dataesr/scientific-paragraphs-categorization huggingface dataset:
Although the quantification of WSOC was always possible, some samples had OC concentrations < DL, assuming that OC = WSOC (and WIOC = 0) would be incorrect and would result in significant error in the estimate of total OC. There could be a significant amount of WIOC that we cannot quantify because of the lower sensitivity of the OC analysis. For this reason, we presented WIOC and OC data only for samples that have both quantifiable OC and WSOC. The amount of inorganic carbon varies between 12 % and 71 % of TC, and thus the acidification process for sea spray is an important step to follow for OC measurements. Organic carbon was converted to organic mass using conversion factors of 1. 4 for the conversion of WIOC to WIOM and 1. 8 for the conversion of WSOC and WSOM  (Facchini et al. , 2008).
For m/z 81, there is overlap with an SO 4 fragment, and a correction suggested by  Schmale et al. (2013)  was applied (Eq. 1). This correction accounted for less than 10 % of the signal at m/z 81 and 3 % of the total sulfate signal. frag_SO 4 [81] = 81 -frag_organic[81] -0. 036 × frag_Na [23] (1) Quantification of sea salt is difficult in the ToF-ACSM as a result of inefficient vaporization and a nonlinear contribution to the Na + signal from surface ionization on the vaporizer. Therefore, in this work we do not attempt to quantify the sea salt fraction, but instead we use the mass spectral information to separate it from the organic aerosols. A standard collection efficiency (CE) of 0. 5 was applied to all data obtained from the ACSM  (Middlebrook et al. , 2012). Regular particle-free sampling periods were performed to ensure that there was no buildup of material on the vaporizer and that the sampling setup was leak-free.
Conclusions The primary objective of this experiment was to study the relationships between sea spray chemical properties and those of seawater. This work presents a unique dataset, which describes the first deployment of a ToF-ACSM to characterize, in a continuous way, the organic fraction present in sea spray aerosol generated from Mediterranean surface seawater. The non-refractory part of the organic content of sea spray was characterized by low concentrations and low variability along a 4300 km transect. Yet, using a positive matrix factorization on the ACSM organic mass spectra, it was possible to extract signatures for fatty acids, amino acids, and marine primary organic aerosols in non-refractory nascent sea spray. We identified four organic classes: two were composed of mixtures of amino acids and fatty acids (a primary aerosol POA NR and a slightly oxidized MOA NR factor), and two were identified as more oxidized organic aerosol (OOA NR and MSA-OA NR ).
Acknowledgements. The underway optical instrumentation was provided by  Emmanuel Boss 's group funded by  NASA Ocean Biology and Biogeochemistry. We thank  Oliver Grosso ,  Dominique Lefèvre , and  Thibault Wagener  for their contribution to the continuous surface pumping system and the follow-up of CytoSense during the cruise. More information on the PEACE-TIME cruise can be found at https://doi. org/10. 17600/17000300. Sea2Cloud was endorsed by SOLAS. We thank the captain and the crew of  R/V Pourquoi Pas ? for their professionalism and their work at sea. Financial support. This study is a contribution to the  PEACETIME  project (http://peacetime-project. org, last access: 5 May 2021), a joint initiative of the MERMEX and ChArMEx components supported by  CNRS-INSU ,  IFREMER ,  CEA , and  Météo-France  as part of the  MISTRALS program  coordinated by  CNRS-INSU.
For each genotype, the mean of the absolute expression levels (i. e. , normalized) was calculated, and graphs of qRT-PCR results show fold of change + SEM. All the data were analyzed by unpaired two-sided Student's t test using Microsoft Excel. Asterisks highlight the pertinent comparisons and indicate levels of significance: *P < 0. 05, **P < 0. 01, and ***P < 0. 001. Data are shown as mean + SEM. Immunological Analyses. Samples were fixed with 4% (wt/vol) paraformaldehyde overnight and then processed either for paraffin embedding or directly for whole-mount immunostaining. Microtome sections of 5 μm thickness were processed for immunostaining. Immunofluorescence analyses were performed as described in ref. 31. The following dilutions of primary antibodies were used: CDH1 (cat 610182, BD Transduction Laboratories) 1:100, CTNNB1 (cat, C2206, Sigma-Aldrich) 1:100, active CTNNB1 (ABC) (cat 05-665, Millipore) 1:100, DAZL (cat GTX89448, Genetex) 1:200, DDX4/MVH (cat 13840, Abcam) 1:200, FOXL2 (cat 5096, Abcam) 1:300, GFP (cat TP401, Torrey Pines Biolabs) 1:750, GSK3β (cat 135653, Santa Cruz) 1:250, LEF1 (cat 137872, Abcam) 1:250, MKI67 (cat M3062, Spring Bioscience) 1:150, POU5F1 (cat 611202, BD Transduction Laboratories) 1:250, SCP3 (cat 15093, Abcam) 1:200, SOX2 (cat 97959, Abcam) 1:200, SOX9 (cat HPA001758, Sigma-Aldrich) 1:500, TRA98 (cat 82527, Abcam) 1:150, and FUT4 (SSEA1) (cat 21702, Santa Cruz) 1:200.
Slides were counterstained with 4',6-diamidino-2-phenylindole (DAPI) diluted in the mounting medium at 10 μg/mL (Vectashield, Vector Laboratories) to detect nuclei. Imaging was performed with a motorized Axio Imager Z1 microscope (Zeiss) coupled with an Axiocam Mrm camera (Zeiss), and images were processed with Axiovision LE and ImageJ. ImageJ software was used for quantification of proliferating germ cells versus total germ cells. Cell imaging was performed with a Leica DM6000 TCS SP5 confocal microscope on an upright stand (Leica Microsystems, Mannheim, Germany), using objectives HC PL APO CORR 20X multi-immersion NA 0. 7 and HCX APO L 63X oil 1. 4 NA. The lasers used were argon laser (488 nm), HeNe laser (543 nm), and diodes laser 405 nm. The microscope was equipped with a galvanometric stage in order to do z-acquisitions, a resonant scanner and with an automated xy stage for mosaic acquisitions.
Data Availability. All study data are included in the article and/or SI Appendix. ACKNOWLEDGMENTS. This work was supported by grants from the Agence Nationale de la Recherche (ANR-13-BSV2-0017-02 ARGONADS, ANR-20-CE14 ARDIGERM, and ANR-11-LABX-0028-01), Canceropole PACA (Emergence), and Crédits Scientifiques Incitatifs Emergence from Nice Sophia Antipolis University. M. L. R. was supported by a fellowship from La Ligue Nationale contre le Cancer. A. S was supported by a grant from La Ligue Nationale Contre le Cancer (équipe labellisée Ligue Nationale Contre le Cancer). We acknowledge Dr. James Woodgett (Samuel Lunenfeld Research Institute, Toronto, Canada) for providing us the Gsk3b knockout mice. The microscopy was done at the Prism facility, "Plateforme PRISM," and the histological experiments were done at the "Experimental Histopathology Platform"-Institut de Biologie Valrose CNRS UMR 7277 Inserm U1091 UNS.
Criteria for Discontinuation of the Procedure The healthcare providers (obstetrician, midwives, anesthetist, and pediatrician) in charge of the baby or the mother may stop the procedure-i. e. , clamp the cord-if they judge it is required for the safety of the patient. The reason for stopping the procedure and the timing at cord clamping will be recorded. In that case, the patient is not excluded from the study and the variable is recorded as planned in the protocol. The patient data are analyzed according to intention to treat principle. The follow-up of the infants is planned till the age of 3 months (90 days), corresponding to the last visit. If the patient is transferred in another hospital, the variable will be recorded till the age of 3 months.
Statistical Analysis Plan Statistical analyses will be independently performed by the Biostatistics Department of University of Lille under the responsibility of Professor Alain Duhamel. For the data analysis, statisticians will be unaware of the treatment group allocation. Data will be analyzed using the SAS software (SAS Institute Inc. , Cary, NC, USA) and all statistical tests will be performed with a two-tailed alpha risk of 0. 05. All analyses will be performed in all randomized patients based on their original group of randomizations, according to the intention-to-treat principle. No interim analysis will be performed. A detailed statistical analysis plan will be written and finalized prior to the database lock. Baseline characteristics will be described for each group. Quantitative variables will be expressed as mean (standard deviation), or median (interquartile range) for non-Gaussian distribution.
Acknowledgments: We acknowledge the Data Safety Monitoring Board of this study;  EuroCare-France  for its participation and collaboration; implication and contribution of team members of all the participating hospitals including: obstetricians, anesthetists, pediatricians, surgeons, clinical research data set technicians. Florence Nosal for her help in funding acquisition. Eloise Dewuite  for her help in project administration. Alain Duhamel  and  Julien Labreuche  for their help in methodologic design of the study. Florence Flamein  for her help in project management and investigation. Principal investigators engaged in this study:  Beuchee Alain ,  Boubred Farid ,  Cambonie Gilles ,  Claris Olivier ,  Flamant Cyril ,  Kermorvant Elsa ,  Mokhtari Mostafa ,  Savey Baptiste ,  Tandonnet Olivier ,  Tourneux Pierre.
