A theoretical study of the quadratic Zeeman effect

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Some Aspects of Measurement Error in Linear Regression of Astronomical Data

I describe a Bayesian method to account for measurement errors in linear regression of astronomical data. The method allows for heteroscedastic and possibly correlated measurement errors, and intrinsic scatter in the regression relationship. The method is based on deriving a likelihood function for the measured data, and I focus on the case when the intrinsic distribution of the independent variables can be approximated using a mixture of Gaussians. I generalize the method to incorporate multiple independent variables, non-detections, and selection effects (e.g., Malmquist bias). A Gibbs sampler is described for simulating random draws from the probability distribution of the parameters, given the observed data. I use simulation to compare the method with other common estimators. The simulations illustrate that the Gaussian mixture model outperforms other common estimators and can effectively give constraints on the regression parameters, even when the measurement errors dominate the observed scatter, source detection fraction is low, or the intrinsic distribution of the independent variables is not a mixture of Gaussians. I conclude by using this method to fit the X-ray spectral slope as a function of Eddington ratio using a sample of 39 z < 0.8 radio-quiet quasars. I confirm the correlation seen by other authors between the radio-quiet quasar X-ray spectral slope and the Eddington ratio, where the X-ray spectral slope softens as the Eddington ratio increases.Comment: 39 pages, 11 figures, 1 table, accepted by ApJ. IDL routines (linmix_err.pro) for performing the Markov Chain Monte Carlo are available at the IDL astronomy user's library, http://idlastro.gsfc.nasa.gov/homepage.htm

Well-Posedness And Accuracy Of The Ensemble Kalman Filter In Discrete And Continuous Time

The ensemble Kalman filter (EnKF) is a method for combining a dynamical model with data in a sequential fashion. Despite its widespread use, there has been little analysis of its theoretical properties. Many of the algorithmic innovations associated with the filter, which are required to make a useable algorithm in practice, are derived in an ad hoc fashion. The aim of this paper is to initiate the development of a systematic analysis of the EnKF, in particular to do so in the small ensemble size limit. The perspective is to view the method as a state estimator, and not as an algorithm which approximates the true filtering distribution. The perturbed observation version of the algorithm is studied, without and with variance inflation. Without variance inflation well-posedness of the filter is established; with variance inflation accuracy of the filter, with resepct to the true signal underlying the data, is established. The algorithm is considered in discrete time, and also for a continuous time limit arising when observations are frequent and subject to large noise. The underlying dynamical model, and assumptions about it, is sufficiently general to include the Lorenz '63 and '96 models, together with the incompressible Navier-Stokes equation on a two-dimensional torus. The analysis is limited to the case of complete observation of the signal with additive white noise. Numerical results are presented for the Navier-Stokes equation on a two-dimensional torus for both complete and partial observations of the signal with additive white noise

Planning for Pedestrians and Bicyclists in North Carolina.

Over the past decade, as obesity has continued to rise among both youth and adults, interest has grown in developing policies to promote community environments that support healthy lifestyles.1 A broad range of local, regional, state, and federal policies under the rubrics of active living, smart growth, and sustainable development share the underlying assumption that they can help people make healthier choices. From a transportation planning perspective, the benefits of pedestrian and bicycle plans resulting from the building of infrastructure to support pedestrian and bicycle travel include improved health (for example, through increased levels of physical activity and reduced obesity), a better environment (for example, through lower carbon emissions), and a stronger economy (for example, through lower fuel bills). However, until more recently, the health benefits have not been specifically explored

Urine metabolomic analysis to detect metabolites associated with the development of contrast induced nephropathy.

