information. The need for improved marine sensors for monitoring contaminants is established. We report here the development and application of a multi-capability optical sensor for the real-time in situ monitoring of three key marine environmental and offshore/oil parameters: hydrocarbons, synthetic-based fluids and heavy metal concentrations. The use of these sensors will be a useful tool for real-time in situ environmental monitoring during the process of decommissioning offshore structures. Multi-capability array sensors could also provide information on the dispersion of contamination from drill cuttings piles either while they are in situ or during their removal.

Health professionals' and service users' perspectives of shared care for monitoring wet age-related macular degeneration: a qualitative study alongside the ECHoES trial

Objectives: To explore the views of eye health professionals and service users on shared community and hospital care for wet or neovascular age-related macular degeneration (nAMD).

Method: Using maximum variation sampling, 5 focus groups and 10 interviews were conducted with 23 service users and 24 eye health professionals from across the UK (consisting of 8 optometrists, 6 ophthalmologists, 6 commissioners, 2 public health representatives and 2 clinical eye care advisors to local Clinical Commissioning Groups). Data were transcribed verbatim and analysed thematically using constant comparative techniques derived from grounded theory methodology.

Results: The needs and preferences of those with nAMD appear to be at odds with the current service being provided. There was enthusiasm among health professionals and service users about the possibility of shared care for nAMD as it was felt to have the potential to relieve hospital eye service burden and represent a more patient-centred option, but there were a number of perceived barriers to implementation. Some service users and ophthalmologists voiced concerns about optometrist competency and the potential for delays with referrals to secondary care if stable nAMD became active again. The health professionals were divided as to whether shared care was financially more efficient than the current model of care. Specialist training for optometrists, under the supervision of ophthalmologists, was deemed to be the most effective method of training and was perceived to have the potential to improve the communication and trust that shared care would require.

Conclusions: While shared care is perceived to represent a promising model of nAMD care, voiced concerns suggest that there would need to be greater collaboration between ophthalmology and optometry, in terms of interprofessional trust and communication.

Data-Augmentation for Reducing Dataset Bias in Person Re-identification

In this paper we explore ways to address the issue of dataset bias in person re-identification by using data augmentation to increase the variability of the available datasets, and we introduce a novel data augmentation method for re-identification based on changing the image background. We show that use of data augmentation can improve the cross-dataset generalisation of convolutional network based re-identification systems, and that changing the image background yields further improvements.

A Lightweight Tool for Anomaly Detection in Cloud Data Centres

Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

Parents' perceptions of microneedle-mediated monitoring as an alternative to blood sampling in the monitoring of their infants

OBJECTIVES: Microneedle (MN) arrays could offer a pain-free, minimally invasive approach to monitoring. This is envisaged to be particularly beneficial for younger patients, but parents' views to date are unknown. The aim of this study was to explore parental perceptions of MN-mediated ISF monitoring, as an alternative to the use of conventional blood sampling, and to understand the important factors for technique approval.

METHODS: Semi-structured interviews were conducted with parents with recent experience of a premature birth. Recruitment was through the Northern Ireland premature infant charity, Tinylife. Interviews progressed until data saturation was reached and thematic analysis employed.

KEY FINDINGS: The study included 16 parents. Parental support for MN-mediated monitoring was evident, alongside the unpopularity of traditional blood sampling in neonates. Factors facilitating MN approval included the opportunity for pain reduction, the simplicity of the procedure, the potential for increased parental involvement and the more favourable appearance, owing to the minute size of MNs and similarities with a sticking plaster. Confirmation of correct application, a pain-free patch removal and endorsement from trusted healthcare professionals were important.

CONCLUSION: These findings will inform researchers in the field of MN development and enlighten practitioners regarding parental distress resulting from conventional blood sampling. Further work is necessary to understand MN acceptability among practitioners. This work should assist in the development of an acceptable MN device and facilitate the reduction of parental distress.

Resistivity and Induced Polarization Monitoring of Biogas combined with Microbial Ecology on a Brown field Site

The accumulation of biogenic greenhouse gases (methane, carbon dioxide) in organic sediments is an important factor in the redevelopment and risk management of many brownfield sites. Good practice with brownfield site characterization requires the identification of free-gas phases and pathways that allow its migration and release at the ground surface. Gas pockets trapped in the subsurface have contrasting properties with the surrounding porous media that favor their detection using geophysical methods. We have developed a case study in which pockets of gas were intercepted with multilevel monitoring wells, and their lateral continuity was monitored over time using resistivity. We have developed a novel interpretation procedure based on Archie’s law to evaluate changes in water and gas content with respect to a mean background medium. We have used induced polarization data to account for errors in applying Archie’s law due to the contribution of surface conductivity effects. Mosaics defined by changes in water saturation allowed the recognition of gas migration and groundwater infiltration routes and the association of gas and groundwater fluxes. The inference on flux patterns was analyzed by taking into account pressure measurements in trapped gas reservoirs and by metagenomic analysis of the microbiological content, which was retrieved from suspended sediments in groundwater sampled in multilevel monitoring wells. A conceptual model combining physical and microbiological subsurface processes suggested that biogas trapped at depth may have the ability to quickly travel to the surface.