Superior results can be obtained with LOFAR because of its large number of antennas (about 200 are used in the measurements reported in this work), its large baseline (about 100 km), its high timing stability (better than 1 ns over a few seconds), and the possibility to retrieve the time trace of each antenna. These VHF observations are, however, not sensitive to currents at length scales of order 100 m and greater. To ameliorate this, a broadband magnetic-loop antenna  12  was installed in the vicinity of the LOFAR core. These combined observations between LOFAR and a broadband antenna have facilitated the identification of the IRNL mode. We show and analyze in "Data analysis" section the data for the two flashes for which simultaneous recordings are available from the magnetic loop antenna and LOFAR.
Data analysis For two flashes we have recorded simultaneous measurements with LOFAR and the broadband antenna. Both flashes occurred on April 24, 2019 shortly after each other. The general structure of each of the two flashes can be seen from Fig. 1. Since in  8  we have already shown the general structure of flash A, we focus here on the first 50 ms. The time calibration is such that t = 0 is close to the beginning of the flash, 21:30:56. 221 UTC for Flash A and 21:03:06. 757 UTC for B. The general locations of the two flashes with respect to LOFAR are marked in Fig. 2. From the structure of the leaders it can be inferred that for Flash A there was a positive charge layer below 4. 5 km with a large number of negative leaders and a negative charge layer between 4. 5-6. 5 km height marked by the tell-tale twinkles  17.
For Flash B the negative charge layer lay much lower, below and around 2 km height. Twinkling positive leaders are seen in a band around 4 km height and also above 6 km from which it can be inferred that there were two negative charge layers. The top two panels show the time traces as measured with the broadband antenna and the VHF power as measured by LOFAR. The broadband and LOFAR signal are aligned using the GPS timing of both systems. The VHF noise power is normalized to the background-noise, about 6 × 10 -13 W/m 2 , the strength of the signal in the absence of any lightning activity. This noise background is partly due to electronic noise in the LOFAR system and mostly due to galactic (extra terrestrial) radiation  24. The data from the broadband antenna are available for only a part of each flash due to the fact that the broadband antenna stores traces of 167 ms length upon triggering.
It may also be that at the high velocity stage the propagation mode of these negative leaders becomes continuous rather than stepping. CS002 CS001 CS003 CS004 CS005 CS007 CS011 CS013 CS017 CS021 CS024 CS026 CS028 CS030 CS031 CS032 CS101 CS103 CS201 CS301 CS302 CS401 CS501 RS106 RS205 RS208 RS210 RS305 RS306 RS307 RS310 RS406 RS407 RS409 RS508 RS509 A B Figure  4  shows the initial stage of Flash B, which also contained an IRNL, from t = 0. 5 till 2. 5 ms, indicating that the IRNL mode is common immediately after lightning initiation. Also this flash showed a second IRNL mode, in this case at 9-15 ms. Since the second IRNL occured a bit later in the flash, the velocity along the indicated track drops in between the two IRNL modes to values lower than seen in Fig. 3. Even though the velocity barely reaches 10 6 m/s, and broadband data is not available, the features of the two IRNL modes are clearly recognizable, including: intense VHF emission, elevated speeds, low source density, broad channels that fan out, and copious number of produced negative leaders.
5. This is an archetypical example of an IRNL mode of propagation. The right half of Fig. 5  shows the same area some 130 ms later during the same flash. For this period there are no data available from the broadband antenna. Figure  5  shows a negative leader propagating straight downward from the negative charge layer at 4 km into the positive charge layer at and below 2 km altitude. This occurred at the same location, projected on the ground plane, as where the first negative leader on the left side of the figure stalled. At t = 403 ms the structure of the imaged leader changes, as indicated by the cyan colors, to a structure reminiscent of that of an IRNL. 5 ms later, at a distance of about 4 km, normal negative leaders are imaged again, amounting to a speed of 8 × 10 5 m/s. The northern branch (which is followed for making the velocity plot) propagates slightly slower.
