We examine the role of information-based measures in detecting and analysing phase transitions.
In the paper "Information and Phase Transitions in Socio-Economic Systems", the authors Terry Bossomaier, Lionel Barnett and Michael Harré present an interesting study on the role of information-based measures in detecting and analysing phase transitions.
A multifaceted study was conducted which manipulated various aspects of mental workload in order to study the utility of these two measures in detecting changes in load and their relationship to learning outcomes.
Indeed, it has been previously shown that a primary deficit in profiting from encoding cues at baseline and follow-up was superior to free recall and other traditional measures in detecting cognitive impairment [ 27].
Based on the results from the MMSE, our results suggest that the AQ may be superior to objective cognitive measures in detecting longitudinal change when compared on sample sizes required to detect a treatment effect.
Our data indicate that myocardial strain parameters are superior to LV ejection fraction and chamber diameter, intracardiac pressure, and relaxation measures in detecting the severity of heart failure as estimated by NYHA functional class.
