dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgment This work was supported by the  Istituto Nazionale di Fisica Nucleare (INFN) ; the  National Science Foundation  under Grant Nos. NSF-PHY-0605119 ,  NSF-PHY-0500337 ,  NSF-PHY-0855314 ,  NSF-PHY-0902171 ,  NSF-PHY-0969852 ,  NSF-PHY1307204 , and  NSF-PHY-1404205 ; the  Alfred P. Sloan Foundation ; and  Yale University. This material is also based upon work supported by the  US Department of Energy (DOE) Office of Science  under Contract Nos. DE-AC02-05CH11231  and  DE-AC52-07NA27344 ; and by the  DOE Office of Science, Office of Nuclear Physics  under Contract Nos. DE-FG02-08ER41551 ,  DE-FG03-00ER41138 ,  DE-SC0011091 , and  DE-SC0012654. This research used resources of the  National Energy Research Scientific Computing Center (NERSC).
The equinoctial and Russell-McPherron time-of-year/time-of-day patterns Figure  8C  compares the theoretical Russell-McPherron and equinoctial effects by overlaying the F-UT patterns, both derived using the eccentric dipole geomagnetic field model of  Koochak & Fraser-Smith (2017)  with constants interpolated to the year 2007 (the mid-point of 1995-2019, the interval for which 1-minute resolution interplanetary data are available. The dipole tilt angle w was computed as a function of F and UT, being the angle between the Earth's (eccentric) dipole axis M and the geocentric position vector of the subsolar point, S, computed using the SUBSOL routine of the LOWTRAN7 Sun and Moon Models Matlab software package. The colour contours in Figure  8c  give the absolute value of the dipole tilt angle, |w|, superposed on which are contours showing the IMF orientation factor used by P a , namely A h = sin 4 (h/2), where h is the clock angle of the IMF in the GSM frame, computed from a given IMF orientation in the GSEQ frame using the CXFORM Coordinate transformation package described in Section 2.
As for Figure  6 , we mapped the location of the eccentric axial poles in geographic coordinates into the GSEQ frame using the CXFORM Coordinate transformation package, initially written by Ed Santiago of Los Alamos National Laboratory and Ryan Boller of NASA's Goddard Space Flight Centre and re-coded for Matlab by Patrik Forssén (SatStar Ltd & Karlstad University) in 2017. This software package is based on the equations by Mike Hapgood of RAL Space, Rutherford Appleton Laboratory  (Hapgood, 1992). The loci of the eccentric dipole axial poles in the XY frame of the GSEQ reference frame are shown in Figure  9 , in which the rotation of the Earth makes the poles rotate clockwise. The points show the location of the poles at 12 UT. The greater offset in the axial eccentric dipole poles from the rotational pole in the southern hemisphere makes the radius of the orbits larger for the southern hemisphere.
For the observations, the geomagnetic index data are linearly interpolated to hourly values from the 3-hourly indices. Figure  16a  shows the F-UT pattern of P a /P o for the subset of the data when the mean IMF Y component in the GSEQ frame, [B Y ] GSEQ was negative over the prior hour. Figure  16b  shows the corresponding plot for [B Y ] GSEQ > 0. Both plots show the behaviour expected of the R-M effect on solar-wind magnetosphere coupling (dominated by magnetopause reconnection) with [B Y ] GSEQ < 0, giving peak enhanced P a /P o at the March equinox (F % 0. 22) and UT of about 22 hrs, whereas [B Y ] GSEQ > 0 gives peak enhanced P a ⁄P o at the September equinox (F % 0. 73) and UT of about 10 hr. The CXFORM Coordinate transformation package was also used to compute the GSEQ to GSM transformation of unit IMF vectors in the +Y and ÀY directions of GSEQ and to give the IMF clock angle h and hence the Russell-McPherron predictions of the sin 4 (h/2) IMF orientation factor in P a and hence the factor P RM (F, UT).
Analysis of geomagnetic response by IMF Y-component polarity We have also used the model to also simulate the results for the [B Y ] GSEQ > 0 and [B Y ] GSEQ < 0 data subsets. This further subdivision means there are 30 IMF polarity-index permutations and we here show the result for just the one case, the ar(midn) index, in Figure  22. The left-hand column is for IMF [B Y ] GSEQ < 0, the middle column for [B Y ] GSEQ > 0 and the right-hand column for all data. The top row shows the R-M solar wind forcing pattern P RM (F, UT) in each case. The middle panel shows the model predictions of the ar(midn) index and the bottom panel the corresponding averages of the observed ar(midn). It can be seen that agreement is good, and the model successfully predicts both sub-divisions of the data. 4. 4 Large events and the effect of average levels of activity  Lockwood et al.
