dataesr/scientific-paragraphs-categorization huggingface dataset:
Data availability The atomic coordinates included in the study have been deposited in the Protein Data Bank (PDB) with the following accession codes: apo dParg, 8ADK [https://doi. org/10. 2210/pdb8adk/pdb]; dParg:PARGi complex, 8ADJ [https://doi. org/10. 2210/pdb8adj/pdb]. The mass spectrometry proteomics data have been deposited to the Proteo-meXchange Consortium via the PRIDE partner repository  96  with the dataset identifier PXD036512. Full images of the blots and gel as well as data used to generate graphs can be found in the Source data file. Source data are provided with this paper.
407 and 0. 575 kR with an average of 0. 478 kR. The IPH brightness in the upwind limb-oriented observations ranged between 0. 147 and 0. 558 kR with an average of 0. 300 kR. The best fit IPH brightness in the downwind IPH campaign data ranged between 0. 266 and 0. 354 kR with an average of 0. 306 kR. The best fit IPH brightness for the downwind oriented limb data ranged between 0. 168 and 0. 399 kR with an average of 0. 282 kR. The uncertainties in the spectra varied for each data point, and ranged between 0. 020 and 0. 070 kR, with an average of 0. 040 kR. Relative to the IPH emission, the uncertainties ranged between 4% and 26% with an average of 11%. The IPH velocity is presented both as Doppler shift along the line of sight, in km/s, as well as in wavelength, relative to the at-rest Lyman-α line center.
Solar Cycle Effects The MAVEN/ECH observations utilized here included one data point in Mars Year (MY) 33, 107 data points in MY34, 13 datapoints in MY35, and 4 data points in MY36. During this timeline, solar activity was declining through Solar Cycle 24 into its minimum phase (∼mid September 2019) through the rising activity phase of Solar Cycle 25. The Solar Lyman-α irradiance was obtained by the empirical model developed by  Kretzschmar et al. (2018)  that uses SOHO Solar Ultraviolet Measurement of Emitted Radiation instrument observations at Lyman-α center  (Lemaire et al. , 2015)  with Lyman-α composite  (Woods et al. , 2000; Machol et al. , 2019). The empirical model is found at https://lasp. colorado. edu/lisird/data/lyman_alpha_model_ssi/. The solar Lyman-α irradiance is averaged over a solar rotation cycle (28 days) and shown for reference in Figure  9.
The IPH brightness was 0. 506 kR for the single datapoint in MY33, and averaged 0. 381 kR in MY34, 0. 363 kR in MY35, and 0. 520 kR in MY36, for data from each MY (from combined upwind, downwind, IPH campaign and limb-oriented data). The Solar Irradiance averaged 0. 0240 W/m 2 /nm in MY 33, 0. 0220 W/m 2 /nm in MY 34, 0. 0220 W/m 2 /nm in MY35, and 0. 0237 W/m 2 /nm in MY 36. The data set includes a unique feature of having both upwind and downwind observations for IPH obtained around the same epoch in MY35, during Solar Cycle 24's minimum phase. Of the 13 observations available from that epoch, 7 were upwind and 6 were downwind. Four of the seven upwind observations were obtained during IPH campaigns, and three were obtained during limb-pointed scans. Additionally, four of the six downwind observations were obtained during IPH campaigns, and two were obtained during limb-pointed scans.
The absence of a smoother temperature trend is likely due to the data fitting algorithm that would result in very small changes in the χ 2 value for temperatures that are a few thousand K different paired with the limited spectral resolution of the data. Due to these factors, the derived temperatures should not be considered definitive. In examining the relative contribution of IPH to the planetary emission from Mars' orbit, it was found that the IPH contribution ranged between significant (close to upwind orientations) and comparable (close to downwind orientation). This result is critical for lower-resolution Lyman-α observations made from Mars (and other planetary bodies with thermal H emissions) where assumptions are made to ignore IPH contributions or to assume a fixed value across a range of observing conditions.
