dataesr/scientific-paragraphs-categorization huggingface dataset:
The p. 332_333del mutation is an in-frame deletion located within the sapC domain. Given the interplay between sapC and GCase, we examined whether any of these three iRBD patients with PSAP LoF mutations also carry a GBA variant. Furthermore, we tested the presence of GBA copy number variants (CNVs), as was done previously  [27]. We found that two of the patients, carrying the p. Glu166Ter and p. 332_333del variants, also carried a GBA variant: p. Arg349Ter and p. Glu326Lys, respectively. None carried GBA CNVs. All PSAP and GBA variants were confirmed by Sanger sequencing. We further examined the frequency of PSAP LoF variants on gnomAD database v2. 11 (https://gnomad. broadinstitute. org). None of the LoF variants found in this study have been reported in gnomAD, and the overall frequency of PSAP LoF variants was extremely low, with a total allele count of high-quality LoF variants of 10 in 141,456 individuals (~0.
Acknowledgments We wholeheartedly thank the participants in this study. This work was financially supported by the  Michael J. Fox Foundation, Parkinson's Society Canada , the  Canadian Consortium on Neurodegeneration in Aging (CCNA) , and the  Canada First Research Excellence Fund (CFREF) , awarded to  McGill University  for the  Healthy Brains for Healthy Lives (HBHL) program. JFG holds a  Canada Research Chair in Cognitive Decline in Pathological Aging. GAR holds a  Canada Research Chair in Genetics of the Nervous System  and the  Wilder Penfield Chair in Neurosciences. WO is Hertie Senior Research Professor , supported by the  Charitable Hertie Foundation, Frankfurt/Main, Germany. The Oxford Discovery study was funded by the  Monument Trust Discovery Award  from  Parkinson's UK  and supported by the  National Institute for Health Research (NIHR) Oxford Biomedical Research Centre  based at  Oxford University Hospitals NHS Trust  and  University of Oxford , the  NIHR Clinical Research Network  and the  Dementias and Neurodegenerative Diseases Research Network (DeNDRoN).
4D ). Instances of "footwall snapping" are best documented in horst structures, which are often asymmetric and feature a dominant border fault (e. g. ,  27, 46) , suggesting that horst-bounding antithetic faults initiate sequentially rather than simultaneously. We complement our half-graben dataset with river profile analyses from 3 horst blocks (Table  S3 ), assuming that the spatial pattern of rock uplift is controlled by the dominant fault. The Rwenzori horst, which stands out as a structural and topographic anomaly along the Western branch of the East-African Rift  (46) , is characterized by a thick brittle crust  (25-30 km, 47)  and the lowest EE in our compilation (0. 28; 0. 19/0. 46)possibly reflecting the combination of a rapid rock uplift rate and strong gneissic lithologies. By contrast, horst blocks such as the Ruby Mountains from the Basin & Range have a documented history of strain re-localization on antithetic faults  (27) , and likely developed in brittle crust about half as thick as the Rwenzori horst.
To do so, we extract the topography h2D(x,y) shaped by slip on fault F1 (e. g. , Figure  1B ) as late as possible into the simulations before the localization of new faults alters the relief of the initial half-graben (See example from simulation M60 in Figure  S3A ). The uplift shape function U* is determined by fitting equation  (11)  to footwall relief averaged along the y-direction, excluding the steep fault-facing scarp, i. e. , between distances of 5 and 100 km away from F1, into the footwall (Figure  S3B ). This is achieved through MATLAB's non-linear least squares fitting toolbox. This uplift function does not vary along the strike of the fault (Figure  S3A ). Major footwall rivers that drain away from the master fault are identified and analyzed through the TopoToolbox MATLAB package  (20).
Measuring erosional efficiency and structural characteristics in real half-graben systems Methodology. We analyze the elevation profiles of rivers draining away from the master fault into the footwalls of 9 half-grabens spanning 4 rift systems (Table  S2 ). Our analysis is based on 30-m resolution SRTM topography acquired through the Open Topography online portal (opentopography. org). We use the TopoToolbox MATLAB package  (20)  to identify river networks that drain over large extents of the footwall, away from the tips of the master fault  (22, 23) , and down to a chosen reference altitude. We target ranges where the morphology is clearly dominated by fluvial as opposed to glacial valleys, and focus on portions of the range where relief averaged along strike smoothly decays away from the master fault (e.
g. , Figure  S5B ). We select two points on the master fault (UTM coordinates listed in Tables  S2  and S3 ), which delineate the fault-normal topographic swath over which relief is averaged, non-dimensionalized and fitted with equation  (11)  to determine the shape of the uplift function, following the same methodology as in our synthetic tests. Maps of drainage area determined by the TopoToolbox scripts are then integrated upstream to produce standard c-plots and cU-plots corrected for the dimensionless uplift function (e. g. , Figure  S5C ), which only varies in the fault-normal direction (e. g. , Figure  S5A ). Erosional efficiency and its confidence interval are determined from cU-plots with the same approach as in our synthetic tests. While we have strived to select systems that are still actively growing, it is possible that the uplift rate on the master fault may have fluctuated through time, and over a range of time scales, adding some uncertainty to our analysis.
Extension was later taken up by 2 antithetic fault systems formed within the last 10 Myrs, which now separate the Ruby Mountains from the Huntington Valley to the West and the Ruby Valley to the East. While both of these fault systems show evidence for Quaternary slip (e. g. , faults 1714 and 1718 in the USGS Quaternary Faults Database: 53), the E-dipping Ruby Valley fault appears dominant in terms of both structural and topographic relief. Ref. 52 estimated its throw at ~2. 4 km. Given the documented switches in polarity of the master normal faults and the coexistence of significant deformation on antithetic fault systems, we classify the Ruby Mountains as a horst structure, or in a broader sense, an area with a documented history of localized brittle strain migrating into the footwall of a master normal fault.
Lacking geophysical constraints on the thickness of the brittle crust in the area, we use the same estimate (10-15 km) as in the Santa Rosa range, which is based on seismogenic layer thickness measured over the entire state of Nevada  (39). Toiyabe Range, Nevada, USA. The N-S trending Toiyabe Range (Figure  S16 ) is located in the central Basin and Range province. It is a horst block bound on its western and eastern sides by high-angle normal faults which separate it from the Reese River and Big Smokey Valleys  (54, 55). Both fault systems show evidence of Quaternary activity (e. g. , faults 1336c and 1337 in the USGS Quaternary Faults Database: 56, 57), but the E-dipping Toiyabe Range fault zone has been noted to have the dominant tectonic and geomorphic expression in the southern portion of the range (  55 ), which we focus on in our river profile analysis.
Acknowledgments J. -A. O. , W. R. B. and M. D. B. were supported by  NSF  grants  EAR-1650166 ,  EAR-17-14909 , and  EAR-19-03897. J. -A. O. benefited from an  ENS "Actions Incitatives"  grant as well as support through the  CNRS-INSU-TelluS-SYSTER program. We thank our editor and reviewers for their insightful feedback. We also acknowledge  Jean Braun ,  Brian Yanites ,  Cindy Ebinger  and  Boris Gailleton  for fruitful discussions.
Here, on the basis of this larger dataset, we combine an unprecedented number of production and decay processes of the Higgs boson to scrutinize its interactions with elementary particles. Interactions with gluons, photons, and W and Z bosons-the carriers of the strong, electromagnetic and weak forces-are studied in detail. Interactions with three third-generation matter particles (bottom (b) and top (t) quarks, and tau leptons (τ)) are well measured and indications of interactions with a second-generation particle (muons, μ) are emerging. These tests reveal that the Higgs boson discovered ten years ago is remarkably consistent with the predictions of the theory and provide stringent constraints on many models of new phenomena beyond the standard model. The standard model of particle physics has been tested by many experiments since its formulation  [1] [2] [3] [4]  and, after accounting for the neutrino masses, no discrepancies between experimental observations and its predictions have been established so far.
