Bounds on isocurvature perturbations from CMB and LSS data

We obtain very stringent bounds on the possible cold dark matter, baryon and neutrino isocurvature contributions to the primordial fluctuations in the Universe, using recent cosmic microwave background and large scale structure data. In particular, we include the measured temperature and polarization power spectra from WMAP and ACBAR, as well as the matter power spectrum from the 2dF galaxy redshift survey. Neglecting the possible effects of spatial curvature, tensor perturbations and reionization, we perform a Bayesian likelihood analysis with nine free parameters, and find that the amplitude of the isocurvature component cannot be larger than about 31% for the cold dark matter mode, 91% for the baryon mode, 76% for the neutrino density mode, and 60% for the neutrino velocity mode, at 2-sigma, for uncorrelated models. On the other hand, for correlated adiabatic and isocurvature components, the fraction could be slightly larger. However, the cross-correlation coefficient is strongly constrained, and maximally correlated/anticorrelated models are disfavored. This puts strong bounds on the curvaton model, independently of the bounds on non-Gaussianity.Comment: 4 pages, 1 figure, some minor corrections; version accepted in PR

Technical Note: Phantom study to evaluate the dose and image quality effects of a computed tomography Organ-based Tube Current Modulation Technique

Purpose This technical note quantifies the dose and image quality performance of a clinically available organ-dose-based tube current modulation (ODM) technique, using experimental and simulation phantom studies. The investigated ODM implementation reduces the tube current for the anterior source positions, without increasing current for posterior positions, although such an approach was also evaluated for comparison. Methods Axial CT scans at 120 kV were performed on head and chest phantoms on an ODM-equipped scanner (Optima CT660, GE Healthcare, Chalfont St. Giles, England). Dosimeters quantified dose to breast, lung, heart, spine, eye lens, and brain regions for ODM and 3D-modulation (SmartmA) settings. Monte Carlo simulations, validated with experimental data, were performed on 28 voxelized head phantoms and 10 chest phantoms to quantify organ dose and noise standard deviation. The dose and noise effects of increasing the posterior tube current were also investigated. Results ODM reduced the dose for all experimental dosimeters with respect to SmartmA, with average dose reductions across dosimeters of 31% (breast), 21% (lung), 24% (heart), 6% (spine), 19% (eye lens), and 11% (brain), with similar results for the simulation validation study. In the phantom library study, the average dose reduction across all phantoms was 34% (breast), 20% (lung), 8% (spine), 20% (eye lens), and 8% (brain). ODM increased the noise standard deviation in reconstructed images by 6%–20%, with generally greater noise increases in anterior regions. Increasing the posterior tube current provided similar dose reduction as ODM for breast and eye lens, increased dose to the spine, with noise effects ranging from 2% noise reduction to 16% noise increase. At noise equal to SmartmA, ODM increased the estimated effective dose by 4% and 8% for chest and head scans, respectively. Increasing the posterior tube current further increased the effective dose by 15% (chest) and 18% (head) relative to SmartmA. Conclusions ODM reduced dose in all experimental and simulation studies over a range of phantoms, while increasing noise. The results suggest a net dose/noise benefit for breast and eye lens for all studied phantoms, negligible lung dose effects for two phantoms, increased lung dose and/or noise for eight phantoms, and increased dose and/or noise for brain and spine for all studied phantoms compared to the reference protocol

Application of Fractal Dimension for Quantifying Noise Texture in Computed Tomography Images