This global heliospheric model calculated the interstellar neutral H distribution at a sphere of radius 70 AU from the Sun as the boundary condition for a local model  (Izmodenov et al. , 2013; Katushkina et al. , 2015). The local model simulated the H distribution inside the 70-AU sphere by solving the kinetic equation to account for non-Maxwellian kinetic features, temporal variations of solar radiation pressure, and ionization rates during the solar cycle. Charge exchange ionization rates were taken from the analysis of the SOHO/SWAN Lyman-α observations  (Katushkina et al. , 2019; Koutroumpa et al. , 2017 ) that were normalized using in situ data from the OMNIWeb database collected in the ecliptic plane (https://omniweb. gsfc. nasa. gov/). The dependence of radiation pressure on time, radial velocity, and heliolatitude of H atoms was adopted from  Kowalska-Leszczynska et al.
(2020). The total solar Lyman-α flux measured at the Earth's orbit was taken from  Machol et al. (2019)  (http://lasp. colorado. edu/lisird/data/composite_lyman_alpha/). Using the H distribution from the model simulations, the solar Lyman-α radiation backscattered by H atoms was calculated. Single-scattered photon emissions were calculated by integrating the radiative transfer equation, and the multiple scattering emissions were calculated using the radiative transfer code developed by  Quémerais (2000) , which utilized the Monte Carlo method. In the simulations done for this work, the spectral properties that are moments of the Lyman-α spectrum were calculated. Namely, the brightness, line shift (Doppler shift), and line width (temperature) were obtained for the 125 observations made by MAVEN/IUVS.
Summary Data from the MAVEN IUVS Echelle channel were analyzed for derivation of IPH properties both upwind and downwind of the flow. The data set includes both dedicated campaign as well as fortuitous limb-pointed data upwind of the IPH flow, and serendipitous data downwind of the IPH flow from comet-pointed and limb-pointed data. The IPH emission brightness, Doppler shift, and thermal broadening were derived using a least square fitting algorithm. The resulting derivations showed trends of decreasing brightness with increasing angle from upwind. Independent model results showed similar trends and showed a consistent factor of two difference in brightness values. The data-model comparison also showed very good agreement with the derived and simulated velocities (Doppler shift). The temperature derivations in the data did not match the modeled values, likely due to limitations in the spectral resolution of the data.
The velocity values from campaign versus limb data compared remarkably well with simulated values. The temperature derivations from both campaign and limb data were similarly divergent from simulated values. The results of the analysis and associated conclusions of this work do not change when using only the IPH campaign or limb datasets separately. We conclude that there is merit to analysis of both datasets in deriving IPH properties and expect more statistically significant trends to show with additional data obtained from future observations. In summary, IPH atoms observed from Mars' vantage have provided constraints that show some agreements as well as disagreements with theoretical predictions. Understanding these differences will refine our understanding of how the IPH flow is affected by interface dynamics at the outer edge of the heliosphere as the flow propagates closer to the Sun.
Acknowledgments This work was funded, in part, by  NASA  contract # 1000320450  from the  University of Colorado to Boston University. MM acknowledges the MAVEN mission for supporting the analysis of IUVS data. The MAVEN mission is supported by  NASA  in association with the  University of Colorado  and  NASA 's  Goddard Space Flight Center. MM thanks the reviewers for their careful read of the manuscript and their helpful suggestions that helped improve the delivery of this work.
Collection of follow-up data using the eCRF occurred at 4-monthly intervals up to 24 months and yearly thereafter. In this analysis, the maximum follow-up considered was 24 months and outcome information beyond 24 months was censored. Submitted data were examined for completeness and accuracy by the coordinating centre (Thrombosis Research Institute, London, UK). In accordance with the study protocol, 20% of all eCRFs were monitored against source documentation. 23.
| Statistical analysis Continuous variables were expressed as medians and interquartile ranges and categorical variables as frequencies and percentages. As studies with large sample sizes tend to produce statistically significant findings in the presence of clinically irrelevant differences, no formal statistical tests were performed for the baseline tables. T A B L E 1 (Continued)  Only complete cases were presented in descriptive tables. Multiple imputation was applied for the estimation of the DM association coefficients and in the comparative effectiveness analyses. 24  Final estimates were obtained by combining results across five imputed datasets. Statistical analyses were carried out using SAS (version 9. 4).
