Homogenization of an ensemble of interacting resonant scatterers

We study theoretically the concept of homogenization in optics using an ensemble of randomly distributed resonant stationary atoms with density $\rho$. The ensemble is dense enough for the usual condition for homogenization, viz. $\rho\lambda^3 \gg 1$, to be reached. Introducing the coherent and incoherent scattered powers, we define two criteria to define the homogenization regime. We find that when the excitation field is tuned in a broad frequency range around the resonance, none of the criteria for homogenization is fulfilled, meaning that the condition $\rho\lambda^3\gg 1$ is not sufficient to characterize the homogenized regime around the atomic resonance. We interpret these results as a consequence of the light-induced dipole-dipole interactions between the atoms, which implies a description of scattering in terms of collective modes rather than as a sequence of individual scattering events. Finally, we show that, although homogenization can never be reached for a dense ensemble of randomly positioned laser-cooled atoms around resonance, it becomes possible if one introduces spatial correlations in the positions of the atoms or non-radiative losses, such as would be the case for organic molecules or quantum dots coupled to a phonon bath.Comment: 9 pages, 5 figures. Corrected mistakes in reference

The rworkflows suite: automated continuous integration for quality checking, documentation website creation, and containerised deployment of R packages

Reproducibility is essential to the progress of research, yet achieving it remains elusive even in computational fields. Continuous Integration (CI) platforms offer a powerful way to launch automated workflows to check and document code, but often require considerable time, effort, and technical expertise to setup. We therefore developed the rworkflows suite to make robust CI workflows easy and freely accessible to all R package developers (https://github.com/neurogenomics/rworkflows). rworkflows consists of 1) a CRAN/Bioconductor-compatible R package template, 2) an R package to quickly implement a standardised workflow, and 3) a centrally maintained GitHub Action. Each time it is triggered by a push to a GitHub repository, it automatically creates virtual machines across multiple OS, installs all dependencies, runs code checks, builds/deploys a documentation website, and builds/deploys version-controlled containers with a built-in RStudio interface. Additional analyses demonstrate that >50% of all R packages are only available via GitHub, highlighting the need for accessible solutions. Thus, rworkflows greatly reduces the barriers to implementing robust and reproducible best practices

Effectiveness of UK provider financial incentives on quality of care: a systematic review

Background: Provider financial incentives are being increasingly adopted to help improve standards of care while promoting efficiency. / Aim: To review the UK evidence on whether provider financial incentives are an effective way of improving the quality of health care. / Design and setting: Systematic review of UK evidence, undertaken in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. / Method: MEDLINE and Embase databases were searched in August 2016. Original articles that assessed the relationship between UK provider financial incentives and a quantitative measure of quality of health care were included. Studies showing improvement for all measures of quality of care were defined as ‘positive’, those that were ‘intermediate’ showed improvement in some measures, and those classified as ‘negative’ showed a worsening of measures. Studies showing no effect were documented as such. Quality was assessed using the Downs and Black quality checklist. / Results: Of the 232 published articles identified by the systematic search, 28 were included. Of these, nine reported positive effects of incentives on quality of care, 16 reported intermediate effects, two reported no effect, and one reported a negative effect. Quality assessment scores for included articles ranged from 15 to 19, out of a maximum of 22 points. / Conclusion: The effects of UK provider financial incentives on healthcare quality are unclear. Owing to this uncertainty and their significant costs, use of them may be counterproductive to their goal of improving healthcare quality and efficiency. UK policymakers should be cautious when implementing these incentives — if used, they should be subject to careful long-term monitoring and evaluation. Further research is needed to assess whether provider financial incentives represent a cost-effective intervention to improve the quality of care delivered in the UK

The Issues and Challenges of Assessing Media Literacy Education

In the media literacy literature, the challenges associated with assessment have, to a great extent, been ignored. The purpose of this mixed methods study was therefore to explore the views of media literacy scholars and professionals on assessment challenges through qualitative interviews (n = 10) with the intent of using this information to develop a quantitative survey to validate and extend the qualitative findings with a larger sample of media literacy professionals and scholars from around the world (n = 133). The findings offer an overview of the assessment challenges encountered by these participants

The Repressors of mTORC1 Signaling, REDD1 and REDD2, Are Induced in Immobilized Rat Skeletal Muscle

Please view abstract in the attached PDF file

EpiCompare: R package for the comparison and quality control of epigenomic peak files

Summary EpiCompare combines a variety of downstream analysis tools to compare, quality control and benchmark different epigenomic datasets. The package requires minimal input from users, can be run with just one line of code and provides all results of the analysis in a single interactive HTML report. EpiCompare thus enables downstream analysis of multiple epigenomic datasets in a simple, effective and user-friendly manner. Availability and Implementation EpiCompare is available on Bioconductor (≥ v3.15): https://bioconductor.org/packages/release/bioc/html/EpiCompare.html All source code is publically available via GitHub: https://github.com/neurogenomics/EpiCompare Documentation website https://neurogenomics.github.io/EpiCompare EpiCompare DockerHub repository: https://hub.docker.com/repository/docker/neurogenomicslab/epicompare Competing Interest Statement The authors have declared no competing interest