dataesr/scientific-paragraphs-categorization huggingface dataset:
Second, we used the fastAnc function in phytools to estimate the maximum likelihood ancestral states for mushroom body and rCBR volumes at each node. The presence of pollen feeding at internal nodes in the Heliconiini tree was estimated using three different methods: (1) MCMC stochastic character mapping in phytools  75  (2) maximum likelihood using the ace function in the R package ape v 5. 5  76  and (3) maximum parsimony using the asr_-max_parsimony function in the R package castor v1. 7. 0  77. Variation in the number of Kenyon cells, calyx synapses, microglomeruli, and in the volumes of the visual and olfactory calyces were explored using a series of generalised liner models (GLMs) and GLMMs, using the glm and glmer function from the R package lme4 v 1. 1-30  78  , respectively. For interspecific differences, species was treated as a fixed effect, and for differences between Heliconius and outgroup Heliconiini, species was treated as a random effect and Heliconius membership as a fixed effect.
Pairwise differences were assessed by calculating the estimated marginal means using the function emmeans in the R package emmens v 1. 7. 0 and correcting for multiple comparisons using the Tukey test  79. Analysis of variation in the scaling relationship between the visual and olfactory calyces was additionally tested for using the function sma from the R package smatr  73  and the R package bayou  72. Recall performance in the behavioural assays was analysed with GLMMs using the glmer function from the R package lme4  78. These models included species and training as fixed effects (in addition to their interaction), with an individual-level random effect. All post hoc comparisons were made by obtaining the estimated marginal means using the R package emmeans and were corrected for selected multiple comparisons using the Tukey test  79.
Acknowledgements We are very grateful to the environmental ministries of  Costa Rica, Panama, French Guiana, Ecuador  and  Peru  for permission to collect and export samples. We thank the  Organization for Tropical Studies, Le Leona Eco Lodge , the  Smithsonian Tropical Research Institute , the  Estación Científica Yasuní ,  PUCE ,  F. Ramirez Castro ,  Neil Rosser ,  Ronald Mori Pezo  the  Dasmahapatra group , and the broader Heliconius research community for support in the field and for discussions, and to  Swidbert Ott  for advice and encouragement early on in this project. We are grateful to the  Wolfson Bioimaging Centre, University of Bristol , the  University College London Confocal Imaging facility , and  Matt Wayland  and the  Dept. of Zoology Imaging Facility, University of Cambridge , for imaging assistance.
This work was supported by a  Royal Commission  for the  Great Exhibition Research Fellowship  (S. H. M. ), a  Leverhulme Trust   Early Career Fellowship  (S. H. M. ), a  Short-term STRI Fellowship  (S. H. M. ), a  Royal Society Research  Grant (S. H. M. ), a  Newton Trust INT Research Grant  (S. H. M. ), a  NERC Independent Research Fellowship   NE/N014936/1  (S. H. M. ), an  ERC Starter Grant   758508  (S. H. M. ) and a  PhD Studentship  from  Trinity College, Cambridge  (F. J. Y. ).
Context. Using data from eROSITA, the soft X-ray instrument aboard Spectrum-Roentgen-Gamma (SRG), we report the discovery of two new hard transients, eRASSU J050810. 4-660653 and eRASSt J044811. 1-691318, in the Large Magellanic Cloud. We also report the detection of the Be/X-ray binary RX J0501. 6-7034 in a bright state. Aims. We initiated follow-up observations to investigate the nature of the new transients and to search for X-ray pulsations coming from RX J0501. 6-7034. Methods. We analysed the X-ray spectra and light curves from our XMM-Newton observations, obtained optical spectra using the South African Large Telescope to look for Balmer emission lines and utilised the archival data from the Optical Gravitational Lensing Experiment (OGLE) for the long-term monitoring of the optical counterparts.
eROSITA To analyse the data, we used the eROSITA Standard Analysis Software System (eSASS  Brunner et al. 2022 ) version eSASSusers_211214. To produce eROSITA source products like light curves and spectra, we used the eSASS task srctool (see e. g. ,  Maitra et al. 2021; Haberl et al. 2022a). We defined circular regions to extract source (radius 50 , 60 , and 40 ) and background events (from a nearby source-free region; radius 50 , 90 , and 65 ) for eRASSU J050810. 4-660653, RX J0501. 6-7034, and eRASSt J044811. 1-691318, respectively. For the spectra and light curves, we selected all valid pixel patterns (PATTERN = 15). For the light curves, we combined the data from all cameras (telescope modules TM 1-7) and applied a cut in the fractional exposure of 0. 15 (FRACEXP > 0. 15) to exclude data from the edge of the detectors.
