How long is a piece of Strix? Methods in measuring and measuring the measurers

An experiment to quantify intra- and interobserver error in anatomical measurements found that interobserver measurements can vary by over 14% of mean specimen length; disparity in measurement increases logarithmically with the number of contributors; instructions did not reduce variation or measurement disparity; scale of the specimen influenced the precision of measurement (relative error increasing with specimen size); different methods of taking a measurement yielded different results, although they did not differ in terms of precision, and topographical complexity of the elements being considered may potentially influence error (error increasing with complexity). These results highlight concerns about introduction of noise and potential bias that should be taken into account when compiling composite datasets and meta-analyses.

Measuring the value to the public of pig welfare improvements: a contingent valuation approach

The welfare of farm animals is a policy area that has increased greatly in importance in recent years. When deciding whether a proposed policy should be implemented, it can be useful for policymakers to compare the costs of the proposed improvement with the perceived benefits. The costs are relatively straightforward to calculate but little is known about the benefits. The Contingent Valuation Method (CVM), a direct survey-based method, can be used to shed some light on this. This approach elicits the willingness-to-pay (WTP) for the provision of some public good or service. This paper reports the results of a contingent valuation study of the value of welfare improvements for growing pigs. Attitudes and opinions with regard to form animal welfare are explored and WTP elicited for various pig welfare improvements including increases in space allowance, environmental enrichment and research into improved pig housing design. The results reveal a positive WTP for these improvements. However, it is also noteworthy that a significant proportion of the general public is willing to pay nothing for these improvements. Overall, the study illustrates the usefulness of the CVM approach as a tool for policymakers in assessing the merits of possible policy initiatives affecting the welfare of animals.

Measuring the state of consciousness in a free-living diving sea turtle

We report on results from two types of data-logger attached to hawksbill turtles (Eretmochelys coriacea) in the breeding season at the Seychelles, Indian Ocean. Conventional time-depth recorders (TDRs) showed prolonged bouts of long dives to the seabed, consistent with benthic resting. This behaviour has been widely reported in sea turtles and appears to be a common feature for energy conservation. An Inter-Mandibular Angle Sensor (IMASEN) recorded mouth opening and buccal pumping by one turtle for 2.5 days. Buccal pumping occurred widely while the turtle was submerged, consistent with a function of olfactory sensory perception of the turtle's environment. However, buccal pumping stopped during the middle of long benthic dives consistent with the turtle entering a phase of sleep. It therefore appears that by recording buccal oscillations, it is possible to assess the state of consciousness of turtles allowing the eco-physiology of diving to be more fully explored. (C) 2007 Elsevier B.V. All rights reserved.

Measuring health-related quality of life after stroke: A brief tool.

Routine assessment of health-related quality of life (HRQoL) can be time consuming and burdensome for a person with stroke. Therefore the aim of this study was to develop and test a brief instrument for assessing HRQoL among people with stroke. The Quality of Life after Stroke Scale (QLASS) was constructed from items within the Quality of Life Index-Stroke Version and the Chronic Respiratory Disease Questionnaire. It was administered to 92 people with stroke at three points in time: immediately after discharge from hospital, 6 months and 12 months later. Results suggest that the QLASS has 19 items which represent three factors: emotional functioning, mastery and fatigue which correlate with valid measures of health status and activities of daily living. The QLASS is proposed as a brief, valid HRQoL tool for use among people with stroke.

Methods for measuring proteasome activity: Current limitations and future developments

The proteasome has been validated as a therapeutic target, with proteasome inhibitors showing particular efficacy in the treatment of Multiple Myeloma. A wide range of methods have been developed to profile proteasome activity. These include the current method of choice fluorogenic peptide substrates, as well as bioluminescent imaging, immunological methods, and more recently, site-specific fluorescent probes. The aim of this review is to evaluate the currently available methods for profiling proteasome activity and their suitability for use in translational studies. Ongoing development of techniques for profiling proteasome activity will facilitate future research into proteasome-related pathologies, thus accelerating the development of more specific drug regimes. (C) 2010 Elsevier Ltd. All rights reserved.

Measuring inconsistency in network intrusion rules

In this preliminary case study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. Finally, we measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. We conclude that such measures are useful for the network intrusion domain assuming that incorporating domain knowledge for correlation of rules is feasible.

