An experience of attempting to apply the randomised controlled trial (RCT) design in a ‘real world’ community-based clinical setting – one family therapist’s current journey. Context, 99, 6-9.

This paper describes an early career researcher's expereince of using randomised controlled trial methodology to investigarte the effectiveness of psychotherapeutic interventions for traumatised families in a 'real world' setting.

Effect of signal intensity normalization on the multivariate analysis of spectral data in complex 'real-world' datasets

Spectral signal intensities, especially in 'real-world' applications with nonstandardized sample presentation due to uncontrolled variables/factors, commonly require additional spectral processing to normalize signal intensity in an effective way. In this study, we have demonstrated the complexity of choosing a normalization routine in the presence of multiple spectrally distinct constituents by probing a dataset of Raman spectra. Variation in absolute signal intensity (90.1% of total variance) of the Raman spectra of these complex biological samples swamps the variation in useful signals (9.4% of total variance), degrading its diagnostic and evaluative potential.

Tools for Finding Inconsistencies in Real-world Logic-based Systems

Currently there is extensive theoretical work on inconsistencies in logic-based systems. Recently, algorithms for identifying inconsistent clauses in a single conjunctive formula have demonstrated that practical application of this work is possible. However, these algorithms have not been extended for full knowledge base systems and have not been applied to real-world knowledge. To address these issues, we propose a new algorithm for finding the inconsistencies in a knowledge base using existing algorithms for finding inconsistent clauses in a formula. An implementation of this algorithm is then presented as an automated tool for finding inconsistencies in a knowledge base and measuring the inconsistency of formulae. Finally, we look at a case study of a network security rule set for exploit detection (QRadar) and suggest how these automated tools can be applied.

Energy compensation in the real world: Good compensation for small portions of chocolate and biscuits over short time periods in complicit consumers using commercially available foods

While investigations using covert food manipulations tend to suggest that individuals are poor at adjusting for previous energy intake, in the real world adults rarely consume foods of which they are ill-informed. This study investigated the impact in fully complicit consumers of consuming commercially available dark chocolate, milk chocolate, sweet biscuits and fruit bars on subsequent appetite. Using a repeated measures design, participants received four small portions (4 × 10-11 g) of either dark chocolate, milk chocolate, sweet biscuits, fruit bars or no food throughout five separate study days (counterbalanced in order), and test meal intake, hunger, liking and acceptability were measured. Participants consumed significantly less at lunch following dark chocolate, milk chocolate and sweet biscuits compared to no food (smallest t(19) = 2.47, p = 0.02), demonstrating very good energy compensation (269-334%). No effects were found for fruit bars (t(19) = 1.76, p = 0.09), in evening meal intakes (F(4,72) = 0.62, p = 0.65) or in total intake (lunch + evening meal + food portions) (F(4,72) = 0.40, p = 0.69). No differences between conditions were found in measures of hunger (largest F(4,76) = 1.26, p = 0.29), but fruit bars were significantly less familiar than all other foods (smallest t(19) = 3.14, p = 0.01). These findings demonstrate good compensation over the short term for small portions of familiar foods in complicit consumers. Findings are most plausibly explained as a result of participant awareness and cognitions, although the nature of these cognitions cannot be discerned from this study. These findings however, also suggest that covert manipulations may have limited transfer to real world scenarios.

Multi-bubble sonoluminescence: Laboratory curiosity, or real world application?

Sonoluminescence (SL) involves the conversion of mechanical [ultra]sound energy into light. Whilst the phenomenon is invariably inefficient, typically converting just 10^-4 of the incident acoustic energy into photons, it is nonetheless extraordinary, as the resultant energy density of the emergent photons exceeds that of the ultrasonic driving field by a factor of some 10 ¹². Sonoluminescence has specific [as yet untapped] advantages in that it can be effected at remote locations in an essentially wireless format. The only [usual] requirement is energy transduction via the violent oscillation of microscopic bubbles within the propagating medium. The dependence of sonoluminescent output on the generating sound field's parameters, such as pulse duration, duty cycle, and position within the field, have been observed and measured previously, and several relevant aspects are discussed presently. We also extrapolate the logic from a recently published analysis relating to the ensuing dynamics of bubble 'clouds' that have been stimulated by ultrasound. Here, the intention was to develop a relevant [yet computationally simplistic] model that captured the essential physical qualities expected from real sonoluminescent microbubble clouds. We focused on the inferred temporal characteristics of SL light output from a population of such bubbles, subjected to intermediate [0.5-2MPa] ultrasonic pressures. Finally, whilst direct applications for sonoluminescent light output are thought unlikely in the main, we proceed to frame the state-of-the- art against several presently existing technologies that could form adjunct approaches with distinct potential for enhancing present sonoluminescent light output that may prove useful in real world [biomedical] applications.