dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS We thank the aquariology service of the  Yilan Marine Research Station (ICOB, Academia Sinica in Taiwan) , who provided the larvae used in this study. We also deeply thank  Kinya Ota  who provided a great help for microscopy and time-lapse movie settings and acquisitions. We thank  Carole Petetin  who drew Figure 1. We also thank  Stephanie Bertrand ,  Laurence Besseau ,  Marleen Klann ,  Jamie Canepa , and  Billy Moore  for their help on the morphological observations and critical reading of the manuscript. This study was supported by  Agence Nationale de la Recherche  ( ANR-19-CE34-0006-Manini  and  ANR-19-CE14-0010-SENSO ).
(2019)  from data obtained as part of the HOBYS  (Motte et al. 2010; Hennemann et al. 2014)  and Hi-GAL projects  (Molinari et al. 2010 ). The region outlined in green represents the area mapped with GLOSTAR. A few well-known star-forming regions and radio continuum sources  (Downes & Rinehart 1966)  are labeled in yellow. 3 8 • 4 0 • 4 2 • 4 4 • 76 • 77 • 78 • 79 • 80 • 81 • 82 • 83 • Galactic Longitude 4 2 • 2 0 h 2 4 m 2 0 h 3 6 m 2 0 h 3 6 m 2 0 h 3 6 m 2 0 h 4 8 m 2 0 h 2 4 m 2 0 h 3 6 m 3 8 • 4 0 • -1 • 0 • 1 • 2 • Galactic Latitude Table  1. Summary of the VLA observations. Observing Date Observing Date Galactic coverage Beam size a ; PA D-conf. Notes. ( a) These values are for the methanol dirty cubes constructed for the D-array configuration data. and second most frequently found interstellar maser line (e.
Observations and data reduction The observations were carried out as part of the GLOSTAR survey, which is described in detail in  Brunthaler et al. (2021). Here we discuss the Cygnus X region portion of the survey. To characterize the radio emission and various tracers of star formation, we carried out simultaneous observations of C-band continuum emission (covering 4. 2-5. 2 and 6. 5-7. 5 GHz), the methanol (CH 3 OH) line at 6. 7 GHz, seven radio recombination lines  (H96α, H98α, H99α, H110α, H112α, H113α, and H114α) , and formaldehyde (H 2 CO) transition at 4. 8 GHz. Observations were taken in both the D and B configurations to simultaneously achieve the best sensitivity for extended emission and excellent angular resolution (see Table  1  for details). The D-and B-configuration data provide angular resolutions of 15 × 11 and 1.
5 × 1. 0, respectively. This corresponds to approximate physical scales of 0. 1 pc and 1700 au, respectively, at a distance of 1. 4 kpc. Two 1 GHz wide base bands in full polarization mode were registered for the continuum. These were centered at 4. 7 and 6. 9 GHz and consisted of eight 128 MHz wide spectral windows each. The methanol maser line, which has a rest frequency of 6668. 5192 MHz  (Breckenridge & Kukolich 1995) , was observed with 8 MHz of bandwidth and 2048 channels, resulting in a channel spacing of 0. 176 km s -1 , and a total velocity coverage of 360 km s -1. Our observations, which covered almost the whole Cygnus X complex (i. e. , an area of 7 o × 3 o ), required a total of 28 epochs, which were scheduled as part of GLOSTAR under program ID 14A-420. Each epoch observed a 1 o ×1.
5 o strip (see Table  1 ), typically using 532 single pointings. Two 11-second scans were spent on each pointing for a total (on-source) integration time of ∼15 seconds. The spectral line data from each epoch were calibrated independently within the Common Astronomy Software Applications (CASA) package using version v4. 6. 0 and a customized version of the VLA pipeline. The continuum subtraction was performed on the visibility data using the CASA task uvcontsub, where we excluded channels expected to contain emission lines in order to fit the continuum. Specifically, we excluded the local standard of rest (LSR) velocity range from ∼ -30 to +20 km s -1 for the methanol line, which covers the velocity range of the complex  (Schneider et al. 2006). The calibrated visibilities were imaged using the CLEAN algorithm as implemented in the package tclean within CASA version v5.
