dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical test All statistical tests were performed using SPSS© software and non-parametric tests were used. In order to assess the side effect (right vs left), a Wilcoxon test for paired samples was performed on all samples of group 1 and 2 separately. To assess the impact of the injection on the mechanical properties, a Wilcoxon test was performed on group 3, and a Mann-Whitney test was performed on group 4 (=group1 + group2 + group3).
leidenuniv. nl whole 2π steradians of the Northern sky; deeper Tier-2 and Tier-3 observations are focussing on smaller areas with high-quality multi-wavelength datasets. Here we focus on the ongoing LOFAR HBA 120-168 MHz Tier-1 survey, hereafter referred to as the LOFAR Two-metre Sky Survey (LoTSS). This is the second northern hemisphere survey that will be conducted with the LOFAR HBA and is significantly deeper than the first, the Multifrequency Snapshot Sky Survey (MSSS;  Heald et al. 2015). MSSS was primarily conducted as a commissioning project for LOFAR and a testbed for large-scale imaging projects, whereas LoTSS will probe a new parameter space. LoTSS is a long term project but over 2,000 square degrees of the northern sky have already been observed and additional data are continuously being taken.
g. Jarvis et al. 2015). The survey images, in combination with other datasets, will be used to measure cosmological parameters, including tests of alternative theories of gravity, and using the Integrated Sachs-Wolfe effect to constrain the nature of dark energy (e. g. Raccanelli et al. 2012 , Jarvis et al. 2015 and Schwarz et al. 2015). Detailed maps of nearby galaxies will be used for studies of cosmic ray diffusion and magnetic fields. The shortest LOFAR baselines (less than 50 m) allow for degree scale emission to be accurately recovered, and the number of well imaged supernova remnants and H II regions will be increased by an order of magnitude to forward studies of the interstellar medium and star formation. Galactic synchrotron emission mapping will provide new information about the strength and topology of the large-scale galactic magnetic field  (Iacobelli et al.
2013). In addition, the survey datasets will be used for a range of other projects. The low-frequency polarisation maps will be used by the Magnetism Key Science project to measure the Faraday spectra of sources  (Beck et al. 2013). The high spectral resolution makes it possible to investigate the physics of the cold, neutral medium in galaxies and its role in galaxy evolution by means of radio recombination lines (e. g. Oonk et al. 2014 and Morabito et al. 2014). The wide area coverage will allow for tight constraints on the population of transient sources and the exploration of new parameter space will open up the possibility of serendipitous discoveries. The eventual exploitation of international baselines will facilitate science that requires subarcsecond resolution. For example, it will allow us to access a regime in which AGN and star-forming galaxies can be accurately distin-guished by morphology (e.
(2015). The greatest challenge we face in reaching the observational aims of the LoTSS is to routinely perform an accurate, robust, and efficient calibration of large datasets to minimise the direction-dependent effects that severely limit the image quality. This complex direction-dependent calibration procedure, which corrects for the varying ionospheric conditions (e. g. Mevius et al. 2016 ) and errors in the beam models, is crucial to create high-fidelity images at full resolution and sensitivity. Several approaches are being developed to minimise these directiondependent effects (e. g. Tasse 2014 and Yatawatta 2015) , including the facet calibration procedure  (van Weeren et al. 2016a and Williams et al. 2016). This procedure has already been successfully applied to several fields to produce high-resolution images with high fidelity and a sensitivity approaching the thermal noise  (Williams et al.
The status of the observing programme for the LoTSS is summarised in Section 3. In Sections 4, 5, 6 and 7 we describe the calibration techniques, imaging procedure, image quality and source cataloguing that we have used for this preliminary data release. The data release itself is summarised in Section 8. In Section 9 we provide an example of the improvement in image fidelity, sensitivity and resolution that will be achieved once direction-dependent calibration has been performed on our datasets. Section 10 provides a brief overview of the scientific potential of the LoTSS data before we summarise in Section 11. 1 ). The size of the markers is proportional to the square root of the survey resolution. Grey, blue and red markers show the ongoing/completed surveys, forthcoming surveys, and the LOFAR HBA surveys respectively.
