The Temperature of the CMB at 10 GHz

We report the results of an effort to measure the low frequency portion of the spectrum of the Cosmic Microwave Background Radiation (CMB), using a balloon-borne instrument called ARCADE (Absolute Radiometer for Cosmology, Astrophysics, and Diffuse Emission). These measurements are to search for deviations from a thermal spectrum that are expected to exist in the CMB due to various processes in the early universe. The radiometric temperature was measured at 10 and 30 GHz using a cryogenic open-aperture instrument with no emissive windows. An external blackbody calibrator provides an in situ reference. A linear model is used to compare the radiometer output to a set of thermometers on the instrument. The unmodeled residuals are less than 50 mK peak-to-peak with a weighted RMS of 6 mK. Small corrections are made for the residual emission from the flight train, atmosphere, and foreground Galactic emission. The measured radiometric temperature of the CMB is 2.721 +/- 0.010 K at 10 GHz and 2.694 +/- 0.032 K at 30 GHz.Comment: 8 pages including 5 figures. Submitted to The Astrophysical Journa

Traversed Graph Representation for Sparse Encoding of Macro-Reentrant Tachycardia

© Springer International Publishing Switzerland 2016.Macro-reentrant atrial and ventricular tachycardias originate from additional circuits in which the activation of the cardiac chambers follows a high-frequency rotating pattern. The macro-reentrant circuit can be interrupted by targeted radiofrequency energy delivery with a linear lesion transecting the pathway. The choice of the optimal ablation site is determined by the operator’s experience, thus limiting the procedure success, increasing its duration and also unnecessarily extending the ablated tissue area in the case of incorrect ablation target estimation. In this paper, an algorithm for automatic intraoperative detection of the tachycardia reentry path is proposed by modelling the propagation as a graph traverse problem. Moreover, the optimal ablation point where the path should be transected is computed. Finally, the proposed method is applied to sparse electroanatomical data to demonstrate its use when undersampled mapping occurs. Thirteen electroanatomical maps of right ventricle and right and left atrium tachycardias from patients treated for congenital heart disease were analysed retrospectively in this study, with prediction accuracy tested against the recorded ablation sites and arrhythmia termination points

CMB component separation by parameter estimation

We propose a solution to the CMB component separation problem based on standard parameter estimation techniques. We assume a parametric spectral model for each signal component, and fit the corresponding parameters pixel by pixel in a two-stage process. First we fit for the full parameter set (e.g., component amplitudes and spectral indices) in low-resolution and high signal-to-noise ratio maps using MCMC, obtaining both best-fit values for each parameter, and the associated uncertainty. The goodness-of-fit is evaluated by a chi^2 statistic. Then we fix all non-linear parameters at their low-resolution best-fit values, and solve analytically for high-resolution component amplitude maps. This likelihood approach has many advantages: The fitted model may be chosen freely, and the method is therefore completely general; all assumptions are transparent; no restrictions on spatial variations of foreground properties are imposed; the results may be rigorously monitored by goodness-of-fit tests; and, most importantly, we obtain reliable error estimates on all estimated quantities. We apply the method to simulated Planck and six-year WMAP data based on realistic models, and show that separation at the muK level is indeed possible in these cases. We also outline how the foreground uncertainties may be rigorously propagated through to the CMB power spectrum and cosmological parameters using a Gibbs sampling technique.Comment: 20 pages, 10 figures, submitted to ApJ. For a high-resolution version, see http://www.astro.uio.no/~hke/docs/eriksen_et_al_fgfit.p

A maximum likelihood approach to the destriping technique

The destriping technique is a viable tool for removing different kinds of systematic effects in CMB related experiments. It has already been proven to work for gain instabilities that produce the so-called 1/f noise and periodic fluctuations due to e.g. thermal instability. Both effects when coupled with the observing strategy result in stripes on the observed sky region. Here we present a maximum-likelihood approach to this type of technique and provide also a useful generalization. As a working case we consider a data set similar to what the Planck satellite will produce in its Low Frequency Instrument (LFI). We compare our method to those presented in the literature and find some improvement in performance. Our approach is also more general and allows for different base functions to be used when fitting the systematic effect under consideration. We study the effect of increasing the number of these base functions on the quality of signal cleaning and reconstruction. This study is related to Planck LFI activities.Comment: Revised version, accepted by A&A, 12 pages, 14 figure

Engineering an endocrine Neo-Pancreas by repopulation of a decellularized rat pancreas with islets of Langerhans

