dataesr/scientific-paragraphs-categorization huggingface dataset:
This was the motivation for deferring the publication of the paper; we now feel, given that the replacement detector will be ready in the near future, that it is time to have a reference in the literature for this instrument from the astronomical standpoint. This paper is organised as follows. In Sect. 2 a brief description of the EMIR instrument is given that includes several references to technical papers where the interested reader can find a more in-depth description of the different subunits. Sections 4 and 5 outline the process of multi-slit mask design. Section 6 introduces the instrument data reduction pipeline. Section 7 presents some results obtained during the commissioning and science verification phases. Finally, Sect. 8 summarises the main features of the EMIR instrument and its observing capabilities.
Depending on the choice of slit width, the absolute astrometrical precision needed will vary. In general terms, it is advisable to use target object astrometry with at least an accuracy of one-third of the slit width. Gaia and HST coordinates are the recommended input catalogues, but UKIDSS has also been proven to work with mid-size slit widths, between 0. 8 and 1. 2. The Optimizer Slit Positioner (OSP) tool was specifically designed to cope with all the tasks associated with building the configuration file that will be input into the instrument control software at the GTC to form the desired pattern in the CSU. A detailed description of this tool and additional auxiliary scripts can be found at the EMIR web page 5. Figure  5  shows a picture of a mask being built with the OSP overlaid in a UKIDSS sky image.
The principal aim is to accurately classify the sources to provide a better understanding of, particularly, the redder parts of the infrared CMD. GALEP extracts its source candidates from the UKIDSS database  (Lawrence et al. 2007) , while several additional infrared catalogues are used for auxiliary information. Most of the sources A107, page 5 of 10 that GALEP intended to measure lie within or very close to the Galactic plane and towards the internal Galaxy. Hence, most of the fields are of very high source density, which imposes the use of automatic selection for designing the multi-slit masks. The first step in the design to automatise it is the translation to numeric values of the scientific merit of the candidates. GALEP selects its candidates to be mostly red giants, of types K and M, and with heliocentric distance between 7 and 9 kpc, while the precise range varies with the location of the field.
Assigned fiducial stars are plotted as blue circles. Unassigned targets or fiducial objects are plotted as crosses of the corresponding colour, red for the targets and blue for fiducial stars. Field objects are green circles. There are also yellow crosses representing target objects that cannot be assigned since they have contaminating neighbours in either of the two nodding positions. See text for details. and background signatures. The removal of all these features is a tedious task and, in most cases, beyond the reach of the user astronomer who is not fully aware of the instrument specificities. Like most modern instruments, EMIR has its own data reduction pipeline (DRP, PyEmir 6  ,  Cardiel et al. 2019a,b; Pascual et al. 2019) , written in Python, that can cope with the large majority of the different aspects of data reduction.
GALEP Using EMIR we plan to obtain NIR spectroscopy of several thousand Galactic sources, mainly located in the inner regions. These targets are being selected from their positions on IR colour-magnitude diagrams and will include disc, bar bulge, and ring sources. The principal aim is to accurately classify the sources to provide a better understanding of, particularly, the redder parts of the infrared CM diagram. Without this information there will remain ambiguities in the interpretation of structures in the inner Galaxy. This project will measure and classify a significant fraction of the sources in specific areas in a way that will avoid the a priori hypotheses for their interpretation. The zones will be spread over a wide area along the plane that can be reachable from the GTC. The GALEP data will be cross-correlated and compared with other existing databases, like Gaia and LAMOST, on which our group have been working for several years; this will permit us to explore the Galactic stellar population in a number of ways.
The combination of radial velocities, proper motions, parallaxes, and metallicities from Gaia, LAMOST, and APOGEE is opening new opportunities to observe the Galaxy and its morphological components as time-dependent systems in evolution. GALEP at EMIR will add new capabilities to the already existing databases as it will permit the spectroscopic detection of the stellar population in the hidden central areas of the Galaxy. Some spectra were already taken during the commissioning and science verification phases of the EMIR instrument. The data were reduced using PyEmir (see  Sect. 6)    MASGOMAS-10. It was observed with EMIR in long-slit mode during September 2017, with a slit width of 0. 8 arcsec that projects on four pixels on the detector. We used an ABBA pattern with nodding distances that varied between 5 and 12 arcsec, depending on the observing field, and checked that the telescope motion did not result in the B image of our target overlapping with the A image of some nearby star.
