Estimating the causal effect of a time-varying treatment on time-to-event using structural nested failure time models

In this paper we review an approach to estimating the causal effect of a time-varying treatment on time to some event of interest. This approach is designed for the situation where the treatment may have been repeatedly adapted to patient characteristics, which themselves may also be time-dependent. In this situation the effect of the treatment cannot simply be estimated by conditioning on the patient characteristics, as these may themselves be indicators of the treatment effect. This so-called time-dependent confounding is typical in observational studies. We discuss a new class of failure time models, structural nested failure time models, which can be used to estimate the causal effect of a time-varying treatment, and present methods for estimating and testing the parameters of these models

Groundwater dependence and drought within the southern African development community

A groundwater situation analysis of the SADC region has been undertaken as part of the World Bank GEF Programme as a basis for ensuring equitable use of groundwater resources, particularly during periods of drought, both for human needs and for sustaining ecosystems. Much of the groundwater in the region occurs in weathered crystalline rocks suitable for dispersed supply to rural communities, although there are several aquifers capable of sustaining urban demand that contribute to the supply of several major cities and towns. A number of SADC Member States, such as Botswana, Namibia and South Africa, are very dependent on groundwater, whereas the Democratic Republic of Congo is least dependent. Groundwater dependence and groundwater demand, together providing an indication of drought vulnerability, have been assessed from the availability and coverage of groundwater data, but it is very apparent that reliable and comprehensive groundwater data are major deficiencies throughout the SADC region. Few attempts have thus been made to calculate renewable groundwater resource volumes or develop optimum use of groundwater, despite the fact that susceptibility of many Member States to drought requires them to consider mitigation strategies to lessen the hardships imposed largely on their rural population. Such strategy requires long-term intervention and not short-term emergency responses, a process that is directly related to availability of comprehensive groundwater datasets. Considerable effort in groundwater assessment and monitoring and the accumulation, evaluation and dissemination of essential datasets will thus be required to maintain population livelihoods in future years when water supply is projected to be in deficit in over half of the SADC Member States

Pleistocene human footprints from the Willandra Lakes, southeastern Australia

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Supersonic wings with significant leading-edge thrust at cruise

Experimental/theoretical correlations are presented which show that significant levels of leading edge thrust are possible at supersonic speeds for certain planforms which match the theoretical thrust distribution potential with the supporting airfoil geometry. The analytical process employed spanwise distribution of both it and/or that component of full theoretical thrust which acts as vortex lift. Significantly improved aerodynamic performance in the moderate supersonic speed regime is indicated

Computational Topology Techniques for Characterizing Time-Series Data

Topological data analysis (TDA), while abstract, allows a characterization of time-series data obtained from nonlinear and complex dynamical systems. Though it is surprising that such an abstract measure of structure - counting pieces and holes - could be useful for real-world data, TDA lets us compare different systems, and even do membership testing or change-point detection. However, TDA is computationally expensive and involves a number of free parameters. This complexity can be obviated by coarse-graining, using a construct called the witness complex. The parametric dependence gives rise to the concept of persistent homology: how shape changes with scale. Its results allow us to distinguish time-series data from different systems - e.g., the same note played on different musical instruments.Comment: 12 pages, 6 Figures, 1 Table, The Sixteenth International Symposium on Intelligent Data Analysis (IDA 2017

Breaking the low pay, no pay cycle: the effects of the UK Employment Retention and Advancement programme

This paper presents the final economic results of the UK Employment Retention and Advancement (ERA) programme. ERA’s distinctive combination of post-employment advisory support and financial incentives was designed to help low-income individuals who entered work sustain employment and advance in the labour market. ERA targeted three groups. ERA produced short-term earnings gains for two lone parent target groups. However, these effects generally faded after the programme ended, largely because the control group caught up with the ERA group. For the New Deal 25 Plus target group (mostly long term unemployed men), ERA produced modest but sustained increases in employment and earnings

Betti number signatures of homogeneous Poisson point processes

The Betti numbers are fundamental topological quantities that describe the k-dimensional connectivity of an object: B_0 is the number of connected components and B_k effectively counts the number of k-dimensional holes. Although they are appealing natural descriptors of shape, the higher-order Betti numbers are more difficult to compute than other measures and so have not previously been studied per se in the context of stochastic geometry or statistical physics. As a mathematically tractable model, we consider the expected Betti numbers per unit volume of Poisson-centred spheres with radius alpha. We present results from simulations and derive analytic expressions for the low intensity, small radius limits of Betti numbers in one, two, and three dimensions. The algorithms and analysis depend on alpha-shapes, a construction from computational geometry that deserves to be more widely known in the physics community.Comment: Submitted to PRE. 11 pages, 10 figure

Pseudorehearsal in value function approximation

Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole balancing task. We have found that pseudorehearsal seems to assist learning even in such very simple problems, given proper initialization of the rehearsal parameters

Bayesian Exponential Random Graph Models with Nodal Random Effects

We extend the well-known and widely used Exponential Random Graph Model (ERGM) by including nodal random effects to compensate for heterogeneity in the nodes of a network. The Bayesian framework for ERGMs proposed by Caimo and Friel (2011) yields the basis of our modelling algorithm. A central question in network models is the question of model selection and following the Bayesian paradigm we focus on estimating Bayes factors. To do so we develop an approximate but feasible calculation of the Bayes factor which allows one to pursue model selection. Two data examples and a small simulation study illustrate our mixed model approach and the corresponding model selection.Comment: 23 pages, 9 figures, 3 table

Supersonic aircraft Patent

Design of supersonic aircraft with novel fixed, swept wing planfor