In addition, more precise measurements of the new particle's interactions with other elementary particles were achieved  20. The results of all these investigations demonstrated that its properties were compatible with those of the standard model Higgs boson. However, the statistical uncertainties associated with these early measurements allowed considerable room for possible interpretations of the data in terms of new phenomena beyond the standard model and left many predictions of the standard model untested. The characterization of the Higgs boson continued during the Run 2 data-taking period between 2015 and 2018. About 9 million Higgs bosons are predicted to have been produced in the ATLAS detector during this period, of which only about 0. 3% are experimentally accessible. This is 30 times more events than at the time of its discovery, owing to the higher rate of collisions and the increase of the collision energy from 8 teraelectronvolts (TeV) to 13 TeV, which raises the production rate.
In this Article, the full Run 2 dataset, corresponding to an integrated luminosity of 139 inverse femtobarns (fb -1 ), is used for the measurements of Higgs boson production and decay rates, which are used to study the couplings between the Higgs boson and the particles involved. This improves on the previous measurements obtained with partial Run 2 datasets  21, 22. The corresponding predictions depend on the value of the Higgs boson mass, which has now been measured by the ATLAS and CMS experiments  [23] [24] [25]  with an uncertainty of approximately 0. 1%. The predictions employed in this article use the combined central value of 125. 09 GeV  23. The dominant production process at the LHC, which accounts for about 87% of Higgs boson production, is the heavy-quark loop-mediated gluon-gluon fusion process (ggF).
The considerably more challenging measurements of Higgs boson couplings to second-generation fermions are explored via searches for the H → μ + μ -decay  40  and, included in the combination for the first time, H cc → decay  41. Owing to the large multi-jet background, the latter decay mode is currently accessed only via WH and ZH production. Finally, the inputs to the combination are complemented by the latest direct searches in the VBF and ZH production processes for Higgs boson decays into invisible particles that escape the detector  42, 43. A summary of these input measurements used in the combination is available in Extended Data Table  1. H → ZZ → ℓ + ℓ -ℓ + ℓ -decays All input measurements are performed with the full set of Run 2 data, except for the measurements of previous works  30, 39  , which use a partial Run 2 dataset collected during 2015 and 2016.
The direct searches for invisible Higgs boson decays and the H cc → measurements are employed only for measurements of the relevant Higgs boson coupling strengths, and the H bb → measurements at high Higgs boson transverse momenta  37  are considered only when probing the kinematic properties of Higgs boson production. All other inputs are used for the measurements of production cross-sections, branching fractions and coupling strengths. The measurement of kinematic properties of Higgs boson production excludes input measurements from previous works  30, 32, [39] [40] [41]  , owing to their limited sensitivity. Analyses performed with the Run 2 data introduce a number of improvements, often resulting in up to 50% better signal sensitivities compared to those expected from just the increase in the analysed amount of data.
A common set of event generators were used in all analyses to describe the gluon and quark interactions in the proton-proton collisions. The generated particles were passed through a detailed simulation of the ATLAS detector response prior to their reconstruction and identification. The statistical analysis of the data is described in more detail in Methods. It relies on a likelihood formalism, where the product of the likelihood functions describing each of the input measurements is calculated in order to obtain a combined likelihood  51. The effects of experimental and theoretical systematic uncertainties on the predicted signal and background yields are implemented by including nuisance parameters in the likelihood function. The values of those additional parameters are either fully determined by the included data, or constrained by Gaussian terms that multiply the likelihood.
Combined measurement with ATLAS Run 2 data The Higgs boson production rates are probed by the likelihood fit to observed signal yields described earlier. Because the production cross-section σ i and the branching fraction B f for a specific production process i and decay mode f cannot be measured separately without further assumptions, the observed signal yield for a given process is expressed in terms of a single signal strength modifier μ σ σ B B = ( / )( / ) if i i f f SM SM , where the superscript 'SM' denotes the corresponding standard model prediction. Assuming that all production and decay processes scale with the same global signal strength μ = μ if , the inclusive Higgs boson production rate relative to the standard model prediction is measured to be μ = 1. 05±0. 06 = 1. 05±0. 03(stat.
