52 research outputs found

    Euclid:Validation of the MontePython forecasting tools

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    The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. We expand and adjust the mock Euclid likelihoods of the MontePython software in order to match the exact recipes used in previous Euclid Fisher matrix forecasts for several probes: weak lensing cosmic shear, photometric galaxy clustering, the cross-correlation between the latter observables, and spectroscopic galaxy clustering. We also establish which precision settings are required when running the Einstein-Boltzmann solvers CLASS and CAMB in the context of Euclid. For the minimal cosmological model, extended to include dynamical dark energy, we perform Fisher matrix forecasts based directly on a numerical evaluation of second derivatives of the likelihood with respect to model parameters. We compare our results with those of other forecasting methods and tools. We show that such MontePython forecasts agree very well with previous Fisher forecasts published by the Euclid Collaboration, and also, with new forecasts produced by the CosmicFish code, now interfaced directly with the two Einstein-Boltzmann solvers CAMB and CLASS. Moreover, to establish the validity of the Gaussian approximation, we show that the Fisher matrix marginal error contours coincide with the credible regions obtained when running Monte Carlo Markov Chains with MontePython while using the exact same mock likelihoods. The new Euclid forecast pipelines presented here are ready for use with additional cosmological parameters, in order to explore extended cosmological models

    Euclid:Validation of the MontePython forecasting tools

    Get PDF
    The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. We expand and adjust the mock Euclid likelihoods of the MontePython software in order to match the exact recipes used in previous Euclid Fisher matrix forecasts for several probes: weak lensing cosmic shear, photometric galaxy clustering, the cross-correlation between the latter observables, and spectroscopic galaxy clustering. We also establish which precision settings are required when running the Einstein-Boltzmann solvers CLASS and CAMB in the context of Euclid. For the minimal cosmological model, extended to include dynamical dark energy, we perform Fisher matrix forecasts based directly on a numerical evaluation of second derivatives of the likelihood with respect to model parameters. We compare our results with those of other forecasting methods and tools. We show that such MontePython forecasts agree very well with previous Fisher forecasts published by the Euclid Collaboration, and also, with new forecasts produced by the CosmicFish code, now interfaced directly with the two Einstein-Boltzmann solvers CAMB and CLASS. Moreover, to establish the validity of the Gaussian approximation, we show that the Fisher matrix marginal error contours coincide with the credible regions obtained when running Monte Carlo Markov Chains with MontePython while using the exact same mock likelihoods. The new Euclid forecast pipelines presented here are ready for use with additional cosmological parameters, in order to explore extended cosmological models

    Platelet-rich plasma: a narrative review

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    Solution combustion synthesized ZnO/Na2Ti6O13 composite for degradation of 4-nitrophenol under solar irradiation

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    The ZnO-Na2Ti6O13 composites were synthesized by facile solution combustion method with different molar concentrations of sodium titanate which is prepared by hydrothermal route. The formation of the composites was confirmed by the X-ray diffraction (XRD) analysis. Field emission scanning electron microscope (FESEM) and transmission electron microscope (TEM) results revealed that the synthesized composites exhibit porous morphology, whereas the pristine Na2Ti6O13 nanoparticles have whisker like morphology. Diffuse reflectance spectroscopy (DRS) and photoluminescence (PL) studies were utilized to compute the bandgap and the presence of defects in the composites respectively. The photocatalytic activity of ZnO-Na2Ti6O13 catalyst was investigated through the degradation of 4-nitrophenol under solar light over a period of 180 min and the composite with 0.05 M of Na2Ti6O13 showed higher degradation efficiency (96%) than the other concentrations of Na2Ti6O13 and pristine ZnO. The reduced bandgap, high charge transfer, more oxygen vacancies and the production of high superoxide anion radicals have profound effect on the higher photocatalytic efficiency of the composite with 0.05 of M Na2Ti6O13

    A virtual experimenter to increase standardization for the investigation of placebo effects

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    Abstract Background Placebo effects are mediated by expectancy, which is highly influenced by psychosocial factors of a treatment context. These factors are difficult to standardize. Furthermore, dedicated placebo research often necessitates single-blind deceptive designs where biases are easily introduced. We propose a study protocol employing a virtual experimenter – a computer program designed to deliver treatment and instructions – for the purpose of standardization and reduction of biases when investigating placebo effects. Methods To evaluate the virtual experimenter’s efficacy in inducing placebo effects via expectancy manipulation, we suggest a partially blinded, deceptive design with a baseline/retest pain protocol (hand immersions in hot water bath). Between immersions, participants will receive an (actually inert) medication. Instructions pertaining to the medication will be delivered by one of three metaphors: The virtual experimenter, a human experimenter, and an audio/text presentation (predictor “Metaphor”). The second predictor includes falsely informing participants that the medication is an effective pain killer, or correctly informing them that it is, in fact, inert (predictor “Instruction”). Analysis will be performed with hierarchical linear modelling, with a sample size of N = 50. Results from two pilot studies are presented that indicate the viability of the pain protocol (N = 33), and of the virtual experimenter software and placebo manipulation (N = 48). Discussion It will be challenging to establish full comparability between all metaphors used for instruction delivery, and to account for participant differences in acceptance of their virtual interaction partner. Once established, the presence of placebo effects would suggest that the virtual experimenter exhibits sufficient cues to be perceived as a social agent. He could consequently provide a convenient platform to investigate effects of experimenter behavior, or other experimenter characteristics, e.g., sex, age, race/ethnicity or professional status. More general applications are possible, for example in psychological research such as bias research, or virtual reality research. Potential applications also exist for standardizing clinical research by documenting and communicating instructions used in clinical trials
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