The VHF power shows a strong increase when the negative leader was propagating downward from 3. 5 km height. There are no separate surges in VHF power visible to indicate stepping, which might be due to the fact that there were several IRNL branches active at the same time. Unfortunately there is no broadband time trace available for this time period so the stepping nature could not be confirmed. The lack of broadband data not withstanding, the picture shows another typical example of an IRNL. ] m k [ t h g i e H ] m k [ g n i t s a E time [ms] ] m k [ t h g i e H ] m k [ t h g i e H ] m k [ g n i h t ] m k [ t h g i e H ] m k [ g n i t s a E time [ms] ] m k [ t h g i e H ] m k [ t h g i e H ] m k [ g n i h t ] m k [ t h g i e H ] m k [ g n i t s a E time [ms] ] m k [ t h g i e H ] m k [ t h g i e H ] m k [ g n i h t ] m k [ t h g i e H ] m k [ g n i t s a E time [ms] ] m k [ t h g i e H ] m k [ t h g i e H ] m k [ g n i h t As discussed above, the VHF power shows strong spikes on top of the broader emission from the IRNL in Fig.
The Superterp is the core of LOFAR, it contains a dense array of antennas and is located near Exloo, the Netherlands. For radio-astronomy observations, the antenna signals are added coherently to effectively operate as a gigantic radio dish antenna with a diameter of 1000 km when the international stations are included. From each LOFAR station we use 6 dual-polarized low-band antennas sensitive to 30-80 MHz. Each antenna samples at 200 MHz and has a 5 s long buffer. Using only the Dutch stations we reach baselines of up to 100 km (see Fig. 2 ). Upon an external trigger, the antenna buffers are frozen and data are read out. Sometimes some data is lost during during downloading, however this does not really affect the image quality due to the large number of available antennas (typically 300-400).
For every 5 s of raw data from the TBBs we store close to 1 TB of data for later off-line processing. Lightning imaging. For completeness we outline here the impulsive imaging procedure we followed, see also  8  where a much more detailed description given. The source code used for the analysis can be found at  36. The procedure is a mixture of an interference and a time-of-arrival approach, where arrival time differences of a pulse at different antennas are obtained from the peak in the cross correlation between two antennas. The location of the source is obtained using a Levenberg-Marquardt fitting algorithm  37  for the arrival-time differences. Three quality indicators are used to ensure that the sources are well located. The most important is the obtained value for the Root Mean Square time difference between the calculated and measured arrival time differences ( RMS d ) of the fit.
Acknowledgements The  LOFAR cosmic ray key science project  acknowledges funding from an  Advanced Grant  of the  European Research Council  ( FP/2007(FP/ -2013)  ) [ ERC  grant number  227610 ]; The project has also received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  [grant number  640130 ]; We furthermore acknowledge financial support from  FOM  [FOM-project  12PR304 ]; BMH is supported by the  NWO  [grant number  VI. VENI. 192. 071 ];AN is supported by the  DFG  [grant number  NE 2031/2-1 ]; TW is supported by  DFG  [grant number  4946/1-1 ]; The work of the IAP team was supported by  European Regional Development Fund-Project CRREAT  [grant number  CZ. 02. 1. 01/0. 0/0. 0/15-003/0000481 ] and by the  GACR  [grant number  20-09671S ].
Methods and Data This exploratory study is based on 20 semi-structured interviews of French working fathers from heterogeneous backgrounds selected in order to grasp a wide range of fathers' experiences: blue-collar (operators, technicians) and white-collar fathers (engineers, directors). The 11 companies where they work are certified as familyfriendly employers. They are both public and private, of different sizes and sectors (delivery service sector, microelectronics, automotive, IT. ) and located in Normandy (France). All interviews were conducted face-to-face from 2014 to 2017. Each interview took about 1 h and was conducted in French. Each interview was based on a talk about WLB and fatherhood, perceptions of WLB initiatives, reasons for use, obstacles and facilitators, and strategies.
Interviews were audio-recorded and transcribed. The interview analysis consisted of an axial coding and a thematic analysis, both horizontal and vertical. The aim was to understand and to compare fathers' representations, experiences, and behaviors regarding WLB. The data analysis consisted of two steps: firstly, examining the individual unit of production of each interview, in order to create categories and analyze themes, and secondly, extracting meaning from the data to understand the contents. We did an iterative coding of recurring first-order categories ("informant's voice") and identified both emerging secondorder categories and aggregate dimensions  (Gioia et al. 2013 ) that brought to light the main dimensions of fathers' beliefs, experiences, and strategies regarding WLB policies.
Acknowledgements The author thanks  Harvard Kennedy School's Women and Public Policy Program (WAPPP) , the  Social Trends Institute (STI)  and the  International Center for Work and Family for initiating , funding and supporting the conference 'Elevating Fatherhood: Policies, Organizations and  Health & Wellbeing'. She  also thanks all the participants of the conference for their enlightened suggestions and helpful comments to improve this chapter. She finally thanks all the fathers who kindly accepted to share their experience in this research.