) ±0. 03(exp. ) ± 0. 04(sig. th. ) ± 0. 02(bkg. th. ). The total measurement uncertainty is decomposed into components for statistical uncertainties, experimental systematic uncertainties, and theory uncertainties in both signal and background modelling. Both the experimental and the theoretical uncertainties are almost a factor of two lower than in the Run 1 result  20. The presented measurement supersedes the previous ATLAS combination with a partial Run 2 dataset  22  , decreasing the latest total measurement uncertainty by about 30%. Higgs boson production is also studied per individual process. As opposed to the top quark decay products from ttH production, the identification efficiency of b jets from the bbH production is low, mak- ing the bbH process experimentally indistinguishable from ggF pro- duction.
Signal cross-sections measured in each of the introduced kinematic regions are compared with those predicted when assuming that the branching fractions and kinematic properties of the Higgs boson decay are described by the standard model. The results of the simultaneous measurement in 36 kinematic regions are presented in Fig. 7. Compared to previous results with a smaller dataset  22  , a much larger number of regions are probed, particularly at high Higgs boson transverse momenta, where in many cases the sensitivity to new phenomena beyond the standard model is expected to be enhanced. All measurements are consistent with the standard model predictions.
Conclusion In summary, the production and decay rates of the Higgs boson were measured using the dataset collected by the ATLAS experiment during Run 2 of the LHC from 2015 to 2018. The measurement results were found to be in excellent agreement with the predictions of the standard model. In different scenarios, the couplings to the three heaviest fermions, the top quark, the b quark and the τ lepton, were measured with uncertainties ranging from about 7% to 12% and the couplings to the weak bosons (Z and W) were measured with uncertainties of about 5%. In addition, indications are emerging of the presence of very rare Higgs boson decays into second-generation fermions and into a Z boson and a photon. Finally, a comprehensive study of Higgs boson production kinematics was performed and the results were also found to be compatible with standard model predictions.
In the ten years since its discovery, the Higgs boson has undergone many experimental tests that have demonstrated that, so far, its nature is remarkably consistent with the predictions of the standard model. However, some of its key properties-such as the coupling of the Higgs boson to itself-remain to be measured. In addition, some of its rare decay modes have not yet been observed and there is ample room for new phenomena beyond the standard model to be discovered. Substantial progress on these fronts is expected in the future, given that detector upgrades are planned for the coming years, that systematic uncertainties are expected to be reduced considerably  59  , and that the size of the LHC's dataset is projected to increase by a factor of 20.
Online content Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi. org/10. 1038/s41586-022-04893-w. p T H (GeV) p T H (GeV) p T H (GeV) p T H (GeV) p T Z (GeV) p T W (GeV) p T H (GeV) m jj (GeV) m jj (GeV).
Statistical framework The results of the combination presented in this paper are obtained from a likelihood function defined as the product of the likelihoods of each input measurement. The observed yield in each category of reconstructed events follows a Poisson distribution the parameter of which is the sum of the expected signal and background contributions. The number of signal events in any category k is split into the different production and decay modes: ∑ ∑ n σ B A = ( )( ϵ) , k k i f i f if k signal L where the sum indexed by i runs either over the production processes (ggF, VBF, WH, ZH, ttH, tH) or over the set of the measured production kinematic regions, and the sum indexed by f runs over the decay final states (ZZ, WW, γγ, Zγ, bb , cc, τ + τ -, μ + μ -). The quantity k L is the inte- grated luminosity of the dataset used in category k, and A ( ϵ The impact of experimental and theoretical systematic uncertainties on the predicted signal and background yields is taken into account by nuisance parameters included in the likelihood function.