A Syntax-based approach to measuring the degree of inconsistency for belief bases

Measuring the degree of inconsistency of a belief base is an important issue in many real world applications. It has been increasingly recognized that deriving syntax sensitive inconsistency measures for a belief base from its minimal inconsistent subsets is a natural way forward. Most of the current proposals along this line do not take the impact of the size of each minimal inconsistent subset into account. However, as illustrated by the well-known Lottery Paradox, as the size of a minimal inconsistent subset increases, the degree of its inconsistency decreases. Another lack in current studies in this area is about the role of free formulas of a belief base in measuring the degree of inconsistency. This has not yet been characterized well. Adding free formulas to a belief base can enlarge the set of consistent subsets of that base. However, consistent subsets of a belief base also have an impact on the syntax sensitive normalized measures of the degree of inconsistency, the reason for this is that each consistent subset can be considered as a distinctive plausible perspective reflected by that belief base,whilst eachminimal inconsistent subset projects a distinctive viewof the inconsistency. To address these two issues,we propose a normalized framework formeasuring the degree of inconsistency of a belief base which unifies the impact of both consistent subsets and minimal inconsistent subsets. We also show that this normalized framework satisfies all the properties deemed necessary by common consent to characterize an intuitively satisfactory measure of the degree of inconsistency for belief bases. Finally, we use a simple but explanatory example in equirements engineering to illustrate the application of the normalized framework.

Measuring workforce segregation: religious composition of private-sector employees at individual sites in Northern Ireland

In this paper I examine the scope of publicly available information on the religious composition of employees in private-sector companies in Northern Ireland. I highlight the unavailability of certain types of monitoring data and the impact of data aggregation at company as opposed to site level. Both oversights lead to underestimates of the extent of workplace segregation in Northern Ireland. The ability to provide more-coherent data on workplace segregation, by religion, in Northern Ireland is crucial in terms of advancing equality and other social-justice agendas. I argue that a more-accurate monitoring of religious composition of workplaces is part of an overall need to develop a spatial approach in which the importance of ethnically territorialised spaces in the reproduction of ethnosectarian disputation is understood.

Measuring Inconsistency in a Network Intrusion Detection Rule Set Based on Snort

In this preliminary study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which are based on Snort and incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. We measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. Finally, we propose a new measure of inconsistency for prioritized knowledge which incorporates the normalized number of atoms in a language involved in inconsistency to provide a deeper inspection of inconsistent formulae. We conclude that such measures are useful for the network intrusion domain assuming that introducing expert knowledge for correlation of rules is feasible.

Measuring the blame of each formula for inconsistent prioritized knowledge bases.

It is increasingly recognized that identifying the degree of blame or responsibility of each formula for inconsistency of a knowledge base (i.e. a set of formulas) is useful for making rational decisions to resolve inconsistency in that knowledge base. Most current techniques for measuring the blame of each formula with regard to an inconsistent knowledge base focus on classical knowledge bases only. Proposals for measuring the blames of formulas with regard to an inconsistent prioritized knowledge base have not yet been given much consideration. However, the notion of priority is important in inconsistency-tolerant reasoning. This article investigates this issue and presents a family of measurements for the degree of blame of each formula in an inconsistent prioritized knowledge base by using the minimal inconsistent subsets of that knowledge base. First of all, we present a set of intuitive postulates as general criteria to characterize rational measurements for the blames of formulas of an inconsistent prioritized knowledge base. Then we present a family of measurements for the blame of each formula in an inconsistent prioritized knowledge base under the guidance of the principle of proportionality, one of the intuitive postulates. We also demonstrate that each of these measurements possesses the properties that it ought to have. Finally, we use a simple but explanatory example in requirements engineering to illustrate the application of these measurements. Compared to the related works, the postulates presented in this article consider the special characteristics of minimal inconsistent subsets as well as the priority levels of formulas. This makes them more appropriate to characterizing the inconsistency measures defined from minimal inconsistent subsets for prioritized knowledge bases as well as classical knowledge bases. Correspondingly, the measures guided by these postulates can intuitively capture the inconsistency for prioritized knowledge bases.