Context.Molecular filaments and hubs have received special attention recently thanks to new studies showing their key role in star formation. While the (column) density and velocity structures of both filaments and hubs have been carefully studied, their magnetic field (B-field) properties have yet to be characterized. Consequently, the role of B-fields in the formation and evolution of hub-filament systems is not well constrained.Aims.We aim to understand the role of the B-field and its interplay with turbulence and gravity in the dynamical evolution of the NGC 6334 filament network that harbours cluster-forming hubs and high-mass star formation.Methods.We present new observations of the dust polarized emission at 850μm toward the 2 pc × 10 pc map of NGC 6334 at a spatial resolution of 0.09 pc obtained with theJames Clerk MaxwellTelescope (JCMT) as part of the B-field In STar-forming Region Observations (BISTRO) survey. We study the distribution and dispersion of the polarized intensity (PI), the polarization fraction (PF), and the plane-of-the-sky B-field angle (χB_POS) toward the whole region, along the 10 pc-long ridge and along the sub-filaments connected to the ridge and the hubs. We derived the power spectra of the intensity andχBPOSalong the ridge crest and compared them with the results obtained from simulated filaments.Results.The observations span ~3 orders of magnitude in StokesIandPIand ~2 orders of magnitude inPF(from ~0.2 to ~ 20%). A large scatter inPIandPFis observed for a given value ofI. Our analyses show a complex B-field structure when observed over the whole region (~ 10 pc); however, at smaller scales (~1 pc),χBPOSvaries coherently along the crests of the filament network. The observed power spectrum ofχBPOScan be well represented with a power law function with a slope of − 1.33 ± 0.23, which is ~20% shallower than that ofI. We find that this result is compatible with the properties of simulated filaments and may indicate the physical processes at play in the formation and evolution of star-forming filaments. Along the sub-filaments,χBPOSrotates frombeing mostly perpendicular or randomly oriented with respect to the crests to mostly parallel as the sub-filaments merge with the ridge and hubs. This variation of the B-field structure along the sub-filaments may be tracing local velocity flows of infalling matter in the ridge and hubs. Our analysis also suggests a variation in the energy balance along the crests of these sub-filaments, from magnetically critical or supercritical at their far ends to magnetically subcritical near the ridge and hubs. We also detect an increase inPFtoward the high-column density (NH2≳ 1023 cm−2) star cluster-forming hubs. These latter largePFvalues may be explained by the increase in grain alignment efficiency due to stellar radiation from the newborn stars, combined with an ordered B-field structure.Conclusions.These observational results reveal for the first time the characteristics of the small-scale (down to ~ 0.1 pc) B-field structure of a 10 pc-long hub-filament system. Our analyses show variations in the polarization properties along the sub-filaments that may be tracing the evolution of their physical properties during their interaction with the ridge and hubs. We also detect an impact of feedback from young high-mass stars on the local B-field structure and the polarization properties, which could put constraints on possible models for dust grain alignment and provide important hints as to the interplay between the star formation activity and interstellar B-fields.

Wide-field imaging has become a major challenge for modern radio astronomy, which uses high sensitivity acquisition systems that deal with huge amounts of data. In this paper we investigate a fast wide-field imaging solution based on the w-projection algorithm, which is intended for modern astronomy systems. The core idea of the proposed method is to reduce the computational complexity of the convolution kernel generation step, specifically by replacing the standard two-dimensional FFT by the one-dimensional Hankel transform. Experimental results show that the optimised w-projection proposed here produces equivalent dirty image results in a circular image region, at a significantly lower computational cost than standard $w$-projection. One of the main advantages of the proposed solution is its slow scaling with the number of w-planes, thus enabling more accurate output results at a lower computational cost.

ConclusionThe data collection and merging in the CAT-system work smoothly and show good potential.The models perform very well on this external patient cohort and could provide doctors and patients with valuable information on patientspecific survival.The model does not include smoking status of the patients, which has been shown to have a major impact on tumor control and survival and therefore could potentially improve the model predictions further.

