Doubling daily inhaled corticosteroid dose is ineffective in mild to moderately severe attacks of asthma in adults

Background: Asthma guidelines recommend increasing or doubling inhaled corticosteroid (ICS) dose to treat mild and moderate exacerbations of asthma in adults. Aim: To: (i) compare the effectiveness of doubling existing daily ICS dose (fluticasone) with maintaining usual ICS dose and usual daily ICS dose accompanied by oral steroids (OS) (dexamethasone) during mild and moderately severe exacerbations of asthma in adults; (ii) examine determinants of success and failure; and (iii) compare side-effect profiles. Methods: A randomized, double-blind, placebo-controlled (double-dummy), triple crossover trial. Participants acted as their own control. Outcome measures included treatment success/failure, peak expiratory flow (PEF) after 7 days therapy or at treatment failure, and side-effects. Results: From 22 participants (nine males and 13 females), 18 pairs of data were available for maintaining usual ICS versus doubling ICS and doubling ICS versus OS, and 19 for maintaining usual ICS versus OS. Median (fifth-95th percentile) age was 46.5 (32-64) years and forced expiratory volume in one second (FEV1) 73% (29-97%) predicted. The outcome after doubling ICS was not superior to maintaining usual ICS, with 11 (61%) failures in both arms (P = 0.66). OS, with only 5 (26%) failures, was superior to maintaining usual ICS with 12 (63%) failures (P = 0.04), and to doubling ICS with 5 (28%) versus 11 (61%) failures (P = 0.07). Median PEF (as percentage of run-in best) at end-points were 90.5% (57.1-177.1) for OS, 78.3% (39.5-103.1) for maintaining usual ICS and 77.9 (27.7-110.3) for doubling ICS. Neither gender nor PEF at exacerbation were predictive of failure. Although doubling ICS was not an effective therapy overall, ICS dose at exacerbation were predictive of success in the doubling ICS arm (P = 0.04). Treatment failures when doubling daily ICS dose were more common if achieved fluticasone dose was less than 2000 mu g (three of 11, 73%) compared to 2000 mu g or greater (eight of eight, 37.5%). Increasing age and the presence of an upper respiratory tract infection (URTI) were predictive of failure with OS. Side-effects were more commonly reported with OS (52.6%) than doubling ICS (42.1%) or maintaining usual ICS (19.1%) with the most common being mood changes (36.8%), sleep disturbance (31.6%) and changes in appetite (26.3%). Conclusions: Doubling daily ICS dose per se is not effective for the treatment of mild to moderately severe exacerbations of asthma in adults. Success may depend on achieved ICS dose. Oral steroids are effective, but side-effects are common. A review of current guidelines may be warranted.

Off-line signature verification and forgery detection using fuzzy modeling

Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Formal verification of type flaw attacks in security protocols

Security protocols are often modelled at a high level of abstraction, potentially overlooking implementation-dependent vulnerabilities. Here we use the Z specification language's rich set of data structures to formally model potentially ambiguous messages that may be exploited in a 'type flaw' attack. We then show how to formally verify whether or not such an attack is actually possible in a particular protocol using Z's schema calculus.

Off-line signature verification and forgery detection system based on fuzzy modeling

This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.