XMM-Newton We triggered XMM-Newton follow-up observations from our anticipated ToO programs for the three targets (see Table  2 ). We used the XMM-Newton Science Analysis Software (SAS) 19. 1. 0 1 package to process the data from the European Photon Imaging Camera (EPIC), which is equipped with pn-  (Strüder et al. 2001 ) and MOS-type  (Turner et al. 2001 ) chargecoupled device (CCD) detectors. From the processed EPIC event files, we created such products as images, spectra, and light curves using the SAS task evselect. We performed a maximum likelihood source detection simultaneously on the 15 images from the three EPIC instruments in five energy bands (0. 2-0. 5 keV, 0. 5-1 keV, 1-2 keV, 2-4. 5 keV, and 4. 5-12 keV) as described in  Sturm et al. (2013). The resulting X-ray positions are listed in Table  2.
We extracted energy spectra from circular regions around source (radius 40 , 45 , and 30 ) and nearby background (radius 60 , 60 , and 50 ) for eRASSU J050810. 4-660653, RX J0501. 6-7034, and eRASSt J044811. 1-691318, respectively. Events with PATTERN 1-4 for EPIC-pn  (Strüder et al. 2001)  and PATTERN 1-12 for EPIC-MOS  (Turner et al. 2001)  were selected, applying the conservative event filtering with FLAG 0 for EPIC-pn and EPIC-MOS. The EPIC source spectra were binned to a minimum of 20 counts per bin to use Gaussian statistics and the response files were computed with the SAS tasks arfgen and rmfgen. In modelling the EPIC spectra, we followed the same approach as for the eROSITA spectra with a power law with two absorption column densities as basic model. This model adequately fits the spectra from eRASSU J050810.
Discussion We analysed X-ray and optical data of three HMXB candidates in the LMC. Two of them, eRASSU J050810. 4-660653 and eRASSt J044811. 1-691318, were discovered as new hard X-ray transients in eROSITA data, while RX J0501. 6-7034 was known from observations with the Einstein observatory and ROSAT as candidate for a Be/X-ray binary  (Long et al. 1981; Schmidtke et al. 1994). The arc-second accuracy of the XMM-Newton/EPIC positions allowed us to uniquely identify the optical counterparts of the new transients and confirm the association of the suggested counterpart SV* HV 2289 with RX J0501. 6-7034. Their X-ray spectral and temporal properties, together with the long-term behaviour of optical brightness and colours of the counterparts, and, lastly, the existence of Hα emission, confirm all three objects as Be/X-ray binaries.
Conclusions The discovery of two new Be/X-ray binary systems in eROSITA data and the detection of pulsations from RX J0501. 6-7034 increase the number of Be/X-ray binary pulsars in the LMC to 27. Their spin-period distribution does not show the bimodal characteristics of the SMC pulsars, but more LMC systems are still needed to test if this difference is significant. A90, page 10 of 13 Acknowledgements. This work is based on data from eROSITA, the soft X-ray instrument aboard SRG, a joint Russian-German science mission supported by the Russian Space Agency (Roskosmos), in the interests of the Russian Academy of Sciences represented by its Space Research Institute (IKI), and the Deutsches Zentrum für Luft-und Raumfahrt (DLR). The SRG spacecraft was built by Lavochkin Association (NPOL) and its subcontractors, and is operated by NPOL with support from the Max Planck Institute for Extraterrestrial Physics (MPE).
The development and construction of the eROSITA X-ray instrument was led by MPE, with contributions from the Dr. Karl Remeis Observatory Bamberg & ECAP (FAU Erlangen-Nürnberg), the University of Hamburg Observatory, the Leibniz Institute for Astrophysics Potsdam (AIP), and the Institute for Astronomy and Astrophysics of the University of Tübingen, with the support of DLR and the Max Planck Society. The Argelander Institute for Astronomy of the University of Bonn and the Ludwig Maximilians Universität Munich also participated in the science preparation for eROSITA. The eROSITA data shown here were processed using the eSASS/NRTA software system developed by the German eROSITA consortium. This work used observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA.
