dataesr/scientific-paragraphs-categorization huggingface dataset:
In the larger fraction, noble gases are isolated via hot gettering to remove reactive gases. The purified noble gases are then analyzed for δ 40/36 Ar, δ 40/38 Ar, δ 86/82 Kr, δ 86/84 Kr, δ 86/83 Kr, δKr/Ar, and δXe/Ar on a 10 kV Thermo Finnigan MAT253 dual-inlet IRMS. We reject one sample from RICE due to incomplete sample transfer and one sample from WDC due to problems with the water trap. Calibration is done for each measurement campaign by running samples of La Jolla pier air. All calibration (core-top) data were measured using Method 2 as described by  Bereiter et al. (2018a) , with a longer equilibration time during the splitting step than used in that study to improve isotopic equilibration between the fractions. The exception is the DE08-OH site, where the ice sample (rather than the extracted gas sample) was split into two fractions -the advantage of this approach is that it does not require a gas splitting step that is time-consuming and may fractionate the isotopes; the downside is that the samples may have slightly different isotopic composition due to the stochastic nature of bubble trapping and the different gas loss histories of the ice pieces.
Measurements of the WDC downcore dataset were performed over five separate measurement campaigns that occurred in February-April 2014, February-April 2015, August 2015, August 2020, and August 2021. The first three campaigns are described by  Bereiter et al. (2018b) , in which the 86 Kr xs data are a by-product of measuring δKr/N 2 for reconstructing global mean ocean temperature. Campaigns 1 and 2 are in good agreement, whereas campaign 3 appears offset from the other two by an amount that exceeds the analytical precision (offset around 35 per meg ‰ -1 ). To validate the main features in the record, we performed two additional campaigns (4 and 5), in which all the gas extracted from each ice sample was quantitatively gettered and only analyzed for Ar and Kr isotopic composition. The downcore record, as well as the five analytical campaigns, is discussed in detail in Sect.
78 in real firn, as krypton is more readily adsorbed onto firn surfaces, retarding its movement (similar to gases moving through a gas chromatography column). This may be one explanation for why models simulate too little 86 Kr xs. Another likely explanation for the model-data mismatch is that certain critical sub-grid processes (such as the aforementioned pore size dependence of the Péclet number) are not adequately represented in these models. Barometric pumping may further actively shape the pore network through the movement of water vapor, thereby keeping certain preferred pathways connected and open below the density at which percolation theory would predict their closure  (Schaller et al. , 2017). The fate of a pore restriction is determined by the balance between the hydrostatic pressure (that acts to close it) and vapor movement away from its convex surfaces (that acts to keep it open); we speculate that barometric Darcy airflow keeps high-flow channels connected longer by eroding convex surfaces.
Present-day controls on Kr-86 excess in Antarctica In this section we investigate the large-scale patterns of climate variability in the Southern Hemisphere that could affect and therefore 86 Kr xs over Antarctica. We begin by investigating the patterns in the wind field that are associated with changes in at ice core sites, before examining how more canonical patterns of Southern Hemisphere climate variability, such as the southern annular mode (SAM), might affect over the whole of Antarctica. We use ERA-Interim reanalysis data for the 1979-2017 period  (Dee et al. , 2011)  to evaluate the present-day controls on synoptic-scale pressure variability in Antarctica. Kr-86 excess in an ice core sample averages over several years of pressure variability, and therefore we focus on annual mean correlation in our analysis.
Barometric variability in West Antarctica during the last deglaciation 5. 1 The 0-24 ka WAIS Divide Kr-86 excess record The WAIS Divide downcore 86 Kr xs dataset we present here was produced during five separate measurement campaigns that occurred in February-April 2014, February-April 2015, August 2015, August 2020, and August 2021. Campaigns 1-3 were reported previously  (Bereiter et al. , 2018a, b) , and campaigns 4 and 5 were meant to resolve conflicts between the 86 Kr xs datasets from these earlier campaigns. Three slightly different measurement approaches were used. Campaign 1 uses Method 1 from  Bereiter et al. (2018a) , in which the air sample splitting is done in a water bath for over 12 h to equilibrate the sample. Campaigns 2 and 3 use Method 2 from  Bereiter et al. (2018a) , in which a bellows is used to split the air samples for over 4 to 6 h.