Purpose Evaluation of noise texture information in CT images is important for assessing image quality. Noise texture is often quantified by the noise power spectrum (NPS), which requires numerous image realizations to estimate. This study evaluated fractal dimension for quantifying noise texture as a scalar metric that can potentially be estimated using one image realization. Methods The American College of Radiology CT accreditation phantom (ACR) was scanned on a clinical scanner (Discovery CT750, GE Healthcare) at 120 kV and 25 and 90 mAs. Images were reconstructed using filtered back projection (FBP/ASIR 0%) with varying reconstruction kernels: Soft, Standard, Detail, Chest, Lung, Bone, and Edge. For each kernel, images were also reconstructed using ASIR 50% and ASIR 100% iterative reconstruction (IR) methods. Fractal dimension was estimated using the differential box‐counting algorithm applied to images of the uniform section of ACR phantom. The two‐dimensional Noise Power Spectrum (NPS) and one‐dimensional‐radially averaged NPS were estimated using established techniques. By changing the radiation dose, the effect of noise magnitude on fractal dimension was evaluated. The Spearman correlation between the fractal dimension and the frequency of the NPS peak was calculated. The number of images required to reliably estimate fractal dimension was determined and compared to the number of images required to estimate the NPS‐peak frequency. The effect of Region of Interest (ROI) size on fractal dimension estimation was evaluated. Feasibility of estimating fractal dimension in an anthropomorphic phantom and clinical image was also investigated, with the resulting fractal dimension compared to that estimated within the uniform section of the ACR phantom. Results Fractal dimension was strongly correlated with the frequency of the peak of the radially averaged NPS curve, having a Spearman rank‐order coefficient of 0.98 (P‐value \u3c 0.01) for ASIR 0%. The mean fractal dimension at ASIR 0% was 2.49 (Soft), 2.51 (Standard), 2.52 (Detail), 2.57 (Chest), 2.61 (Lung), 2.66 (Bone), and 2.7 (Edge). A reduction in fractal dimension was observed with increasing ASIR levels for all investigated reconstruction kernels. Fractal dimension was found to be independent of noise magnitude. Fractal dimension was successfully estimated from four ROIs of size 64 × 64 pixels or one ROI of 128 × 128 pixels. Fractal dimension was found to be sensitive to non‐noise structures in the image, such as ring artifacts and anatomical structure. Fractal dimension estimated within a uniform region of an anthropomorphic phantom and clinical head image matched that estimated within the ACR phantom for filtered back projection reconstruction. Conclusions Fractal dimension correlated with the NPS‐peak frequency and was independent of noise magnitude, suggesting that the scalar metric of fractal dimension can be used to quantify the change in noise texture across reconstruction approaches. Results demonstrated that fractal dimension can be estimated from four, 64 × 64‐pixel ROIs or one 128 × 128 ROI within a head CT image, which may make it amenable for quantifying noise texture within clinical images

Why do medical graduates choose rural careers?

Introduction: This study is based on the metaphor of the &lsquo;rural pipeline&rsquo; into medical practice. The four stages of the ruralpipeline are: (1) contact between rural secondary schools and the medical profession; (2) selection of rural students into medicalprograms; (3) rural exposure during medical training; and (4) measures to address retention of the rural medical workforce.Methods: Using the rural pipeline template we conducted a literature review, analysed the selection methods of Australiangraduate entry medical schools and interviewed 17 interns about their medical career aspirations.Results: Literature review: The literature was reviewed to assess the effectiveness of selection practices to predict successfulgradation and the impact of rural pipeline components on eventual rural practice. Undergraduate academic performance is thestrongest predictor of medical course academic performance. The predictive power of interviews is modest. There are limited dataon the predictive power of other measures of non-cognitive performance or the content of the undergraduate degree. Prior ruralresidence is the strongest predictor of choice of a rural career but extended rural exposure during medical training also has asignificant impact. The most significant influencing factors are: professional support at national, state and local levels; careerpathway opportunities; contentedness of the practitioner&rsquo;s spouse in rural communities; preparedness to adopt a rural lifestyle;educational opportunities for children; and proximity to extended family and social circle. Analysis of selection methods: Staffinvolved in student selection into 9 Australian graduate entry medical schools were interviewed. Four themes were identified:(1) rurality as a factor in student selection; (2) rurality as a factor in student selection interviews; (3) rural representation on studentselection interview panels; (4) rural experience during the medical course. Interns&rsquo; career intentions: Three themes were identified:(1) the efficacy of the rural pipeline; (2) community connectedness through the rural pipeline; (3) impediments to the effect of therural pipeline, the most significant being a partner who was not committed to rural lifeConclusion: Based on the literature review and interviews, 11 strategies are suggested to increase the number of graduateschoosing a career in rural medicine, and one strategy for maintaining practitioners in rural health settings after graduation.</div

Characterization of grain boundaries in silicon

Zero-bias conductance and capacitance measurements at various temperatures were used to study trapped charges and potential barrier height at the boundaries. Deep-level transient spectroscopy (DLTS) was applied to measure the density of states at the boundary. A study of photoconductivity of grain boundaries in p-type silicon demonstrated the applicability of the technique in the measurement of minority carrier recombination velocity at the grain boundary. Enhanced diffusion of phosphorus at grain boundaries in three cast polycrystalline photovoltaic materials was studied. Enhancements for the three were the same, indicating that the properties of boundaries are similar, although grown by different techniques. Grain boundaries capable of enhancing the diffusion were found always to have strong recombination activities; the phenomena could be related to dangling bonds at the boundaries. Evidence that incoherent second-order twins of (111)/(115) type are diffusion-active is presented

