Morningness-eveningness orientation and attitude change:evidence for greater systematic processing and attitude change at optimal time-of-day

This study examines the relationship between morningness-eveningness orientation and time-of day on attitude change, and tests the hypothesis that people will be more persuaded when tested at their optimal time-of-day (i.e., morning for M-types and evening for E-types) than non-optimal time-of-day (i.e., evening for M-Types and morning for E-types). Two hundred and twenty participants read a message that contained either strong vs. weak quality counter-attitudinal arguments (anti-voluntary euthanasia) in the morning (9.00. a.m.) or in the evening (7.00. p.m.). When tested at their respective optimal time-of-day (for both M- and E-types) there was a reliable difference in attitude change between the strong vs. weak messages (indicating message processing had occurred) while there was no difference between strong vs. weak messages when tested at their non-optimal time-of-day. In addition, the amount of message-congruent thinking mediated the attitude change. The results show that M- and E-types pay greater attention to and elaborate on a persuasive message at their optimal time-of-day, and this leads to increased attitude change, compared to those tested at their non-optimal time-of-day. © 2012.

From the physics of interacting polymers to optimizing routes on the London Underground

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii ) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise.