dataesr/scientific-paragraphs-categorization huggingface dataset:
; visualisation, L. G. ; supervision, L. R. , L. B. -M. and A. M. ; project administration, L. R. , C. I. H. , B. N. , L. P. and N. J. ; funding acquisition, H. G. , J. R. , L. Y. and J. D. L. All authors have read and agreed to the published version of the manuscript. Funding: RESPOND received funding from ViiV Healthcare LLC (Grant number 207709), Gilead Sciences (Grant number CO-EU-311-4339), and Merck Sharp & Dohme (Grant number LKR196747). Additional support was provided by participating cohorts contributing data in-kind and/or statistical support: Austrian HIV Cohort Study (AHIVCOS), The Australian HIV Observational Database (AHOD), CHU Saint-Pierre, University Hospital Cologne, EuroSIDA, Frankfurt HIV Cohort Study, Georgian National AIDS Health Information System (AIDS HIS), Modena HIV Cohort, San Raffaele Scientific Institute, Swiss HIV Cohort Study (SHCS), AIDS Therapy Evaluation in the Netherlands Cohort (ATHENA), and the Royal Free HIV Cohort Study.
7, Cohortes) to the Aquitaine Cohort. The Australian HIV Observational Database (AHOD) is funded as part of the Asia Pacific HIV Observational Database, a programme of The Foundation for AIDS Research, amfAR, and is supported in part by a grant from the U. S. National Institutes of Health's National Institute of Allergy and Infectious Diseases (NIAID) (grant number U01-AI069907) and by unconditional grants from Merck Sharp & Dohme; Gilead Sciences; Bristol-Myers Squibb; Boehringer Ingelheim; and Janssen-Cilag; ViiV Healthcare. The Kirby Institute is funded by The Australian Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, The University of New South Wales; by grants from the Fondo de Investigación Sanitaria (grant number FIS 99/0887) and Fundación para la Investigación y la Prevención del SIDA en Espanã (grant number FIPSE 3171/00), to the Barcelona Antiretroviral Surveillance Study (BASS); by the National Institute of Allergy and Infectious Diseases, National Institutes of Health (grants number 5U01AI042170-10, 5U01AI046362-03), to the Terry Beirn Community Programs for Clinical Research on AIDS (CPCRA); by primary funding provided by the European Union's Seventh Framework Programme for research, technological development, and demonstration under EuroCoord grant agreement no 260694; and by unrestricted grants from Bristol-Myers Squibb, Janssen R&D, Merck and Co.
Inc. , Pfizer Inc. , GlaxoSmithKline LLC, (the participation of centres from Switzerland is supported by The Swiss National Science Foundation (Grant 108787)) to the EuroSIDA study; by unrestricted educational grants of AbbVie, Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline, Pfizer, Janssen Pharmaceuticals to the Italian Cohort Naive to Antiretrovirals (The ICONA Foundation); and financed within the framework of the Swiss HIV Cohort Study, supported by the Swiss National Science Foundation (grant # 148522), and by the SHCS Research Foundation. JMM received a personal 80:20 research grant from Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain, during 2017-24.
The new results are combined with published ages obtained with different chronometers (U -Pb, Sm -Nd, Rb -Sr, K -Ar, 40 Ar/ 39 Ar). This dataset reveals that the two units record different thermal evolutions from the Permian post-orogenic extension to the Jurassic rifting. Ages of cooling initiation and associated cooling rates are estimated by Monte Carlo simulations based on DiffArgP. The Grosina unit records a Permo-Triassic slow cooling of 5-10 • C/Myr initiated during Early Permian in relation to the post-Variscan relaxation of the isotherms and cooling of the lithosphere that caused a large-scale thermal subsidence. By contrast, the Campo unit records a fast cooling of 25-100 • C/Myr associated to the tectonic exhumation of basement rocks during the Jurassic rifting and the formation of the Alpine Tethys rifted margin.
See text for details; complete dataset provided as Supplementary Material S5. Errors are represented at a 2σ level of confidence; KDE plots were produced using IsoplotR  (Vermeesch, 2018). in CP028c, and (3) muscovite still preserves its peak-metamorphic compositions as attested by applied thermometry (695 • C and 567 • C, respectively). This is in line with estimates obtained by biotite thermometry (see below) as well as for the regional and contact metamorphism around the Early Permian Sondalo gabbro  (Petri et al. , 2017 (Petri et al. , , 2016)). These temperature estimates are notably above the expected closure temperature of the argon system in muscovite. Therefore, the overlapping 182 and 178 Ma ages of muscovite CM260 and muscovite CP028c can be interpreted as cooling ages. This is not straightforward for the older muscovite CP003b that can also be interpreted as a crystallization age given its structural position.
Cooling and exhumation history of the Campo and Grosina basements These new ages, together with a compilation of published U -Pb, Sm-Nd, Rb-Sr, K-Ar and 40 Ar/ 39 Ar ages performed on both the Grosina and Campo basements (see Fig. 10 , Supplementary Material S5 and S7), constitute a consistent dataset to estimate the respective cooling history of the two units. Deciphering the thermal history and cooling rates is hampered by the fact that closure temperatures are sensitive to the cooling rate itself, mineral composition, and grain size. To a first approximation, geochronological data can be linked to the closure temperature of the probed chronometer/mineral system (details presented in Supplementary Fig. S7 ). Two distinct events of cooling can be identified (Fig. 10  and Supplementary Material S7): a Permo-Triassic cooling, and a subsequent Jurassic cooling.
Thermal evolution during Permian post-orogenic extension From our dataset, the Permian cooling phase is best recorded in the Grosina unit with the 261 ± 2 Ma muscovite age, and the 246 ± 13 and 245 ± 2 Ma biotite ages, indicating a cooling during Permo-Triassic times. At a regional scale, this period corresponds to the end of the intense magmatic and metamorphic event immediately following the Variscan orogeny and its collapse (Fig. 13ab ;  Petri et al. , 2017). This period is associated with the emplacement of both mafic and felsic intrusives from the lower continental crust to the upper continental crust  (Hermann and Rubatto, 2003; von Quadt et al. , 1994 ), and regional high-temperature metamorphism (see compilation in Fig. 11 ;  Hermann and Rubatto, 2003; Petri et al. , 2016). The cessation of the HT regional conditions implies a progressive thermal relaxation and deepening of the isotherms that caused a thermal subsidence permitting the deposition of Triassic shallow-marine sediments (Fig.
This implies that continental basement units were likely not exhumed. As a consequence, we maintain P constant at 3 kbar. Node G3 simulates final riftrelated exhumation close to the surface (170 ± 10 Ma, 100 • C, 0. 5 kbar). The selected timing is based on both stratigraphic and thermochronological data documenting the evidence for final rifting stage and basement exhumation  (Mohn et al. , 2010; Müntener and Hermann, 2001; Petri et al. , 2019). Node G4 at 0 Ma has similar P-T conditions than node G3. The 10,000 paths that were generated (Fig. 12a ) converge around 260 Ma and around 240 Ma, but are not converging for node G3 because of its large difference in age with our dataset combined to the low T-t gradient of the path. The initial temperature conditions are consistent with qualitative P-T estimates of 550-600 • C that can be deduced from the regional presence of andalusite of probable Early Permian age in the Grosina unit.
Thermal evolution during Jurassic rifting From our 40 Ar/ 39 Ar dataset, the Jurassic, rift-related cooling seems to be only recorded in the Campo unit. The new hornblende, muscovite and biotite ages presented in this study span a narrow temporal range within ca. 4 Myr between hornblende and biotite (sample CP031a) and between muscovite and biotite (sample CP028c). It points to a cooling of the Campo basement during the Jurassic that appears to be rapid, with estimates based on theoretical closure temperatures reaching up to 30-45 • C/Myr (Supplementary Fig. S7 ). Such rapid cooling is also indicated by the near-constant age of consecutive steps for biotites, translated by lower MSWD values of the sub-plateau ages for the Jurassic cooling (Campo unit) compared to the Permian cooling (Grosina unit; Figs.
This indicates that our dataset is clearly supporting a final cooling initiated between 180 and 175 Ma, with rather fast cooling rates of 25-100 • C/Myr (Fig. 12bc ). This age slightly precedes the cessation of activity of necking detachment faults and a drowning of the Tethyan necking zones reported from several studies (Southern Alps:  Decarlis et al. , 2017; Eastern Alps: Mohn et al. , 2012; External Crystalline Massifs: Ribes et al. , 2020)  that occurred in Toarcian-Aalenian times. The thermal evolution of the necking zone before node C3 remains more ambiguous. Our Monte Carlo simulations do not converge for both nodes C1 and C2 (when active, Fig. 12c ). We know that the maximal temperature of node C3 should be likely limited, as petrological observations from the Campo unit do not report any evidence from syn-rift high temperature metamorphism, but the initial temperature (position of node C2) and the amount of heating cannot be directly constrained.
Data collection The following informations were collected on standardized forms: epidemiological parameters; acute heart failure clinical, biological and therapeutic history; clinical manifestations; laboratory findings; MCS type, indication and complication(s); in-ICU organ-support treatments; noninvasive myocarditis work-up results; myocardial biopsy characteristics, results and complications; biopsy results; treatments introduced in the ICU; ECMO-weaning status; bridge-to-transplantation or ventricular assist device (LVAD); ICU complications; vital status, transplantation status at ICU and hospital discharges and at last follow-up.
Statistical analyses Results for categorical variables, expressed as number (%), were compared with χ 2 or the exact test of Fischer; those for continuous variables, expressed as median [25th-75th percentile interquartile range (IQR)], were compared using Wilcoxon's rank test. Categorical variables of invasive and noninvasive diagnosis work-up were compared using the test of McNemar. Statistical significance was defined as p ≤ 0. 05. Analyses were computed with IBM SPSS Statistics v22. 0 software (IBM Corp, Armonk, NY).
Ethical considerations The database is registered with the "Commission Nationale de l'Informatique et des Libertés" (2217847v0). In accordance with the ethical standards of our hospital's institutional review board, the Committee for the Protection of Human Subjects, and French law, written informed consent was not needed for demographic, physiological and hospital-outcome data analyses because this observational study did not modify existing diagnostic or therapeutic strategies; however, patients were informed of their inclusion in the study.
Participants We considered data from second-and third-year physiotherapy students. This study was conducted over three university years from September 2017 to July 2020. Repeat students and students with flexible work arrangements (i. e. , top-level athletes) were excluded. The study complied with the standards set by the Declaration of Helsinki  (34). All participants gave written informed consent after being instructed as to the nature and purpose of the study, which was approved by the local ethics committee of Paris-Saclay University under registration number CER-Paris-Saclay-2020-095. A baseline group (2017-18 baseline group) was formed of secondyear physiotherapy students who attended only in-person gross anatomy courses with no specific physiotherapy musculoskeletal blended learning in anatomy (from September 2017 to July 2018).
Secondary outcomes An investigation field was made through an online data survey to evaluate the pedagogical value of musculoskeletal blended learning and its usefulness for preparing the student for their anatomy final written exam at "X" physiotherapy school. The retrospective target and eligible population and the eligibility criteria corresponded to second-to third-year physiotherapy students at "X" physiotherapy school over three university years from September 2017 to July 2020. Concerning the sources and methods of selection, all the participants were recruited through the survey. Participants were able to complete the survey at any time during the period mentioned above. All data were self-reported by the participants. The survey was anonymous, and data confidentiality was assured in accordance with the European General Data Protection Regulation.
Statistical methods A descriptive analysis was performed to determine the average score of each blended learning unit. The Shapiro-Wilk W test was used to evaluate each variable for normality and established that nonparametric statistic tests should be used (Shapiro test with p < 0. 001). The mean score during both semesters concerned was compared for 2017-18 and 2019-20 with Kruskal-Wallis test. The mean score between groups (i. e. , 2017-18 baseline group, 2018-19 and 2019-20 experimental groups) was compared with Mann-Whitney test. Statistical analysis was performed using JASP ® (Version 0. 14. 1, Amsterdam, Netherlands). A Fisher's exact test was performed to determine the association between dependent and independent variables. Statistical analysis was performed using SPSS statistical software (Version 23.
We apply the cross-correlation technique  (Snellen et al. 2010 ) in order to search for atomic and ionised metals as well as molecules, and we fit the traces in the cross-correlation functions to determine spectral and orbital parameters using time-resolved spectroscopy. Section 2 describes the observations and data reduction procedures. Section 3 describes the telluric and preparatory corrections and further details the analysis process for the crosscorrelation technique and trace fitting of this dataset, which presents the basis of our findings. In Sect. 4, we present the results of the analysis and discuss their implications. Conclusions are presented in Sect. 5.
Observations and data reduction We observed one transit of the ultra-hot Jupiter WASP-189 b using the ESPRESSO echelle spectrograph at the ESO Very Large Telescope in Chile  (Pepe et al. 2021 ) and two transits with the MAROON-X high-resolution optical spectrograph at the 8. 1 m Gemini-North observatory in Hawaii  (Seifahrt et al. 2018 (Seifahrt et al. , 2020)). The transits were observed on 2021-06-04 with ESPRESSO (programme ID 107. 22QF, PI: Prinoth) and on 2022-04-03 and 2022-06-02 with MAROON-X (programme ID GN-2022A-FT-208, PI: Pelletier). The ESPRESSO observations were performed in highresolution mode with a spectral resolution of R = λ ∆λ = 140 000 covering the wavelength range between 380-788 nm. It is known that the readout speed of 500 kpx s -1 associated with the unbinned (1 × 1) readout mode introduces correlated noise at the bias level that is much larger than with the binned (2 × 1) readout mode.
1%, respectively, become visible when spectra are recorded at different telescope positions and then divided by each other  (Allart et al. 2020). The high-frequency pattern (1 Å) is below the photon-noise level, while the low-frequency pattern was corrected as discussed in Sect. 3. 2. Science observations were performed with fibre A on the target and fibre B on the sky. The observations performed with ESPRESSO were reduced using the ESPRESSO data reduction workflow (pipeline version 2. 3. 3) provided by ESO and executed via EsoReflex (version 3. 13. 5) 2. The pipeline provides both one-and two-dimensional products with and without sky subtraction. The one-dimensional products contain a stitched, blaze-corrected spectrum, corrected for Earth's velocity around the barycentre of the Solar system (BERV) with both vacuum and air wavelength solutions.
(2022). The shaded regions indicate the standard deviation away from the peak. Neutral atoms are generally well described by the model at 2500 K. The dashed vertical line shows the expected systemic velocity of -24. 452 ± 0. 012 km s -1. The model prediction of TiO has been scaled by a factor of six to match the predicted signal strength in  Prinoth et al. (2022)  for the purpose of comparing the datasets from the instruments in Fig. 6. with the projected orbital velocity of the planet, we were not able to confirm this detection when including three more transit observations. Apart from Cr + and Sc + , we confirm all detections and tentative detections in  Prinoth et al. (2022)  and  Stangret et al. (2022). Additionally, we detected Sr, Sr + , and Ba + , which have not been detected in the atmosphere of this planet previously.
Robust confirmation of TiO The combination of the two MAROON-X and the ESPRESSO observations robustly confirms the detection for TiO in the transmission spectrum of WASP-189 b. Combining the data of all eight transit time series, we detected TiO at 6. 65σ. The observed significance is in agreement with the model at 2500 K if scaled by a factor of six (needed to bring the model prediction in agreement with  Prinoth et al. 2022). Despite the additional noise caused by interference patterns in the ESPRESSO data in the form of internal reflections in the optical path, it is possible to detect and thus confirm TiO (see Fig. 6 ). The detection of TiO in the MAROON-X and ESPRESSO data combined is mostly driven by the MAROON-X data.
With the exception of H, Ba + , Ca + , Ni, and TiO, all detected species either showed an increase in signal strength over the course of the transit or appeared to be constant. A decrease in signal strength may be caused by a loss of the absorbing species towards the hot trailing terminator. We propose that this can be explained through either ionisation or dissociation on the dayside. Figure  8  shows the ionisation temperatures and energies for the detected atomic species for the first and second ionisation states. The ionisation curves were computed using FastChem  (Stock et al. 2018 (Stock et al. , 2022)) , assuming chemical equilibrium. The ionisation energies were taken from the NIST database  (Kramida et al. 2022). The temperature on the dayside is likely high enough to thermally ionise species with relatively lower ionisation energies.
A182, page 10 of 38 Fig. 6. Cross-correlation results in K p -V sys space for TiO in WASP-189 b's atmosphere during eight transit events with HARPS & HARPS-N, ESPRESSO, and MAROON-X. From left to right: MAROON-X alone, MAROON-X restricted to ESPRESSO wavelength coverage (wlc), and ESPRESSO alone (see Table  1 ). The dashed lines indicate the expected location of the signal if we assume a symmetric planet with a static atmosphere. The model predictions show the expected signal strength using models at 2500 (in teal) and 3000 K (in magenta) in chemical and hydrostatic equilibrium of solar metallicity, previously used in  Prinoth et al. (2022) , and have been scaled by a factor of six for clarity to show that the model discrepancy is equivalent in the data from the three different instruments despite their different wavelength coverage.
The predicted signals are a measure of the sensitivity of the dataset and show that we expect MAROON-X to have a stronger signal. We note that discrepancies with  Prinoth et al. (2022)  stem from a different weighting algorithm based on the predicted signal strength (through model injection) applied here. This weighting algorithm favours the signal of better nights, increasing the signal strength overall. The results show that the signal is recovered in the new datasets alone as well but with a lower relative flux compared with expectations from the model injection. Fig. 7. Change in signal strength between the start and the end of the transit as a function of the observed deviation from the expected systemic velocity. The error bars denote 1σ uncertainties calculated via Gaussian error propagation.
Transition metals are plotted in teal. The dashed, dash-dotted, and dotted lines indicate that the detected signal strength of the neutral atom, ionised atom, and oxide weakens over the course of the transit, respectively. Solid lines indicate that the signal strengths of the detections either strengthen over the course of the transit or remain constant, and thus behave as expected. The ionisation curves move towards lower temperatures with decreasing pressure (increasing altitude). Additionally, the fractions decrease at high temperatures for alkaline earth metals due to a second ionisation. The ionisation energies (bottom panel) are from the NIST database  (Kramida et al. 2022 ) which predict that Na, Ba, Ca, Ba + , and Sr are all easily ionised. Regarding H, it may significantly ionise at very high altitudes.
Acknowledgements. B. P. , H. J. H. , and N. W. B acknowledge partial financial support from  The Fund of the Walter Gyllenberg Foundation. S. P. and B. B. acknowledge financial support from the  Natural Sciences and Engineering Research Council (NSERC) of Canada  and the  Fond de Recherche Québécois-Nature et Technologie (FRQNT; Québec). M. Br. acknowledges support from the  National Science Foundation Graduate Research Fellowship  under Grant No. DGE 1746045. R. L. acknowledges funding from the  University of La Laguna  through the  Margarita Salas Fellowship  from the  Spanish Ministry of Universities  ref. UNI/551/2021-May 26 , and under the  EU Next Generation  funds. B. T. acknowledges the financial support from the  Wenner-Gren Foundation  ( WGF2022-0041 ). M. Bu. acknowledges support from the  Swedish Research Council  VR through grant no.
In each genotype group, the proportion of patients reaching the primary endpoint and the corresponding 90% con dence interval (CI) were calculated, and the lower boundary was compared with 50%. Given the low rate of virological failure, association between possible predictors (HCV genotype, Apri score, HIV status and adherence score) were studied by univariate graphical description with 95% CI. Statistical analysis was performed with SAS software version 9. 4.
Nevertheless, the adopted model was based on full gratuity of rst-and second-line treatment and HCV clinical follow-up. This gratuity was a main strength and key to the model of care's success, as is already the case for HIV care in SSA. Another important strength is that the study also assessed self-reported adherence, which can contribute to understanding the risk of failure to rst-line DAAs. Another strength was the opportunity to create a network for HCV screening and care in the areas where it was conducted. This network now has the potential to reinforce collaboration between governments and ministries of health to improve the management of viral hepatitis in Africa, strengthen the partnership with NGOs involved in viral hepatitis control in Africa and provide international research agencies and WHO with new data on HCV in Africa, which are currently lacking, and thus help to establish recommendations adapted to the African context.
, 2011)  and simulation of cropping systems using climatedependent sowing dates  (Waha et al. , 2012). The LPJmL model has also been applied over the IGB river basins of South Asia. The South Asian model version, used in this study, includes representation of double-cropping patterns with zone-speci c monsoon dependent sowing dates for kharif and xed sowing dates for rabi season  (Biemans et al. , 2016). It also includes the application of water-saving potential by the implementation of different irrigation systems  (Jägermeyr et al. , 2016). Additional developments include improved spatial resolution i. e. from 0. 5 degrees to 5 arc-min using high resolution gridded climate dataset  (Lutz, ter Maat, et al. , 2016) , representation of a groundwater reservoir together with groundwater withdrawals leading to groundwater depletion and representation of large scale irrigation through extensive canal systems  (Wijngaard et al.