Semi-Competing Risks on A Trivariate Weibull Survival Model

A setting of a trivairate survival function using semi-competing risks concept is proposed. The Stanford Heart Transplant data is reanalyzed using a trivariate Weibull distribution model with the proposed survival function

Experiences with domestic defluoridation in India

During the International Drinking Water Supply and Sanitation Decade 1980-1990 in India, there was a marked preference in rural drinking water supply programmes, to seek community based water treatment solutions, attached to handpumps where such problems existed. This was true for iron removal and defl uoridation. However, over the next few years most of these treatments systems became inoperative, primarily attributed to a lack of a sense of ownership by user communities, resulting in an attitude of indifference towards the operation and maintenance of these plants. It is also possible that the complexities of O&M by user communities, in the rural Indian socio-political context, had not been institutionally understood. Since 1990s there has been an increasing trend to seek household based water quality treatment solution within rural drinking water supply programmes in India. This paper summarises the experiences of UNICEF in India in tackling the problem of high fl uoride content in rural drinking water supply sources, using household-based defl uoridation fi lter using activated alumina. Since 1991, UNICEF supported the research work for development of the technology by the Department of Chemistry, Indian Institute of Technology (IIT), Kanpur. This resulted in pilot projects on Domestic Defl uoridation Units in the states of Andhra Pradesh and Rajasthan during 1996-2002. Gradually a demand for these fi lters has grown and the private sector is gradually becoming interested. Perhaps this approach, addressing households specifi cally rather than the nebulous “community” in general, is ensuring the use of safer water to a greater degree

REDS: Random Ensemble Deep Spatial prediction

There has been a great deal of recent interest in the development of spatial prediction algorithms for very large datasets and/or prediction domains. These methods have primarily been developed in the spatial statistics community, but there has been growing interest in the machine learning community for such methods, primarily driven by the success of deep Gaussian process regression approaches and deep convolutional neural networks. These methods are often computationally expensive to train and implement and consequently, there has been a resurgence of interest in random projections and deep learning models based on random weights -- so called reservoir computing methods. Here, we combine several of these ideas to develop the Random Ensemble Deep Spatial (REDS) approach to predict spatial data. The procedure uses random Fourier features as inputs to an extreme learning machine (a deep neural model with random weights), and with calibrated ensembles of outputs from this model based on different random weights, it provides a simple uncertainty quantification. The REDS method is demonstrated on simulated data and on a classic large satellite data set

Ecosystem Approach to Small Scale Tropical Marine Fisheries

This is a 4-page brochure about a WorldFish led project. Throughout the world, poor fisheries management contributes to resource degradation, poverty, and food insecurity. This European Union project on an Ecosystem Approach to Small-scale Tropical Marine Fisheries is led by WorldFish and implemented in collaboration with national partners in Asia (Southeastern)-Indonesia; the Asia (Southeastern)-Philippines; the Solomon Islands and Tanzania. The overall objective is to use an ecosystem approach to fisheries management (EAFM) to improve governance of small-scale fisheries (SSF). The EAFM puts sustainability and equitability at the forefront of fisheries governance which enhances their contribution to poverty reduction.Specific objectives are to: 1. Assess existing institutional arrangements and identify opportunities for an EAFM to improve integrated SSF management; 2. Develop EAFM strategies and actions suitable for developing country contexts; 3. Strengthen the capacity of local fishery stakeholders and government agencies to collaborate and work within an EAFM. The project is taking a participatory and gender sensitive approach, both core philosophies of WorldFish. Representatives of all relevant stakeholder groups are involved in this action research project

Anterior Prefrontal Cortex Contributes to Action Selection through Tracking of Recent Reward Trends

The functions of prefrontal cortex remain enigmatic, especially for its anterior sectors, putatively ranging from planning to self-initiated behavior, social cognition, task switching, and memory. A predominant current theory regarding the most anterior sector, the frontopolar cortex (FPC), is that it is involved in exploring alternative courses of action, but the detailed causal mechanisms remain unknown. Here we investigated this issue using the lesion method, together with a novel model-based analysis. Eight patients with anterior prefrontal brain lesions including the FPC performed a four-armed bandit task known from neuroimaging studies to activate the FPC. Model-based analyses of learning demonstrated a selective deficit in the ability to extrapolate the most recent trend, despite an intact general ability to learn from past rewards. Whereas both brain-damaged and healthy controls used comparisons between the two most recent choice outcomes to infer trends that influenced their decision about the next choice, the group with anterior prefrontal lesions showed a complete absence of this component and instead based their choice entirely on the cumulative reward history. Given that the FPC is thought to be the most evolutionarily recent expansion of primate prefrontal cortex, we suggest that its function may reflect uniquely human adaptations to select and update models of reward contingency in dynamic environments

Large-Scale Image Processing with the ROTSE Pipeline for Follow-Up of Gravitational Wave Events

Electromagnetic (EM) observations of gravitational-wave (GW) sources would bring unique insights into a source which are not available from either channel alone. However EM follow-up of GW events presents new challenges. GW events will have large sky error regions, on the order of 10-100 square degrees, which can be made up of many disjoint patches. When searching such large areas there is potential contamination by EM transients unrelated to the GW event. Furthermore, the characteristics of possible EM counterparts to GW events are also uncertain. It is therefore desirable to be able to assess the statistical significance of a candidate EM counterpart, which can only be done by performing background studies of large data sets. Current image processing pipelines such as that used by ROTSE are not usually optimised for large-scale processing. We have automated the ROTSE image analysis, and supplemented it with a post-processing unit for candidate validation and classification. We also propose a simple ad hoc statistic for ranking candidates as more likely to be associated with the GW trigger. We demonstrate the performance of the automated pipeline and ranking statistic using archival ROTSE data. EM candidates from a randomly selected set of images are compared to a background estimated from the analysis of 102 additional sets of archival images. The pipeline's detection efficiency is computed empirically by re-analysis of the images after adding simulated optical transients that follow typical light curves for gamma-ray burst afterglows and kilonovae. We show that the automated pipeline rejects most background events and is sensitive to simulated transients to limiting magnitudes consistent with the limiting magnitude of the images

Branching Ratios for The Radiometric Calibration of EUNIS-2012

The Extreme Ultraviolet Normal Incidence Spectrograph (EUNIS) sounding rocket instrument is a two-channel imaging spectrograph that observes the solar corona and transition region with high spectral resolution and a rapid cadence made possible by unprecedented sensitivity. The upcoming flight will incorporate a new wavelength channel covering the range 524-630 Angstroms, the previously-flown 300-370 Angstroms channel, and the first flight demonstration of cooled active pixel sensor (APS) arrays. The new 524-630 Angstrom channel incorporates a Toroidal Varied Line Space (TVLS) grating coated with B4C/Ir, providing broad spectral coverage and a wide temperature range of 0.025 to 10 MK. Absolute radiometric calibration of the two channels is being performed using a hollow cathode discharge lamp and NIST-calibrated AXUV-100G photodiode. Laboratory observations of He I 584 Angstroms and He II 304 Angstroms provide absolute radiometric calibrations of the two channels at those two respective wavelengths by using the AXUV photodiode as a transfer standard. The spectral responsivity is being determined by observing line pairs with a common upper state in the spectra of Ne I-III and Ar II-III. Calculations of A-values for the observed branching ratios are in progress