The array has been further extended during 2016 to increase the maximum baseline length to 1600 km with three new stations in Poland, and a station in Ireland is currently under construction. These international stations will allow HBA imaging at resolutions of ∼ 0. 3. Imaging at the full resolution provided by the international stations has been shown to be possible for individual targets (e. g. Varenius et al. 2015 with the HBA and Morabito et al. 2016  with the LBA), reaching sensitivities of 150 µJy/beam for the HBA. Accordingly, international stations are present in the LoTSS datasets, although these data are not yet routinely imaged as part of the Survey programme. Such routine imaging will require further work on identification of calibrator sources with significant compact structure, which is currently being undertaken by the LBCS project  (Moldón et al.
Archived datasets To facilitate both spectral line and international baseline studies, the data are not heavily averaged in either frequency or time before they are archived in the LOFAR Long Term Archive (  5 ). We have opted to store the data at 1 s time resolution and 12. 2 kHz frequency resolution (note that some early observations have up to a factor of 4 more averaging). The effects of the time and bandwidth smearing that this averaging causes can be approximated using the equations of  Bridle & Schwab (1989). The time averaging of 1 s is such that for international station imaging at 0. 5 resolution, time smearing will reduce the peak brightness of sources 1 • away from the pointing centre by 7%. The effects of the 12. 2 kHz frequency averaging are approximately equal: at 0. 5 resolution and 150 MHz the effects of bandwidth smearing will reduce the peak brightness of sources 1 • away from the pointing centre by 8%.
Whilst archiving the data at such high time and frequency resolution is crucial to facilitate valuable spectral line and international baseline studies, the downside is that the data volume is very large. The dataset for each pointing is approximately 16 TB, thus the estimated data size for the entire LoTSS is over 50 PB. However, prior to calibrating or imaging the data for the 5 resolution LoTSS, we can rapidly preprocess the data with an averaging of a factor of four in time and four in frequency. This averaging can be done because for 5 imaging a time resolution of 4 s and a frequency resolution of 48. 8 kHz is sufficient to prevent significant smearing within the LOFAR field of view. With this averaging, at a distance of 1. 85 • from the pointing centre, which corresponds to the maximum distance at which LoTSS pointings overlap (see Figure  3 ), we estimate a 3% peak brightness loss due to time averaging smearing and a 4% peak brightness loss due to bandwidth smearing.
58 •. In total, 65% of pointings have all six nearest neighbours within 2. 80 • and 98% have at least four neighbouring pointings within 2. 80 •. Note that the panel on the right was created from a grid with a complete spherical spiral structure and ignores the 42 test pointings that were conducted with a slightly different tiling strategy. van de Gronde, & Roerdink 2012) before being averaged. Only the averaged data products, which have sizes between 3 TB and 16 TB per pointing (depending on the averaging), were stored in the LOFAR archive. Prior to calibration, the data were downloaded from the LO-FAR Long Term Archive to local computing facilities at a speed of about 30MB/s. At this speed, the retrieval of a 3 TB dataset took ≈1day and a 16 TB dataset took ≈1 week. After the data were retrieved from the archive, we averaged the calibrator data to 4 channels per 0.
195 MHz subband and 4 seconds, flagged again for interference (which is identified by AOFLAGGER on the XY and YX polarisations) and removed the international stations from the measurement set if they were included in the observation. Each subband of the calibrator data was then calibrated using the BLACKBOARD SELFCAL (BBS) software  (Pandey et al. 2009 ) to obtain XX and YY solutions for each time slot and frequency channel, taking into account differential Faraday rotation. In these data the only calibrators observed were 3C 295 and 3C 196, and these were used to calibrate 4 and 59 pointings respectively. The model used for the calibration of 3C 295 uses the flux density scale provided by  Scaife & Heald (2012)  with the flux density split equally between two point source components separated by 4.