29  This is in keeping with the positive association between HbA1c level and outcome where, the higher the glycaemic burden, the higher the risk. 30  The no-drug DM subgroup was quite large, with 47. 2% of patients declared as diabetics by the investigators, far more than in other reports, 40% in the ROCKET-AF trial and 27% in a retrospective health care database analysis. 35, 36  The different rates of patients with no-drug DM across studies may be related to the nature of the GARFIELD-AF registry, which included patients from different health care systems and with wide variations in treatment strategies. Patients with no-drug DM may have had prediabetes, namely impaired fasting glucose or impaired glucose tolerance, condition where lifestyle counselling without OAD is recommended as first line.
Some reported that insulin-only treated DM was associated with a higher risk of stroke  9  or of non-haemorrhagic stroke and CV death  10, 44  ; whereas others reported a similar risk of non-haemorrhagic stroke/SE in both OAD and insulin-treated patients. 8  Other reports showed no excess of non-haemorrhagic stroke/SE compared with patients without DM, but a higher risk of death. 25, 28  The discrepancies may exist because of differences in study populations. Meta-analyses of randomized clinical trials or registries and retrospective health care databases analyses may yield different outcome data as compared with prospective registries such as GARFIELD-AF. 45  The different nature of AF in various studies, prevalent versus newly diagnosed AF, may play a role. A substantial proportion of patients with IRD concomitantly receive OAD.
, 2019). Most of the geologic work around Mount Dallol has been conducted for potash mining. Seismic profiles were obtained and holes were drilled by the mining companies operating on Dallol and in its vicinity. Most data have been acquired on the western side of the Danakil depression, along the margin with the uplifted continental basement. South of Dallol, seismic profiles have been obtained by Allana Potash parallel and perpendicular to the Danakil depression. North of Dallol, profiles have been obtained by Circum Minerals and Yara Dallol. More than 300 holes were drilled by the Ralph M. Parsons Company in the 60s  (Holwerda and Hutchinson, 1968) , and were complemented by 88 holes by Allana Potash and Nova Potash. Data and analysis of many drill holes, as well as Allana seismic profiles, have also been disclosed  (Rauche and van der Klauw, 2015) , and combined with additional data, were used to infer geodynamic interpretations  (Bastow et al.
Remote sensing data analysis Most of the images taken by civilian and declassified satellites in the visible and near-infrared ranges until 2020 were examined for this study, as well as a subset of images obtained between 2020 and 2023. Those who were found the most useful for this study are listed in Supplementary Table  S1. High-resolution images from KeyHole-4B, OrbView-3, Pleiades-1A/B, QuickBird-2, Spot-6, and WorldView-2 were used to map the details of the YLF and associated features at irregular time steps. The benefits of 10-30 m resolution data from ASTER and Landsat-7 lie in their spectral capabilities, making identification of potential surface composition variations between two consecutive passes, usually not more than 1 or 2 months. They were used to determine the succession of events at the time of  YLF formation, in 2004 -2005 (Supplementary Table   S2 ).
Moreover, the thermal channels of Terra/ASTER were useful to identify possible surface temperature variations associated with the hydrothermal activity of the YLF, both diurnal, and between different orbits. Sentinel 2A/B data were also analysed, but did not yield information not already available using data from the other multispectral satellites. The YLF is nearly fully covered by four 1x1 km pixels from the Terra/MODIS Land Surface Temperature dataset. In spite of this coarse resolution, surface temperatures are measured daily, during day time and night time, making it possible to monitor whether or not development of the YLF in 2004-2005 was associated with significant thermal anomalies at surface. Satellite images having visible and near-infrared channels were studied with conventional processing for geologic interpretations.
