Characteristics of successful interventions to reduce turnover and increase retention of early career nurses: a systematic review

Background nurse shortages have been identified as central to workforce issues in healthcare systems globally and although interventions to increase the nursing workforce have been implemented, nurses leaving their roles, particularly in the first year after qualification, present a significant barrier to building the nurse workforce. Objective to evaluate the characteristics of successful interventions to promote retention and reduce turnover of early career nurses. Design this is a systematic review Data sources Online databases including Academic Search Complete, Medline, Health Policy reference Centre, EMBASE, Psychinfo, CINAHL and the Cochran Library were searched to identify relevant publications in English published between 2001 and April 2018. Studies included evaluated an intervention to increase retention or reduce turnover and used turnover or retention figures as a measure. Review methods The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Studies were quality-assessed using the Joanna Briggs Institute Critical Appraisal tools for Quasi Experimental and Randomised Controlled Trials. Retention/turnover data were used to guide the comparison between studies and appropriate measures of central tendency and dispersion were calculated and presented, based on the normality of the data. Results A total of 11, 656 papers were identified, of which 53 were eligible studies. A wide variety of interventions and components within those interventions were identified to improve nurse retention. Promising interventions appear to be either internship/residency programmes or orientation/transition to practice programmes, lasting between 27-52 weeks, with a teaching and preceptor and mentor component. Conclusions Methodological issues impacted on the extent to which conclusions could be drawn, even though a large number of studies were identified. Future research should focus on standardising the reporting of interventions and outcome measures used to evaluate these interventions and carrying out further research with rigorous methodology. Clinical practice areas are recommended to assess their current interventions against the identified criteria to guide development of their effectiveness. Evaluations of cost-effectiveness are considered an important next step to maximise return on investment

A rule-based kinetic model of RNA polymerase II C-terminal domain phosphorylation

The complexity ofmany RNA processing pathways is such that a conventional systemsmodelling approach is inadequate to represent all themolecular species involved. We demonstrate that rule-based modelling permits a detailed model of a complex RNA signalling pathway to be defined. Phosphorylation of the RNApolymerase II (RNAPII)C-terminal domain (CTD; a flexible tail-like extension of the largest subunit) couples pre-messenger RNA capping, splicing and 30 end maturation to transcriptional elongation and termination, and plays a central role in integrating these processes. The phosphorylation states of the serine residues of many heptapeptide repeats of the CTD alter along the coding region of genes as a function of distance from the promoter. From a mechanistic perspective, both the changes in phosphorylation and the location atwhich they take place on the genes are a function of the time spent byRNAPII in elongation as this interval provides the opportunity for the kinases and phosphatases to interactwith theCTD.On this basis,we synthesize the available data to create a kinetic model of the action of the known kinases and phosphatases to resolve the phosphorylation pathways and their kinetics.</p

Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network

Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled to the high resolution (HR) space using a single filter, commonly bicubic interpolation, before reconstruction. This means that the super-resolution (SR) operation is performed in HR space. We demonstrate that this is sub-optimal and adds computational complexity. In this paper, we present the first convolutional neural network (CNN) capable of real-time SR of 1080p videos on a single K2 GPU. To achieve this, we propose a novel CNN architecture where the feature maps are extracted in the LR space. In addition, we introduce an efficient sub-pixel convolution layer which learns an array of upscaling filters to upscale the final LR feature maps into the HR output. By doing so, we effectively replace the handcrafted bicubic filter in the SR pipeline with more complex upscaling filters specifically trained for each feature map, whilst also reducing the computational complexity of the overall SR operation. We evaluate the proposed approach using images and videos from publicly available datasets and show that it performs significantly better (+0.15dB on Images and +0.39dB on Videos) and is an order of magnitude faster than previous CNN-based methods

Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network

Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled to the high resolution (HR) space using a single filter, commonly bicubic interpolation, before reconstruction. This means that the super-resolution (SR) operation is performed in HR space. We demonstrate that this is sub-optimal and adds computational complexity. In this paper, we present the first convolutional neural network (CNN) capable of real-time SR of 1080p videos on a single K2 GPU. To achieve this, we propose a novel CNN architecture where the feature maps are extracted in the LR space. In addition, we introduce an efficient sub-pixel convolution layer which learns an array of upscaling filters to upscale the final LR feature maps into the HR output. By doing so, we effectively replace the handcrafted bicubic filter in the SR pipeline with more complex upscaling filters specifically trained for each feature map, whilst also reducing the computational complexity of the overall SR operation. We evaluate the proposed approach using images and videos from publicly available datasets and show that it performs significantly better (+0.15dB on Images and +0.39dB on Videos) and is an order of magnitude faster than previous CNN-based methods