This is the case of systematic uncertainties in the luminosity measurement  63  , in the reconstruction and selection efficiencies  [64] [65] [66] [67] [68] [69] [70]  and in the calibrations of the energy measurements  [71] [72] [73] [74]. Their effects are propagated coherently by using common nuisance parameters whenever applicable. Only a few components of the systematic uncertainties are correlated between the analyses performed using the full Run 2 data and those using only the 2015 and 2016 data, owing to differences in their assessment, in the reconstruction algorithms and in software releases. Systematic uncertainties associated with the modelling of background processes, as well as uncertainties due to the limited number of simulated events used to estimate the expected signal and background yields, are treated as being uncorrelated between analyses.
Confidence intervals for a given confidence level (CL), usually 68%, are then defined as the regions fulfilling λ F α α ( ) < (CL) for a 1σ (2σ) CL with one degree of freedom. The values of the parameters α corresponding to these confidence intervals are obtained by scanning the profile likelihood. Similarly, the p value p SM = 1 - F n (λ(α SM )) is used to test the compatibility of the measurement and the standard model prediction. The correlations between the parameters are estimated by inverting the matrix of the second derivatives of the likelihood. The expected significances and limits are determined using the 'Asimov' datasets  52  , which are obtained by setting the observed yields to their expected values when the nuisance parameters are set to the values that maximize the likelihood θ.
All primers were modified to contain Illumina adaptors and individual barcodes to allow individual identification for the three genetic loci. The regions were amplified by PCR cycles in a total volume of 25 μL, following specific conditions according to the taxonomic group (following  [68] ). Library preparation was carried out following Illumina MiSeq protocol 16S Metagenomic Sequencing Library Preparation  [69]. The final library was run on a MiSeq sequencer (Illumina, San Diego, CA, USA) using a 2 × 150 bp MiSeq Reagent Kit (Illumina, San Diego, CA, USA) for a projected average of 12,000 paired-end reads per sample. The software package OBITools (http://metabarcoding. org/obitools) was used for sequence processing. After filtering, the final haplotypes were blasted against known reference sequences in the GenBank database (https://www.
ncbi. nlm. nih. gov/genbank/) and our Molecular Operational Taxonomic Units (MOTU) reference database  [68]. Sequences with less than 90% of similarity were classified only to the class level, whereas the ones with values between 90% to 95% were classified to the family level. In addition, sequences with similarity values beyond 95% were classified to the genus or species level. If a haplotype was similar to more than one species or genus, only species or genera recognized to occur on Branco Islet, or the surrounding islands of the archipelago were considered  [70]. Haplotypes identified as contaminations (e. g. , human DNA) were removed.
Funding:  CJP  ( SFRH/BD/145851/2019 ), RV ( SFRH/BPD/79913/2011 ) and  AP (IF/01257/2012 ) were supported by PhD, post-doc grants and IF contract, respectively, all funded by the  Portuguese 'Fundac  ¸ão para a Ciência e a Tecnologia, I. P' (FCT; https://www. fct. pt/),financed by the  European Social Fund  and the  Human Potential Operational Programme, POPH/FSE. RV was also funded by  Portuguese funds through FCT, under the 'Norma Transitoria'  ( DL57/2016/CP1440/CT0002 ). The travel expenses of RV and AM to Monaco were supported by  MOM  (https://musee. oceano. org/en/)and the lab work was supported by  Monaco Explorations  (https://www. monacoexplorations. org/en/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Sequencing libraries were prepared following the PacBio IsoSeq Express 2. 0 Workflow and using the NEBNext Single Cell/Low Input cDNA Synthesis & Amplification Module for the SMRTbell Express Template Prep Kit 2. 0. The resulting library was multiplexed and sequenced on a single Sequel II PacBio SMRT cell for 30 hrs. Library preparation and sequencing was carried out at DNA Sequencing Center at Brigham Young University (Provo, UT, USA). Genomic HiFi reads were generated by circular consensus sequencing (CCS) where consensus sequences have three or more passes with quality values equal to or greater than 20, from the subreads. bam files and using pbccs tool (v. 6. 0. 0) in the pbbioconda package (https://github. com /PacificBiosciences/pbbioconda). Using the same pbbioconda package and the Iso-seq v3 tools, high quality (> Q30) transcripts were generated from HiFi read clustering without polishing.