Haemodynamic variables and functional outcome in hypothermic patients following out-of-hospital cardiac arrest

To evaluate the association between haemodynamic variables during the first 24h after intensive care unit (ICU) admission and neurological outcome in out-of-hospital cardiac arrest (OHCA) victims undergoing therapeutic hypothermia.

OUT-OF-STEP DETECTION BASED ON ZUBOV’S APPROXIMATION BOUNDARY METHOD

Disturbances in power systems may lead to electromagnetic transient oscillations due to mismatch of mechanical input power and electrical output power. Out-of-step conditions in power system are common after the disturbances where the continuous oscillations do not damp out and the system becomes unstable. Existing out-of-step detection methods are system specific as extensive off-line studies are required for setting of relays. Most of the existing algorithms also require network reduction techniques to apply in multi-machine power systems. To overcome these issues, this research applies Phasor Measurement Unit (PMU) data and Zubov’s approximation stability boundary method, which is a modification of Lyapunov’s direct method, to develop a novel out-of-step detection algorithm. The proposed out-of-step detection algorithm is tested in a Single Machine Infinite Bus system, IEEE 3-machine 9-bus, and IEEE 10-machine 39-bus systems. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques and a comparative study with an existing blinder method demonstrate that the decision times are faster. The simulation case studies also demonstrate that the proposed algorithm does not depend on power system parameters, hence it avoids the need of extensive off-line system studies as needed in other algorithms.

The Effects of Living in Segregated vs. Mixed Areas in Northern Ireland: A Simultaneous Analysis of Contact and Threat Effects in the Context of Micro-Level Neighbourhoods

This study examines the consequences of living in segregated and mixed neighbourhoods on ingroup bias and offensive action tendencies, taking into consideration the role of intergroup experiences and perceived threat. Using adult data from a cross-sectional survey in Belfast, Northern Ireland, we tested a model that examined the relationship between living in segregated (N = 396) and mixed (N = 562) neighbourhoods and positive contact, exposure to violence, perceived threat and outgroup orientations. Our results show that living in mixed neighbourhoods was associated with lower ingroup bias and reduced offensive action tendencies. These effects were partially mediated by positive contact. However, our analysis also shows that respondents living in mixed neighbourhoods report higher exposure to political violence and higher perceived threat to physical safety. These findings demonstrate the importance of examining both social experience and threat perceptions when testing the relationship between social environment and prejudice.