We note that imperfections in the sky model will result in calibration errors and efforts are ongoing to reduce these imperfections by utilising models derived from other surveys such as TGSS  (Intema et al. 2016 and MSSS (Heald et al. 2015). However, even with the sky model we presently use we often find that direction dependent effects, rather than sky model imperfections, are the primary limitation of the image quality (see Section 4. 2). The control parsets and scripts that have been developed to perform the entire calibration procedure that is described above are executed by the pipeline framework that is now part of the LOFAR software package. Using this pipeline framework makes it simple to efficiently run our completely automated reduction on multiple computers. The pipeline framework handles data tracking, parallel execution, and checks each step is properly completed, which allows for jobs to be resumed.
The phase calibration of the target provides a solution for each station every 32 seconds and, generally, when a nearby station is used for a phase reference, these solutions change smoothly as a function of time. Hence, the difference between these solutions and the same solutions smoothed along the time axis (using a median filter with a window size of 5 samples) is close to 0 radians for short baselines. Therefore, for each station we use the closest station as a reference for the phase solutions and identify periods of rapidly varying phases which are those where the difference between the raw solutions and the smoothed solutions are significant (we set a threshold of 0. 29 radians for a 12 subband dataset). If, for multiple stations (we use a threshold of 5 stations), we identify the same time period as having a rapidly varying phase the ionospheric conditions are classified as poor and the data are flagged for all stations.
Imaging We have somewhat mitigated direction-dependent effects by not utilising the full resolution of the Dutch stations of LOFAR (≈ 5 ) and only using baselines shorter than 12 kλ (corresponding to ≈ 25 resolution) when imaging. However, wide-field imaging of these direction-independent calibrated LOFAR datasets is still difficult due to the low dynamic range of the images and the large number of bright sources. The high sidelobes of the LOFAR synthesised beam (∼ 12% when imaging our data using the Briggs 1995 weighting scheme and a robust parameter of -0. 5) can further hinder this procedure. Furthermore, we use the AWimager  (Tasse et al. 2013)  to apply the time dependent LOFAR station beam model in the imaging procedure to output both primary-beam corrected and uncorrected images, but with this imager we were unable to image all 48 MHz of bandwidth with a single wide-band CLEAN due to the large amount of data (∼250 GB of data per pointing), and at the time of writ- ing, multi-frequency deconvolution was not supported.
5 • × 6. 5 • to ensure that bright sources far down the beam are deconvolved. We initially CLEAN our Stokes I image to a threshold of 20 mJy/beam without using a CLEAN mask. The PyBDSM source finding software  (Mohan & Rafferty 2015)  is then run on the resulting deconvolved apparent brightness image that has an approximately uniform noise across the imaged area, but due to the limited dynamic range there are regions of increased noise around bright sources. This is used to create a CLEAN mask that contains islands that tightly encompass all sources detected in the image but not artefacts around bright sources or source sidelobes, and a noise map that accurately describes the local noise at each position in the image. To approximately CLEAN the image to the local noise at each position, we first CLEAN the entire image using the CLEAN mask and a threshold that is either the largest noise measurement on the PyBDSM generated noise map or 20 mJy/beam (whichever is less).
The large synthesised beams are because over 80% of these datasets (which were observed simultaneously) were flagged due to poor ionospheric conditions that were identified by the flagging procedure outlined in Section 4. 1. Therefore, we exclude these two fields from further analysis. To make the images uniform in resolution we convolve the remaining 61 images with a Gaussian of appropriate size to make the beam of each image 25 × 25. We note that these LOFAR images could be used to obtain a model of the sky that is higher resolution and more sensitive than that used in the initial phase calibration, and that this model could be used to self calibrate the LOFAR datasets. However, this procedure was not followed because self-calibration is time consuming and, while there is a dependance on the quality of the initial sky model in the target region, in most cases it was not found to significantly improve the image quality when imaging at 25 resolution.