The synthesized beams are on average 15 × 11 at position angle (PA)=-49 o and 1. 5 × 1. 0 at PA=-33 o in the D and B configuration, respectively. The 1σ rms noise measured in channels free of maser emission is, on average, 0. 028 Jy beam -1 per 0. 18 km s -1 channel for both configurations. To complement our study, we also analyzed GLOSTAR continuum images toward sites with maser emission. A full description of the GLOSTAR continuum data calibration and imaging is given in  Brunthaler et al. (2021) , while the full analysis of continuum images of Cygnus X will be presented in a forthcoming paper. Here, we briefly discuss the imaging strategy. The calibration and imaging of the continuum data was performed with the Obit package  (Cotton 2008). The 2 GHz bandwidth was first rearranged into nine frequency subbands, which were used to image each pointing individually.
4. 5). Methanol line data from Effelsberg were also inspected to look for flux variations in the VLA-detected masers  (Sect. 4. 4). The noise in the continuum images is not uniform, but rather varies across the mapped region, and can be high around strong sources with complex or extended emission. We locally measured the noise in regions close to the maser locations, resulting in 1σ values in the range from 0. 056 to 0. 43 mJy beam -1 for B-configuration images. For the D configuration, the 1σ rms noise ranges from 0. 10 to 2. 6 mJy beam -1. The higher values measured in D-configuration data are due to bright extended emission, which is present across the Cygnus X region, and are resolved out by the array in the B configuration. The highest local rms noise occurs around the strong radio source, DR21, a compact HII region.
4 × 3. 4) for the D configuration (B configuration) centered on the recorded brightness peak position. Additionally, we used the visibility data from all VLA pointings (observed at any date) that lay within the 21 × 21 region. The cubes were CLEANed to the expected rms by setting a threshold of 38 mJy. This threshold corresponds to the expected 1σ rms for a single field. The final sensitivities, however, are higher (cf. Sect. 2) because each field was covered by six neighboring fields. Dand B-configuration data were imaged separately using a velocity spacing of 0. 18 km s -1. The spectral extent of these cubes covers LSR velocities from -100 to +50 km s -1. The CLEANed cubes produced for all potential source candidates were first scanned with our source extraction code and then inspected visually to search for detections.
2, respectively. For a maser detected at S/N=10, the formal (statistical) precision in position is ≈ 0. 7 and ≈ 0. 06 for the D and B configurations, respectively. However, additional errors -due to, for instance, uncompensated atmospheric delays that arise when applying the phase corrections determined for the calibrator sources to the Cygnus X data -likely worsen the position accuracy. In order to estimate realistic position uncertainties, we compared our VLA positions with the positions determined from observations with the European Very-long-baseline interferometry (VLBI) Network (EVN;  Rygl et al. 2012 ; see Appendix A for details). For the B configuration, the differences have rms values of 0. 15 and 0. 12 and mean values of 0. 09 and 0. 05 in RA and Dec. , respectively. Thus, additional position errors of ±0.
Detected methanol masers We detected methanol maser emission toward 13 different locations and one case of methanol absorption (toward the continuum emission of the compact HII region DR21); two of these maser sources (G76. 8437+0. 1233 and G78. 9884+0. 2211) are newly detected. The spatial distribution of these methanol sources is shown in Fig. 1 , overlaid on a mosaic image obtained at 500 µm with the Spectral and Photometric Imaging REceiver (SPIRE) aboard the Herschel Space Observatory  (Cao et al. 2019 ) from data taken as part of the Herschel imaging survey of OB Young Stellar objects (HOBYS;  Motte et al. 2010; Hennemann et al. 2014 ) and the Herschel infrared Galactic Plane Survey (Hi-Gal;  Molinari et al. 2010). Remarkably, several of the masers (five in total) are associated with the ridge of dense molecular material that extends from DR21 to W75N, which is the region with the highest degree of star formation activity in Cygnus X and home to numerous high-mass stars.
In order to derive the properties (mass, temperature, and luminosities) of these dust cores, we fit Observed spectra of the 13 sources with methanol maser emission and the one with methanol absorption. For every source, the top and bottom panels represent D-and B-configuration data, respectively. These spectra were extracted at the peak pixel from the data cubes (see text). The vertical lines show the systemic LSR velocities of the dense molecular gas of the star-forming regions that host the masers, which were taken from the literature (see Table  6 ). the spectral energy distribution (SED) of the dust emission with a modified blackbody model, where B ν (T ) is the Planck function for the temperature, T , of the dust and M is the core mass. Here, we adopted a dust mass opacity of κ ν = κ 0 (ν/ν 0 ) β , where κ 0 = 0.
