Motivations for contributing to health-related articles on Wikipedia: An interview study

Background: Wikipedia is one of the most accessed sources of health information online. The current English-language Wikipedia contains more than 28,000 articles pertaining to health. Objective: The aim was to characterize individuals’ motivations for contributing to health content on the English-language Wikipedia. Methods: A set of health-related articles were randomly selected and recent contributors invited to complete an online questionnaire and follow-up interview (by Skype, by email, or face-to-face). Interviews were transcribed and analyzed using thematic analysis and a realist grounded theory approach. Results: A total of 32 Wikipedians (31 men) completed the questionnaire and 17 were interviewed. Those completing the questionnaire had a mean age of 39 (range 12-59), 16 had a postgraduate qualification, 10 had or were currently studying for an undergraduate qualification, 3 had no more than secondary education, and 3 were still in secondary education. In all, 15 were currently working in a health-related field (primarily clinicians). The median period for which they have been an active editing Wikipedia was 3-5 years. Of this group, 12 were in the United States, 6 were in the United Kingdom, 4 were in Canada, and the remainder from another 8 countries. Two-thirds spoke more than 1 language and 90% (29/32) were also active contributors in domains other than health. Wikipedians in this study were identified as health professionals, professionals with specific health interests, students, and individuals with health problems. Based on the interviews, their motivations for editing health-related content were summarized in 5 strongly interrelated categories: education (learning about subjects by editing articles), help (wanting to improve and maintain Wikipedia), responsibility (responsibility, often a professional responsibility, to provide good quality health information to readers), fulfillment (editing Wikipedia as a fun, relaxing, engaging, and rewarding activity), and positive attitude to Wikipedia (belief in the value of Wikipedia). An additional factor, hostility (from other contributors), was identified that negatively affected Wikipedians’ motivations. Conclusions: Contributions to Wikipedia’s health-related content in this study were made by both health specialists and laypeople of varying editorial skills. Their motivations for contributing stem from an inherent drive based on values, standards, and beliefs. It became apparent that the community who most actively monitor and edit health-related articles is very small. Although some contributors correspond to a model of “knowledge philanthropists,” others were importantly focused on maintaining articles (improving spelling and grammar, organization, and handling vandalism). There is a need for more people to be involved in Wikipedia’s health-related content

Mapping solar irradiance within Schrödinger Basin for future robotic sample return missions

The US National Research Council (NRC) identified eight scientific concepts and thirty-five prioritized investigations to be addressed with continued lunar exploration. These objectives are broadly consistent with those identified throughout the international community. the majority of these objectives require sample return from the Moon. Schrödinger basin has been highlighted as a particularly attractive location to find suitable samples

Mining whole sample mass spectrometry proteomics data for biomarkers: an overview

In this paper we aim to provide a concise overview of designing and conducting an MS proteomics experiment in such a way as to allow statistical analysis that may lead to the discovery of novel biomarkers. We provide a summary of the various stages that make up such an experiment, highlighting the need for experimental goals to be decided upon in advance. We discuss issues in experimental design at the sample collection stage, and good practise for standardising protocols within the proteomics laboratory. We then describe approaches to the data mining stage of the experiment, including the processing steps that transform a raw mass spectrum into a useable form. We propose a permutation-based procedure for determining the significance of reported error rates. Finally, because of its general advantages in speed and cost, we suggest that MS proteomics may be a good candidate for an early primary screening approach to disease diagnosis, identifying areas of risk and making referrals for more specific tests without necessarily making a diagnosis in its own right. Our discussion is illustrated with examples drawn from experiments on bovine blood serum conducted in the Centre for Proteomic Research (CPR) at Southampton University

Fast algorithm for border bases of Artinian Gorenstein algebras

Given a multi-index sequence $$\sigma$$, we present a new efficient algorithm to compute generators of the linear recurrence relations between the terms of $$\sigma$$. We transform this problem into an algebraic one, by identifying multi-index sequences, multivariate formal power series and linear functionals on the ring of multivariate polynomials. In this setting, the recurrence relations are the elements of the kerne l$I$\sigma of the Hankel operator $H$\sigma associated to $$\sigma$$. We describe the correspondence between multi-index sequences with a Hankel operator of finite rank and Artinian Gorenstein Algebras. We show how the algebraic structure of the Artinian Gorenstein algebra $A$\sigma$$associated to the sequence$$\sigma yields the structure of the terms $\sigma\alpha$for all$$\alpha$ $\in$ N n$. This structure is explicitly given by a border basis of$A$\sigma$$, which is presented as a quotient of the polynomial ring$K[x 1 ,. .. , xn$] by the kernel$I$\sigma$$of the Hankel operator$H$\sigma$$. The algorithm provides generators of$I$\sigma$$constituting a border basis, pairwise orthogonal bases of$A$\sigma$$ and the tables of multiplication by the variables in these bases. It is an extension of Berlekamp-Massey-Sakata (BMS) algorithm, with improved complexity bounds. We present applications of the method to different problems such as the decomposition of functions into weighted sums of exponential functions, sparse interpolation, fast decoding of algebraic codes, computing the vanishing ideal of points, and tensor decomposition. Some benchmarks illustrate the practical behavior of the algorithm

A variable neighborhood search algorithm for the constrained task allocation problem

A Variable Neighborhood Search algorithm is proposed for solving a task allocation problem whose main characteristics are: (i) each task requires a certain amount of resources and each processor has a finite capacity to be search between task it is assigned; (ii) the cost of solutions includes fixed cost when using processors, assigning cost and communication cost between task assigned to different processors. A computational experiment shows that the algorithm is satisfactory in terms of time and solution qualit