GOYA aims to survey several cosmological fields using the multiple capabilities of the EMIR MOS mode. The Extended Groth Strip (EGS) was the field selected for the first batch of observations. These projects plan start obtaining data once the commissioning of the Hawaii-2RG detector is completed. We present here the first results of a pilot spectroscopic study of a sample of low-mass star-forming galaxies at intermediate redshifts (0. 7 < z < 1. 5), specifically selected to study the formation redshift and the cosmic role of dwarf galaxies. The high surface density of star-forming galaxies qualifies them as ideal fillers for the GOYA survey MOS masks, guarantying the coverage of a minimum sample. In Fig. 12  we present two star-forming galaxies at intermediate redshift that show Hα emission in EMIR long-exposure MOS masks.
Acknowledgements. EMIR has been funded by GRANTECAN S. L. via a procurement contract; by the  Spanish  funding agency grants  AYA2001-1656 ,  AYA2002-10256-E, FIT-020100-2003-587 ,  AYA2003-01186 ,  AYA2006-15698-C02-01 ,  AYA2009-06972 ,  AYA2012-33211 ,  AYA2015-63650-P  and  AYA2015-70498-C2-1-R ; and by the  Canarian funding agency  grant  ACIISI-PI 2008/226. Part of this work was supported by  AYA2018-RTI-096188-B-I00  and the  French CNRS , the  Aix-Marseille University , the  French Programme National de Cosmologie et Galaxies (PNCG)  of  CNRS/INSU  with  INP  and  IN2P3 , co-funded by  CEA  and  CNES.
of physico-chemical properties The texture and morphology of the GRM-based films were investigated with the aid of a high-resolution field-emission scanning electron microscope (FE-SEM) instrument (Zeiss, SUPRA 35VP) operating at 10 kV. The microstructure of the graphene-based materials was examined utilizing a high-resolution field emission transmission electron microscope (Thermo Fisher Scientific, Talos F200i) operating at 200 kV. TEM specimens were prepared by drop casting 5 μl of aqueous suspension of the materials onto holey carbon support copper TEM grids. X-Ray diffraction data were recorded using a Bruker D8 Advance system with a nickel filtered CuKa anode (λ = 1. 5406 Å) operating at 40 kV and 40 mA. Raman spectra were recorded with the 514. 5 nm laser line using a laser power lower than ~1.
ACKNOWLEDGEMENTS This research was partly supported by the project ' National Infrastructure in Nanotechnology, Advanced Materials and Micro-/ Nanoelectronics ' ( MIS 5002772 ) which is implemented under the  Action Reinforcement of the Research and Innovation Infrastructure , funded by the  Operational Programme Competitiveness, Entrepreneurship and Innovation  ( NSRF 2014-2020 ) and co-financed by Greece and the  European Union  ( European Regional Development Fund). K. B. and S. N. Y. acknowledge support by the  European Union 's  H2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement N. 721642 (SOLUTION).
Acknowledgments. -We thank  Patrick Eggenberger ,  Rebecca Leane ,  Bruce Macintosh ,  Eric Mamajek ,  Georges Meynet ,  Payel Mukhopadhyay ,  Stephen Ro ,  Ningqiang Song , and  Natalia Toro  for helpful discussions. AD, SARE, PS, and KZ were supported by the  U. S. Department of Energy  under contract number  DE-AC02-76SF00515  while at SLAC. SARE was also partially supported by  SNF  grant  P400P2 186678. KZ is supported by the  NSF GRFP  under grant  DGE-1656518.
To test our hypotheses, we conducted a perceptual study investigating perceived pose equivalences when presenting poses with varying self-contacts to observers. We used a pose dataset of four identities with different body shapes performing 17 different poses containing self-contacts between the arms or hands and the upper body. We presented observers (N = 81) with a source pose, a target identity, and two variations of the pose on this target identity, and asked them to select the pose variation which best mimicked the source pose. One of these variations had the same self-contacts as the source pose, and the other had one self-contact present in the source released. These pose variations were generated using the deformation transfer method of  Basset et al. basset2020contact  with different contact preservation parameters.