, 2003; Studer et al. , 2015). All water isotope data in this figure  are   onset is too abrupt to be caused by insolation changes, and thus we can interpret that change with more confidence. The scatter in the late Holocene WDC 86 Kr xs data exceeds the stated analytical precision. Potential explanations include (1) an underestimation of the true analytical precision, (2) interannual to decadal variations in storminess at WDC, and (3) aliasing of centimeter-scale variations in ice core 86 Kr xs linked to layering in firn microstructural properties. Understanding the cause of this relatively high scatter in the 86 Kr xs records will require more work, in particular measurements of several high-resolution 86 Kr xs records in various sectors of Antarctica.
Based on previous work, we argue these two amplify one another in driving WDC storminess, yet we expect the former to make the larger contribution. To disentangle zonally uniform changes to the SPJ from changes specific to the Pacific sector (such as ENSO and the split jet), 86 Kr xs records from different sectors of Antarctica are needed. Replication of the deglacial and Holocene WDC 86 Kr xs record presented here is also a high priority at both the WDC itself and the nearby SDM and RICE cores to validate that the signals we describe and interpret here are indeed real and regional in scale. The position of the SHWs during the LGM has been a topic of much scientific inquiry. Proxy data have been interpreted to show a northward LGM shift of the SHWswith other scenarios, including no change at all, not excluded by the data  (Kohfeld et al.
A1 Gas loss correction Gas loss processes artificially enrich the δ 40 Ar isotopic ratio used to calculate 86 Kr xs  (Kobashi et al. , 2008b; Severinghaus et al. , 2003 Severinghaus et al. , , 2009)). Figure  A1b  shows the relationships between the two most common gas loss proxies, δO 2 /N 2 and δAr/N 2 , for all samples in the calibration dataset. We find a slope close to the 2 : 1 slope commonly reported in the literature  (Bender et al. , 1995) ; the exception is the DE08-OH site where the data fall on a 1 : 1 slope. Depletion in fugitive gases (such as O 2 and Ar) represents the sum of losses during bubble closure in the firn  (Bender, 2002; Huber et al. , 2006; Severinghaus and Battle, 2006)  and those during drilling, handling, storage, and analysis of the samples  (Ikeda-Fukazawa et al.
(2009)  we plot δ 18 O (corrected for gravity and small atmospheric δ 18 O atm variations) against gravitationally corrected δO 2 /N 2 in Fig. A1c. We find a slope of 3. 5 per meg enrichment in δ 18 O per ‰ of δO 2 /N 2 gas loss. This is less than values reported elsewhere  (Severinghaus et al. , 2009)  but provides further evidence for mass-dependent fractionation during gas loss. Our core-top dataset further suggests a correlation between δ 40 Ar -4 × δ 15 N (a measure of δ 40 Ar enrichment impacted by both thermal fractionation and gas loss) and gravitationally corrected δAr/N 2 (Fig. A1d ), suggesting Ar loss leads to enrichment of the remaining δ 40 Ar. Following  Severinghaus et al. (2009) , we assume that the δ 40 Ar correction scales with gas loss indicator (δO 2 /N 2 -δAr/N 2 ): 40 GL = ε 40 × (δO 2 /N 2 -δAr/N 2 ) | gravcorr , (A1) with 40 GL the isotopic gas loss correction on δ 40 Ar and ε 40 a scaling parameter.
Note that gravitationally corrected δO 2 /N 2 and δAr/N 2 data are used. Here we rely on data from the Antarctic Byrd ice core for a best estimate of ε 40 (Fig. A2 ); some samples from this core suffered extreme gas loss with (δO 2 /N 2 -δAr/N 2 ) as low as -100 ‰. This dataset suggests ε 40 = -0. 008, or 8 per meg δ 40 Ar enrichment per ‰ of (δO 2 /N 2 -δAr/N 2 ) gas loss. Because of the 2 : 1 slope between δO 2 /N 2 and δAr/N 2 , we find that (δO 2 /N 2 -δAr/N 2 ) ≈ δAr/N 2 and therefore the coefficient ε 40 would have a similar slope when regressed against δAr/N 2 instead of (δO 2 /N 2 -δAr/N 2 ). The value of ε 40 = -0. 008 agrees reasonably well with other studies. Kobashi et al. (2008b)  compare replicate sample pairs to back-out gas loss and find (statistically significant) correlations between δ 40 Ar enrichment and δAr/N 2 (again, which is similar to δO 2 /N 2 -δAr/N 2 ).
