Guidance on the Selection of Appropriate Indicators for Quantification of Antimicrobial Usage in Humans and Animals

An increasing variety of indicators of antimicrobial usage has become available in human and veterinary medicine, with no consensus on the most appropriate indicators to be used. The objective of this review is therefore to provide guidance on the selection of indicators, intended for those aiming to quantify antimicrobial usage based on sales, deliveries or reimbursement data. Depending on the study objective, different requirements apply to antimicrobial usage quantification in terms of resolution, comprehensiveness, stability over time, ability to assess exposure and comparability. If the aim is to monitor antimicrobial usage trends, it is crucial to use a robust quantification system that allows stability over time in terms of required data and provided output; to compare usage between different species or countries, comparability must be ensured between the different populations. If data are used for benchmarking, the system comprehensiveness is particularly crucial, while data collected to study the association between usage and resistance should express the exposure level and duration as a measurement of the exerted selection pressure. Antimicrobial usage is generally described as the number of technical units consumed normalized by the population at risk of being treated in a defined period. The technical units vary from number of packages to number of individuals treated daily by adding different levels of complexity such as daily dose or weight at treatment. These technical units are then related to a description of the population at risk, based either on biomass or number of individuals. Conventions and assumptions are needed for all of these calculation steps. However, there is a clear lack of standardization, resulting in poor transparency and comparability. By combining study requirements with available approaches to quantify antimicrobial usage, we provide suggestions on the most appropriate indicators and data sources to be used for a given study objective

The Evaluation of Route Guidance Systems

BACKGROUND We were commissioned by the Transport and Road Research Laboratory to: "collaborate with the German government and their representatives who are responsible for conducting the LISB trial in Berlin in order to produce an agreed methodology, which is acceptable in both Germany and the UK, for assessing the automatic route guidance systems which will be provided in Berlin and London." The brief suggested a number of aspects to be included, and required detailed proposals, timescales and costs for implementation in London. 1.1.2 The background to the brief lies in decisions to introduce pilot automatic route guidance systems in the two cities. The principles of the systems are similar, and have been described in detail elsewhere (Jeffery, 1987). In brief, they involve : (i) a central computer which retains information on a specified road network, which is updated using real time information from the equipment users; (ii) infra red beacons at selected junctions which transmit information to equipped vehicles and receive information from those vehicles; (iii) in-vehicle equipment which includes a dead-reckoning system for position finding, a device for requesting guidance and specifying the destination, a micro-computer which selects the optimal route, and a display which indicates when a turn is required on the main network, and the compass direction and distance to the final destination; iv) transmission from the equipped vehicles of origin, requested destination, links used since passing the last beacon and, for each link, the time of entry and departure and time spent delayed. It is this travel time information which is used to update the central computer's knowledge of the best routes. (Continues..

Why do you take that route?

The purpose of this paper is to determine whether a particular context factor among the variables that a researcher is interested in causally affects the route choice behavior of drivers. To our knowledge, there is limited literature that consider the effects of various factors on route choice based on causal inference.Yet, collecting data sets that are sensitive to the aforementioned factors are challenging and the existing approaches usually take into account only the general factors motivating drivers route choice behavior. To fill these gaps, we carried out a study using Immersive Virtual Environment (IVE) tools to elicit drivers' route choice behavioral data, covering drivers' network familiarity, educationlevel, financial concern, etc, apart from conventional measurement variables. Having context-aware, high-fidelity properties, IVE data affords the opportunity to incorporate the impacts of human related factors into the route choice causal analysis and advance a more customizable research tool for investigating causal factors on path selection in network routing. This causal analysis provides quantitative evidence to support drivers' diversion decision.Comment: 7 pages, 3 figure

On-Line Instruction-checking in Pipelined Microprocessors

Microprocessors performances have increased by more than five orders of magnitude in the last three decades. As technology scales down, these components become inherently unreliable posing major design and test challenges. This paper proposes an instruction-checking architecture to detect erroneous instruction executions caused by both permanent and transient errors in the internal logic of a microprocessor. Monitoring the correct activation sequence of a set of predefined microprocessor control/status signals allow distinguishing between correctly and not correctly executed instruction