Observations of free–free and anomalous microwave emission from LDN 1622 with the 100 m Green Bank Telescope

LDN 1622 has previously been identified as a possible strong source of dust-correlated anomalous microwave emission (AME). Previous observations were limited by resolution meaning that the radio emission could not be compared with current generation high-resolution infrared data from Herschel, Spitzer or Wide-field Infrared Sky Explorer. This paper presents arcminute resolution mapping observations of LDN 1622 at 4.85 and 13.7 GHz using the 100 m Robert C. Byrd Green Bank Telescope. The 4.85 GHz map reveals a corona of free–free emission enclosing LDN 1622 that traces the photodissociation region of the cloud. The brightest peaks of the 4.85 GHz map are found to be within ≈10 per cent agreement with the expected free–free predicted by Southern H-Alpha Sky Survey Atlas H α data of LDN 1622. At 13.7 GHz, the AME flux density was found to be 7.0 ± 1.4 mJy and evidence is presented for a rising spectrum between 13.7 and 31 GHz. The spinning dust model of AME is found to naturally account for the flux seen at 13.7 GHz. Correlations between the diffuse 13.7 GHz emission and the diffuse mid-infrared emission are used to further demonstrate that the emission originating from LDN 1622 at 13.7 GHz is described by the spinning dust model

Eliminating artefacts in polarimetric images using deep learning

Polarization measurements done using Imaging Polarimeters such as the Robotic Polarimeter are very sensitive to the presence of artefacts in images. Artefacts can range from internal reflections in a telescope to satellite trails that could contaminate an area of interest in the image. With the advent of wide-field polarimetry surveys, it is imperative to develop methods that automatically flag artefacts in images. In this paper, we implement a Convolutional Neural Network to identify the most dominant artefacts in the images. We find that our model can successfully classify sources with 98 per cent true positive and 97 per cent true negative rates. Such models, combined with transfer learning, will give us a running start in artefact elimination for near-future surveys like WALOP

First Season QUIET Observations: Measurements of Cosmic Microwave Background Polarization Power Spectra at 43 GHz in the Multipole Range 25 ≤ ℓ ≤ 475

The Q/U Imaging ExperimenT (QUIET) employs coherent receivers at 43 GHz and 94 GHz, operating on the Chajnantor plateau in the Atacama Desert in Chile, to measure the anisotropy in the polarization of the cosmic microwave background (CMB). QUIET primarily targets the B modes from primordial gravitational waves. The combination of these frequencies gives sensitivity to foreground contributions from diffuse Galactic synchrotron radiation. Between 2008 October and 2010 December, over 10,000 hr of data were collected, first with the 19 element 43 GHz array (3458 hr) and then with the 90 element 94 GHz array. Each array observes the same four fields, selected for low foregrounds, together covering ≈1000 deg^2. This paper reports initial results from the 43 GHz receiver, which has an array sensitivity to CMB fluctuations of 69 μK√s. The data were extensively studied with a large suite of null tests before the power spectra, determined with two independent pipelines, were examined. Analysis choices, including data selection, were modified until the null tests passed. Cross-correlating maps with different telescope pointings is used to eliminate a bias. This paper reports the EE, BB, and EB power spectra in the multipole range ℓ = 25-475. With the exception of the lowest multipole bin for one of the fields, where a polarized foreground, consistent with Galactic synchrotron radiation, is detected with 3σ significance, the E-mode spectrum is consistent with the ΛCDM model, confirming the only previous detection of the first acoustic peak. The B-mode spectrum is consistent with zero, leading to a measurement of the tensor-to-scalar ratio of r = 0.35^(+1.06)_(–0.87). The combination of a new time-stream "double-demodulation" technique, side-fed Dragonian optics, natural sky rotation, and frequent boresight rotation leads to the lowest level of systematic contamination in the B-mode power so far reported, below the level of r = 0.1

The Q/U Imaging Experiment: Polarization Measurements of Radio Sources at 43 and 95 GHz

We present polarization measurements of extragalactic radio sources observed during the cosmic microwave background polarization survey of the Q/U Imaging Experiment (QUIET), operating at 43 GHz (Q-band) and 95 GHz (W-band). We examine sources selected at 20 GHz from the public, >40 mJy catalog of the Australia Telescope (AT20G) survey. There are ~480 such sources within QUIET's four low-foreground survey patches, including the nearby radio galaxies Centaurus A and Pictor A. The median error on our polarized flux density measurements is 30–40 mJy per Stokes parameter. At signal-to-noise ratio > 3 significance, we detect linear polarization for seven sources in Q-band and six in W-band; only 1.3 ± 1.1 detections per frequency band are expected by chance. For sources without a detection of polarized emission, we find that half of the sources have polarization amplitudes below 90 mJy (Q-band) and 106 mJy (W-band), at 95% confidence. Finally, we compare our polarization measurements to intensity and polarization measurements of the same sources from the literature. For the four sources with WMAP and Planck intensity measurements >1 Jy, the polarization fractions are above 1% in both QUIET bands. At high significance, we compute polarization fractions as much as 10%–20% for some sources, but the effects of source variability may cut that level in half for contemporaneous comparisons. Our results indicate that simple models—ones that scale a fixed polarization fraction with frequency—are inadequate to model the behavior of these sources and their contributions to polarization maps