Image quality The 25 resolution images produced from our datasets form the most sensitive wide-area low-frequency survey yet produced (see Figure  1 ). The quality of images varies significantly between pointings due to the presence of bright sources in the field and the quality of the input sky model, but it is predominantly dictated by the position-and time-varying ionospheric conditions that cannot be corrected by a direction-independent calibration. This prevents accurate high-resolution imaging, as the ionosphere introduces phase errors which cause position changes that are non-negligible in size compared to the synthesised beam. Even though we have only used baselines shorter than 12 kλ when imaging, the uncorrected ionospheric phase errors cause a noticeable blurring of sources, which reduces their peak brightness, alters their position and increases the image noise.
Furthermore, the quality of all our images is significantly hindered by imperfections in the LOFAR beam model which result in large direction-dependent amplitude (i. e. flux density and spectral index) variations as a function of time. The magnitude of all the quality variations amongst images will be reduced substantially once direction-dependent calibration is fully implemented. However, it is likely that poor ionospheric conditions will mean that a large number of directions will be required to properly calibrate an affected dataset. It may even be the case that, for some pointings, the ionosphere is so spatially variable that there is insufficient flux density within each isoplanatic patch to allow the calibration of all directions. Alternatively, it could be that the number of directions becomes so large that the number of degrees of freedom required for calibration approaches or exceeds the number of independent measurements of visibilities.
Astrometric uncertainties The astrometry of our images is set by our phase calibration, in which we use a model created from the VLSS, WENSS and NVSS surveys (see Section 4. 1). These surveys are at lower resolutions than ours and inaccuracies in the model will not be uncommon. For example, there will be double sources that are unresolved in the lower-resolution model but resolved in our higher-resolution datasets and there will be complex extended emission that is poorly characterised in the model. These imperfections in the phase calibration catalogue will result in a systematic error in the position of our sources and this will vary between pointings. Furthermore the final astrometric accuracy of our images can also be affected by inaccuracies in the beam model and the ionospheric conditions during the observation.
4 GHz FIRST measurements. The final cross-matched catalogue was used to correct the systematic position offset within each LOFAR pointing. This was done by using the median right ascension and declination offsets (∆RA and ∆Dec) to align the LOFAR source positions with those measured in FIRST. During this process we progressively filtered out sources with offsets more than three median absolute deviations (MAD) from the median offset until the median offset converged. The calculated offsets, which range from -3 to 6 in RA and -6 to 3 in DEC, were then applied by altering the headers of the LOFAR image files. After the correction of the systematic position offset, the LOFAR catalogues were remade and again cross matched with FIRST using the same criteria. It is apparent from this cross matching that the quality of the direction-independent calibration of the LOFAR datasets still varies significantly, which is indicated by variations in both the number of LOFAR sources matched with FIRST sources after filtering out all sources that are not compact and isolated, and the standard deviation of the position offsets.
We note, that due to the tight mask used during the deconvolution of our LOFAR images we do not expect a large CLEAN bias which would cause a systematic reduction in our flux measurements (e. g. Becker, White, & Helfand 1995). However, we do expect that this bias varies significantly between pointings due to the uncorrected direction-dependent amplitude errors (see  Williams et al. 2016 ) and the large variation in the uncorrected direction dependent ionospheric effects. A detailed simulation to inject sources into our datasets and assess the level of CLEAN bias should take into account these effects, but such a assessment is beyond the scope of this preliminary data release publication. A thorough evaluation of CLEAN bias will be performed on the final direction dependent calibrated LoTSS data, although we note that an initial investigation was performed by  Williams et al.
Public data release The images and catalogues that were presented in this paper have now been made publicly available 7. This released dataset consists of direction-independent calibrated images of 54 pointings in the region from right ascension 10h45m00s to 15h30m00s and declination 45 • 00 00 to 57 • 00 00 (63 pointings were calibrated but two had a very high fraction of flagged data and seven were found to have poor ionospheric conditions during the observation). We have also released a catalogue of the region which contains over 44,000 sources which were detected with a signal in excess of seven times the local noise on the mosaiced images. The sensitivity within the 381 square degrees that was mosaiced varies significantly (see Figure  12 ) but we have estimated that the catalogue is 90% complete for sources with flux densities in excess of 3.
