Defence Science and Technology Laboratory

About: Defence Science and Technology Laboratory is a government organization based out in Salisbury, United Kingdom. It is known for research contribution in the topics: Burkholderia pseudomallei & Francisella tularensis. The organization has 926 authors who have published 1242 publications receiving 30091 citations. The organization is also known as: Dstl & [dstl].

Web‐based horizon scanning: concepts and practice

Abstract: Purpose – In this review, the aim is first to define horizon scanning and then outline the general approach currently employed by many organisations using web‐based resources. It then aims to discuss the benefits and drivers of horizon scanning, to identify some organisations currently undertaking activities in the field, and explain in detail how the web‐based horizon scanning approach is implemented. The aim is then to conclude with a discussion of good practice and areas for further research.Design/methodology/approach – The basis for this review is a symposium held at the UK Defence Science and Technology Laboratory in March 2010, where groups undertaking horizon scanning activities shared practices and reviewed the state of the art. Practitioners from both public sector and private organisations attending this symposium, as well as others, were invited to contribute to the manuscript, developing this as an iterative exercise over the last year.Findings – Structured processes of web‐based horizon scan...

DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced Response.

Abstract: In recent years social and news media have increasingly been used to explain patterns in disease activity and progression. Social media data, principally from the Twitter network, has been shown to correlate well with official disease case counts. This fact has been exploited to provide advance warning of outbreak detection, forecasting of disease levels and the ability to predict the likelihood of individuals developing symptoms. In this paper we introduce DEFENDER, a software system that integrates data from social and news media and incorporates algorithms for outbreak detection, situational awareness and forecasting. As part of this system we have developed a technique for creating a location network for any country or region based purely on Twitter data. We also present a disease nowcasting (forecasting the current but still unknown level) approach which leverages counts from multiple symptoms, which was found to improve the nowcasting accuracy by 37 percent over a model that used only previous case data. Finally we attempt to forecast future levels of symptom activity based on observed user movement on Twitter, finding a moderate gain of 5 percent over a time series forecasting model.

Detection of the organophosphorus nerve agent VX and its hydrolysis products in white mustard plants grown in contaminated soil

Abstract: The Chemical Weapons Convention (CWC) aims to prohibit the development, production, acquisition, stockpiling, retention, transfer or use of chemical weapons by States Parties. Verification of compliance or investigations into allegations of use requires accurate detection of chemical warfare agents (CWAs) and their breakdown products. Detection of CWAs such as organophosphorus nerve agents in the environment relies mainly upon the analysis of soil. Here we present a novel method for the detection of the nerve agent VX and its hydrolysis products through analysis using a combination of gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) of ethanol extracts of contaminated vegetation (white mustard, Sinapis alba), which localised the compounds of interest, and in this study retained them in an extractable form longer than the soil.