In the past few years, the presence of fragmentation in the QRS complex has been demonstrated to be related to diseases such as myocardial fibrosis, cardiac sarcoidosis, arrythmogenic cardiopathies, acute coronary syndrome, and Brugada syndrome, among others.
In recent years, interest has been paid to the identification of the arrhythmia anatomical origin in ventricular tachycardia from available information in the patient, including ECG morphology and electrograms stored in implantable devices.
Physiological rhythms arise from nonlinear interactions between biological mechanisms and environmental conditions. A possible approach to study these dynamics is by means of simplified mathematical models. An essential aspect of these models is how to determine the statistical significance of the rhythms present in a temporal series.
Client knowledge remains a key strategic point in hospitality management. However, the role that can be played by large amounts of available information in the Customer Relationship Management (CRM) systems, when addressed by using emerging Big Data techniques for efficient client profiling, is still in its early stages.
The rapid development of the cloud computing technology is favoring the emergence of new platforms offering a new broad range of possibilities for data analytics. An example of this is SCOOP, a scientific cloud computing platform designed to massively collect data from Implantable Cardioverter Defibrillators (ICDs) generating cooperatively new knowledge in the cardiac electrophysiology field.
Fault activation caused by construction, earthquakes, or mining can produce disastrous water-inrush episodes in underground mines. Fault activation is generally caused by stress concentration at the fault tip, so in this study, a computational model of a typical underground stope with a hidden fault was established for quantitatively assessing the magnitude of the stress concentration of the stress fields of the fault-tip.