The latter further confirms that simple similarity metrics do not correlate with human perception. the capacity of human subjects to imitate the pose of a target character. The study showed that subjects (equipped with motion capture markers and an eye tracker) gave more attention to certain joints of the target before imitating the pose, such as the head and the wrists. More recently, Muller et al. muller2021self used a similar approach to annotate a dataset of 2D images of human characters in the wild. They presented 3D models of human characters to subjects tasked to take pictures of themselves imitating the character's pose. Their dataset focuses on poses containing self-contacts, which illustrates that human subjects are able to understand and imitate poses containing self-contacts with acceptable precision.
Selecting Human Poses To create the data used in this study, we first selected a set of poses with self-contacts. As already mentioned, we focus on self-contacts involving the arms or hands and the upper body of the characters (above the thighs, thighs included), as they are frequent in everyday human poses. We thus aim to obtain a representative set of poses in these configurations. We selected a total of 17 poses from a dataset of 3D human scans  [Bogo et al. (2014) ] and a dataset of artist-generated animations (Mixamo 1 ), and created by hand by modifying pose parameters of a parametric human body model  [Loper et al. (2015) ]. These poses all present one or two self-contacts between the hands or arms and the upper body, e. g. crossing arms, hand resting on the hip, clapping. Figure  3  shows examples of the resulting poses on a fixed body shape.
Transferring and Releasing Self-Contacts To evaluate how self-contacts are perceived when transferring poses between different character shapes, we first created a number variations of the poses selected in Section 3. 1 by retargeting them on several body shapes (called identity hereafter). We selected four identities for our study, using the identity parameters of the SMPL parametric human body model  [Loper et al. (2015) ]. This model's identity parameters represent well the variation of human body shapes along its main variation axes, as it was trained on a large dataset of captures of human subjects. We generated four target identities with representative body shapes by sampling models at ±2 standard deviations of the mean for the two first identity parameters (see Figure  5 ). To limit the size of our study, we also chose to focus this first study on male characters.
For each pose, a reference solution (with all the self-contacts transferred) is available, as well as several variations with each individual self-contact involving the hand, arm or upper-arm released. Our dataset contains 68 reference solutions, and one pose variation for each selfcontact present in our poses. Among our 17 poses, 4 (respectively 13) presented one (respectively two) self-contacts involving the arms or the hands and the upper body of the character. This resulted in 30 pose variations with a self-contact released, and thus 120 combinations of body shape and pose variation. We compare these combinations to our reference solutions with no released self-contacts in the study presented in the next section.
Summary of stimuli This section summarizes the stimuli shown to the users during the perceptual study. We consider two categories of contacts, arm and hand, depending on whether the self-contact involves parts of a hand or parts of an arm. Each pose variation is labeled w. r. t the category of the released self-contact. Our dataset contains 68 pose variations in the category arm and 52 in the category hand. We also measured the contact release distance (see Equation  2 ) for each pose variation generated with our method. Our pose variations had a mean release distance of 4. 98cm and a standard deviation of 3. 42cm. For the hand and arm category, the release distances had a mean of 5. 23cm and 4. 80cm, respectively, and standard deviation of 2. 99cm and 3. 70cm, respectively. Figure  7  shows a histogram of all the contact release distances on our dataset, labeled by category.
Protocol Before the study, participants were presented with instructions illustrated with an example of question. They were asked to sign an informed consent form before proceeding to the study. They then filled a short demographic questionnaire to gather the information summarized above. 3D models from the pose dataset presented in Section 3. 4 were used in this study. We randomly split our variation dataset in 4 subsets of 30 questions. Each participant was presented with only one of these subsets. For each question, observers were tasked to select which of two characters best imitated the pose of a source character displayed in the upper left of the screen. The choices were deformation transfer results of a new identity (displayed in the screen lower left) to the source pose. One displayed similar self-contacts as the source, and the other had one self-contact released, presented randomly on the left or the right.
