On the Parameter of the Burr Type X under Bayesian Principles

A comprehensive Bayesian analysis has been carried out in the context of informative and non-informative priors for the shape parameter of the Burr type X distribution under different symmetric and asymmetric loss functions. Elicitation of hyperparameter through prior predictive approach is also discussed. Also we derive the expression for posterior predictive distributions, predictive intervals and the credible Intervals. As an illustration, comparisons of these estimators are made through simulation study

Experience of Anti-VEGF Treatment and Clinical Levels of Depression and Anxiety in Patients With Wet Age-Related Macular Degeneration

PURPOSE: To investigate detailed patient experiences specific to receiving vascular endothelial growth factor inhibitors (anti-VEGF) for wet age-related macular degeneration (wAMD), and to acquire a snapshot of the frequency of clinically significant levels of depression, anxiety, and posttraumatic stress among patients and levels of burden in patients’ carers. DESIGN: Observational cross-sectional mixed-methods study. METHODS: Three hundred patients with wAMD receiving anti-VEGF treatment and 100 patient carers were recruited. Qualitative data on patients’ experience of treatment were collected using a structured survey. Standardized validated questionnaires were used to quantify clinically significant levels of anxiety, depression, and posttraumatic stress, as well as cognitive function and carers’ burden. RESULTS: Qualitative data showed that 56% of patients (n =132) reported anxiety related to antiVEGF treatment. The main sources of anxiety were fear of going blind owing to intravitreal injections and concerns about treatment effectiveness, rather than around pain. From validated questionnaires, 17% of patients (n= 52) showed clinical levels of anxiety and 12% (n =36) showed clinical levels of depression. Depression levels, but not anxiety, were significantly higher in patients who received up to 3 injections compared with patients who received from 4 to 12 injections (analysis of variance [ANOVA] P = .027) and compared with patients who received more than 12 injections (ANOVA P = .001). CONCLUSIONS: Anti-VEGF treatment is often experienced with some anxiety related to treatment, regardless of the number of injections received. Clinical levels of depression seem to be more frequent in patients at early stages of anti-VEGF treatment. Strategies to improve patient experience of treatment and minimize morbidity are suggested

You are how you travel: A multi-task learning framework for Geodemographic inference using transit smart card data

Geodemographics, providing the information of population's characteristics in the regions on a geographical basis, is of immense importance in urban studies, public policy-making, social research and business, among others. Such data, however, are difficult to collect from the public, which is usually done via census, with a low update frequency. In urban areas, with the increasing prevalence of public transit equipped with automated fare payment systems, researchers can collect massive transit smart card (SC) data from a large population. The SC data record human daily activities at an individual level with high spatial and temporal resolutions. It can reveal frequent activity areas (e.g., residential areas) and travel behaviours of passengers that are intimately intertwined with personal interests and characteristics. This provides new opportunities for geodemographic study. This paper seeks to develop a framework to infer travellers' demographics (such as age, income level and car ownership, et al.) and their residential areas for geodemographic mapping using SC data with a household survey. We first use a decision tree diagram to detect passengers' residential areas. We then represent each individual's spatio-temporal activity pattern derived from multi-week SC data as a 2D image. Leveraging this representation, a multi-task convolutional neural network (CNN) is employed to predict multiple demographics of individuals from the images. Combing the demographics and locations of their residence, geodemographic information is further obtained. The methodology is applied to a large-scale SC dataset provided by Transport for London. Results provide new insights in understanding the relationship between human activity patterns and demographics. To the best of our knowledge, this is the first attempt to infer geodemographics by using the SC data

Trip purpose identification using pairwise constraints based semi-supervised clustering

Clustering of smart card data captured by automated fare collection (AFC) systems has traditionally been viewed as an unsupervised method. However, the small number of labelled data points in addition to the unlabelled smart card data can facilitate better partitioning and classification. In this paper, prior knowledge about the activities is translated into pairwise constraints and used in COP-KMEANS clustering algorithm to identify the trip purpose. The effectiveness of the method was evaluated by comparison of the results with the ground truth. The results demonstrate that semi-supervised clustering enhances the accuracy of the trip purpose identification

