A Kinetic Database For Astrochemistry (KIDA)

We present a novel chemical database for gas-phase astrochemistry. Named the KInetic Database for Astrochemistry (KIDA), this database consists of gas-phase reactions with rate coefficients and uncertainties that will be vetted to the greatest extent possible. Submissions of measured and calculated rate coefficients are welcome, and will be studied by experts before inclusion into the database. Besides providing kinetic information for the interstellar medium, KIDA is planned to contain such data for planetary atmospheres and for circumstellar envelopes. Each year, a subset of the reactions in the database (kida.uva) will be provided as a network for the simulation of the chemistry of dense interstellar clouds with temperatures between 10 K and 300 K. We also provide a code, named Nahoon, to study the time-dependent gas-phase chemistry of zero-dimensional and one-dimensional interstellar sources

Cultural adaptation and validation of patient decision aids: a scoping review

Vanessa Chenel,1,2 W Ben Mortenson,3–5 Manon Guay,6,7 Jeffrey William Jutai,8,9 Claudine Auger1,2 1School of Rehabilitation, Faculty of Medicine, Université de Montréal, 2Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR) – Institut universitaire sur la réadaptation en déficience physique de Montréal, Centre intégré universitaire de santé et de services sociaux du Centre-Sud-de-l’Île-de-Montréal, Montreal, QC, 3Department of Occupational Science and Occupational Therapy, Faculty of Medicine, University of British Columbia, 4GF Strong Rehabilitation Centre, 5International Collaboration on Repair Discoveries, University of British Columbia, Vancouver Coastal Health Research Institute, Vancouver, BC, 6School of Rehabilitation, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 7Research Centre on Aging, Centre intégré universitaire de santé et de services sociaux de l’Estrie – Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, 8Interdisciplinary School of Health Sciences, University of Ottawa, 9Bruyère Research Institute, Ottawa, ON, Canada Abstract: In order to promote self-determination, patients have to be actively involved with their care providers in health-care decision making, especially when such decisions involve personal preferences. Decision aids (DAs) are tools that can contribute to patient-centered decision-making processes. To benefit from previous fieldwork and avoid duplicating developmental efforts and producing many similar DAs, the adaptation of existing DAs to new cultural contexts is a resource-saving option. However, there are no guidelines on how to culturally adapt and validate DAs. This study aimed to identify and document existing procedures for the cultural adaptation and validation of patient DAs. A scoping review examined studies conducting cultural adaptation and/or validation of patient DAs. The following databases were searched in February 2016: CINAHL, EMBASE, Medline (Ovid), PASCAL, PsychINFO, and PubMed. From the 13 studies selected, 11 main procedures were identified: appraisal of the original DA, assessment of the new cultural context, translation, linguistic adaptation, cultural adaptation, usability testing, exploration of DA acceptability, test-retest reliability, content validity, con­struct validity, and criterion validity. A conceptual synthesis of these studies suggests there are four phases in the adaptation/validation process of DAs aimed at: 1) exploring the original DA and the new cultural context, 2) adapting the original DA to the new cultural context, 3) lab testing the preliminary version of the adapted DA, and 4) field testing the adapted DA in a real use context. By facilitating the adaptation and broader implementation of DAs, patients may ultimately be empowered in decision-making processes. Keywords: decision making, decision support techniques, translation, cultural adaptation, validation studie

Evaluation of the pre-posterior distribution of optimized sampling times for the design of pharmacokinetic studies

Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic–pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples

Characterization of the MgO2+ dication in the gas phase: electronic states, spectroscopy and atmospheric implications

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