The XMM-Newton project is supported by the DLR and the Max Planck Society. This research has made use of the VizieR catalogue access tool, CDS, Strasbourg, France. The original description of the VizieR service was published in  Ochsenbein et al. (2000). This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www. cosmos. esa. int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www. cosmos. esa. int/ web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. LD acknowledges support from the Bundesministerium für Wirtschaft und Energie through the DLR grant FKZ 50 QR 2102.
5 and 18 , respectively. The observations were coadded and calibrated using the piic/gildas 1 software in the final version of the calibration database with the data associated files (DAFs;  Zylka 2013; Berta & Zylka 2022). piic allows for several free parameters to guide the data reduction. They were varied to find the optimum setting, trying to avoid biases and minimize map artifacts. For NGC 891, we ran piic (version of 3/2021) with 40 iterations, using third-order polynomials to fit the subscan timelines, and a threshold for the signal-to-noise ratio of 2 and 4 for 1. 15 mm and 2 mm, respectively, above which a pixel was considered as a source and was protected in each iteration. To guide the algorithm, the inner part of the source was masked using an ellipse of 180 × 20 rotated by the position angle of NGC 891 and centered on the nucleus.
The outermost regions of the disk at these wavelengths show indications of a warped morphology. This morphology is also evident in the H i map at the same spatial scales as the NIKA2 maps, and it becomes more prominent at larger radial distances up to ∼24 kpc from the center of the galaxy. In general, the emission at the NIKA2 wavelengths agrees well with other wavelengths at FIR and submm, even in the outermost regions of the galaxy. A more detailed presentation of the morphology of the mm maps and a comparison with other wavelengths follows in Sect. 5. The observing strategy (fast scanning at ±45 • relative to the major axis of NGC 891) and data reduction (low-order polynomials fit to the timelines, etc. ) were optimized to retrieve the extended mm emission of NGC 891 in the best possible way.
Ancillary data A set of high-resolution maps of the galaxy is necessary for a resolved analysis. Modern instrumentation at infrared (IR) and submm wavelengths renders the resolved analysis of the dusty ISM feasible. High-resolution radio maps are needed to constrain the SED of the radio continuum emission locally. For the purposes of the current analysis, we compiled data ranging from the near-infrared (NIR) up to cm wavelengths. We used photometrical data received from space infrared and submm telescopes: the Spitzer Space Telescope (SST), the Wide-field Infrared Survey Explorer (WISE), Herschel, and the Planck Space Telescope, as well as ground-based telescopes: A7, page 3 of 15  (a)  3. 35 6. 1 1. 4 (5. 02 ± 0. 15) × 10 9 (b) 3. 2% (m) Spitzer (IRAC1) (a)  3. 56 1. 7 0. 6 (5. 07 ± 0. 14) × 10 9 (b) 10.
(4. 66 ± 0. 80) × 10 4 (g) 10% (n) Effelsberg 100 m 28416. (5. 54 ± 0. 30) × 10 4 (h) 10% (n) Effelsberg 100 m 34459. (4. 27 ± 0. 57) × 10 4 (i) 10% (n) EVLA (C-band) (d)  49965. 15. 4 2 (4. 30 ± 0. 52) × 10 4 (b) 2% (d) WSRT 60019. (4. 15 ± 0. 43) × 10 4 ( j) 10% (n) GBT 61813. (3. 48 ± 0. 42) × 10 4 (k) 10% (n) Effelsberg 100 m 62457. (3. 99 ± 0. 41) × 10 4 (l) 10% (n) Effelsberg 100 m 63114. (4. 09 ± 0. 41) × 10 4 (g) 10% (n)   Notes. The NIKA2 observations presented here for the first time are highlighted in bold. The entries with available resolution and pixel size information are the maps we used for the resolved galaxy analysis, while the other observations were used for the global analysis. The indices in parentheses in the first column indicate the repository from which the maps were retrieved, while those in the fifth and sixth columns indicate the references that provide the luminosities and uncertainties: (a) DustPedia database; (b) This work; the James Clerk Maxwell Telescope (JCMT), the Very Large Array (VLA), the Arcminute Microkelvin Imager (AMI), the 100 m Effelsberg Telescope, the Owens Valley Radio Observatory (OVRO), the Westerbork Synthesis Radio Telescope (WSRT), and the Green Bank Telescope (GBT).