In the above analysis we used the overall mean of am for the interval 1959-2019 to estimate the overall mean of the transpolar voltage, hU cf i and so evaluate the fractional perturbation DU cf /hU cf i. The above sample numbers for the UT variation in am are sufficient to allow us to divide the am dataset into three 20-year intervals. To investigate the role of hU cf i, we here break the am data into three  20-year intervals, 1960-1979, 1980-1999 and 2000-2019  for which average am values are 21, 25 and 17 nT (by Eq. (  16 ), corresponding to U cf ~39, 43 and 34 kV) and we again compute [V X ] NP and [V X ] SP for the eccentric dipole axial pole locations at the middle of each interval. The observed (black) and modelled (mauve) UT variations (averaged over all F) are shown in parts d-f of Figure  23.
Dedication This paper is dedicated to the memory of Annick Berthelier who, as well as highlighting many issues around the time-ofyear/time-of-day patterns of solar wind forcing and geomagnetic response, did much to help preserve historical geomagnetic data and to maintain the continuation of long sequences of indices. In 1987, what became the International Service of Geomagnetic Indices (I. S. G. I. ) was moved from the Netherlands to France and placed under the joint responsibility of her and her colleague Michel Menvielle. After she died in 1997, at the age of just 54, he noted in her obituary: "We shall all remember Annick's profound sense for the good of the science community and of the stringent necessity for anyone to contribute. This is what pushed her to take charge of I. S. G. I. , a work in which she deeply invested herself in her last years, when she understood that a definite action was needed to ensure the durability of the magnetic indices data base.
A confocal microscope with a 40Â objective (numerical aperture: 0. 47) was used for the 325 nm laser line and a 50Â objective (numerical aperture: 0. 5) was used for the other excitation laser lines. The experimental error was about 2 cm À1. RBS/C was performed at RT on a Van de Graaff AN-2500 Type-A accelerator facility using a 2 MeV helium ( 4 He) ion beam and a silicon PIN diode detector placed at 1651 relative to the beam direction. Post-irradiation damage was evaluated by Monte Carlo (MC) simulations using the computational code McChasy. 24, 25 T PL and PLE were carried out using a Fluorolog 3 Horiba Scientific modular system equipped with a 450 W Xe arc lamp coupled to a monochromator. The emission/excitation was controlled by the entrance and exit monochromators. Both PL and PLE spectra were acquired in the front face geometry.
Rutherford backscattering spectrometry in channelling mode To validate the previous findings, an independent RBS/C study was conducted. With this approach, it is possible to clarify the questions about the damage created by Xe SHI irradiation in the InGaN/GaN MQWs as well as the damage depth profile. Fig. 4  shows RBS/C spectra recorded along the h0001i direction of the InGaN/GaN MQWs before and after irradiation. A representative random (51 off-axis) RBS spectrum is also plotted. Using the McChasy software, the simulation of the random spectrum allows estimating the InN molar fraction to be 0. 21 assuming a nominal quantum well thickness of 2. 7 nm (consistent with X-ray diffraction measurements performed on the MQW-asgr sample -Fig. S2  in the ESI †). This value matches the In composition obtained by m-Raman under 442 nm resonant excitation, confirming the validity of the methodology, and the analysis performed in Section 3.
Acknowledgements This work was supported by the project '' Nano-engineering of wide bandgap semiconductors using ion beams '' (NASIB) by  FCT (Portuguese Foundation for Science and Technology)  and  FEDER  ( POCI-01-0145-FEDER-028011  and  LISBOA-01-0145-FEDER-02966 ). This work was developed within the scope of the project  i3N  ( UIDB/50025/2020  and  UIDP/50025/2020 ) and  INESC MN  ( UID/05367/2020 ) financed by national funds through the  FCT/MEC. J. Cardoso  acknowledges the PhD grant  DAEPHYS-FCT PD/BD/142780/2018  financed by the  European Social Fund (FSE)  and national funds of FCT/MCTES. The irradiation experiments were performed at the  Grand Accelerateur National d'Ions Lourds (GANIL), Caen, France , and the authors thank the  CIMAP , the CIRIL and GANIL staff for their help.