AbstractThe DARA Big Data project is a flagship UK Newton Fund & GCRF program in partnership with the South African Department of Science & Technology (DST). DARA Big Data provides bursaries for students from the partner countries of the African VLBI Network (AVN), namely Botswana, Ghana, Kenya, Madagascar, Mauritius, Mozambique, Namibia and Zambia, to study for MSc(R) and PhD degrees at universities in South Africa and the UK. These degrees are in the three data intensive DARA Big Data focus areas of astrophysics, health data and sustainable agriculture. The project also provides training courses in machine learning, big data techniques and data intensive methodologies as part of the Big Data Africa initiative.

Recently, incidental dose to the heart was found to be predictive for overall survival in lung cancer patients receiving radiotherapy [McWilliam et al EJC 2017, Johnson et al Radiother Oncol 2018]. These patients often present with multiple comorbidities that should be incorporated in survival analysis. However, such data is often missing. We investigated whether calcifications, identified on the radiotherapy planning CT, can be used as a surrogate for cardiac health. In particular, we investigated the interaction between calcifications, dose and survival. Data from 814 unselected non-small cell lung cancer patients was used, all treated with 55Gy in 20 fractions. Methodology was developed to automatically segment calcifications within the heart, the aortic arch and their surroundings. The 3D planning CT scans, and the associated lung and spinal cord delineations were processed using well-established image processing algorithms, e.g., convex hull, thresholding, morphological operations, connected pixel analysis and flood filling to detect calcifications. Moreover, shape analysis was included to enhance regions that presented tubular or plate-like appearance. The detection algorithm was validated in a small subset of 10 patients, and this group was used to determine the success and error rate of the automatic segmentation. Finally, a Cox-proportional hazards multivariate analysis was performed for overall survival of all patients accounting for tumour size, total calcification volume, mean dose across all identified calcifications, and interaction between calcification volume and dose. The success rate of the algorithm for identifying calcifications was 81.8%, its error rate was 8.8%. The multivariate survival analysis identified tumour size (continuous, p<<0.0001) and the interaction of calcification volume and their mean dose (continuous, p=0.029) as significant. Calcification volume (p=0.57) or mean calcification radiation dose alone (p=0.269) were not found to be significant. Multivariate analysis shows a significant interaction between volume of the identified calcifications and their mean radiotherapy dose predicting survival. Further improvements to identify calcifications in the descending thoracic aorta and validation of our methodology are required. Further work linking our results with the established Agatston or Coronary Artery Calcium score is in progress. * EVO-FB share first authorship

ThunderKAT is the image-plane transients programme for MeerKAT. The goal as outlined in 2010, and still today, is to find, identify and understand high-energy astrophysical processes via their radio emission (often in concert with observations at other wavelengths). Through a comprehensive and complementary programme of surveying and monitoring Galactic synchrotron transients (across a range of compact accretors and a range of other explosive phenomena) and exploring distinct populations of extragalactic synchrotron transients (microquasars, supernovae and possibly yet unknown transient phenomena) - both from direct surveys and commensal observations - we will revolutionise our understanding of the dynamic and explosive transient radio sky. As well as performing targeted programmes of our own, we have made agreements with the other MeerKAT large survey projects (LSPs) that we will also search their data for transients. This commensal use of the other surveys, which remains one of our key programme goals in 2016, means that the combined MeerKAT LSPs will produce by far the largest GHz-frequency radio transient programme to date.

Radio observations of young stellar objects (YSOs) enable the study of ionized plasma outflows from young protostars via their free–free radiation. Previous studies of the low-mass young system TTau have used radio observations to model the spectrum and estimate important physical properties of the associated ionized plasma (local electron density, ionized gas content, and emission measure). However, without an indication of the low-frequency turnover in the free–free spectrum, these properties remain difficult to constrain. This paper presents the detection of TTau at 149MHz with the Low Frequency Array (LOFAR)—the first time a YSO has been observed at such low frequencies. The recovered total flux indicates that the free–free spectrum may be turning over near 149MHz. The spectral energy distribution is fitted and yields improved constraints on local electron density (  ́ 7.2 2.1 103 ( ) cm), ionized gas mass (  ́  M 1.0 1.8 10 6 ( ) ), and emission measure (  ́ 1.67 0.14 105 ( ) pc cm).