Results In this section, we present descriptive statistics on the results of this study. We also test for statistical significance of the effects of our different stimuli. We assessed normality of the data using the Shapiro-Wilk test. As our data was found to be non-normally distributed, we used the non-parametric Kruskal-Wallis one-way analysis of variance test to study potential main effects of a specific factor on our results. When an effect is found for a factor, we explore it further using Tukey post-hoc test to compare pair-wise means. We chose a statistical significance threshold of 5%, meaning that we consider an effect significant if the probability that the difference between means is due Figure  9 : Rate at which observers selected the pose variation with a contact present in the source released, depending on the contact release distance.
According to the Web of Science's Core Collection database, the United States was the place of origin of more than 65 000 papers, while England, China and Italy contributed about 20 000 each. Spain, Germany, France, Canada, and Australia have each contributed between 8000-11 000 papers to date. The leaders among LMICs are India (about 15 000), Brazil (about 5500), Turkey (about 6500), Iran (about 5300), Pakistan (about 3200), and South Africa (about 3000)  [9]. These numbers show that the population size of each country plays a role in the research capacity and productivity, but not nearly as much as the country's economic potential and investments in health research. After two years of the pandemic, during which intense learning about the new virus and the disease that it causes occurred globally, there are many avenues in which further research efforts could be placed -especially in LMICs, where there are still many unknowns even about basic epidemiology, the number of deaths from COVID-19, and post-COVID-19 disability.
Acknowledgements: We would like to thank the following ISoGH members who contributed with the ideas, but did not complete the scoring (listed alphabetically by their first name):  Anna Wahyuni Widayanti ,  Bernard Naafs ,  Claudia Pagliari ,  Danilo Buonsenso ,  Douglas Fraser Wares ,  Folorunso Fasina ,  Ian Russell ,  Joseph Cuthbertson ,  Joyce Wamoyi ,  Kabiru Akinyemi ,  Kathy Rowlen ,  Marie Buchtova ,  Nuzulul Putri ,  Nzau Mvuezolo ,  Obinna Oleribe ,  Omar Sued ,  Paloma Alonso-Stuyck ,  Purnima Madhivanan ,  Rosnah Sutan ,  Sally Brinkman ,  Sam Okuonzi ,  Tammary Esho ,  Timothy Carey , and  Zohra Lassi.
For ITER and DEMO scenario development Accessibility of the ITER and DEMO relevant plasma regimes is explored by means of an integrated model GOTRESS+  [19]  which consists of the iterative transport solver as a kernel of the integrated model, the equilibrium and current profile alignment code (ACCOME) and the neutral beam heating/currentdrive code (OFMC) as shown in figure  8. Both the safety factor and ion temperature profiles are nearly converged after four iterations. This integrated code predicts that an ITER-like plasma regime of H 98,y = 1. 0, β N = 2. 1, κ x = 1. 81, δ x = 0. 41, f GW = 0. 79 can be achieved with 20 MW of heating power (P N-NB = 10 MW, P P-NB = 10 MW) at I p = 4. 6 MA and B T = 2. 3 T (the second scenario (II) in table  2 ). The MHD stability of the converged profile is examined over the entire profile by the MARG2D or MINERVA-DI code  [20]  as post-processing.
The DEMO-relevant steady-state regime of β N = 4. To access a hybrid plasma, the plasma current profile control during plasma current ramp-up is essential. In JT-60SA the ECH power deposition location is controlled by changing the steerable mirrors for fine-tuning of the plasma current profile. In order to obtain the hybrid scenario in JT-60SA, favorable ECH resonance and ECH power during the current ramp-up phase are explored by using the integrated modeling code CRONOS  [21]. Figure  9  shows the current ramp-up scenario simulation in an L-mode phase. Here the target plasma is set to H 98,y = 1. 2, β N = 3. 0, and q 95 = 4. 4 in I p = 3. 5 MA and B T = 2. 3 T (the third scenario (III) in table  2 ). The ECH power with 138 GHz (second harmonic resonance) is injected from the plasma breakdown, and the ECH power increases until the L-H transition.