Direction-dependent calibration Whilst the images presented in this publication are sensitive low-frequency images, these LOFAR datasets, if accurately calibrated, will produce high fidelity images with ≈ 5 resolution and ≈ 100 µJy/beam sensitivity as was demonstrated by e. Routinely producing such images is the challenge that the LO-FAR surveys team is presently tackling. We are putting in place strategies to deal with the large data rate, the computational expense of the calibration, the manual interaction of the calibration, and how to effectively share the data for maximum scientific exploitation. In a future data release, we intend to make direction-dependent calibrated images and catalogues available to the wider scientific community. As a qualitative demonstration of the improvement that direction-dependent calibration will offer, in Figure  13  we show Table  3 : An example of entries in the source catalogue for the 54 direction-independent calibrated images.
g. Mc-Greer, Helfand, & White 2009 and Bañados et al. 2015). These searches will eventually identify many powerful radio-sources at z > 6, which are ideal targets to carry out H I 21cm absorption line studies in the Epoch of Reoinization. The detection of the H I 21cm line will allow us to study the immediate AGN surroundings and interstellar gas in the host galaxy, constrain the cosmic evolution of gas excitation, and detect possible homo- 8 The facet calibration code can be found at https://github. com/lofar-geneity of the last neutral regions from cosmic reionization (e. g. Carilli, Gnedin, & Owen 2002 , Carilli et al. 2007 and Furlanetto & Loeb 2002). The LoTSS images can be used to examine the propagation of cosmic ray electrons in nearby galaxies such as M 106 and M 51 (Figure  15 ).
Summary In this publication we have described the LoTSS, for which we aim to produce high fidelity images of the entire Northern sky with a resolution of ≈ 5 and sensitivity of ≈ 100 µJy/beam at most declinations. We have summarised a survey strategy that should allow us to reach these ambitious observational aims. This consists of 3170 pointings each observed for 8 hrs with frequency coverage from 120 to 168 MHz and archived with sufficient spectral and time resolution to allow future spectral line studies and subarcsecond resolution imaging. The survey was initiated in mid-2014 in the region of the HETDEX Spring Field. As of November 2016 we will have observed 20% of the sky above a declination of 25 • and we are preparing to further increase our observing rate. The main challenge of the survey is to robustly and efficiently perform a complex direction-dependent calibration of very large datasets.
This is crucial in order to exploit the full potential of our LOFAR datasets. To demonstrate that such a reduction can reach our observational aims we have used the facet calibration technique, which was developed by  van Weeren et al. (2016a)  and  Williams et al. (2016) , to perform a directiondependent calibration on one of the LoTSS datasets. The result is a high fidelity 120-168 MHz image with a resolution of 4. 8 × 7. 9 and a sensitivity of 100 µJy/beam. These final high-resolution, high-fidelity LoTSS images will facilitate significant contributions to a wide variety of astronomical research areas and we intend to release such images to the wider scientific community in the future once our reduction strategy is fi-nalised and we have processed a large area of the sky. In this publication we have instead publicly released preliminary images and catalogues from a completely automated directionindependent calibration of 63 datasets in the region from right ascension 10h45m00s to 15h30m00s and declination 45 • 00 00 to 57 • 00 00.
Acknowledgements TS and HR acknowledge support from the  ERC   Advanced Investigator programme NewClusters 321271. PNB, JS, WLW, MJH and VH are grateful for support from the  UK STFC  via grants  ST/M001229/1 ,  ST/M001008/1  and  ST/J001600/1. EKM acknowledges support from the  Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) , through project number  CE110001020. AD acknowledges support from the  BMBF , through project  05A15STA. MH acknowledges financial support by the  DFG  through the Forschergruppe 1254. RM gratefully acknowledge support from the  European Research Council  under the European Union's  Seventh Framework Programme  (FP/2007-2013) / ERC  Advanced Grant  RADIOLIFE-320745. GJW gratefully acknowledges support from The  Leverhulme Trust. JZ gratefully acknowledges a  South Africa National Research Foundation Square Kilometre Array Research Fellowship.