Kobashi et al. (2008b)  find ε 40 values of -0. 006, -0. 005, and +0. 007, depending on the depth range and analytical campaign evaluated. The positive value is surprising given that most observations, as well as theory, suggest ε 40 should be negative -we consider this a spurious result given the weak δ 40 Ar-δAr/N 2 correlation in that particular dataset. The other two values of ε 40 are in reasonable agreement with the Byrd value. For the Siple Dome ice core  (Severinghaus et al. , 2003) , regressing δ 40 Ar against δKr/Ar gives a slope of +0. 007; this implies ε 40 = -0. 007, in good agreement with our findings. Last, our core-top data suggest δ 40 Ar enrichment with an ε 40 value of -0. 0072 (Fig. A1d ), also in good agreement with Byrd. Given the uncertainty in the gas loss parameter, we verify that our results are valid for a wide range of ε 40 values (Fig.
A2 Thermal correction In the presence of a temperature gradient, thermal diffusion causes isotopic enrichment towards the colder location. The thermal diffusion sensitivity in units of ‰ K -1 for the various gases is given as  (Grachev and Severinghaus, 2003a, b; Kawamura et al. , 2013)  follows. The samples from the calibration dataset are from the climatically stable late Holocene period and typically close together in depth; the uncertainty in the T estimation for individual samples therefore exceeds the temporal variability in T. To reduce the uncertainty in the thermal correction we estimate T for individual samples using Eq. (A2) and for each site average the available data to get a site average firn temperature gradient T. The thermal correction is then given by the following. The two methods are compared in Figs.
A3c (individual sample T ) and Fig. A3d  (site mean T ); it is clear that the T approach reduces the spread in 86 Kr xs (error bars), but not its mean (white dots). The T estimates in individual samples are subject to errors in the isotopic measurements; some of these errors will cancel out in the T. For the downcore WDC record through the deglaciation we can no longer assume a stationary T ; we instead rely on dynamic firn densification model simulations of T  (Buizert et al. , 2015). A comparison of the simulated and databased T is shown in Fig. A5  for WDC. The data clearly show a lot more scatter and variability than the simulations do. We interpret this mainly as analytical noise in the δ 15 N Clim. Past, 19, 579-606, 2023  https://doi. org/10. 5194/cp-19-579-2023.
A3 Elevation correction To correct the deglacial WAIS Divide record for elevation changes, here we estimate the 86 Kr xs dependence on site elevation using the calibration dataset. Note that elevation and synoptic activity are strongly correlated for the investigated sites (r = -0. 86), with synoptic activity decreasing with elevation because the cyclonic systems do not penetrate deeply into the Antarctic interior. Figure  A6  shows the result of this exercise. We find a slope of 34 per meg ‰ -1 of 86 Kr xs per 1000 m of elevation change, with a correlation of r = 0. 96 when considering site mean 86 Kr xs and r = 0. 86 when considering individual samples. Note that the GISP2 site is not included in the analysis because it is in Greenland where the elevation-86 Kr xs relationship may be different from Antarctica -it does, however, fit the Antarctic trend rather well.
Recently, an estimation of the French population's exposure to soy isoflavones was published  [65]. It showed that soy non-eaters consuming hidden soy through transformed foodstuffs were exposed to a mean intake of 1. 9 mg/day of isoflavones, while the mean exposure among soy consumers was about 6. 9 mg/day. These figures hide a great variability as, in the same recent-French-exposure estimation, soy isoflavone intake varied from 0 to 213 mg/day  [65]. In  [66] , the authors provided an extensive set of isoflavone measurements in French foodstuffs. These data were obtained by specific ELISAs after a water extraction of the isoflavone glucosides. It can be seen that some foods can bring between 40 and 50 mg of isoflavones per usual portion. From the literature, it seems like there are no reproductive effects in adults at a dose below 20 mg/day, but an increase in hypothyroidism symptoms was noticed in women at 16 mg/day  [67].
• Coumestrol Few data exist on the effect of coumestrol on metabolic syndrome and lipid-associated disorders. Data were essentially obtained on animals and express contradictory opinions. On one hand, some studies consider coumestrol as a beneficial agent for lipidic and glycemic profiles, such as  [163] , which examined the effect of different extracts of alfalfa sprouts in rats. In this study, 10-hydroxycoumestrol was the only polyphenol potentially involved in a beneficial effect. On the other hand, some authors considered that coumestrol, as a natural endocrine disruptor, was able to impair liver function and consequently lipid and glucose blood levels in rats  [164]. Additionally, Liu et al. [83]  associated plasma phytoestrogens, including coumestrol, with a lower risk of developing metabolic syndrome.
