Multilevel ensemble Kalman filtering for spatio-temporal processes

We design and analyse the performance of a multilevel ensemble Kalman filter method (MLEnKF) for filtering settings where the underlying state-space model is an infinite-dimensional spatio-temporal process. We consider underlying models that needs to be simulated by numerical methods, with discretization in both space and time. The multilevel Monte Carlo (MLMC) sampling strategy, achieving variance reduction through pairwise coupling of ensemble particles on neighboring resolutions, is used in the sample-moment step of MLEnKF to produce an efficient hierarchical filtering method for spatio-temporal models. Under sufficient regularity, MLEnKF is proven to be more efficient for weak approximations than EnKF, asymptotically in the large-ensemble and fine-numerical-resolution limit. Numerical examples support our theoretical findings.Comment: Version 1: 39 pages, 4 figures.arXiv admin note: substantial text overlap with arXiv:1608.08558 . Version 2 (this version): 52 pages, 6 figures. Revision primarily of the introduction and the numerical examples sectio

Discriminatory language in the workplace: unmasking prejudices and stereotypes

The link between language, communication and open discrimination has been the focus of numerous studies. For many years, language has been a vehicle of prejudice and negative stereotypes. However, in the last few years, overt verbal aggressions have diminished thanks to the implementation of equality policies and awareness-raising initiatives. Despite that, negative attitudes against protected groups might not have disappeared and may instead be transmitted subtly, such as through uncivil language. The goal of this research is to study the relation between language and subtle discrimination against lesbian and gay (LG) workers. With this goal in mind, 39 in-depth interviews were conducted. The analysis showed that LG people are victims of subtle discrimination and that language is one of the most common vehicles of prejudice and negative stereotypes. Jokes, inappropriate comments and questions are the expression of negative attitudes, which are probably present at an implicit level. Due to the ambiguity of these expressions and the settings where they have been studied — the workplace — these acts could be defined as uncivil behaviours. Practical implications, limitations and directions for future research are discussed.info:eu-repo/semantics/acceptedVersio

Information filtering via Iterative Refinement

With the explosive growth of accessible information, expecially on the Internet, evaluation-based filtering has become a crucial task. Various systems have been devised aiming to sort through large volumes of information and select what is likely to be more relevant. In this letter we analyse a new ranking method, where the reputation of information providers is determined self-consistently.Comment: 10 pages, 3 figures. Accepted for publication on Europhysics Letter

Context and consequences of liquor sachets use among young people in Malawi

This article presents a relatively new phenomenon regarding alcohol related problems in Malawi; the context and consequences of the consumption of liquor sachets among young people. The results presented are part of a larger study looking at the prevalence and social norms related to alcohol use, as well as people’s opinions on policies and interventions related to alcohol in Malawi. The results presented here are from a qualitative component in three Malawian communities. The results imply that the introduction of sachets has contributed to an increase in alcohol consumption among young people. Major issues of concern are issues of age limits, packaging and alcohol content, as well as lack of empirical evidence on which to base policies and interventions. Finally, there is a need to mobilize positive adult role models for young people with regards to alcohol.Key words: Liquor sachets, Malawi, youth, alcohol consequences, qualitative stud

The use of information and communication technologies by portuguese teachers

We present a study made in Portugal, in 2001/2002, on the use of Information and Communication Technologies (ICT) by teachers of all teaching levels (except high education), in both public and private schools. It was an initiative of the Ministry of Education (“Nonio – 21st Century” program), which was carried out by the Competence Centre “Softsciences” and the Centre for Computational Physics of the University of Coimbra. Some of the conclusions of this study, that has collected data from 19337 teachers, are the following: the majority of Portuguese teachers own a PC and approximately half of them use it in several activities, though their use of computers with students is limited. Primary school teachers use often the PC in their schools, though, probably, in an incipient way. The self-training of teachers in ICT is quite common. The Internet is more used by 3rd cycle (last part of middle school) and high school teachers, being most of its users male and young. These and other conclusions should be taken into account in a strategy towards incrementing a better use of new technologies in schools. The whole study is available in: http://nautilus.fid.uc.pt/cec/estud

Time-averaged MSD of Brownian motion

We study the statistical properties of the time-averaged mean-square displacements (TAMSD). This is a standard non-local quadratic functional for inferring the diffusion coefficient from an individual random trajectory of a diffusing tracer in single-particle tracking experiments. For Brownian motion, we derive an exact formula for the Laplace transform of the probability density of the TAMSD by mapping the original problem onto chains of coupled harmonic oscillators. From this formula, we deduce the first four cumulant moments of the TAMSD, the asymptotic behavior of the probability density and its accurate approximation by a generalized Gamma distribution

The effect of discrete vs. continuous-valued ratings on reputation and ranking systems

When users rate objects, a sophisticated algorithm that takes into account ability or reputation may produce a fairer or more accurate aggregation of ratings than the straightforward arithmetic average. Recently a number of authors have proposed different co-determination algorithms where estimates of user and object reputation are refined iteratively together, permitting accurate measures of both to be derived directly from the rating data. However, simulations demonstrating these methods' efficacy assumed a continuum of rating values, consistent with typical physical modelling practice, whereas in most actual rating systems only a limited range of discrete values (such as a 5-star system) is employed. We perform a comparative test of several co-determination algorithms with different scales of discrete ratings and show that this seemingly minor modification in fact has a significant impact on algorithms' performance. Paradoxically, where rating resolution is low, increased noise in users' ratings may even improve the overall performance of the system.Comment: 6 pages, 2 figure

A Multilevel Stochastic Collocation Method for Partial Differential Equations with Random Input Data

Stochastic collocation methods for approximating the solution of partial differential equations with random input data (e.g., coefficients and forcing terms) suffer from the curse of dimensionality whereby increases in the stochastic dimension cause an explosion of the computational effort. We propose and analyze a multilevel version of the stochastic collocation method that, as is the case for multilevel Monte Carlo (MLMC) methods, uses hierarchies of spatial approximations to reduce the overall computational complexity. In addition, our proposed approach utilizes, for approximation in stochastic space, a sequence of multi-dimensional interpolants of increasing fidelity which can then be used for approximating statistics of the solution as well as for building high-order surrogates featuring faster convergence rates. A rigorous convergence and computational cost analysis of the new multilevel stochastic collocation method is provided, demonstrating its advantages compared to standard single-level stochastic collocation approximations as well as MLMC methods. Numerical results are provided that illustrate the theory and the effectiveness of the new multilevel method