The Type IIP Supernova 2012aw in M95: Hydrodynamical Modeling of the Photospheric Phase from Accurate Spectrophotometric Monitoring

We present an extensive optical and near-infrared photometric and spectroscopic campaign of the Type IIP supernova SN 2012aw. The data set densely covers the evolution of SN 2012aw shortly after the explosion through the end of the photospheric phase, with two additional photometric observations collected during the nebular phase, to fit the radioactive tail and estimate the ⁵⁶Ni mass. Also included in our analysis is the previously published Swift UV data, therefore providing a complete view of the ultraviolet-optical- infrared evolution of the photospheric phase. On the basis of our data set, we estimate all the relevant physical parameters of SN 2012aw with our radiation-hydrodynamics code: envelope mass M _env ∼ 20 M _⊙, progenitor radius R ∼ 3 × 10¹³ cm (∼430 R_⊙), explosion energy E ∼ 1.5 foe, and initial ⁵⁶Ni mass ∼0.06 M_⊙. These mass and radius values are reasonably well supported by independent evolutionary models of the progenitor, and may suggest a progenitor mass higher than the observational limit of 16.5 ± 1.5 M _⊙of the Type IIP events. 

PESSTO monitoring of SN 2012hn: further heterogeneity among faint Type I supernovae

We present optical and infrared monitoring data of SN 2012hn collectedby the Public European Southern Observatory Spectroscopic Survey forTransient Objects. We show that SN 2012hn has a faint peak magnitude(MR ˜ -15.65) and shows no hydrogen and no clearevidence for helium in its spectral evolution. Instead, we detectprominent Ca II lines at all epochs, which relates this transient topreviously described `Ca-rich' or `gap' transients. However, thephotospheric spectra (from -3 to +32 d with respect to peak) of SN2012hn show a series of absorption lines which are unique and a redcontinuum that is likely intrinsic rather than due to extinction. Linesof Ti II and Cr II are visible. This may be a temperature effect, whichcould also explain the red photospheric colour. A nebular spectrum at+150 d shows prominent Ca II, O I, C I and possibly Mg I lines whichappear similar in strength to those displayed by core-collapsesupernovae (SNe). To add to the puzzle, SN 2012hn is located at aprojected distance of 6 kpc from an E/S0 host and is not close to anyobvious star-forming region. Overall SN 2012hn resembles a group offaint H-poor SNe that have been discovered recently and for which aconvincing and consistent physical explanation is still missing. Theyall appear to explode preferentially in remote locations offset from amassive host galaxy with deep limits on any dwarf host galaxies,favouring old progenitor systems. SN 2012hn adds heterogeneity to thissample of objects. We discuss potential explosion channels includingHe-shell detonations and double detonations of white dwarfs as well aspeculiar core-collapse SNe.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

A Review of Indirect Bridge Monitoring Using Passing Vehicles

Indirect bridge monitoring methods, using the responses measured from vehicles passing over bridges, are under development for about a decade. A major advantage of these methods is that they use sensors mounted on the vehicle, no sensors or data acquisition system needs to be installed on the bridge. Most of the proposed methods are based on the identification of dynamic characteristics of the bridge from responses measured on the vehicle, such as natural frequency, mode shapes, and damping. In addition, some of the methods seek to directly detect bridge damage based on the interaction between the vehicle and bridge. This paper presents a critical review of indirect methods for bridge monitoring and provides discussion and recommendations on the challenges to be overcome for successful implementation in practice.

Using geotechnical and LIDAR spatial monitoring to determine key environmental slope instability thresholds of a Jurassic coastal landslide: Straidkilly Point, Northern Ireland, UK.