We are indebted to  D. Volin  for several nice discussions and for an illuminating introduction to the  Quantum Spectral Curve. We thank  S. Ekhammar ,  V. Gonçalves ,  A. K. Kashani-Poor ,  V. Kazakov ,  R. Klabbers ,  M. Preti ,  I. Szécsényi  and  P. Vieira  for interesting discussions. We are very grateful to the  Galileo Galilei Institute  and to the scientific program Randomness, Integrability, and  Universality  for support and hospitality during the final stage of this project. This work received support from the  French National Agency for Research  Grant No. ANR-17-CE31-0001-02. Nordita is supported in part by  NordForsk.
Data collection Patients were identified through our computerized database. ARDS was identified based on the Berlin criteria consensus definition  [20] : (1) timing: onset within 1 week of a known clinical insult or new or worsening respiratory symptoms; (2) chest imaging: bilateral opacities, not fully explained by effusions, lobar/lung collapse or nodules; (3) origin of edema: respiratory failure not fully explained by cardiac failure or fluid overload; (4) PaO 2 /FiO 2 ratio (PaO 2 /FiO 2 ) ≤ 300 mmHg with positive end-expiratory pressure (PEEP) or continuous positive airway pressure ≥ 5 cm H2O. ARDS diagnosis was retrospectively reviewed by two physicians (JP and ADJ). As performed in previous studies  [21] [22] [23] , the diagnosis of cirrhosis was based on previous histology findings when available or on various associations of clinical, biological, endoscopic, and/or ultrasonographic or imaging findings, including cutaneous manifestations such as jaundice or skin telangiectasias, evidence of portal hypertension such as variceal bleeding, ascites, hepatic encephalopathy, and biological results of liver failure.
All consecutive adult patients with ARDS undergoing invasive mechanical ventilation hospitalized during the study period in ICU were included in the study. Only the first admission of each patient with ARDS was retained for analysis. Patient data were recorded by the ICU's physicians and included demographics, anthropometrics, clinical and biological data on ICU admission, as well as the Sequential Organ Failure Assessment (SOFA score)  [24] , the Simplified Acute Physiology Score II (SAPS II) and comorbidities. The SOFA score was split in non-hepatic SOFA and hepatic SOFA. Ventilator-associated pneumonia was diagnosed as previously published  [25]. All ventilation data (plateau pressure, tidal volume (Vt), PEEP, driving pressure (plateau pressure-PEEP), respiration rate) were recorded at day 1 of the ARDS onset.
Patients During the study period (2003-2021), 12,080 patients were admitted in ICU, and 7155 (59%) patients underwent mechanical ventilation. Among those patients, 863 (12%) met criteria for ARDS. Of these patients, 863 (100%) had an available survival status 90 days after ICU admission and were included in the analysis. Among these 863 patients, 157 (18%) were ARDS patients with cirrhosis and 706 (82%) were ARDS patients without cirrhosis. Figure  1  presents the flowchart of the study. One hundred and forty-two patients (16%) had been included in prospective randomized trials: 12 in the EXPRESS study  [32] , 26 in the ACURASYS study  [33] , 12 in the PROSEVA study  [34] , 42 in the BIRDS study (NCT01862016), and 49 in the LIVE study  [18]  and one in the HIGH study  [35]. The baseline characteristics for ARDS patients with and without cirrhosis are presented in Table  1  and Additional file 1: Table  S1.
Moreover, in this cohort, patients were managed with lung-protective ventilation. Finally, the results found in the multivariate Cox-proportional hazard model were confirmed in the exploratory multivariate model using logistic regression. Our study has several limitations, starting with the monocentric design that hampers the generalization of the results. Second, although the data were prospectively recorded, the analysis is retrospective. It might lead to inhomogeneity of the population that could impact the evolution of the outcomes of ARDS patients with cirrhosis. We could not assess the proportion of ARDS caused by community-acquired pneumonia, although it might be a factor of poor prognosis in patients with cirrhosis  [48]. We did not assess the CLIF-C ACLF and the CLIF-C AD scores, although we assessed the CLIF-C OF and ACLF grade.
