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

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

Impact of birth weight and gender on early postnatal hypothalamic energy balance regulatory gene expression in the young lamb

Peer reviewedPreprin

Measurement of Resonant Frequency and Quality Factor of Microwave Resonators: Comparison of Methods

Precise microwave measurements of sample conductivity, dielectric, and magnetic properties are routinely performed with cavity perturbation measurements. These methods require the accurate determination of quality factor and resonant frequency of microwave resonators. Seven different methods to determine the resonant frequency and quality factor from complex transmission coefficient data are discussed and compared to find which is most accurate and precise when tested using identical data. We find that the nonlinear least-squares fit to the phase vs. frequency is the most accurate and precise when the signal-to-noise ratio is greater than 65. For noisier data, the nonlinear least squares fit to a Lorentzian curve is more accurate and precise. The results are general and can be applied to the analysis of many kinds of resonant phenomena.Comment: 29 pages, 11 figure

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

Prevalence of HCV NS3 pre-treatment resistance associated amino acid variants within a Scottish cohort

Background: Protease inhibitors (PI) including boceprevir, telaprevir and simeprevir have revolutionised HCV genotype 1 treatment since their introduction. A number of pre-treatment resistance associated amino acid variants (RAVs) and polymorphisms have been associated with reduced response to treatment. Objectives: We measured the prevalence of RAVs/polymorphisms in a PI treatment-naïve HCV genotype 1 Scottish cohort using Sanger sequencing. Study design: Chronically infected, treatment-naïve, HCV genotype 1 patients (n = 146) attending NHS Greater Glasgow and Clyde clinics were investigated for RAVs/polymorphisms to the PIs boceprevir, telaprevir and simeprevir. The NS3/4A region was amplified by nested polymerase chain reaction. The 1.4 kb amplified product was sequenced using an ABI 3710XL DNA sequencer. Sequence analysis was performed using web-based ReCall (beta 2.10). Amino acid positions 36, 41, 43, 54, 55, 80, 109, 122, 155, 156, 168 and 170 were analysed for RAVs/polymorphisms. Results: Overall, 23.29% (34/146) of patients had an RAV or polymorphism detected. Overall, 13.69% (20/146) of patients had HCV virus that contained the Q8 K polymorphism. Other RAVs detected were: V36 M 0.70% (1/146), V36L 0.70% (1/146), T54S 6.85% (10/146), V55A 3.42% (5/146) and V/I170A 0.68% (1/146). Four patients had dual combinations of mutations (T54S + V36L; T54S + V55A and 2 patients with T54S + Q80K). Conclusions: Q80K was the most prevalent baseline polymorphism detected in the Scottish cohort. Simeprevir treatment is not recommended in patients infected with the Q80K genotype 1a variant. This highlights the need for baseline sequencing prior to administration of this drug in this population

Polarization of Thermal Emission from Aligned Dust Grains Under an Anisotropic Radiation Field

If aspherical dust grains are immersed in an anisotropic radiation field, their temperature depends on the cross-sections projected in the direction of the anisotropy.It was shown that the temperature difference produces polarized thermal emission even without alignment, if the observer looks at the grains from a direction different from the anisotropic radiation. When the dust grains are aligned, the anisotropy in the radiation makes various effects on the polarization of the thermal emission, depending on the relative angle between the anisotropy and alignment directions. If the both directions are parallel, the anisotropy produces a steep increase in the polarization degree at short wavelengths. If they are perpendicular, the polarization reversal occurs at a wavelength shorter than the emission peak. The effect of the anisotropic radiation will make a change of more than a few % in the polarization degree for short wavelengths and the effect must be taken into account in the interpretation of the polarization in the thermal emission. The anisotropy in the radiation field produces a strong spectral dependence of the polarization degree and position angle, which is not seen under isotropic radiation. The dependence changes with the grain shape to a detectable level and thus it will provide a new tool to investigate the shape of dust grains. This paper presents examples of numerical calculations of the effects and demonstrates the importance of anisotropic radiation field on the polarized thermal emission.Comment: 13pages, 7figure

No evidence for killer sperm or other selective interactions between human spermatozoa in ejaculates of different males in vitro

This study examines one of the possible mechanisms of sperm competition, i.e. the kamikaze sperm hypothesis. This hypothesis states that sperm from different males interact to incapacitate each other in a variety of ways. We used ejaculates from human donors to compare mixes of semen in vitro from the same or different males. We measured the following parameters: (i) the degree of sperm aggregation, velocity and proportion of morphologically normal sperm after 1 and 3 h incubation in undiluted semen samples, (ii) the proportion of viable sperm plus the same parameters as in (i) in 'swim-up' sperm suspensions after 1 and 3 h incubation, (iii) the degree of self and non-self sperm aggregation using fluorescent dyes to distinguish the sperm of different males, and (iv) the extent of sperm capacitation and acrosome-reacted sperm in mixtures of sperm from the same and different males. We observed very few significant changes in sperm aggregation or performance in mixtures of sperm from different males compared with mixtures from the same male and none that were consistent with previously reported findings. The incapacitation of rival sperm therefore seems an unlikely mechanism of sperm competition in humans

Control theory for principled heap sizing

We propose a new, principled approach to adaptive heap sizing based on control theory. We review current state-of-the-art heap sizing mechanisms, as deployed in Jikes RVM and HotSpot. We then formulate heap sizing as a control problem, apply and tune a standard controller algorithm, and evaluate its performance on a set of well-known benchmarks. We find our controller adapts the heap size more responsively than existing mechanisms. This responsiveness allows tighter virtual machine memory footprints while preserving target application throughput, which is ideal for both embedded and utility computing domains. In short, we argue that formal, systematic approaches to memory management should be replacing ad-hoc heuristics as the discipline matures. Control-theoretic heap sizing is one such systematic approach