Dynamics of spiral waves in a cardiac electromechanical model with a local electrical inhomogeneity

Joint effect of electrical heterogeneity (e.g. induced by ischemia) and mechanical deformation is investigated for an anisotropic, quasi–incompressible model of cardiac electromechanical coupling (EMC) using the active strain approach and periodic boundary conditions. Three local inhomogeneities with different geometry are simulated. Under a specific stimulation protocol, the heterogeneities are able to induce spirals. The interplay between the dimension of the electrical inhomogeneity, the EMC and the mechano-electrical feedback provided by the stretch activated current (SAC) determines the dynamics of the spiral waves of excitation, which could extinguish (in the case of low SAC), or be stable (with the tip rotating inside the inhomogeneity), or drift and be annihilated (in the case of high SAC).     

Static and dynamic headspace analysis of instant coffee blends by proton‐transfer‐reaction mass spectrometry

Instant coffee is a widespread product, generally related to a high consumer acceptability, also because of its ease of preparation. The present work addresses the characterization of the headspace of freshly brewed instant coffees resulting from different blends, during and immediately after preparation. The sample set consisted of 10 coffees, obtained by mixing three different blends in different proportions. The employment of Proton Transfer Reaction‐Mass Spectrometry (PTR‐MS) allowed for direct and real‐time sampling from the headspace, under conditions that mimic those that are encountered above the cup during and right after brewing. Different coffee brews were separated on the basis of the respective volatile profiles, and data showed good consistency with the respective blend compositions. When the headspace evolution was monitored during preparation, similar results were obtained in terms of blend separation; moreover, different blends displayed different and reproducible ‘signatures’ in terms of time evolution. A straightforward method for the prediction of headspace composition is proposed, allowing to predict the volatile profiles of two‐component and three‐component blends on the basis of the respective parent components. Overall, the results constitute a successful example of the applicability of PTR‐MS as a tool for product development in food science. Copyright © 2015 John Wiley & Sons, Ltd.