Correlation between polysomnographic parameters and volumetric changes generated by maxillomandibular advancement surgery in patients with obstructive sleep apnea: a fluid dynamics study.

Study Objectives: Maxillomandibular advancement surgery (MMA) is a therapeutic option for obstructive sleep apnea (OSA). The main objective of this study was to determine the impact of MMA on the physical and airflow characteristics of the upper airway based on data obtained by computational fluid dynamics (CFD) and to correlate these data with polysomnography parameters. Other objectives included the identification of presurgical variables that could help avoid surgeries likely to have a low success rate.

Effect of sterilization processes on alginate/gelatin inks for three-dimensional printing.

309Sterilization is a crucial step in the process of developing bioinks for tissue engineering applications. In this work, alginate/gelatin inks were subjected to three sterilization methods: ultraviolet (UV) radiation, filtration (FILT), and autoclaving (AUTO). In addition, to simulate the sterilization effect in a real environment, inks were formulated in two different media, specifically, Dulbecco's Modified Eagle's Medium (DMEM) and phosphate-buffered saline (PBS).

Overcoming inter-observer planning variability in target volume contouring and dose planning for high-risk neuroblastoma - a European multicenter effort of the SIOPEN radiotherapy committee.

Background And Purpose: To establish an international quality standard for contouring and planning for high-risk neuroblastoma within the prospective High-Risk Neuroblastoma Study 2 of SIOP-Europe-Neuroblastoma (SIOPEN HR-NBL2), which includes a randomized question on dose escalation for residual disease.

Materials And Methods: Data on four patients with high-risk neuroblastoma were selected and distributed to the radiotherapy committee of the HR-NBL2 study for independent contouring and planning. Differences in contouring were analyzed using apparent and kappa-corrected agreement.

Team Emotional Intelligence: Emotional Processes as a Link Between Managers and Workers.

Research has shown that transformational leaders are able, through emotional contagion mechanisms, to transmit their emotions and boost positive feelings among their followers. Although research on leadership and team processes have shown a positive relation between transformational leadership and workers' well-being, there is a lack of studies examining the "black box" of this association. The present study aimed to assess the mediation effect of team emotional intelligence (TEI) of the management team on the relationship between management's transformational behaviors and employees' responses.

Team Emotional Intelligence in Working Contexts: Development and Validation of the Team-Trait Meta Mood Scale (T-TMMS).

The collective construct of Team Emotional Intelligence (TEI) has been widely used and discussed. However, although several studies have examined the relationship between individual emotional intelligence and transformational leadership, few reports have explored the TEI of leadership teams. The aim of this study was to develop a scale to measure TEI, developing and validating the T-TMMS in a sample of 1,746 participants grouped into 152 leadership teams.

Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.

Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for VF-detection are customarily assessed using Holter recordings from public electrocardiogram (ECG) databases, which may be different from the ECG seen during OHCA events. This study evaluates VF-detection using data from both OHCA patients and public Holter recordings.

User behavior shift detection in ambient assisted living environments.

Identifying users' frequent behaviors is considered a key step to achieving real, intelligent environments that support people in their daily lives. These patterns can be used in many different applications. An algorithm that compares current behaviors of users with previously discovered frequent behaviors has been developed.