Three main mechanisms contribute to global right ventricular (RV) function: longitudinal shortening, radial displacement of the RV free wall (bellows effect), and anteroposterior shortening (as a consequence of left ventricular contraction). Since the importance of these mechanisms may vary in different cardiac conditions, a technology being able to assess their relative influence on the global RV pump function could help to clarify the pathophysiology and the mechanical adaptation of the chamber. Previously, we have introduced our 3D echocardiography (3DE)-based solution—the Right VentrIcular Separate wall motIon quantificatiON (ReVISION) method—for the quantification of the relative contribution of the three aforementioned mechanisms to global RV ejection fraction (EF). Since then, our approach has been applied in several clinical scenarios, and its strengths have been demonstrated in the in-depth characterization of RV mechanical pattern and the prognostication of patients even in the face of maintained RV EF. Recently, various new features have been implemented in our software solution to enable the convenient, standardized, and more comprehensive analysis of RV function. Accordingly, in our current technical paper, we aim to provide a detailed description of the latest version of the ReVISION method with special regards to the volumetric partitioning of the RV and the calculation of longitudinal, circumferential, and area strains using 3DE datasets. We also report the results of the comparison between 3DE- and cardiac magnetic resonance imaging-derived RV parameters, where we found a robust agreement in our advanced 3D metrics between the two modalities. In conclusion, the ReVISION method may provide novel insights into global and also segmental RV function by defining parameters that are potentially more sensitive and predictive compared to conventional echocardiographic measurements in the context of different cardiac diseases.

Runaway electrons with strongly anisotropic distributions present in postdisruption tokamak plasmas can destabilize the extraordinary electron (EXEL) wave.The present work investigates the dynamics of the quasi-linear evolution of the EXEL instability for a range of different plasma parameters using a model runaway distribution function valid for highly relativistic runaway electron beams produced primarily by the avalanche process. Simulations show a rapid pitch-angle scattering of the runaway electrons in the high energy tail on the 100 − 1000 µs time scale. Due to the wave-particle interaction, a modification to the synchrotron radiation spectrum emitted by the runaway electron population is foreseen, exposing a possible experimental detection method for such an interaction.

No abstract

No abstract

Physical Internet based supply chains create open, global logistics systems that enable new types of collaboration among participants. The open system allows the logistical examination of vehicle technology innovations such as the platooning concept. This article explores the multiple platoon collaboration. For the reconfiguration of two platoons a heuristic and a reinforcement learning (RL) based models have been developed. To our knowledge, this work is the first attempt to apply an RL-based decision model to solve the problem of controlling platoon cooperation. Vehicle exchange between platoons is provided by a virtual hub. Depending on the various input parameters, the efficiency of the model was examined through numerical examples in terms of the target function based on the transportation cost. Models using platoon reconfiguration are also compared to the cases where no vehicle exchange is implemented. We have found that a reinforcement learning based model provides a more efficient solution for high incoming vehicle numbers and low dispatch interval, although for low vehicle numbers heuristics model performs better.