A composite (red-green-blue) image showing the difference between two measurement times (t 0 , "before," and t 1 , "after" the studied event) was generated by subtracting a given band at t 0 from the same band obtained at t 1 and attributing it to the red channel, and doing the same for two other bands and the two other channels. Thermal information was directly retrieved from the ASTER L2 Surface Kinetic Temperature distributed by the USGS Land Processes Distributed Active Archive Center. The ASTER five thermal infrared channels were used, after atmospheric correction, to determine surface radiance. Surface radiance data were then used to generate emissivity data, from which temperature is derived. Image processing was done using ENVI 5. 5 and ENVI 5. 7 (NV5 Geospatial Solutions, Inc. , Broomfield, Colorado, U.
The whole study area was flooded by Lake Karum by late April, preventing more precise dating. Hydrothermal activity has been intense in the Yellow Lake area, however, throughout the year 2005 (Supplementary Video S1). InSAR data analysis indicates that the volcanic crisis that started at Erta 'Ale on 16 January 2017 did not affect the topography in the area of the YLF  (Xu et al. , 2020). Comparison between satellite imagery before and after the main, January 2017 event (20. 11. 2016: WorldView-2 vs. 12. 02. 2017, ASTER), confirms that the fissure system remained unaffected at the surface.
Pressure-driven, low-temperature hydrothermal flow Whether magmatic heat was significant in the process of YLF development may be evaluated by the temperature of the fluids at the surface when the fissure open. The temperature of the fluids that were first ejected from the hydrothermal fissure, and led to resurfacing along its trace is investigated using thermal data obtained by ASTER (Figure  12 ) and MODIS (Figure  13 ). ASTER surface temperatures are available for 14-11-2004 during daytime, just after YLF initiation. They are also available on 09-01-2005 and 17-02-2005 at night time, at the beginning of a hydrothermal crisis centred at the Yellow Lake area. MODIS daily daytime and night time temperatures are available at a resolution of 1 km. None of these datasets show evidence of anomalous surface temperatures in this time span, suggesting that the fluids that accompanied YLF opening during fall 2004 and those of the subsequent hydrothermal crisis did not advect significant thermal energy to the surface.
Acknowledgments Structural analysis shown in Figure 8 was conducted using SG2PS (Sasvári and Baharev, 2014). Harald Hansen ,  Henok Tsegaye , and the  Yara Dallol  B. V. field camp staff are thanked for help in field logistics, and  Benjamin Van Wyk De Vries  and  Viktor Vereb  for enjoyable joint field work at the Dallol salt dykes. We thank two reviewers and  Neil Mitchell  for careful reviews and suggestions which enriched and broadened the discussion. The identification of potential sills in the Sang et al. (2023) seismic dataset is to be credited to  Neil Mitchell.
Funding Field work was funded by  Europlanet 2020 RI , and laboratory work by DM by the  EXOMHYDR  project and a joint fellowship of the  Polish Academy of Sciences  and  CNRS at Institut de physique du globe de Paris. Europlanet 2020 RI has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No. 654208. The  EXOMHYDR  project is carried out within the  TEAM program  of the  Foundation for Polish Science  co-financed by the  European Union  under the  European Regional Development Fund.
Another advantage of performing this model-independent search in the H → γγ channel is that the same background modelling strategy can be applied to most signal regions; the signal and background can be determined by fitting analytic functions to the diphoton invariant mass (m γγ ) distribution in data. This fit-based background estimation method breaks down only when the signal region does not have a sufficient number of events to constrain the analytic background function. If data in the signal regions are found to be consistent with the SM expectations, including contributions from resonant Higgs boson production, limits are set on the BSM production cross section of the Higgs boson in detector-level signal regions. To enable the use of these detector-level cross-section limits in constraining BSM physics models, the detector efficiencies for different signal regions are evaluated.