Optimization of the leak conductance in the squid giant axon

We report on a theoretical study showing that the leak conductance density, \GL, in the squid giant axon appears to be optimal for the action potential firing frequency. More precisely, the standard assumption that the leak current is composed of chloride ions leads to the result that the experimental value for \GL is very close to the optimal value in the Hodgkin-Huxley model which minimizes the absolute refractory period of the action potential, thereby maximizing the maximum firing frequency under stimulation by sharp, brief input current spikes to one end of the axon. The measured value of \GL also appears to be close to optimal for the frequency of repetitive firing caused by a constant current input to one end of the axon, especially when temperature variations are taken into account. If, by contrast, the leak current is assumed to be composed of separate voltage-independent sodium and potassium currents, then these optimizations are not observed.Comment: 9 pages; 9 figures; accepted for publication in Physical Review

Corporate social responsibility in the Russian federation: A contextualized approach

Corporate social responsibility (CSR) has emerged as a concept for business from within developed, Western economies. Such economies are underpinned by functioning institutions, where compliance with regulation is assumed. Recently, however, the ability of this traditional understanding of CSR to take account of the different economic and institutional arrangements found in non-Western contexts has been challenged. It has been argued that CSR research needs to be more contextualized and that the Western interpretation and assumptions about what CSR is and how it is enacted needs to be broadened and challenged to take account of different stages of economic development. With this argument in mind, this article presents a contextualized critique of CSR undertaken in the Russian Federation. Based on a qualitative study involving managers within privatized Russian firms, this article explores the type, nature, and scope of CSR undertaken and attendant motivation of firms to engage in CSR practice. By taking account of the historical and cultural antecedents of both the Soviet Union and the post-Soviet transition period, the author reveals that while the market is driving conventional forms of CSR within some Russian firms, the historical legacy of both the Soviet Union and more recent political developments have a stronger influence on the type and nature of CSR undertaken. These findings challenge the assumptions about both the voluntary nature of CSR and the prerequisites needed for CSR to take place

VISUAL DETECTION OF RESPONSE TIME IN ATHLETICS: A “GOLD STANDARD”?

The response time (RT) in the sprint start in athletics is determined automatically from sensors on the blocks but the final decision on whether an athlete is disqualified is determined by visual inspection of the sensor data. This study explored the level of uncertainty of the visual detection of athletes’ RT in the sprint start. Fifteen sprinters performed six sprint starts while forces from the front block, rear block and hands were recorded. Two experimenters performed visual RT detection on two consecutive occasions using two sizes for the analysis window. Intra- and inter-reliability analysis indicated that the mean level of uncertainty of the visual detection was approximately 20 ms for the starting block data. More research is needed to formally assess the precision of the visual detection, which may result in changes in the current false start regulation

CT Automated Exposure Control Using A Generalized Detectability Index

Purpose Identifying an appropriate tube current setting can be challenging when using iterative reconstruction due to the varying relationship between spatial resolution, contrast, noise, and dose across different algorithms. This study developed and investigated the application of a generalized detectability index (d\u27gen) to determine the noise parameter to input to existing automated exposure control (AEC) systems to provide consistent image quality (IQ) across different reconstruction approaches. Methods This study proposes a task‐based automated exposure control (AEC) method using a generalized detectability index (d\u27gen). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d\u27gen metric is calculated using lookup tables of task‐based modulation transfer function (MTF) and noise power spectrum (NPS). To generate the lookup tables, the American College of Radiology CT accreditation phantom was scanned on a multidetector CT scanner (Revolution CT, GE Healthcare) at 120 kV and tube current varied manually from 20 to 240 mAs. Images were reconstructed using a reference reconstruction algorithm and four levels of an in‐house iterative reconstruction algorithm with different regularization strengths (IR1–IR4). The task‐based MTF and NPS were estimated from the measured images to create lookup tables of scaling factors that convert between d\u27gen and noise standard deviation. The performance of the proposed d\u27gen‐AEC method in providing a desired IQ level over a range of iterative reconstruction algorithms was evaluated using the American College of Radiology (ACR) phantom with elliptical shell and using a human reader evaluation on anthropomorphic phantom images. Results The study of the ACR phantom with elliptical shell demonstrated reasonable agreement between the d\u27gen predicted by the lookup table and d\u27 measured in the images, with a mean absolute error of 15% across all dose levels and maximum error of 45% at the lowest dose level with the elliptical shell. For the anthropomorphic phantom study, the mean reader scores for images resulting from the d\u27gen‐AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d\u27gen‐AEC method, the observers’ IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P \u3e 0.35). The d\u27gen‐AEC method achieved this equivalent IQ at lower dose for the IR scans compared to the reference scans. Conclusions A novel AEC method, based on a generalized detectability index, was investigated. The proposed method can be used with some existing AEC systems to derive the tube current profile for iterative reconstruction algorithms. The results provide preliminary evidence that the proposed d\u27gen‐AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels