dataesr/scientific-paragraphs-categorization huggingface dataset:
Patient assessment and data collection Anonymized clinical data from baseline evaluation were collected retrospectively, including demographics, heart failure symptoms [New York Heart Association (NYHA) or Ross functional classification], pedigree analysis, resting and ambulatory 12-lead electrocardiogram (ECG), and two-dimensional (2D) Doppler and colour transthoracic echocardiogram. Hypertrophic cardiomyopathy Risk-Kids 5 predictor variables were recorded at the time of, or prior to baseline evaluation: specifically, unexplained syncope (defined as a transient loss of consciousness with no identifiable cause), non-sustained ventricular tachycardia (NSVT) (defined as > _3 consecutive ventricular beats at a rate of > _120 beats per minute lasting < _30 s on ambulatory ECG monitoring), MLVWT Z score,  8  left atrial (LA) diameter Z score (defined as the number of SDs away from population mean the 2D measurement of LA diameter),  9  and maximal left ventricular outflow tract (LVOT) gradient (defined as the maximal LVOT gradient at rest or with Valsalva provocation using continuous wave Doppler from apical three-or five-chamber views).
Statistical methods Statistical analysis was performed using Stata statistical software (Version 14) and R studio (Version 1. 7). Variables are described as mean ± SD, median [interquartile range (IQR)], and counts or percentages as appropriate. Group comparisons were performed using the Student's t-test, Mann-Whitney, or v 2 test as appropriate. Follow-up time was calculated from the time of baseline evaluation to the date of reaching the study end-point, death from another cause, or date of most recent evaluation. The Kaplan-Meier method was used to estimate the incidence of reaching the study end-point. Univariable Cox regression models were used to investigate the association of clinical variables with the study end-point.
A total of 75 imputed datasets were created. Estimates from imputed datasets were combined using Rubin's rule. 11 pertrophic cardiomyopathy Risk-Kids model validation Follow-up was censored at 5 years and the estimated 5-year risk of SCD was calculated for each individual patient using the HCM Risk-Kids model:  5  PðSCD at 5-yearsÞ ¼ 1-0:949437808 expðprognostic indexÞ ; where prognostic index = 0. 2171364 Â (MWT z score À 11. 09) À 0. 0047562 Â (MWT z score2-174. 12) þ 0. 130365 Â (LA diameter z score À 1. 92) þ 0. 429624 Â unexplained syncope þ 0. 1861694 Â NSVT À 0. 0065555 Â (maximal LVOT gradient À 21. 8). 3] [14]  Bootstrapping was used to calculate the confidence intervals (CIs) for Uno's C-index. Harrell's C-index is subject to bias if the amount of censoring is high  13  but is presented to enable comparison with alternative paediatric risk models.
The calibration slope was used to assess the degree of agreement between the observed and predicted risk of SCD (a value close to 1 suggests good overall agreement). 15 Model calibration was described graphically by stratifying patients into three risk groups based on tertiles of model predicted 5-year risk of SCD event from one imputed dataset. The positive predictive value (PPV) of using different thresholds of HCM Risk-Kids estimated risk at 5 years in one imputed dataset was calculated by dividing (sensitivity Â prevalence) by [(sensitivity Â prevalence) þ (1 À specificity) Â (1 À prevalence)] and expressed as a percentage. The negative predictive value (NPV) was calculated by dividing [specificity Â (1 À prevalence)] by [(1 À sensitivity Â prevalence) þ (specificity) Â (1 À prevalence)] and expressed as a percentage.
Hypertrophic cardiomyopathy Risk-Kids Model validation The performance of the HCM Risk-Kids model in predicting risk at 5 years was assessed in 421 patients with 23 events. Harrell's C-index was 0. 745 (95% CI 0. 52-0. 97) and Uno's C-index 0. 714 (95% CI 0. 58-0. 85). The calibration slope was 1. 15 (95% CI 0. 51-1. 80). Table  3  and Figure  3A  describe the agreement between predicted and observed 5-year cumulative proportion of SCD or equivalent events for each tertile of predicted risk in one imputed dataset.
Validation of using a predicted risk of !6% In a single imputed dataset, 125 (29. 7%) patients had a predicted 5-year risk of > _6%. Sudden cardiac death events occurred in. 6 patients (2. 0%) with a predicted risk <6% and 17 (13. 6%) with a predicted risk > _6. The clinical characteristics of those patients experiencing an SCD event with a predicted risk <6% is described in Supplementary material online, Table  4. Five-year survival free from SCD or an equivalent event was 96. 5% (95% CI 92. 2-98. 5) and 81. 3% (95% CI 71. 1-88. 2), respectively, with a corresponding hazard ratio of 6. 16 (95% CI 2. 43-15. 65, P < 0. 001) (Figure  2B ). The combined C-statistic for all imputed datasets for using a 5-year predicted risk threshold of > _6% was 0. 702 (95% CI 0. 60-0. 81). Figure  3B  describes the agreement between predicted and observed 5-year cumulative proportion of SCD events using a threshold of > _6%.
Acknowledgements Dr Jaana Pihkala  ( Department of Paediatric Cardiology, New Children's Hospital, University of Helsinki, Finland );  Dr Anita Hiippala  ( Department of Paediatric Cardiology, New Children's Hospital, University of Helsinki, Finland );  Dr Giulia Grilli  ( Heart Muscle Disease Registry Trieste, University of Trieste, Italy );  Dr Pierluigi Lesizza  ( Heart Muscle Disease Registry Trieste, University of Trieste, Italy );  Dr Alessandro Pierri  ( Heart Muscle Disease Registry Trieste, University of Trieste, Italy );  Simon Theisen  ( Charite -Universitatsmedizin Berlin, Germany ); and  Nadya Al-Wakeel  ( Charite -Universitatsmedizin Berlin, Germany ).
Funding This work was supported by the  British Heart Foundation  ( FS/16/72/ 32270  to G. N. and J. P. K. ). E. F. and J. P. K. are supported by  Max's Foundation and Great Ormond Street Hospital Children's Charity. J. P. K. is supported by a  Medical Research Council Clinical (MRC)-National Institute for Health Research (NIHR) Clinical Academic Research Partnership (CARP)  award. This work is (partly) funded by the  NIHR GOSH BRC. R. Z. O. and C. Q. work at  University College London Hospitals/University College London  who received a proportion of funding from the  UK Department of Health's National Institute for Health Research Biomedical Research Centres funding scheme. The views expressed are those of the authors and not necessarily those of the  NHS , the  NIHR  or the Department of Health.
C. Y. H. receives funding from the  National Institutes of Health  and consulting honoraria from  Myokardia, Inc. /Bristol Myers Squib. This work was financially supported by the  Foundation for Paediatric Research, Finland  (T. H. O. ). C. S. is the recipient of a  National Health and Medical Research Council (NHMRC)   Practitioner Fellowship  (# 1154992 ). J. I. is supported by a  National Health and Medical Research Council (NHMRC)   Career Development Fellowship  (# 1162929 ). J. I. receives research grant support from  Myokardia, Inc.
Study Design and Participants The authors conducted a retrospective cohort study of all patients who underwent ECMO of any configuration for confirmed COVID-19Àrelated ARDS at ten ECMO centers in five European countries (France, Germany, Italy, Sweden, UK) (ClinicalTrials. gov identifier, NCT04383678). All participating centers but one (Lecco, Hospital, Italy) were tertiary care university hospitals and designated COVID-19 ECMO centers. The study protocol was approved by the institutional or national review board of each participating center according to national legislations. Informed consent was waived because of the retrospective nature of this study. The inclusion criteria for the study entry were adults aged 18 years or older with severe hypoxemia with or without hemodynamic instability refractory to conventional therapies associated with laboratory-confirmed COVID-19Àrelated ARDS.
ARDS was defined according to the Berlin definition criteria. 11 ata were collected retrospectively into a dedicated electronic datasheet with prespecified variables by experienced clinicians, and underwent checking of its completeness and quality. Data on baseline characteristics, ECMO therapy, and adverse events were retrieved from the electronic patient records. Data on intermediate survival were retrieved from national registries and electronic patient records, and by contacting patients and their general practitioners. Six-month follow-up was complete for all but four patients whose followup ranged from 3. 0-to-5. 2 months.
Apparatus For electrochemical measurements, the experiments were carried out in a conventional three-electrode double walled cylindrical glass cell. A saturated calomel electrode (SCE) placed in a separate compartment containing the supporting electrolyte and a platinum wire electrode were used as reference and auxiliary electrode, respectively. The polarization curves, at a scan rate of 20 mV. s -1 , and electrochemical impedance spectroscopy (EIS) tests were carried out in aerated solution using an AUTOLAB Potentiostat/Galvanostat (SP-150) Biologic SAS under FRA software. For EIS tests, we measured the response of our electrochemical system to alternating current (a. c) excitation with a frequency ranging from 100 kHz to 100 mHz and peak to peak a. c. amplitude of 10 mV. The impedance diagrams are given in the Nyquist representation.
6 GeV/c, see Ref. [52] ) and the X(3872) line-shape campaign (7 GeV/c, see Ref. [53] ). Since hyperons have relatively long life-time (10 -10 s), they travel a measurable distance before decaying. This makes the track reconstruction a challenging task  [55] [56] [57]  since most standard algorithms assume that all tracks originate in the beam-target interaction point. The simulation study presented here is focused on Phase One of PANDA. A realistic PandaROOT implementation of the Phase One conditions was used  [58]. Some simplifications were made due to limitations in the current version of the simulation software: -The general track reconstruction algorithms that can handle tracks originating far from the interaction point, are still under development and have not yet been deployed as a part of the standard PandaROOT package.
However, the spin observables must satify some constraints: i) they need to stay within the interval [-1, 1] and ii) they need to go to zero at extreme angles, i. e. θ Y = 0 o and θ Y = 180 o. The latter is because at these angles, the incoming beam is either parallel or anti-parallel to the outgoing antihyperon. Their cross product, giving the direction of the normal of the production plane, is thus not defined. The data in this study were weighted according to P Y y (θ Y ) = sin 2θ Y (10) and C Ȳ Y ij (θ Y ) = sin θ Y. (11) since they satisfy the constraints and since this gives a polarisation with a shape that resembles real data  [32, 38].
Fit of the Ξ -→ Λπ -, Λ → pπ -decay chain The second step is to exploit the distinct topology of the pp → Ξ+ Ξ -, Ξ+ → Λπ + , Λ → pπ + , Ξ -→ Λπ -, Λ → pπ -process, that imposes many constraints. Therefore, all Ξ -candidates from the previous step are fitted under the Ξ -→ Λπ -, Λ → pπ -hypothesis where the Λ mass is constrained to its PDG value. This is achieved using the Decay Chain Fitting package  [72] , designed to perform kinematic fitting on a sequence of decays with at least one over-constraint. Taking all constraints and unknown parameters in the fit into account, results in three effective degrees of freedom. The advantage of this approach compared to multiple sequential fits, is that all constraints in a reaction are taken into account simultaneously, on an equal basis. This feature is not available in conventional fitters.
Acknowledgement We acknowledge financial support from the  Bhabha Atomic Research Centre (BARC)  and the  Indian Institute of Technology Bombay, India ; the  Bundesministerium für Bildung und Forschung (BMBF) ,  Germany ; the  Carl-Zeiss-Stiftung   21-0563-2. 8/122/1and 21-0563-2. 8/131/1 , Mainz , Germany; the  Center for Advanced Radiation Technology (KVI-CART ), Groningen, Netherlands; the  CNRS/IN2P3  and the  Université Paris-Sud , France; the  Czech Ministry (MEYS)  grants  LM2015049 ,  CZ. 02. 1. 01/0. 0/0. 0/16  and  013/0001677 , the  Deutsche Forschungsgemeinschaft (DFG) ,  Germany ; the  Deutscher Akademischer Austauschdienst (DAAD) , Germany; the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  824093. the  Forschungszentrum Jülich, Germany ; the  Gesellschaft für Schwerionenforschung GmbH (GSI) ,  Darmstadt, Germany ; the  Helmholtz-Gemeinschaft Deutscher Forschungszentren (HGF) ,  Germany ; the  INTAS, European Commission  funding; the  Institute of High Energy Physics (IHEP)  and the  Chinese Academy of Sciences, Beijing, China ; the  Istituto Nazionale di Fisica Nucleare (INFN), Italy ; the  Ministerio de Educacion y Ciencia (MEC)  under grant  FPA2006-12120-C03-02 ; the  Polish Ministry of Science and Higher Education (MNiSW)  grant No.
While weak disorder is crucial for the establishment of the branches and for certain observables like the conductance of a mirror-confined cavity, it does not prevent the emergence of classical trajectory features underlying the SGM pattern. A Quantum simulation of SGM in a cavity We have performed quantum transport simulations using the Kwant package  [25]. In these simulations, we calculate the electronic transport properties assuming that the electrons move in an effective one-body potential that determines the cavity as shown in Fig. 9 , and that electron-electron interaction effects beyond mean field can be neglected. The non-abrupt character of the chosen confining potential diminishes the importance of diffraction effects  [31, 32]  appearing in this kind of geometry. The electron dynamics is assumed to be perfectly coherent, and the transport properties are calculated at zero temperature.