Decellularization of pancreata and repopulation of these non-immunogenic matrices with islets and endothelial cells could provide transplantable, endocrine Neo- Pancreata. In this study, rat pancreata were perfusion decellularized and repopulated with intact islets, comparing three perfusion routes (Artery, Portal Vein, Pancreatic Duct). Decellularization effectively removed all cellular components but conserved the pancreas specific extracellular matrix. Digital subtraction angiography of the matrices showed a conserved integrity of the decellularized vascular system but a contrast emersion into the parenchyma via the decellularized pancreatic duct. Islets infused via the pancreatic duct leaked from the ductular system into the peri- ductular decellularized space despite their magnitude. TUNEL staining and Glucose stimulated insulin secretion revealed that islets were viable and functional after the process. We present the first available protocol for perfusion decellularization of rat pancreata via three different perfusion routes. Furthermore, we provide first proof-of-concept for the repopulation of the decellularized rat pancreata with functional islets of Langerhans. The presented technique can serve as a bioengineering platform to generate implantable and functional endocrine Neo-Pancreata

Software defect prediction: do different classifiers find the same defects?

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.During the last 10 years, hundreds of different defect prediction models have been published. The performance of the classifiers used in these models is reported to be similar with models rarely performing above the predictive performance ceiling of about 80% recall. We investigate the individual defects that four classifiers predict and analyse the level of prediction uncertainty produced by these classifiers. We perform a sensitivity analysis to compare the performance of Random Forest, Naïve Bayes, RPart and SVM classifiers when predicting defects in NASA, open source and commercial datasets. The defect predictions that each classifier makes is captured in a confusion matrix and the prediction uncertainty of each classifier is compared. Despite similar predictive performance values for these four classifiers, each detects different sets of defects. Some classifiers are more consistent in predicting defects than others. Our results confirm that a unique subset of defects can be detected by specific classifiers. However, while some classifiers are consistent in the predictions they make, other classifiers vary in their predictions. Given our results, we conclude that classifier ensembles with decision-making strategies not based on majority voting are likely to perform best in defect prediction.Peer reviewedFinal Published versio

Angular Power Spectra of the Millimeter Wavelength Background Light from Dusty Star-forming Galaxies with the South Pole Telescope

We use data from the first 100 square-degree field observed by the South Pole Telescope (SPT) in 2008 to measure the angular power spectrum of temperature anisotropies contributed by the background of dusty star-forming galaxies (DSFGs) at millimeter wavelengths. From the auto and cross-correlation of 150 and 220 GHz SPT maps, we significantly detect both Poisson distributed and, for the first time at millimeter wavelengths, clustered components of power from a background of DSFGs. The spectral indices between 150 and 220 GHz of the Poisson and clustered components are found to be 3.86 +- 0.23 and 3.8 +- 1.3 respectively, implying a steep scaling of the dust emissivity index beta ~ 2. The Poisson and clustered power detected in SPT, BLAST (at 600, 860, and 1200 GHz), and Spitzer (1900 GHz) data can be understood in the context of a simple model in which all galaxies have the same graybody spectrum with dust emissivity index of beta = 2 and dust temperature T_d = 34 K. In this model, half of the 150 GHz background light comes from redshifts greater than 3.2. We also use the SPT data to place an upper limit on the amplitude of the kinetic Sunyaev-Zel'dovich power spectrum at l = 3000 of 13 uK^2 at 95% confidence.Comment: 18 pages, 9 figure

The QUIET Instrument

The Q/U Imaging ExperimenT (QUIET) is designed to measure polarization in the Cosmic Microwave Background, targeting the imprint of inflationary gravitational waves at large angular scales (~ 1 degree). Between 2008 October and 2010 December, two independent receiver arrays were deployed sequentially on a 1.4 m side-fed Dragonian telescope. The polarimeters which form the focal planes use a highly compact design based on High Electron Mobility Transistors (HEMTs) that provides simultaneous measurements of the Stokes parameters Q, U, and I in a single module. The 17-element Q-band polarimeter array, with a central frequency of 43.1 GHz, has the best sensitivity (69 uK sqrt(s)) and the lowest instrumental systematic errors ever achieved in this band, contributing to the tensor-to-scalar ratio at r < 0.1. The 84-element W-band polarimeter array has a sensitivity of 87 uK sqrt(s) at a central frequency of 94.5 GHz. It has the lowest systematic errors to date, contributing at r < 0.01. The two arrays together cover multipoles in the range l= 25-975. These are the largest HEMT-based arrays deployed to date. This article describes the design, calibration, performance of, and sources of systematic error for the instrument