An alternative risk shore has also been recently published which largely overlap with HCMRisk-Kids score  [10]. The work-up for assessment of syncope shown in Fig. 3  should be used also for children. Reflex syncope is the most frequent cause of syncope also in children and should be investigated as in adults. However, some tests for the diagnosis of reflex syncope may be not feasible in younger children and their interpretation may be doubtful due to the lack of data regarding their diagnostic accuracy. Exercise stress echocardiography should be considered in children with HCM old enough to use the equipment to unmask an underlying LVOTO. For the above limitations, implantable loop recorder (ILR) has become widely used in children. ILR should be considered in children with HCM and risk factors for SCD, when the aetiologic work-up of syncope is inconclusive and where the identification of an arrhythmic cause would warrant ICD implantation.
With regard to dropwise condensation, if liquid removal depends on gravity, this prevents its application in low gravity space systems. Alternatively, droplets can be removed by the high vapor velocity or by passive techniques based on the use of condensing surfaces with wettability gradients or micrometric/nanometric structuration: these represent an interesting solution for exploiting the benefits of dropwise condensation in terms of heat transfer enhancement and equipment compactness in microgravitational environments. The experimental investigation of the condensation heat transfer for long durations in steady-state zero-gravity conditions, such as inside the International Space Station, may compensate the substantial lack of repeatable experimental data and allow the development of reliable design tools for space applications.
1 mm inner diameter channel during a parabolic flight campaign are reported. Tests were performed under microgravity, Lunar (0. 17 g s ) and Martian gravity (0. 377 g s ) at mass flux from 129 to 341 kg m -2 s -1 and at 60-63. 4 °C saturation temperature. The influence of gravity on flow pattern and condensation heat transfer was significant at low FC-72 mass fluxes. Lunar and Martian gravity caused the film to become thicker at the bottom of the tube and thinner at the top, leading to enhanced condensation heat transfer rates compared to microgravity conditions. With the aim to widen the experimental database of Azzolin et al. 27  , Berto et al. 28  employed the same test section to perform P sat = 440 mbar G = 1. 66 kg m -2 s -1 Numerical simulations of laminar FWC (T SAT -T WALL ) 1 (T SAT -T WALL ) 2 (T SAT -T WALL ) 3 (T SAT -T WALL ) 4 (T SAT -T WALL ) 5 Fig.
It is worth highlighting that none of the aforementioned numerical and analytical studies involve a comparison with experimental data taken in reduced gravity platforms. This fact further stresses the need to enlarge the available experimental database on filmwise condensation for validating such numerical and analytical tools. Predicting methods for condensation heat transfer in microgravity conditions Few predictive tools are available in the literature for identifying the flow conditions at which the gravity effect on the condensation heat transfer is negligible. Such methods are highly instrumental in the design of thermal management systems in aircraft and spacecraft avionics. Among them, Del Col et al. 21 eveloped a dimensionless correlation for predicting the critical mass velocity at which the effect of inclination starts to appear during condensation inside tubes.
5% (60. 5% and 97. 4% of the data falling within ±30% and ±50%). Lee et al. 1  compared the experimental data taken during condensation of FC-72 in microgravity in the 7. 1 mm I. D. tube with the predictions of well-known correlations for the condensation heat transfer coefficient (Akers et al. 56  , Cavallini and Zecchin 57 , Shah  58  , Dobson and Chato 42 , Wang et al. 59  , Koyama et al. 60  , Kim and Mudawar  61  ). The smallest mean absolute deviation between predicted and experimental heat transfer coefficients was obtained with Kim and Mudawar 61 model (MAE = 21. 8%, with 69. 2% of points falling within ±30%), followed by the correlations of Shah  58  (MAE = 27. 6%) and Wang et al. 59  (MAE = 28. 9%). The success of the Kim and Mudawar 61 correlation, indicated by Eq. (  13 ), was attributed to its reliance on a massive database, which includes 17 different working fluids and a broad range of operating conditions and geometrical parameters.
These experimental conditions can be achieved only with space experiments. Considering filmwise condensation, further experiments are required for assessing the effect of gravity on the condensation heat transfer, especially at low mass fluxes, when the heat transfer coefficients are found to be strongly penalized by the absence of gravity. Moreover, condensation heat transfer coefficients and liquid film thickness data should be evaluated under various saturation-to-wall temperature differences, whose effect on the condenser performance has never been assessed before in a reduced gravity environment. The channel shape represents another key factor to counterbalance the detrimental effect of the absence of gravity on condensation heat transfer. Surface tension forces exert a great influence on the liquid film distribution especially for square or rectangular channels, whose behavior under reduced gravity has been addressed only in numerical studies.