We now turn to the interactions between water molecules, which are encoded in the differences between the coherent and incoherent rates in Figure  1b  (blue and grey data points). A series of kinetic Monte Carlo (KMC) simulations were performed to determine the nature of these forces. The hexagonal hopping model described earlier was combined with an interaction potential, Vpp, between water molecules, of the form Vpp = ± B r 3 = ± p 2 4π 0r 3 , (4) which represents a pairwise dipole-dipole interaction, where p is the effective value of the dipole moment and r is the distance separating the two dipoles. Allowing for either positive or negative prefactors provides the ability to explore both repulsive and attractive interactions. Using trajectories from the KMC simulation, simulated coherence functions and dephasing rates were obtained to compare with the ∆K resolved experimental data, while also adjusting the simulation to reproduce the temperature dependent measurements.
Data and code availability The growth and characterisation of the graphene layer on a Ni(111) surface has been published elsewhere  1. In short, the nickel (111) single crystal used in the study was mounted onto a sample holder and can be heated radiatively by a filament on the back of the crystal, or cooled to 100 K using liquid nitrogen. Prior to the measurements, the Ni surface was cleaned by repeated cycles of Ar + sputtering and annealing at 870 K. A monolayer of graphene on Ni(111) was grown by dosing ethene (C2H4) while holding the crystal at 730 K for several hours. The sample temperature was measured using a chromel-alumel thermocouple. While absolute temperatures can be determined to an accuracy of ±5 K, relative temperature values were determined with an accuracy of ±0. 1 K, which was also confirmed by the reproducibility of the adsorption and dynamics measurements.
Here, most of the quoted tolerance arises from uncertainties in the doser cali-bration and doser position relative to the sample. The determined cross section is in good agreement with other water cross sections in the literature on similar systems (e. g. Σ = 130 Å2 in Ref  10  ). The fraction of the surface covered by ice islands cannot be estimated from the scattering data since the diffraction patterns with and without water adsorption are essentially identical (figure  2d , main paper). It follows that the area of the surface covered by ice is extremely small. We can estimate the separation of ice islands from the r. m. s. distance travelled by an H2O monomer using known conditions for dosing and the measured diffusion constant. At 125 K the impinging flux of molecules was 2. 5 • 10 17 m -2 s -1 and the corresponding rate of adsorption is 0.
Acknowledgements The authors would like to thank  G. Alexandrowicz  for many helpful discussions. A. Tamtögl  acknowledges financial support provided by the  FWF (Austrian Science Fund)  within the project  J3479-N20. M. Sacchi  would like to acknowledge the  Royal Society  for funding his research through the  University Research Fellowship   URF/R/191029  and the  UK's HEC Materials Chemistry Consortium , which is funded by  EPSRC  ( EP/R029431 ), for time on the  ARCHER UK National Supercomputing Service. The work is part of the Ph. D. project of  E. Bahn  who would like to thank the  Ecole Doctorale de Physique of the Université de Grenoble  for funding. The authors acknowledge use of and support by the  Cambridge Atom Scattering Facility  (https://atomscattering. phy. cam. ac. uk) and  EPSRC  award  EP/T00634X/1.
AzTEC Observations Of the 108 targets proposed for the LMT 2014-ES3 campaign (Project 2014AHUGD011, PI: D. H. Hughes), we obtained AzTEC data for 100 sources. AzTEC observations, using the photometry map mode which covers a ∼ 3. 5 arcmin diameter area, were conducted between November 2014 and June 2015 under optimal atmospheric conditions with 225GHz ≈ 0. 06 ± 0. 02 (0. 03 ≤ 225GHz ≤ 0. 11). The integration times devoted to each target were in the range of 3 -50 min (21. 3 hr in total), with a median of 11 min (Table  1 ). Pointing measurements on known quasars close to the targets were made before and after science observations, and were used in the data reduction process to compensate for any pointing drifts, resulting in a r. m. s pointing accuracy 1 arcsec. The data was reduced using MACANA, the C++ version of the standard AzTEC data reduction pipeline (e.
RSR observations Six red-Herschel sources, confirmed with AzTEC to be single systems at high-redshift ( phot 4), were selected for spectroscopic follow-up observations with the Redshift Search Receiver on the LMT (Table  2 ). The RSR is a broadband spectrometer covering the Selected for spectroscopic follow-up with the 3mm RSR (see Table  2 ). 3 mm window (73-111 GHz) with four detectors in a dual-beam dual-polarization configuration (RSR,  Erickson et al. 2007 ). The observations were done using both the 32m and 50m (since 2018) configurations of the LMT. The RSR data was reduced using the D package (Data REduction and Analysis Methods in PYthon, written by G. Narayanan) and following the standard procedure (e. g. Yun et al. 2015; Cybulski et al. 2016; Wong et al. 2017). A careful visual inspection of individual scans was performed to identify and remove those with the noisiest spectral features.