, 2006). De ned as a zonal pressure difference between the latitudes of 40°S and 65°S  (Marshall, 2003) , it re ects the contraction (in a positive phase) or expansion (in a negative phase) of the westerly winds belt circling Antarctica. Strongly connected with ENSO, the IOD consists in an interannual oscillation of the SST in the equatorial Indian Ocean, forming a typical west-east dipole  (Saji et al. , 1999). The Dipole Mode Index (DMI) is de ned as the difference of SST averaged in the western (50°E-70°E and 10°S-10°N) and eastern (90°E-110°E and 10°S-0°N) equatorial Indian Ocean, and calculated with the HadISST1. 1 SST dataset with the 1981-2000 climatology removed. To be consistent with the processing of satellite gravity solutions, all climate indices have been detrended and DE seasoned.
OR9 ). The results are shown in Fig. 2  and Table  1. As expected, a classic OLS inversion is not able to select the relevant predictors of the water mass variability, as all coe cients are non-null (Table  1 ). However, the amplitudes of MEI, NAO and IOD coe cients are close to synthetic values (Table  1 ). With a LASSO regression, the value of the β i coe cients diminishes with the penalty λ (Fig. 2b ). Optimal values of the penalty can be estimated with a CV procedure (Fig. 2c ). The penalty minimizing the average CV error is not su cient to set the PDO value to zero (Table  1 , Fig. 2b ), which is likely due to the fact that the PDO is correlated with MEI (online resource Fig. OR9 ). On the other hand, the penalty minimizing the standard error, which takes into account the dispersion due to the random division of the dataset during the CV procedure, is able to select the relevant predictors of the regression model (MEI, NAO and IOD) and set all other parameters to exactly zero.
The PDO consists in a decadal SST oscillation, characterized by a basin-wide dipole dividing the North Paci c along a typical northeast -southwest chevron pattern (Mantua et al. , 1997). It is de ned as the leading EOF of SST anomalies north of 20°N in the Paci c region (Newman et al. , 2016)  and estimated with the ERSSTV5 dataset (Huang et al. , 2017). The PDO is closely related to the ENSO and is sometimes referred to as a "long-lived ENSO", to characterize the longer periods of the climate index. The NPGO expresses as a double gyre in the North Paci c (Di Lorenzo et al. , 2008). It is de ned as the second mode of sea surface height variability in the Northeast Paci c (180°W-110°W; 25°N-62°N). Connected with ENSO and PDO, it contributes to global climate variability, which is evidenced by global sea level trends and sea surface temperature (Di Lorenzo et al.
, 2010). The AMO consists in a multidecadal SST oscillation across the whole Atlantic basin, with cool and warm phases that may last for 20-40 years (En eld et al. , 2001). We use the unsmoothed index, provided by the NOAA/OAR/ESRL PSL, Boulder, Colorado, USA, from their Web site at https://psl. noaa. gov and calculated from 1948 to present as the area weighted average of the Kaplan SST V2 dataset (Kaplan et al. , 1998) over the North Atlantic (0-70°N).
Yang et al. , 2007)18)13)low, see Fig. 2c. ) (e. g. , Arlot & Celisse, 2010), i. e. , each time series is randomly divided in ve parts, successively used as testing (one part) and training (four parts) datasets. This criterion has been shown to work well in the presence of correlated variables(Hebiri & Lederer, 2013). This procedure is similar to the approach ofPfeffer et al. (2018), who extracted climate mode ngerprints for the PDO, ENSO, NPGO, AMO, IOD and IOBM (Indian Ocean Basin Mode;Yang et al. , 2007)in historical reconstructions of steric sea levels.
Introduction GC-biased gene conversion (gBGC) is a recombination-associated transmission bias by which G and C alleles are favoured over A and T alleles. This evolutionary force was discovered in the 2000's from the analyses of early population genomic data sets  (Eyre-Walker, 1999; Galtier, Piganeau, et al. , 2001; Spencer et al. , 2006; Webster and NG Smith, 2004) , and experimentally confirmed later on  (Mancera et al. , 2008; Pratto et al. , 2014; Williams et al. , 2015). gBGC manifests itself as a GC-bias that affects both non-functional and functional sequences and is correlated with the local recombination rate  (Galtier and Duret, 2007). gBGC has a strong impact on patterns of variation genome wide in mammals  (Clément and Arndt, 2011; Duret and Arndt, 2008; Pracana et al. , 2020; Romiguier, Ranwez, et al.