Acknowledgements We are indebted to  Carolin Gold ,  Klaus Ensslin , and  Thomas Ihn  for sharing with us unpublished experimental results which motivated the present work. We are grateful to  Nicolas Cartier  for useful discussions. Funding information Financial support from the  French National Research Agency ANR  through projects  ANR-11-LABX-0058   NIE  ( Labex NIE ) and  ANR-14-CE36-0007-01  ( SGM-Bal)  is gratefully acknowledged. This research project has been supported by the  University of Strasbourg IdEx program.
Aims. A detailed characterisation and theoretical interpretation of the broadband emission of the paradigmatic TeV blazar Mrk 421, with special focus on the multi-band flux correlations. Methods. The dataset has been collected through an extensive multiwavelength campaign organised between 2016 December and 2017 June. The instruments involved are MAGIC, FACT, Fermi-LAT, Swift, GASP-WEBT, OVRO, Medicina and Metsähovi. Additionally, four deep exposures (several hours long) with simultaneous MAGIC and NuSTAR observations allowed a precise measurement of the falling segments of the two spectral components. Results. The very-high-energy (VHE; E > 100 GeV) gamma rays and X-rays are positively correlated at zero time lag, but the strength and characteristics of the correlation change substantially across the various energy bands probed.
MAGIC Mrk 421 belongs to the group of targets that the MAGIC telescopes monitor on a regular basis. The MAGIC telescopes form a system of two 17-m diameter imaging atmospheric Cherenkov telescopes (IACTs). They are situated at an altitude of 2231 m above sea level, on the Canary Island of La Palma at the Roque de los Muchachos Observatory. The integral sensitivity for point sources observations above 220 GeV is (0. 66 ± 0. 03)% C. U. in 50 hours  (Aleksić et al. 2016). The MAGIC dataset presented in this work covers a ≈6month period from MJD 57727 (2016 December 5) until MJD 57892 (2017  May 19). We analysed the data using the standard analysis tools from the MAGIC Analysis and Reconstruction Software (MARS) package  (Zanin et al. 2013; Aleksić et al. 2016). A significant fraction of the observations were carried out with an increased night sky background light contamination (due to the presence of the moon), which directly affects the response of the telescopes  (Ahnen et al.
Petersburg (Russia), Teide (Spain), Tijarafe (Spain), Vidojevica (Serbia), West Mountain (US). The data reduction was performed according to standard prescriptions. To minimise offsets among the different data sets due to the presence of the host galaxy, a common aperture radius of 7. 5 arcsec was used. Following  Nilsson et al. (2007) , we subtracted a host galaxy contribution of 8. 2 mJy from the observed flux density and then corrected for a Galactic extinction of 0. 033 mag according to the NASA/IPAC Extragalactic Database 9 (NED). 7 http://www. oato. inaf. it/blazars/webt/ 8 Calar Alto data was acquired as part of the MAPCAT project: http: //www. iaa. es/~iagudo/_iagudo/MAPCAT. html 9 https://ned. ipac. caltech. edu/.
16, which is the mean value of the dataset. This procedure removes the correlation between the two parameters of the model, which allows a more illustrative description of the evolution of the hardness versus flux to be obtained. The resulting α versus F 3-7keV is shown in Fig. 5. A large variation of α is visible, ranging from ≈1. 8 to ≈2. 8, with a clear harder-when-brighter behaviour, as is typical in Mrk 421  (Aleksić et al. 2015a; MAGIC Collaboration et al. 2020b ) and HBLs in general  (Pian et al. 1998; Krawczynski et al. 2004; MAGIC Collaboration et al. 2020a). A linear fit results in a slope of -0. 64 ± 0. 01, and corroborates the harder-when-brighter behaviour visible in the NuSTAR data. For the linear fit we ignore the spectral fits resulting in a p-value 11 below 5 × 10 -2 in order to remove the few nights (only 18 out of 107) that are not well described by the spectral model.
6  for each of the energy bands. They are computed using a nightly binning for the MAGIC, FACT, Swift-XRT, Swift-UVOT, R-band and radio light curves. Because of the limited sensitivity to detect Mrk 421 on timescales of one day, for Fermi-LAT and Swift-BAT, we adopted a 3-day binning over which to integrate the data and compute the fluxes. Solid markers include all data from Fig. 1. A discrepancy between the MAGIC (>1 TeV) and FACT F var is visible and is explained by the different nightly averaged flux measured during the flare on MJD 57788 due to the different integration time, as previously mentioned. When the day of the flare is ignored, the F var values are fully compatible. All of the MAGIC/FACT/Swift-XRT/BAT/UVOT measurements that are separated from one another by less than 4 hours are considered and are shown with hollow markers.
