Use of the Second Victim Experience and Support Tool (SVEST) to Assess the Impact of a Departmental Peer Support Program on Anesthesia Professionals' Second Victim Experiences (SVEs) and Perceptions of Support Two Years After Implementation.

Anesthesia professionals experience events resulting in psychological and physiologic implications, known as second victim experiences (SVEs). This study evaluated the impact of a peer support program on anesthesia providers' SVEs. In July 2018, a departmental peer support program was implemented.

A randomized clinical trial of high-dosage coenzyme Q10 in early Parkinson disease: no evidence of benefit.

Importance: Coenzyme Q10 (CoQ10), an antioxidant that supports mitochondrial function, has been shown in preclinical Parkinson disease (PD) models to reduce the loss of dopamine neurons, and was safe and well tolerated in early-phase human studies. A previous phase II study suggested possible clinical benefit.

Objective: To examine whether CoQ10 could slow disease progression in early PD.

Using previous models to bias structural learning in the hierarchical BOA.

Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promising candidate solutions. While the primary goal of applying EDAs is to discover the global optimum or at least its accurate approximation, besides this, any EDA provides us with a sequence of probabilistic models, which in most cases hold a great deal of information about the problem. Although using problem-specific knowledge has been shown to significantly improve performance of EDAs and other evolutionary algorithms, this readily available source of problem-specific information has been practically ignored by the EDA community.

Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT-IR and NIR spectral data.

Quantitative non-destructive analysis of individual constituents of historic rag paper is crucial for its effective preservation. In this work, we examine the potentials of mid- and near-infrared spectroscopy, however, in order to fully utilise the selectivity inherent to spectroscopic multivariate measurements, genetic algorithms were used to select spectral data derived from information-rich FT-IR or UV-vis-NIR measurements to build multivariate calibration models based on partial least squares regression, relating spectra to gelatine content in paper. A selective but laborious chromatographic method for the quantification of hydroxyproline (HYP) has been developed to provide the reference data on gelatine content.

Dependency structure matrix, genetic algorithms, and effective recombination.

Abstract In many different fields, researchers are often confronted by problems arising from complex systems. Simple heuristics or even enumeration works quite well on small and easy problems; however, to efficiently solve large and difficult problems, proper decomposition is the key. In this paper, investigating and analyzing interactions between components of complex systems shed some light on problem decomposition.