The mechanism stems from the change in the force balance. In the Ar only seeding case, Ar impurities stagnate at the top of the scrape-off layer (SOL) region. In the Ar and Ne seeding case, the Ar impurities are transported to the inner divertor region. Edge and divertor modeling in the highest plasma current case of I P = 5. 5 MA, B T = 2. 25 T, highest heating power of P in = 41 MW, and low separatrix density of n e,sep = 2. 0 × 10 19 m -3 (the first scenario in table 2) with carbon wall have been performed with the SOLEDGE2D-EIRENE code  [39]. Figure  14  illustrates the divertor heat load as a function of Ar seeding rate. Here the total heat flux to the SOL region is given as a constant value of 30 MW, and the carbon impurity radiation power is about 8 MW. The power heat load onto the outer target decreases with increasing Ar influx and reaches a target value of 10 MW m -2.
The plasma purity defined as the deuterium ion density divided by the electron density, n D,sep /n e,sep at the separatrix remains around 70%-80%; here the Z eff is around 2. 8-3. 1. Compatibility of long-pulse high-β N and radiative plasmas with metal plasma-facing components will be explored in the Integrated Research Phase II. Assessment of divertor plasma conditions with a tungsten wall in a high-density scenario of nl = 1. 0 × 10 20 m -3 (f GW = 0. 8 at I P = 5. 5 MA) with the injection power of 30 MW is made with the SOLPS-ITER code suite  [40]. Here nl is the line averaged density. Nitrogen seeding is adopted, based on the cooling performance in metallic devices  [41, 42]. The operation conditions to reach a criteria of heat flux to the divertor of 10 MW m -2 and a detachment divertor condition of T e < 5 eV are imposed for the auxiliary power of 30 MW and the power flux through the separatrix of 20 MW.
Acknowledgments The authors gratefully acknowledge members of the JT-60SA  Integrated  Project Team for data exchange and fruitful discussions. This work has been carried out within the framework of the  EUROfusion Consortium  and has received funding from the  EURATOM  research and training program 2014-2018 and  2019-2020  under Grant Agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the  European Commission.
Previous snow model intercomparisons have focused on seasonal snow with an emphasis on snowmelt and runoff, but here we are dealing with a different climate where snowfall is low in annual accumulation, and the snowpack is dry, subject to strong wind transport. However, a common feature with other intercomparison concerns the uncertainty in model outputs due to the uncertainty in the baseline meteorological data  (Raleigh et al. , 2015). Within the framework of GABLS (Global Energy and Water Exchanges (GEWEX) Atmospheric Boundary Layer Study), intercomparison studies are conducted for boundary layer parameterization schemes used by numerical weather and climate forecast models. For stable stratifications, the models still have significant biases, which depend on the boundary layer and surface parameterizations used  (Holtslag et al.
Forcing data Data describing the local climate were measured at Dome C on a mast equipped with sensors  (Genthon et al. , 2021) , for a 15 d period from 1 to 15 December 2009, the period during which air and surface temperatures are warmest in this region. They constitute a complete data set to feed surface models. The data collected on the mast at a height of 3. 3 m are wind direction and speed with a Young anemometer, air temperature in a ventilated shelter with a PT100 probe, and specific humidity. In addition, air pressure was measured by a Vaisala sensor at a height of 1. 2 m and measurements of downwelling infrared and visible radiation were made at a height of 3 m with Kipp & Zonen sensors. Periods with missing data were filled with ERA-Interim reanalysis. Due to the lack of precipitation in the period, precipitation rates were set to zero.
Evaluation data Surface and snowpack measurements were used to evaluate the models. Satellite measurements of surface temperature from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and the Infrared Atmospheric Sounding Interferometer (IASI) sensor complemented the continuous measurements from the Baseline Surface Radiation Network (BSRN). Figure  2  shows the measurements from these sensors over the 15 d period. In addition, measurements of the snow temperature profile, made by the Institute for Environmental Geosciences, enabled the characterization of the thermal structure of the snowpack and evaluation of the most sophisticated models with a multilayer vertical discretization  (Brucker et al. , 2011). The first temperature probe was installed on 26 November 2006 at 10 cm in the snow and the deepest at 21 m.