2007). Not all dust cores associated with the methanol sources were covered by the observations of  Motte et al. (2007). Thus, we used 1. 2 mm IRAM data for eight sources and 1. 1 mm Bolocam data for six sources. Figure  4  displays the images of Data were retrieved from the Canadian Astronomy Data Centre. F ν = κ ν B ν (T )M D 2 , (2) (sub)millimeter continuum data for the GLOSTAR 6. 7 GHz methanol masers. The images are 3 × 3 in size and are centered at the positions of the masers. In the SED we also show infrared data from the Infrared Array Camera (IRAC) 3. 6, 4. 5, 5. 8, and 8 µm and the Multiband Imaging Photometer for Spitzer (MIPS) 24 µm bands taken as part of the Spitzer Legacy Survey of the Cygnus X Complex  (Beerer et al. 2010). IRAC aperture photometry and MIPS point spread function (PSF) photometry were retrieved from the NASA/IPAC Infrared Science Archive (IRSA ).
In the case of G78. 8870+0. 7087 and G81. 8713+0. 7807, for which we have a limited number of data points due to saturation, the 70 µm point was included in the fit of the cold component, and the data were weighted with their 20% flux errors. The IRAC data points between 3. 6 and 8 µm -likely originating from a third, hot and inner component -were not used in the SED fitting. The image of this source has issues in the 3. 6, 4. 5, 5. 8, and 8 µm bands as well. Thus, the fluxes from these bands are not shown in the SED. Article number, page 9 of 44 A&A proofs manuscript no. ms Table  6. Properties of the detected methanol line sources. Finally, far-infrared (FIR) luminosities were obtained by integrating the SED of the cold component over wavelength,.
Although we follow a similar approach to  Cao et al. (2019)  to estimate core properties, here the fluxes were extracted individually at each wavelength using the radio flux plug-in in DS9. The integrated source flux was obtained over an aperture that delimits emission within a 30% contour. The local background flux was estimated over an aperture farther out from the source and then subtracted from the source flux. We note that fluxes extracted in this way do not show large deviations from the model fit, unlike some fluxes extracted with the getsources package used by  Cao et al. (2019) , especially at 450 µm. The (sub)millimeter emission in the DR21 ridge is complex and extended, which probably affects the performance of background subtraction by getsources. As a result, the masses derived by us agree with those from  Cao et al.
(2019)  within ∼55%. When comparing the estimated masses with the masses obtained by  Motte et al. (2007)  for the eight overlapping cores from 1. 2 mm data alone, after correcting for the different distance and dust mass opacity used by these authors, we see a slightly better agreement, with a relative difference of ∼50% on average. The properties derived above for the dust cores that are associated with a methanol maser source are used in Sect. 5 to investigate the relationship between methanol masers and massive star-forming dust cores. Pestalozzi et al. (2005)  published a catalog of all known 6. 7 GHz methanol masers from both targeted and unbiased surveys in the Galactic plane. Their catalog contains six masers spread throughout the region observed by GLOSTAR in Cygnus X.
More recently,  Yang et al. (2019)  performed a new targeted survey in the whole Galaxy with the 65 m Shanghai Tianma Radio Telescope. They observed targets from the all-sky Wide Field Infrared Survey Explorer (WISE) point source catalog that could be associated with 6. 7 GHz methanol masers based on their WISE magnitudes. We detected their three new masers and the five already known masers with WISE bright emission listed in  Yang et al. (2019). The only maser from this catalog not detected by us, likely due to variability, is G81. 794+0. 911. However, we do not see this maser in recent Effelsberg data either. In summary, out of thirteen GLOSTAR masers, four were previously reported by both  Pestalozzi et al. (2005)  and  Hu et al. (2016) , five by both  Hu et al. (2016)  and  Yang et al.
Acknowledgements. The authors are grateful to the anonymous referee, whose comments helped to improve this paper. G. N. O. -L. would like to thank  Antonio Hernandez-Gómez  for a detailed reading of an early version of the manuscript and valuable suggestions. We thank  Yue Cao  and  Keping Qiu  for providing mosaics maps of (sub)millimeter emission. We also thank  Nicola Schneider  for sharing her IRAM CO data. G. N. O. -L. acknowledges support from the  von Humboldt Stiftung. T. Cs. has received financial support from the  French State  in the framework of the  IdEx Université de Bordeaux Investments  for the future Program. H. B. acknowledges support from the  European Research Council  under the European Community's  Horizon 2020 framework program  ( 2014-2020 ) via the  ERC Consolidator grant  " From Cloud to Star Formation (CSF)"  (project number  648505 ).