Interestingly, the first two NuSTAR nights on MJD 57757 and MJD 57785, which show an enhanced VHE activity in Fig. 8 , also seem to stand out from the distribution. They are plotted with diamond open markers in Fig. 9. The VHE flux is higher than the bulk of the data. Together with the MJD 57788 flare, these measurements suggest a change in the VHE versus X-ray correlation with respect to the typical behaviour. The correlation is quantified following the same methodology described in the previous section. The Pearson coefficients, the DCF and the slopes from the linear fits are listed in Table 1. The entire dataset (28 measurements) is considered. The Pearson coefficients are consistent within uncertainties between each energy combination and are all greater than 0. 7. Also, the significances are all above 4 σ.
the scatter of the data over the main trend shows that there are many days when the synchrotron emission of Mrk 421 did behave substantially differently. This may be caused by different particle or environment conditions in the main emitting region, or because of the presence of additional components that, during short periods of time, contribute significantly to the overall synchrotron emission of Mrk 421. Either way, the ν s F ν (ν s ) versus ν s data for these days appear as outliers in the the main trend with slope of about 0. 2, shown in Fig. 12. Fig. 13  shows ν s F ν (ν s ) versus the curvature parameter b as defined in Eq. 2. The data tend to indicate a lower curvature with increasing ν s F ν (ν s ) values, although this anti-correlation remains weak and some outliers exist. A linear fit yields a slope of -1.
On the other hand, the large variability of the synchrotron peak frequency discussed may facilitate the detection of correlation patterns. We cross-correlate UV/optical with X-ray fluxes by selecting all possible combinations between the following light curves: optical (R-band), Swift-UVOT, Swift-XRT(0. 3-2 keV) and Swift-XRT(2-10 keV). Regarding Swift-UVOT, we consider data from the W2 filter. Given their proximity in frequency, fluxes in the three Swift-UVOT filters are strongly correlated and all of them yield very similar results. The choice of the W2 filter is further motivated by the slightly larger amount of measurements compared to W1 and M2, providing a better coverage of the source. As in Sect. 4, we use the DCF  (Edelson & Krolik 1988)  to quantify the correlation. It is known that the significance of the correlation assessed directly from the DCF uncertainty given in  Edelson & Krolik (1988)  can be overestimated  (Uttley et al.
The results are displayed in Fig. F. 1 of Appendix F, and show that the anti-correlation disappears (significance drops below 3σ) for all the bands probed. Additionally, we also evaluate the correlation using only data within the time interval MJD 57720-57760. The results are shown in Fig. F. 2 of Appendix F. This time, the significance is above 3σ for the cross-correlations from all energy bands (the DCF values are also higher), confirming the overall dominance of the time interval MJD 57720-57760 in the cross-correlation results. This observation suggests that these two bands are not persistently related to each other (as occurs between the VHE gamma rays and the X-rays in Mrk 421), but instead show a degree of correlation that changes with time, and is significant only during month timescales.
We note though that the NuSTAR observations consist of continuous exposures, while for Swift the observations are shorter and scattered over the MAGIC window (see   4. In the high energy (HE) band, owing to the limited ability to significantly detect Mrk 421 in this energy range, the Fermi-LAT spectra are averaged over 3 days, which provides a good compromise between simultaneity and spectral resolution. Optical (R-band) data are not strictly simultaneous, but the closest observation in time is chosen, which results in a time difference of at most one day. Because of the low variability in the optical band reported in Fig. 1  and Fig. 6 , they can be considered as a good proxy for the simultaneous emission in the optical band. The broadband SEDs are shown with brown data points in Fig. 15.
The SED data describing a quiescent state (averaged over 5 months) reported in  Abdo et al. (2011)  are also plotted, for comparison purposes, with grey full dots. A slight mismatch is visible between Swift-XRT and NuSTAR in their overlapping region (around 10 18 Hz). For the X-ray spectra from MJD 57757, MJD 57785 and MJD 57840, the mismatch is always less than 15%, which is within the systematic uncertainties of these two instruments  (Madsen et al. 2017 ). On MJD 57813 (lower left panel), the mismatch is somewhat larger. The last Swift-XRT point, the one with the largest discrepancy, is 34%±17% off from the lowest-energy point of the NuSTAR spectrum. We note that this remains at the level of 2σ, and thus may well be due to a statistical fluctuation. Moreover, the X-ray flux variability on hour timescales and the longer exposures of NuSTAR (see light curves in Appendix B) may also contribute to this small mismatch between the X-ray fluxes measured by these two instruments.