A complete list of the telescopes and the detectors is given in Table  1. Enriching the available dataset with the NIKA2 maps, presented in this work (see Sect. 2. 1), allows for a high-resolution study of NGC 891 at approximately kiloparsec scales. In order to perform a multiwavelength study, all the maps were convolved to a common spatial resolution. Considering the need to keep the resolution as high as possible, we considered maps of 25 (1. 17 kpc) resolution or lower. This excluded the SPIRE -500 µm map of 36. Because the submm part of the spectrum is well represented at many wavelengths, omitting the SPIRE -500 µm map from the resolved analysis is not expected to introduce any major uncertainties in constraining the SED. Infrared and submm maps were collected from the DustPedia database 2  , and radio maps were compiled from the NASA/IPAC Extragalactic Database (NED) 3.
Data processing We corrected all maps for background emission using the Python Toolkit for SKIRT (PTS;  Verstocken et al. 2020)  framework. First, we masked all pixels belonging to NGC 891 within an elliptical aperture. Then, we used the mesh-based background estimation from photutils  (Bradley et al. 2018)  to estimate the large-scale pixel variations around the galaxy. In this method, a particular image is divided into a grid of rectangular regions in which the background is estimated. Following the method of  Verstocken et al. (2020) , we defined square boxes with a side of six times the FWHM of the image. The background emission and its standard deviation were calculated by interpolating the photutils maps within the central ellipse of the galaxy. Then, the background emission was subtracted from the original image.
For the NIKA2 maps, only a small offset was fit and substracted that only accounts for less than 0. 6% of the total emission at 1. 15 mm and for less than 0. 1% at 2 mm. After the background was subtracted, the error maps were generated for each waveband. For the error maps, we calculated the pixel-topixel noise by measuring the deviation of the pixel values from the smooth background. Maps of the galaxy with a signal-tonoise ratio higher than three in each pixel were then created in order to be used in the subsequent SED modeling analysis. Pixels with fewer than two measurements between 60 and 500 µm were masked out in order to ensure that there are sufficient data to constrain the dust component. The observed NIKA2 data may be contaminated by line emission. We corrected the 1. 15 mm NIKA2 emission for the strongest possible contaminant, the CO(2-1) line, following the method described in Drabek et al.
HerBIE SED fitting tool In order to infer the physical parameters of the dust content and also of the radio emission, we used the hierarchical Bayesian inference for dust emission (HerBIE) SED fitting code. HerBIE was described in  Galliano (2018)  and  Galliano et al. (2021). Using this code, we were able to reveal the integrated galaxy properties, but also to derive the properties of the galaxy on local scales along the line of sight. The HerBIE SED fitting code is able to extract information about the basic properties of galaxies using a hierarchical Bayesian approach. This means that the prior distributions A7, page 5 of 15 are not set before running, but are inferred from the data. This method is more robust than the least-squares approach, for example, in deriving parameters close to the true values and in computing realistic uncertainties.
THEMIS dust model HerBIE incorporates the advanced dust model THEMIS  (Jones et al. 2013 (Jones et al. , 2017)) , which consists of core-mantle carbon and silicate grains. The mantles on all grains are photoprocessed, H-poor, atomic-rich carbon. The size-dependent optical properties of this model were constrained as much as possible by laboratory data. HerBIE offers the opportunity of modeling different physical conditions by taking into account realistic optical properties, size, starlight intensity distributions, and stochastic heating  (Guhathakurta & Draine 1989 ). The code takes the color correction and the calibration uncertainties of each band into account (see Table  1 ). For this study, we used the module powerU, which includes the formulation for a nonuniformly illuminated dust mixture, the starBB, which computes the direct or scattered starlight, and the radio module, which combines the free-free and the synchrotron emissions.
In this way, the stellar emission, the emission from insterstellar dust, but also the radio emission (taking into account the contributions from both the free-free and the synchrotron radiation) were constrained on global scales. The photometry data (luminosity values) for the global SED fitting are listed in Table  1. The luminosities derived in the current study (labeled "b" in Table  1 ) were computed within an ellipse centered at the center of the galaxy (see Fig. 1 ), with major and minor axes of 14 and 2. 2 kpc, respectively. This configuration ensured that the bulk of the emission originating from the disk of the galaxy was measured. The median background level and its RMS value were calculated within an elliptical ring of inner major and minor axes of 18. 2 and 7 kpc, and outer major and minor axes of 23 and 12 kpc, respectively.