Added value of this study This study adds to the scientific literature by comparing the Intergrowth-21st newborn charts with national charts customised to each country's population in  15  European countries, making it possible to assess the consequences of using one universal chart versus country specific charts in an international context. The study uses routine population data on birthweight from 1. 5 million births in European countries participating in the Euro-Peristat network. We find large differences in the prevalence of both SGA and LGA infants between international and national charts, with a strong north to south gradient when using international charts, demonstrating the major impact of the choice of chart on the comparative assessment of the burden of fetal growth anomalies by country and their relative rankings.
Data source The data source is a network study on intrauterine growth conducted in 2016À2017 which included 15 countries (Austria, Belgium, Cyprus, Estonia, Finland, France, Latvia, Lithuania, Luxemburg, Malta, Norway, Poland, Portugal, Scotland and Switzerland). Individual-level information was collected on five variables (birthweight, gestational age at birth, infant sex, vital status at birth (termination of pregnancy, stillbirth, livebirth), and neonatal death before 28 days of life) for all singleton births in the years 2010 and 2014. Data came from birth registers, civil registration systems and routine surveys (see Appendix A). Inclusion criteria, based on Euro-Peristat definitions, were a gestational age of at least 22 weeks of gestation or, if gestational age was missing, birthweight of at least 500 g.
Gestational age was requested in complete weeks of gestation (e. g. a birth at 37 weeks and 6 days of gestation was recorded with a gestational age of 37 weeks). The definition of gestational age was the final estimate in the obstetrical records at birth. Most countries provided data for their whole population for the given years, except for France where data come from a national survey including all births during a one-week period in all maternity hospitals in France. France and Poland provided information on stillbirths, but not on neonatal deaths since they weren't collected in the French Perinatal Survey and they couldn't be linked for the Polish data. France and Poland provided data for the year 2010 only, Portugal and Switzerland provided data for the years 2010 and 2013, and Cyprus provided data from 2007 to 2013 to allow for larger sample sizes in this small country.
Ethical approvals This study uses a sub-set of Euro-Peristat's core variables, which include no indirect or direct personal identifiers. Data are provided to Euro-Peristat in accordance with each data provider's regulations for data use. The procedures for obtaining and maintaining the Euro-Peristat core indicator database were authorised by the French Advisory Committee on Use of Health Data in Medical Research (N°17À048, 30/03/17) and the French National Commission for Data Protection and Liberties (CNIL, DR. À2019À089, 26/03/19).
Study population Among the 1496,321 singleton births in the 15 countries during the study period, we included live births and stillbirths from 33 to 42 weeks of gestation because the Intergrowth-21st newborn charts use these gestational age limits (N = 1477,840). We excluded terminations of pregnancy when it was possible to distinguish them from stillbirths in the dataset (N = 5); this was not possible in Belgium, Cyprus and Luxemburg (in 2010 only). Newborns with undetermined or unknown sex and with missing data on birthweight or gestational age were excluded (N = 2378). Missing data constituted less than 1% of all data, except for Luxembourg (1. 8%). The final sample included 1475,457 births from 15 countries with data on stillbirths and 1062,154 births from 13 countries with data on neonatal deaths and stillbirths.
Funding statement The  Euro-Peristat  network receives funding from the  European Commission  as part of the  InfAct (Information for Action) Joint Action (Consumers, Health, Agriculture  and  Food Executive Agency (CHA-FEA)  Grant  n°801 , 553 ). This work was conducted as part of the  Con-cePTION  project which has received funding from the  Innovative Medicines Initiative 2 Joint Undertaking  under grant agreement No  821 , 520. This Joint Undertaking receives support from the  European Union 's  Horizon 2020 research and innovation program  and  EFPIA. Alice HOCQUETTE was supported by a PhD grant from  EHESP. While the research leading to these Results was conducted as part of the  ConcePTION consortium , this paper only reflects the personal views of the stated authors.
Population and Clinical Data Between January 2015 and March 2018, consecutive AIS-LVO patients with a M1 occlusion who underwent MT triage at our comprehensive stroke center were retrospectively reviewed in this single-center study. Included patients underwent MT triage by MRI that included an axial T2 * sequence, MR angiogram and MR perfusion. Patient clinical and treatment data were extracted from a prospectively maintained stroke database and the electronic medical record.