The Antrim Coast Road stretching from the seaport of Larne in the East of Northern Ireland to the famous Giant’s Causeway in the North has a well-deserved reputation for being one of the most spectacular roads in Europe (Day, 2006). At various locations along the route, fluid interactions between the problematic geology, Jurassic Lias Clay and Triassic Mudstone overlain by Cretaceous Limestone and Tertiary Basalt, and environmental variables result in frequent instances of slope instability within the vadose zone. During such instances of instability, debris flows and composite mudflows encroach on the carriageway posing a hazard to road users. This paper examines the site investigative, geotechnical and spatial analysis techniques currently being implemented to monitor slope stability for one site at Straidkilly Point, Glenarm, Northern Ireland. An in-depth understanding of the geology was obtained via boreholes, resistivity surveys and laboratory testing. Environmental variables recorded by an on-site weather station were correlated with measured pore water pressure and soil moisture infiltration dynamic data.
Terrestrial LiDAR (TLS) was applied to the slope for the monitoring of failures, with surveys carried out on a bi-monthly basis. TLS monitoring allowed for the generation of Digital Elevation Models (DEMs) of difference, highlighting areas of recent movement, erosion and deposition. Morphology parameters were generated from the DEMs and include slope, curvature and multiple measures of roughness. Changes in the structure of the slope coupled with morphological parameters are characterised and linked to progressive failures from the temporal monitoring. In addition to TLS monitoring, Aerial LiDARi datasets were used for the spatio-morphological characterisation of the slope on a macro scale. Results from the geotechnical and environmental monitoring were compared with spatial data obtained through Terrestrial and Airborne LiDAR, providing a multi-faceted approach to slope stability characterization, which facilitates more informed management of geotechnical risk by the Northern Ireland Roads Service.

Monitoring Bridge Dynamic Behaviour using an Instrumented Two Axle Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing, loading and environmental factors. A rational transport policy must monitor and provide adequate maintenance to this infrastructure to guarantee the required levels of transport service and safety. Increasingly in recent years, bridges are being instrumented and monitored on an ongoing basis due to the implementation of Bridge Management Systems. This is very effective and provides a high level of protection to the public and early warning if the bridge becomes unsafe. However, the process can be expensive and time consuming, requiring the installation of sensors and data acquisition electronics on the bridge. This paper investigates the use of an instrumented 2-axle vehicle fitted with accelerometers to monitor the dynamic behaviour of a bridge network in a simple and cost-effective manner. A simplified half car-beam interaction model is used to simulate the passage of a vehicle over a bridge. This investigation involves the frequency domain analysis of the axle accelerations as the vehicle crosses the bridge. The spectrum of the acceleration record contains noise, vehicle, bridge and road frequency components. Therefore, the bridge dynamic behaviour is monitored in simulations for both smooth and rough road surfaces. The vehicle mass and axle spacing are varied in simulations along with bridge structural damping in order to analyse the sensitivity of the vehicle accelerations to a change in bridge properties. These vehicle accelerations can be obtained for different periods of time and serve as a useful tool to monitor the variation of bridge frequency and damping with time.

Geotechnical monitoring using a combination of LIDAR, real-time dGPS, and electrical tomography to assess geotechnical risk of a coastal landslide.

The Antrim Coast Road stretching from the seaport of Larne in the East of Northern Ireland has a well-deserved reputation for being one of the most spectacular roads in Europe (Day, 2006). However the problematic geology; Jurassic Lias Clay and Triassic Mudstone overlain by Cretaceous Limestone and Tertiary Basalt, and environmental variables result in frequent instances of slope instability manifested in both shallow debris flows and occasional massive rotational movements, creating a geotechnical risk to this highway. This paper describes how a variety of techniques are being used to both assess instability and monitor movement of these active slopes near one site at Straidkilly Point, Glenarm. An in-depth understanding of the geology was obtained via boreholes, resistivity surveys and laboratory testing. Environmental variables recorded by an on-site weather station were correlated with measured pore water pressure and soil moisture infiltration data. Terrestrial LiDAR (TLS), with surveys carried out on a bi-monthly basis allowed for the generation of Digital Elevation Models (DEMs) of difference, highlighting areas of recent movement, accumulation and depletion. Morphology parameters were generated from the DEMs and include slope, curvature and multiple measures of roughness. Changes in the structure of the slope coupled with morphological parameters were characterised and linked to progressive failures from the temporal monitoring. In addition to TLS monitoring, Aerial LiDAR datasets were used for the spatio-morphological characterisation of the slope on a macro scale. A Differential Global Positioning System (dGPS) was also deployed on site to provide a real-time warning system for gross movements, which were also correlated with environmental conditions. Frequent electrical resistivity tomography (ERT) surveys were also implemented to provide a better understanding of long-term changes in soil moisture and help to define the complex geology. The paper describes how the data obtained via a diverse range of methods has been combined to facilitate a more informed management regime of geotechnical risk by the Northern Ireland Roads Service.