JHEP07(2023)176 This paper is organized as follows. Section 2 gives a brief description of the ATLAS detector. Section 3 presents the simulated SM samples used to describe the backgrounds, and also the new-physics models used to determine the expected sensitivity of the search in each signal region. Section 4 describes the reconstructed data objects and subsequent selections used in the analysis. Section 5 discusses in detail the signal regions defined for the search. Section 6 describes the modelling of signal and background in each search region. Section 7 addresses systematic uncertainties related to the search. Section 8 presents the results of this search. Finally, section 9 summarizes the conclusions of the paper.
3lo [49]  PDF set. For the t tH sample, the functional form of the renormalization and factorization scale was set to 3   [18]. The generator was interfaced to Pythia 8. 230  [41] , which used the A14 tune  [50]  and the NNPDF2. 3lo [49]  PDF set. The decays of bottom and charm hadrons were simulated using the EvtGen 1. 6. 0 program  [51]. All the SM Higgs boson samples are normalized to cross-section values recommended by ref. [18] , which are shown in table 1. m T (t) • m T ( t) • m T (H) 2 To study the modelling of continuum background, diphoton production event samples were simulated. Besides inclusive diphoton production, specific diphoton processes were also generated for signal regions where electroweak or top-associated production is enhanced. Inclusive diphoton production and diphoton production in association with a vector boson (V γγ) were simulated with the Sherpa 2.
JHEP07(2023)176 the theoretical predictions, and their contributions to various signal regions are evaluated using the MC samples described in section 3. The recent Higgs boson measurements from the ATLAS and CMS experiments have shown that the data are consistent with the theory predictions within statistical and systematic uncertainties, which justifies the fixing of expected resonant background yields to their SM predictions. Potential interference effects between the SM and BSM Higgs boson production processes are not considered in the MC simulation. If the interference effect results in a significant deviation in the production rate from the SM prediction, this search would detect it as a signal.
Conclusions This paper reports a model-independent examination of the diphoton final states where a Higgs boson is produced, using a 139 fb -1 data sample of 13 TeV pp collisions collected by the ATLAS detector during Run 2 of the LHC. A total of 22 signal regions defined with various requirements on the additional reconstructed objects were examined, and no significant excess over the SM expectation was observed. Upper limits at 95% CL were set on the visible cross section of BSM Higgs boson production in each of these signal regions. To enable interpretation of the results as a constraint on other models, a set of detector efficiency factors is also reported. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.
JHEP07(2023)176 and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Türkiye; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.
Acknowledgments We thank  CERN  for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of  ANPCyT , Argentina; YerPhI, Armenia;  ARC, Australia ;  BMWFW  and  FWF , Austria; ANAS, Azerbaijan;  CNPq  and  FAPESP, Brazil ;  NSERC ,  NRC  and  CFI ,  Canada ; CERN;  ANID, Chile ;  CAS ,  MOST  and  NSFC, China ;  Minciencias , Colombia; MEYS CR, Czech Republic; DNRF and  DNSRC, Denmark ;  IN2P3-CNRS.
The novel HLA-C*03:618N allele has one change in exon 1 leading to a premature stop codon. We observed one nucleotide mismatch G>A at position 69 in exon 1, when compared with the HLA-C*03:02:02:01 sequence (Figure  1 ), making residue À2 encoded by TGG (Tryptophan) become TGA (stop codon). The frameshift is predicted to have a significant impact on the protein structure and expression. This new allele is not expected to be detectable on the cell surface as the premature stop codon occurred in the signal sequence of the expected protein. We were unable to perform serological typing using micro-lymphocyte cytotoxicity assay due to the lack of reagents for HLA-C typing. The nucleotide sequence of the exons 1-8 of this new allele was submitted to the GenBank database (Accession No. OP133376) and to the IPD-IMGT/HLA Database 2 (Submission No.