Volatile hydrocarbons inhibit methanogenic crude oil degradation

Methanogenic degradation of crude oil in subsurface sediments occurs slowly, but without the need for exogenous electron acceptors, is sustained for long periods and has enormous economic and environmental consequences. Here we show that volatile hydrocarbons are inhibitory to methanogenic oil biodegradation by comparing degradation of an artificially weathered crude oil with volatile hydrocarbons removed, with the same oil that was not weathered. Volatile hydrocarbons (nC5-nC10, methylcyclohexane, benzene, toluene, and xylenes) were quantified in the headspace of microcosms. Aliphatic (n-alkanes nC12-nC34) and aromatic hydrocarbons (4-methylbiphenyl, 3-methylbiphenyl, 2-methylnaphthalene, 1-methylnaphthalene) were quantified in the total hydrocarbon fraction extracted from the microcosms. 16S rRNA genes from key microorganisms known to play an important role in methanogenic alkane degradation (Smithella and Methanomicrobiales) were quantified by quantitative PCR. Methane production from degradation of weathered oil in microcosms was rapid (1.1 ± 0.1 μmol CH4/g sediment/day) with stoichiometric yields consistent with degradation of heavier n-alkanes (nC12-nC34). For non-weathered oil, degradation rates in microcosms were significantly lower (0.4 ± 0.3 μmol CH4/g sediment/day). This indicated that volatile hydrocarbons present in the non-weathered oil inhibit, but do not completely halt, methanogenic alkane biodegradation. These findings are significant with respect to rates of biodegradation of crude oils with abundant volatile hydrocarbons in anoxic, sulphate-depleted subsurface environments, such as contaminated marine sediments which have been entrained below the sulfate-reduction zone, as well as crude oil biodegradation in petroleum reservoirs and contaminated aquifers

High Resolution Millimeter-Wave Mapping of Linearly Polarized Dust Emission: Magnetic Field Structure in Orion

We present 1.3 and 3.3 mm polarization maps of Orion-KL obtained with the BIMA array at approximately 4 arcsec resolution. Thermal emission from magnetically aligned dust grains produces the polarization. Along the Orion ``ridge'' the polarization position angle varies smoothly from about 10 degrees to 40 degrees, in agreement with previous lower resolution maps. In a small region south of the Orion ``hot core,'' however, the position angle changes by 90 degrees. This abrupt change in polarization direction is not necessarily the signpost of a twisted magnetic field. Rather, in this localized region processes other than the usual Davis-Greenstein mechanism might align the dust grains with their long axes parallel with the field, orthogonal to their normal orientation.Comment: AAS preprint:14 pages, 2 figures (3mm.eps and 1mm.eps); requires aaspp4.sty To be published in Astrophysical Journal Letter

The Inner Rings of Beta Pictoris

We present Keck images of the dust disk around Beta Pictoris at 17.9 microns that reveal new structure in its morphology. Within 1" (19 AU) of the star, the long axis of the dust emission is rotated by more than 10 degrees with respect to that of the overall disk. This angular offset is more pronounced than the warp detected at 3.5" by HST, and in the opposite direction. By contrast, the long axis of the emission contours at ~ 1.5" from the star is aligned with the HST warp. Emission peaks between 1.5" and 4" from the star hint at the presence of rings similar to those observed in the outer disk at ~ 25" with HST/STIS. A deconvolved image strongly suggests that the newly detected features arise from a system of four non-coplanar rings. Bayesian estimates based on the primary image lead to ring radii of 14+/-1 AU, 28+/-3 AU, 52+/-2 AU and 82+/-2 AU, with orbital inclinations that alternate in orientation relative to the overall disk and decrease in magnitude with increasing radius. We believe these new results make a strong case for the existence of a nascent planetary system around Beta Pic.Comment: 5 pages, 2 figures, PDF format. Published in ApJL, December 20,200