The width of the model SED is representative of the uncertainty of HerBIE when it derives the SED. Overall, the global SED is well constrained by the observations, which is also indicated by the relatively low value of 2. 3 of the reduced χ 2 (24 degrees of freedom are considered in this case for a total number of 34 measurements). The best-fit parameters derived with the HerBIE code are presented in Table  2. The quest for a correct determination of the dust mass in a galaxy is a longstanding problem and is mostly related to the availability of the appropriate measurements. First attempts to measure the dust mass of a galaxy were made in the Infrared Astronomical Satellite (IRAS) era, in which observations were only sensitive to the warm dust. This resulted in a strong underestimation of this parameter.
Conclusions We explored the complex mm wavelength range of the SED of the edge-on nearby galaxy NGC 891. We presented new observations of the galaxy at 1. 15 and 2 mm obtained with the NIKA2 camera on the IRAM 30 m telescope. Making use of these unique mm data combined with a set of multi-wavelength ancillary data and the HerBIE SED fitting code, we conclude the following: -By comparing the modeled maps at 1. 15 and 2 mm, we find that there is significant evidence of submm/mm dust emission in excess compared to the dust model in the outermost regions of the galaxy (between 10 and 12 kpc). The NIKA2 fluxes are higher by up to 25% than the model-predicted emission. -Decomposing the emission at mm wavelengths into dust, free-free, and synchrotron, we find different morphologies of each component in the disk and in the halo of the galaxy.
Acknowledgements. We would like to thank the referee,  Santiago Garcia-Burillo , for the useful comments and suggestions, which helped improving the quality of the manuscript. The research work was supported by the  Hellenic Foundation for Research and Innovation (HFRI)  under the  3rd Call for HFRI PhD Fellowships  (Fellowship Number: 5357). We would like to thank the  IRAM  staff for their support during the campaigns. The NIKA2 dilution cryostat has been designed and built at the  Institut Néel. In particular, we acknowledge the crucial contribution of the  Cryogenics Group , and in particular  Gregory Garde ,  Henri Rodenas ,  Jean-Paul Leggeri ,  Philippe Camus. The NIKA2 data were processed using the Pointing and Imaging In Continuum (PIIC) software, developed by  Robert Zylka  at the  Institut de Radioastronomie Millimétrique   (IRAM)  and distributed by IRAM via the GILDAS pages.
PIIC is the extension of the MOPSIC data reduction software to the case of NIKA2 data. This work has been partially funded by the  Foundation Nanoscience Grenoble  and the  LabEx FOCUS   ANR-11-LABX-0013. This work is supported by the  French National Research Agency  under the contracts " MKIDS ", " NIKA " and  ANR-15-CE31-0017  and in the framework of the " Investissements d'avenir" program  ( ANR-15-IDEX-02 ). This work has benefited from the support of the  European Research Council Advanced Grant ORISTARS  under the  European Union 's  Seventh Framework Programme  (Grant Agreement no. 291294 ). F. R. acknowledges financial supports provided by  NASA  through  SAO  Award Number  SV2-82023  issued by the  Chandra X-Ray Observatory Center , which is operated by the  Smithsonian Astrophysical Observatory  for and on behalf of  NASA  under contract  NAS8-03060.
This work was supported by the  Programme National "Physique et Chimie du Milieu Interstellaire" (PCMI) of CNRS/INSU  with  INC/INP  and the  Programme National Cosmology et Galaxies (PNCG) of CNRS/INSU  with INP and  IN2P3 , co-funded by  CEA  and  CNES. M. B. , A. N. , and S. C. M. acknowledge support from the  Flemish Fund for Scientific Research (FWO-Vlaanderen , research project  G0C4723N ).
The observation of the polarised emission from the Cosmic Microwave Background (CMB) from future ground-based and satellite-borne experiments holds the promise of indirectly detecting the elusive signal from primordial tensor fluctuations in the form of large-scale B-mode polarisation. Doing so, however, requires an accurate and robust separation of the signal from polarised Galactic foregrounds. We present a component separation method for multifrequency CMB observations that combines some of the advantages of map-based and powerspectrum-based techniques, and which is direcly applicable to data in the presence of realistic foregrounds and instrumental noise. We demonstrate that the method is able to reduce the contamination from Galactic foregrounds below an equivalent tensor-to-scalar ratio r FG 5×10 -4 , as required for next-generation observatories, for a wide range of foreground models with varying degrees of complexity.