(2017)  who also detected a CO(6-5) transition. Figure  4  shows the identified lines in the RSR spectra. Their fitted parameters are summarized in Table  2. We use these spectroscopic redshifts in Figure  10  to characterize the accuracy of our photometric-redshift determinations. An alternative reduction was produced using a new P wrapper script developed by D. O. Sánchez-Argüelles for the D package, known as _ 2. This script aims to provide the LMT user community with a front-end interface to generate RSR scientific-quality data from raw observations. The _ reduction procedure is very similar to the standard process, and below a brief description is presented. For each detector the RSR backend records the autocorrelation function (ACF) of the observed sky brightness. It is important to notice that the broad 73-111 GHz bandwidth of the RSR is achieved by dividing it into six bands.
The raw data is therefore comprised of six ACFs. The pipeline starts by processing the ACFs using a Fourier transform matrix to reconstruct the spectrum of the astronomical source. At this stage, a user defined low order (≤ 3) polynomial baseline is computed across each band and subtracted from the spectrum. The relatively fast internal switching (≃ 1 kHz) between the RSR beams allows the minimization of the contribution from atmospheric noise into the ACF; nevertheless, small differences in the switching duty-cycle can introduce large baseline artifacts. To increase the detectability of spectral lines, the _ can calculate and subtract 2 The _ and its documentation is publicly available at the LMT github repository https://github. com/LMTdevs/RSR_driver.
DISCUSSION AND CONCLUSIONS As part of the Early Science Phase of the Large Millimeter Telescope, we obtained AzTEC 1. 1 mm observations on a sample of 100 red-Herschel sources. Their red far-infrared colours ( 250 m < 350 m < 500 m ) and bright flux densities ( 500 m ≈ 35 -80 mJy) suggest that they are high star formation rate galaxies (SFRs 500 M ⊙ yr -1 ) at high redshifts ( 3). Combining the AzTEC data with our new deblended Herschel photometry, we constrained the multiplicity fraction in the sample and derived photometric redshifts, IR luminosities, and SFRs for all the sources in the catalog. Our main results are discussed below and are also summarized in Figure  14. Thanks to the FWHM ≈ 9. 5 arcsec angular resolution provided by the 32 m illuminated surface of the LMT (a factor of 4 better than Herschel at 500 m), we found that 8 of the red-Herschel targets break into multiple components (with SNR ≥ 4), which implies a multiplicity fraction of ∼ 9 per cent.
ACKNOWLEDGEMENTS We would like to thank the support and assistance of all the LMT staff. We also thank the anonymous referee for a thorough reading of our paper and for the comments which helped to improve the clarity and robustness of our results. We thank  I. R. Smail  for insightful comments that improved the quality of the paper. A. M. thanks support from  Consejo Nacional de Ciencia y Technología  ( CONA-CYT)  project  A1-S-45680. This work was partially supported by  CONACYT  projects  FDC-2016-1848  and  CB-2016-281948. J. A. Z. and C. M. C. thank the  University of Texas at Austin College of Natural Sciences  for support. C. M. C. also thanks the  National Science Foundation  for support through grants  AST-1814034  and  AST-2009577 , and the  Research Corporation for Science Advancement  from a 2019  Cottrell Scholar Award  sponsored by  IF/THEN , an initiative of  Lyda Hill Philanthropies.
R. J. I. is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) under Germany's Excellence Strategy -EXC-2094 -390783311. M. J. M. acknowledges the support of the  National Science Centre, Poland  through the  SONATA BIS  grant  2018/30/E/ST9/00208. H. D. acknowledges financial support from the  Spanish Ministry of Science, Innovation and Universities (MICIU)  under the  2014 Ramón y Cajal program   RYC-2014-15686  and  AYA2017-84061-P , the later one co-financed by  FEDER (European Regional Development Funds). S. J. M. acknowledges support from the  European Research Council (ERC)  Consolidator Grant C D (ERC-2014-CoG-647939, PI  H L Gomez ) from the  ERC Advanced Investigator Program, COSMICISM  ( ERC-2012-ADG 20120216 ,  PI R. J. Ivison ).
