Individuals with ER display an increased TDR that may be related to an increased arrhythmic risk.

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Background and objective: Medical thoracoscopy (MT) is useful for the management of pleural disease. Rapid on-site evaluation (ROSE) of transbronchial needle aspirates proved to be useful during bronchoscopy. We aimed to evaluate the diagnostic performance of ROSE of MT biopsy specimens and thoracoscopists' impression of the macroscopic appearance and assess the intermodality agreement between ROSE and final histopathologic diagnosis. Methods: Sixty two patients with exudative pleural effusions further investigated with MT were enrolled. MT was performed under local anaesthesia and conscious sedation, using the rigid pleuroscope. ROSE with the Hemacolor rapid staining method of the biopsy specimens was performed. Thoracoscopists' impression of the macroscopic appearance was recorded. The final diagnosis was established following histopathological examination. Results: Thoracoscopic pleural biopsies were diagnosed in 61 patients (98.4%). Group A (n = 25) consisted of patients with malignancy and group B (n = 37) with benign disorders. Area under the curve of ROSE for the diagnosis of malignancy was 0.86 (95% CI: 0.76-0.96, P < 0.001), with a sensitivity of 79.17%, specificity of 94.59%, diagnostic accuracy of 88.5%, positive predictive value of 90.5% and negative predictive value of 87.5%. Intermodality agreement between ROSE and histopathology was good (κ ± SE = 0.615 ± 0.084, P < 0.001). Area under the curve of the thoracoscopists' impression of macroscopic appearance was 0.72 (95% CI: 0.58-0.85, P = 0.001), with a sensitivity of 100%, specificity of 44.7%, positive predictive value of 53.33% and negative predictive value of 100%. Conclusion: Rapid on-site evaluation during MT was found to have high accuracy for predicting malignancy. ROSE can provide the thoracoscopist with an on-site

Peak shaving applications provided by energy storage systems enhance the utilization of existing grid infrastructure to accommodate the increased penetration of renewable energy sources. This work investigates the provision of peak shaving services from a flywheel energy storage system installed in a transformer substation. A lexicographic optimization scheme is formulated to define the flywheel power set-points by minimizing the transformer power limit violations and the flywheel energy losses. Convex functions that represent the flywheel power losses and its maximum power are derived and integrated in the proposed scheme. A two-level hierarchical control framework is introduced to operate the transformer-flywheel-system in a way that handles prediction errors and modelling inaccuracies. At the higher level, a model predictive controller is developed that solves the lexicographic optimization scheme using linear programming. At the lower-level, a secondary controller corrects the power set-points of the model predictive controller using realtime measurements. A software platform has been developed for integrating the proposed controllers in an experimental setup to test their effectiveness in a realistic testbed setting, and the flywheel system characteristics are experimentally identified. Simulation and experimental results validate and verify the modelling, identification, control and operation of a real flywheel system for peak shaving services.

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