ObjectiveContrast induced nephropathy (CIN) is a result of injury to the proximal tubules. The incidence of CIN is around 11% for imaging done in the acute care setting. We aim to analyze the metabolic patterns in the urine, before and after dosing with intravenous contrast for computed tomography (CT) imaging of the chest, to determine if metabolomic changes exist in patients who develop CIN.MethodsA convenience sample of high risk patients undergoing a chest CT with intravenous contrast were eligible for enrollment. Urine samples were collected prior to imaging and 4 to 6 hours post imaging. Samples underwent gas chromatography/mass spectrometry profiling. Peak metabolite values were measured and data was log transformed. Significance analysis of microarrays and partial least squares was used to determine the most significant metabolites prior to CT imaging and within subject. Analysis of variance was used to rank metabolites associated with temporal change and CIN. CIN was defined as an increase in serum creatinine level of ≥ 0.5 mg/dL or ≥ 25% above baseline within 48 hours after contrast administration.ResultsWe sampled paired urine samples from 63 subjects. The incidence of CIN was 6/63 (9.5%). Patients without CIN had elevated urinary citric acid and taurine concentrations in the pre-CT urine. Xylulose increased in the post CT sample in patients who developed CIN.ConclusionDifferences in metabolomics patterns in patients who do and do not develop CIN exist. Metabolites may be potential early identifiers of CIN and identify patients at high-risk for developing this condition prior to imaging

General study of superscaling in quasielastic (e,e′)(e,e') and (ν,μ)(\nu,\mu) reactions using the relativistic impulse approximation

The phenomenon of superscaling for quasielastic lepton induced reactions at energies of a few GeV is investigated within the framework of the relativistic impulse approximation. A global analysis of quasielastic inclusive electron and charged-current neutrino scattering reactions on nuclei is presented. Scaling and superscaling properties are shown to emerge from both types of processes. The crucial role played by final state interactions is evaluated by using different approaches. The asymmetric shape presented by the experimental scaling function, with a long tail in the region of positive values of the scaling variable, is reproduced when the interaction in the final state between the knockout nucleon and the residual nucleus is described within the relativistic mean field approach. The impact of gauge ambiguities and off-shell effects in the scaling function is also analyzed.Comment: 34 pages, 14 figures, accepted in Phys. Rev. C. Section II has been shortene

Brain Amino Acids and Biogenic Amines Under Various Atmospheric Mixtures Semiannual Report, 1 Mar. 1965 - 30 Apr. 1966

Effects of exposure to different gaseous atmospheric mixtures on free amino acids and biogenic amines in rat brain

Tildrakizumab in the treatment of psoriasis: latest evidence and place in therapy.

Psoriasis is a chronic inflammatory disorder that is clinically characterized by scaly cutaneous plaques. New evidence suggests that dysregulation of interleukin (IL)-23, a key cytokine in the T-helper-17 pathway, plays a vital role in the development of psoriatic systemic inflammation. The novel biologic medication tildrakizumab is among the first drugs with specific action against IL-23 that has recently been approved by the United States Food and Drug Administration and the European Medicines Agency for moderate-to-severe psoriasis. Tildrakizumab has been shown in large randomized controlled trials to be effective in improving skin manifestations as well as enhancing quality of life outcomes in patients with psoriasis. Its simple dosing, prolonged duration of action, and mild adverse event profile make it a practical option for patients; however, only a small number of trials have investigated the clinical effectiveness of tildrakizumab, and long-term data regarding the drug's efficacy and safety are currently limited. Hence, further research is needed to better understand the risks and benefits of tildrakizumab. This review summarizes and analyzes phase I, phase II, and phase III clinical trials that investigate the mechanism, pharmacokinetics, efficacy, and safety of tildrakizumab. It also identifies areas in which additional studies are warranted to further elucidate the advantages of tildrakizumab over other biologic therapies

Wide energy-window view on the density of states and hole mobility of poly(p-phenylene vinylene)

Using an electrochemically gated transistor, we achieved controlled and reversible doping of poly(p-phenylene vinylene) in a large concentration range. Our data open a wide energy-window view on the density of states (DOS) and show, for the first time, that the core of the DOS function is Gaussian, while the low-energy tail has a more complex structure. The hole mobility increases by more than four orders of magnitude when the electrochemical potential is scanned through the DOS.Comment: 4 pages, 4 figure