Methods. Our real-time pipeline LUPPI (Low frequency Ultimate Pulsar Processing Instrumentation) is able to cope with a high data rate and to provide real-time coherent de-dispersion down to the lowest frequencies reached by NenuFAR (10 MHz). The full backend functionality is described, as well as the main pulsar observing modes (folded, single-pulse, waveform, and dynamic spectrum). This instrumentation allowed us to detect 172 pulsars in our first targeted search below 85 MHz, including 10 millisecond pulsars (6 of which detected for the first time below 100 MHz). Results. We also present some of the "early science" results of NenuFAR on pulsars: a high frequency resolution mapping of PSR B1919+21's emission profile and a detailed observation of single-pulse sub-structures from PSR B0809+74 down to 16 MHz, the high rate of giant-pulse emission from the Crab pulsar detected at 68.
memory to implement ring buffers 4  in order to allow threads to exchange data and process in parallel. Furthermore it is during this phase that the coherent dispersion chirps 5  are calculated. B) The network thread catches UDP (User Datagram Protocol) packets sent by the beamformer and reads the packet index to look for any missing packets and takes it into consideration to preserve the linearity of the time series. The packets are then stored in the shared memory and a semaphore is used to unleash the computation thread. C) The computation thread is dedicated to feed GPUs with data and get the results back. At this stage, the data blocks are sent to four GPUs (one processing unit per band of 37. 5 MHz). First, a fixed overlap 6  is added to absorb the intrachannel dispersive delay. For a given GPU hardware, the value of the overlap results as a compromise between computing efficiency (which is better when the overlap is small) and the possibility to reach low frequencies (for a given DM value, a larger overlap allows to process data at a lower frequency).
Finally, the result is pushed into the output buffer and a semaphore is activated to launch the write thread. D) The write thread writes the data product out from the output buffer into a RAID 0 (Redundant Array of Independent Disks using data striping) storage unit. The last step is the post-processing to verify that the observation output products are present on the server and to create diagnostic plots ("quicklooks", see §2. 4. 4). The quicklook plots are sent by email to the observer within minutes. If data files are missing on the server a warning email is sent to the observer. The source code of LUPPI is available on the Github 7.
Single-pulse mode In this mode a time series is de-dispersed and integrated in time by a chosen factor (128 by default) to enable the analysis of pulse-to-pulse variations. Data are stored in PSRFITS format and a quicklook program displays the main features of the observation after RFI removal (using the rfifind software from PRESTO 9  , Ransom 2001). This mode is used to observe bright pulsars that show interesting features in their emission beam, such as drifting subpulses, mode changing, or anomalously intense pulses. It will also be used to search for pulsed emission when the DM is higher than 100 pc cm -3 and the scattering is important. Moreover, single pulse data can easily be converted into folded data.
Waveform mode This mode consists in writing the raw complex-voltage data to disk, bypassing the computing thread on Fig. 2. It keeps the full time, frequency and polarisation information from the original raw signal (thus a very large data rate). This mode can be used to perform non-standard analyses, such as scattered giant pulses searches, a census of the Globular Clusters pulsar population, or interstellar and interbinary scintillation studies. Additionally, waveform data can be converted into folded or single pulse data by coherent dedispersion and integration. The two UnDySPuTeD machines also provide LUPPI with additional, independent modes described below:.
The quicklook The creation of a quicklook is a crucial part of the observation because it makes it possible to monitor the operation of the pipeline as well as the quality of the observation with respect to, e. g. , RFI. Its aim is to allow quick validation of an observation and to reduce the response time in case of problem. This python software is based on the PSRCHIVE library and it is designed to be a complete pipeline compatible with all radio telescopes generating folded PSRFITS files. A quicklook of an observation of PSR B0329+54 is shown in Fig. 5. The quicklook plot presents the observation data in all its dimensions: time, phase, frequency, and polarisation in various panels. Panel 1 shows the pulse profile with the total intensity (in black), the linear polarisation (in red), and the circular polarisation (in blue).
Data archive Currently, NenuFAR pulsar data are transferred to the Nancay Data Center (CDN) for temporary storage and distribution within the community. At the CDN, the data are stored on a RAID 6 storage cluster. Pulsar data recorded in folded mode ( §2. 3. 1), single-pulse mode ( §2. 3. 2), and dynamic spectrum ( §2. 3. 4) mode will be kept at the CDN, whereas waveform data ( §2. 3. 3) and data recorded in UDP waveform mode ( §2. 3. 5) are usually only kept temporarily and are removed after processing. A dedicated NenuFAR Data Centre is currently being commissioned, it will have open access user interfaces to data products.