l/f Noise in the Superconducting Transition of a MgB2 Thin Film

The noise voltage spectral density in the superconducting transition of a MgB2 thin film on a SiN-coated Si thick substrate was measured over the frequency range 1 Hz-to-1 KHz. Using established bolometer noise theory the theoretical noise components due to Johnson, 1/f(excess) and phonon noise are modeled to the measured data. It is shown that for the case of a MgB2 thin film in the vicinity of the mid-point of transition, coupled to a heat sink via a fairly high thermal conductance (approximately equal to 10(sup -1) W/K)) that the measured noise voltage spectrum is 1/f limited and exhibits lit dependence with a varying between 0.3 and 0.5 in the measured frequency range. At a video frame rate frequency of 30 Hz the measured noise voltage density in the film is approximately equal to 61 nV /the square root of HZ, using this value an upper limit of electrical NEP approximately equal to 0.67pW / the square root of Hz is implied for a practical MgB2 bolometer operating at 36.1 K

Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe

Modelling the spread of coronavirus globally while learning trends at global and country levels remains crucial for tackling the pandemic. We introduce a novel variational-LSTM Autoencoder model to predict the spread of coronavirus for each country across the globe. This deep Spatio-temporal model does not only rely on historical data of the virus spread but also includes factors related to urban characteristics represented in locational and demographic data (such as population density, urban population, and fertility rate), an index that represents the governmental measures and response amid toward mitigating the outbreak (includes 13 measures such as: 1) school closing, 2) workplace closing, 3) cancelling public events, 4) close public transport, 5) public information campaigns, 6) restrictions on internal movements, 7) international travel controls, 8) fiscal measures, 9) monetary measures, 10) emergency investment in health care, 11) investment in vaccines, 12) virus testing framework, and 13) contact tracing). In addition, the introduced method learns to generate a graph to adjust the spatial dependences among different countries while forecasting the spread. We trained two models for short and long-term forecasts. The first one is trained to output one step in future with three previous timestamps of all features across the globe, whereas the second model is trained to output 10 steps in future. Overall, the trained models show high validation for forecasting the spread for each country for short and long-term forecasts, which makes the introduce method a useful tool to assist decision and policymaking for the different corners of the globe

Melatonin treatment for newborns with hypoxic ischaemic encephalopathy

OBJECTIVES: This is a protocol for a Cochrane Review (intervention). The objectives are as follows:. To assess the effects and safety of melatonin compared to standard care, including therapeutic hypothermia, for improving survival and reducing neurological sequelae in newborns with neonatal encephalopathy

MgB2 Thin-Film Bolometer for Applications in Far-Infrared Instruments on Future Planetary Missions

A SiN membrane based MgB2 thin-film bolometer, with a non-optimized absorber, has been fabricated that shows an electrical noise equivalent power of 256 fW/square root Hz operating at 30 Hz in the 8.5 - 12.35 micron spectral bandpass. This value corresponds to an electrical specific detectivity of 7.6 x 10(exp 10) cm square root Hz/W. The bolometer shows a measured blackbody (optical) specific detectivity of 8.8 x 10(exp 9) cm square root Hz/W, with a responsivity of 701.5 kV/W and a first-order time constant of 5.2 ms. It is predicted that with the inclusion of a gold black absorber that a blackbody specific detectivity of 6.4 x 10(exp 10) cm/square root Hz/W at an operational frequency of 10 Hz, can be realized for integration into future planetary exploration instrumentation where high sensitivity is required in the 17 - 250 micron spectral wavelength range

Telehealth technology: Potentials, challenges and research directions for developing countries

Telehealth has been developed and successfully applied in clinical practices, gained a strong interest and demonstrated its usefulness for medical diagnosis, treatments and rehabilitation worldwide. The advent of high speed communication technology and complex signal processing techniques, and recent advancements in cloud and cognitive computing, has created a new wave of opportunities for delivering remote healthcare applications and services, where the cost-effective diagnosis and treatment solutions as well as healthcare services are important and need to be deployed widely. Nevertheless, there is still a significant challenge in fully adopting this technology due to asymmetry among the healthcare centers, hospitals and the user-ends, especially in developing countries. This paper provides an overview of the telehealth, then to addresses the possible telehealth technologies and applications that could be applied to improve the healthcare service performance, with the focus on the developing countries. The incorporation of different technologies in telehealth including, Internet of Things (IoT), cloud and cognitive computing, medical image processing and effective encoding is introduced and discussed. Finally, the possible research directions, challenges for the efficient telehealth, and potential research and technology collaborations are outlined