Mutual assessment in the social programmer ecosystem: an empirical investigation of developer profile aggregators

The multitude of social media channels that programmers can use to participate in software development has given rise to online developer profiles that aggregate activity across many services. Studying members of such developer profile aggregators, we found an ecosystem that revolves around the social programmer. Developers are assessing each other to evaluate whether other developers are interesting, worth following, or worth collaborating with. They are self-conscious about being assessed, and thus manage their public images. They value passion for software development, new technologies, and learning. Some recruiters participate in the ecosystem and use it to find candidates for hiring; other recruiters struggle with the interpretation of signals and issues of trust. This mutual assessment is changing how software engineers collaborate and how they advance their skills.Leif Singer, Fernando Figueira Filho, Brendan Cleary, Christoph Treude, Margaret-Anne Storey, Kurt Schneide

Being honest with causal language in writing for publication

The misleading use of causal language in publication is problematic for authors, reviewers and consumers of the information. Published research in quality journals has important knowledge implications and it is, therefore, contingent on authors to use language that is accurate and appropriate to their work. Language implying unsupported causal relationships may overstate the evidence-base, especially if accepted by uncritical readers or unwitting members of the general public who may not understand how to interpret inferential statistics

Mixed-state quasiparticle transport in high-T_c cuprates: localization by magnetic field

Theory of quasiparticle transport in the mixed state of a d-wave superconductor is developed under the assumption of disordered vortex array. A novel universal regime is identified at fields above H*= c*H_{c2}(T/T_c)^2, characterized by a field-independent longitudinal thermal conductivity. It is argued that this behavior is responsible for the high-field plateau in the thermal conductivity experimentally observed in cuprates by Krishana, Ong and co-workers.Comment: 4 pages REVTeX + 1 PostScript figure. Final version to appear in PRL. Several changes in response to referee comments. For related work and info visit http://www.pha.jhu.edu/~fran

Exploratory factor analysis and principal component analysis in clinical studies: Which one should you use?

Factor analysis covers a range of multivariate methods used to explain how underlying factors influence a set of observed variables. When research aims to identify these underlying factors, exploratory factor analysis (EFA) is used. In contrast, when the aim is to test whether a set of observed variables represents the underlying factors, in accordance with an existing conceptual basis, confirmatory factor analysis is performed. EFA has many similarities with a commonly used data reduction technique called principal component analysis (PCA). These similarities, along with using the related terms factor and component interchangeably, contribute to confusion in analysis. The difficulty in identifying the appropriate use of statistical methods and their application and interpretation impacts clinical and research implications (Beavers et al., 2013; Tabachnick & Fidell, 2001). We acknowledge previous articles in nursing journals offering guidance on the use of factor analysis (Gaskin & Happell, 2014; Watson & Thompson, 2006)

Using risk and odds ratios to assess effect size for meta-analysis outcome measures

Best practice is built on the principle of aggregating all available evidence on a topic to make a clinical decision on the most appropriate intervention for the situation at hand. Systematic reviews and meta-analyses are powerful tools that summarize the evidence for current best practice guidelines for the available interventions for a particular problem (Moher, Liberati, Tetzlaff, & Altman, 2009). Meta-analysis combines the results of multiple studies to produce an aggregated and more precise estimates of the benefits of the interventions. Meta-analysis of high-quality randomized trials is considered the highest level of evidence to inform practice

Is knowledge and practice safer in England after the release of national guidance on the resuscitation of patients in mental health and learning disabilities?

This paper reports on the issue of resuscitation in mental health inpatient environments. It reviews the literature on national standards and best practice when emergency situations arise in mental health settings. The discussion on the best practice literature takes place alongside the reporting of a national evaluation of how National Patient Safety Agency improvement guidelines for the provision for life support, and resuscitation for mental health service users was effectively implemented across health-care providers in England. Methods used to establish the effective use of the guidelines include feedback from clinical staff and staff responsible for the implementation of the new national standards for resuscitation. Serious incident data were also compared prior to the release of the national guidelines and after the guideline release dates. This included looking at events around choking and cardiac/respiratory arrest in inpatient areas. There were five deaths post-implementation of the guidelines that were considered to have serious enough error associated with the resuscitation process. This was down from 18 prior to the release of the guidelines. However, our survey showed that despite organisations reporting 100% compliance with the implementation of the guidelines, around half of frontline clinical staff were not aware of them. Although our survey responses show a contradiction between organisational and clinical staff awareness, our analysis suggests a reduction in moderate and severe harm cases and of deaths. There is evidence of a reduction in the worst types of error resulting in death, albeit with small numbers