Linköping University

About: Linköping University is a education organization based out in Linköping, Sweden. It is known for research contribution in the topics: Population & Thin film. The organization has 15671 authors who have published 50013 publications receiving 1542189 citations.

Context matters in implementation science: a scoping review of determinant frameworks that describe contextual determinants for implementation outcomes

Abstract: The relevance of context in implementation science is reflected in the numerous theories, frameworks, models and taxonomies that have been proposed to analyse determinants of implementation (in this paper referred to as determinant frameworks). This scoping review aimed to investigate and map how determinant frameworks used in implementation science were developed, what terms are used for contextual determinants for implementation, how the context is conceptualized, and which context dimensions that can be discerned. A scoping review was conducted. MEDLINE and EMBASE were searched from inception to October 2017, and supplemented with implementation science text books and known published overviews. Publications in English that described a determinant framework (theory, model, taxonomy or checklist), of which context was one determinant, were eligible. Screening and inclusion were done in duplicate. Extracted data were analysed to address the study aims. A qualitative content analysis with an inductive approach was carried out concerning the development and core context dimensions of the frameworks. The review is reported according to the PRISMA guidelines. The database searches yielded a total of 1113 publications, of which 67 were considered potentially relevant based on the predetermined eligibility criteria, and retrieved in full text. Seventeen unique determinant frameworks were identified and included. Most were developed based on the literature and/or the developers’ implementation experiences. Six of the frameworks explicitly referred to “context”, but only four frameworks provided a specific definition of the concept. Instead, context was defined indirectly by description of various categories and sub-categories that together made up the context. Twelve context dimensions were identified, pertaining to different aggregation levels. The most widely addressed context dimensions were organizational support, financial resources, social relations and support, and leadership. The findings suggest variation with regard to how the frameworks were developed and considerable inconsistency in terms used for contextual determinants, how context is conceptualized, and which contextual determinants are accounted for in frameworks used in implementation science. Common context dimensions were identified, which can facilitate research that incorporates a theory of context, i.e. assumptions about how different dimensions may influence each other and affect implementation outcomes. A thoughtful application of the concept and a more consistent terminology would enhance transparency, simplify communication among researchers, and facilitate comparison across studies.

Some Relations Between Extended and Unscented Kalman Filters

Abstract: The unscented Kalman filter (UKF) has become a popular alternative to the extended Kalman filter (EKF) during the last decade. UKF propagates the so called sigma points by function evaluations using the unscented transformation (UT), and this is at first glance very different from the standard EKF algorithm which is based on a linearized model. The claimed advantages with UKF are that it propagates the first two moments of the posterior distribution and that it does not require gradients of the system model. We point out several less known links between EKF and UKF in terms of two conceptually different implementations of the Kalman filter: the standard one based on the discrete Riccati equation, and one based on a formula on conditional expectations that does not involve an explicit Riccati equation. First, it is shown that the sigma point function evaluations can be used in the classical EKF rather than an explicitly linearized model. Second, a less cited version of the EKF based on a second-order Taylor expansion is shown to be quite closely related to UKF. The different algorithms and results are illustrated with examples inspired by core observation models in target tracking and sensor network applications.

Modeling Molecular Interactions in Water: From Pairwise to Many-Body Potential Energy Functions.

Abstract: Almost 50 years have passed from the first computer simulations of water, and a large number of molecular models have been proposed since then to elucidate the unique behavior of water across different phases. In this article, we review the recent progress in the development of analytical potential energy functions that aim at correctly representing many-body effects. Starting from the many-body expansion of the interaction energy, specific focus is on different classes of potential energy functions built upon a hierarchy of approximations and on their ability to accurately reproduce reference data obtained from state-of-the-art electronic structure calculations and experimental measurements. We show that most recent potential energy functions, which include explicit short-range representations of two-body and three-body effects along with a physically correct description of many-body effects at all distances, predict the properties of water from the gas to the condensed phase with unprecedented accuracy,...