Imaging Data and Evaluation All imaging were performed on either a 1. 5T GE Signa or 3. 0T GE MR750 MRI scanner using standard departmental protocols, using an eight channel GE HR brain coil (GE Healthcare, Milwaukee, Wisconsin). Technical details and parameters for the sequences used in this study were as follows. Diffusion Weighted Imaging parameters: TR = 6,000 ms, TE = 78. 2 ms; b-value = 0 and 1,000 s/mm 2 ; flip angle 90 • , and slice thickness of 5 mm. Perfusion-weighted imaging was performed using a dynamic susceptibility contrast technique following the intravenous administration of Multihance (529 mg/ml; Bracco, Milan, Italy) at a dose of 0. 2 ml/kg body weight into an antecubital vein at a rate of 4. 0 mL/s using a power injector  (19). Perfusion parameters were: TR = 1,800 ms, TE = 35 ms; flip angle 80 • , and slice thickness of 5 mm.
Standard perfusion maps, including time-tomaximum of the residue function (TMax), were generated using the automated RAPID software (iSchemaView, Menlo Park, CA)  (20). Quantitative perfusion delays were assessed as the volumes of cerebral tissue with TMax delays of >6 and 10 s using RAPID. The ischemic penumbra was defined as the volume of brain tissue with a TMax >6 s on gadolinium-based dynamic-contrast susceptibility imaging. Collaterals were measured by HIR, which was defined as the volume of brain tissue with TMax >10 s volume divided by the volume of tissue with TMax >6 s  (10). A lower HIR ratio indicates a less severe perfusion delay and more robust collaterals  (8, 10, 12, 13). Core infarction and TMax volume measurements were quantified by an automatic software (RAPID, iSchemaView, Menlo Park, CA, USA).
, , 2016;; Reznikov et al. , 2013; Revach et al. , 2015). The principle of FIB-SEM is that a biological sample is exposed to a focused ion beam (usually consisting of Ga ions) capable of removing thin layers of material by milling in a highly precise manner (5-10 nm). Between each sample milling, a scanning electron beam is used to image the newly exposed surface. By repeating this process hundreds or even thousands of times, a large sample volume can be acquired with an isotropic voxel reaching 3 nm  (Wei et al. , 2012; Xu et al. , 2020) , in resin and at room temperature. With the recent development of automated acquisition procedures, even relatively large volumes (>1,000 mm 3 ) can be acquired within a few days, providing large ultrastructural datasets  (Peddie and Collinson, 2014; Narayan and Subramaniam, 2015).
, 2017). We observed that 100% of the cells displayed some BODIPY staining (Figure  2 ) and selected cells for acquisition based on their LDs distribution. Cells suitable for acquisition showed an average of 37 G 22 LDs/cell (N = 63, median = 29 LDs/cell) (Figure  2D ), which assured having at least 15 LDs for correlation within a sub-volume of the cell. Whole grid landmarks such as symbols or missing grid squares were used to relocate cells in the FIB-SEM (Figure  2A ). One or two cells were acquired in one acquisition session, which lasted 36-60 h (Figure  2E ). Correlation of both datasets was performed under the ICY software  (De Chaumont et al. , 2012). We initialized the correlation by manually marking the centers of each LD in the FIB-SEM stack. In parallel, the centroids of the LDs were automatically defined by wavelet spot detection in the FM stack.
On analysis of the resulting image transformation (Figures  2F-2I ), we observed image stretching in the yz direction of the FIB-SEM coordinate system (Figure  2H ). This distortion can be explained by uncompensated drift during stack acquisition. We used fast scanning with line averaging to provide an acceptable compromise between the signal to noise ratio and charging artifacts. However, some charging of the surface occurs, which likely causes the slight image distortion in the xy plane. FIB-SEM data are also collected at a 90 with respect to the FM data, which means that the axis with the lowest resolution (z) is different in FM and FIB-SEM. However, the contribution of this factor to the overall correlation precision is accounted for in the error estimation calculation. Although in theory more fiducials should increase the correlation precision, this is not always the case as it also depends on their localization accuracy and on how they are distributed in the volume  (Paul-Gilloteaux et al.
(I) Two representative micrographs showing the overlay of the transformed FM on top of the FIB-SEM dataset (magnified 31. 5 from E). The affine transformation allowed for correlation of both LDs in the high-LDs-density area (green) as well as the low-LDs areas (orange). and S2D). These experiments show that LDs are suitable and attractive as internal fiducial markers for 3D correlation.