dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The authors want to thank all the reviewers from others medical specialties who brought their expertise on several fields of these recommendations:  Christophe Dadure  ( Department of Paediatric Anaesthesia, CHU de Lapeyronie, Montpellier )  Florence Fenollar  ( Infection Control Committee, IHU -Mediterranee Infection, Marseille ),  Beatrice Clarivet  ( Hygiene Operational Unit, Lapeyronie Hospital, Montpellier ),  Frederic Barbut  ( Hygiene Operational Unit, St-Antoine Hospital, Paris ),  Anne Laffargue  ( Department of Paediatric Anaesthesia, Jeanne-de-Flandre Hospital, Lille ),  Antoine Khalil  ( Radiology, Bichat-Claude-Bernard Hospital, Paris ),  Karine Lacombe  ( Infectious Diseases Department, St-Antoine Hospital, Paris ), and  Clemence Richaud  ( Infection Control Committee, Institut Mutualiste Monsouris, Paris ).
| Case study In order to provide an empirical example of our proposed method and predictions, we use data on terrestrial isopods (Oniscidea) from central Aegean islands (see Appendix S1), for which we do have the necessary information (see  Sfenthourakis, 1994 Sfenthourakis, , 1996)). The 43 islands included in this case study range in area from 0. 025 to 477. 94 km 2 and have a variable topography, geological structure and isolation history (see also the papers in  Sfenthourakis et al. 2018  for additional ecological and palaeogeographical data on Aegean islands). Isopod species richness on these islands ranges from five to 38 species, with a grand total of 69 species across all the islands. On each island, the whole range of habitats exploited by terrestrial isopods has been sampled, and a detailed description of the habitats in each sampling site has been recorded.
Motivated by this theoretical analysis, we propose the polar quadrature amplitude modulation (PQAM or Polar-QAM), a PN robust modulation scheme based on a structured APSK. The constellation and the binary labeling of the Polar-QAM are jointly designed to improve the system performance on PN channels while maintaining a low-complexity implementation. In particular, it enables to implement the symbol detection with a simple threshold comparison, and the soft-output demapper with piecewise linear functions. The proposed modulation scheme is compared to conventional and state-of-the-art solutions taking into account different performance metrics. The performance of the Polar-QAM is assessed analytically and numerically considering state-of-the-art channel codes. Our results highlight that the Polar-QAM significantly enhances performance in terms of achievable data rate with valuable complexity reductions of the transceiver.
IVF procedure As recommended by the European Society of Human Reproduction and Embryology (ESHRE), the IVF protocol was an ultra-long-agonist protocol consisting of an intra-muscular injection of 3 mg Triptoreline (Decapeptyl, Ipsen, France) at least three months before the EST procedure  [11]. Controlled ovarian stimulation was initiated 2 weeks after the EST procedure. The dose and type of gonadotropins were determined on individual basis according to data from previous IVF cycles, age, BMI and ovarian reserve. All women underwent serial transvaginal ultrasounds and hormonal dosages during stimulation, and human chorionic gonadotropin (HCG) was administered subcutaneously (Ovitrelle, Merck Serono, Germany) when three or more leading follicles with a mean diameter greater than 18 mm were visualized.
VI. ACKNOWLEDGEMENT We are thankful to  Michael Kleder  for the CON2VERT and VERT2CON MATLAB packages that gave us the first numerical glimpse of our result. ASA and JR acknowledge the financial support from the  Belgian Fonds de la Recherche Scientifique -FNRS  under grants no F. 4515. 16 (QUICTIME), R. 50. 05. 18. F (QuantAlgo). ASA further acknowledges the  FNRS  for support through the grant  F3/5/5-MCF/XH/FC-16749  FRIA. KB acknowledges the  CQT Graduate Scholarship. KB and LCK are grateful to the  National Research Foundation  and the  Ministry of Education, Singapore  for financial support.
Acknowledgements The authors thank the discussions on the regional geology and the location of the studied outcrops to  Prof. M. El Houicha  ( Université Chouaïb Doukkali ). We thank the technicians of the Laboratory or the  Area de Paleontología of the Complutense University and Instituto de Geociencias  for the preparation of thin sections. JS-L would like to express their gratitude to  A. J. Quintana García  ( Scientific-Technical Services, University of Oviedo ) for their assistance with the scanning electron microscope. This study is a contribution to the IGCP 652.
The F1 hybrids plants containing Sha cytoplasm were sterile and unable to produce pollen, while F1s with the Mr-0 cytoplasm produced viable seeds  [71]. The Sha lineages appeared to contain CMS factors and the nuclear Rf to restore male fertility  [70]. CNI can arise through the disruption of coadaptation in major organellar complexes and intergenomic conflict between mitochondrial and nuclear genes. Much still needs to be done in order to understand the mechanisms of coevolution between genomes and which cellular functions are mainly affected by disruption of coadaptation. Databases on protein-protein but also RNA-protein or DNA-protein interactions could be useful to further investigate and identify nuclear and organellar interacting partners, coupled with the analysis of whole organellar genome diversity and functional validation  [72].
Data collection Field sampling was carried out within the no-take zone of Torre Guaceto MPA and at two unprotected locations (Fig  1 ): one north of the MPA borders (in the following indicated as EXT/N), and another south of the MPA (EXT/S in the following). Unprotected locations were selected at ~4-10 km from the MPA borders and are comparable to protected locations in terms of habitat type, depth, substrate complexity, slope and wave exposure. The distance between protected and unprotected locations is large enough to exclude significant spillover of adult fish  [11] , but relatively small compared with the dispersal range of propagules (eggs and larvae), which can be transported by currents up to 200 km from spawning areas  [34] [35] [36] , and juveniles, which can disperse over tens of km  [35].
Only individuals >8 cm TL were counted, because juveniles (i. e. settlers and recruits) do not share the same habitat and depth range of adults. In addition, excluding juveniles from the count avoids the introduction of significant amounts of noise related to the erratic dynamics to which recruitment is subject. Transects were replicated (8 to 32 times per location depending on the year, for a total of 716 replicates) to evaluate uncertainty due to census error and spatial variability at the local scale. Replicates were done at a minimum distance of 50 m from each other to avoid spatial cross-correlation of density estimates. Data on fish density per year and location are reported in (S1 Table ).
In our study, overall evidence for density dependence was much lower at the unprotected location north of the MPA (EXT/N) than inside Torre Guaceto MPA and the unprotected location south of it (EXT/S). A possible interpretation for this result is that the data collected at EXT/N span only a small range of variation compared with the other two locations: consequently, the range of observed fish densities may be too narrow to provide sufficiently robust evidence about the actual demographic dynamics at that specific location. In fact, the structure of the second best model indicates that population dynamics at the two unprotected locations (EXT/N and EXT/S) are also regulated by population density and cannot be distinguished from each other. If population dynamics at the two unprotected locations were actually different (as in the first and third best models), this might be justified by a differential recruitment subsidy provided by the MPA after every annual reproduction event, i.
Acknowledgments The opinions expressed in this article are those of the authors only and do not represent the  European Commission 's official position. Many thanks are expressed to  Simona Bussotti  and  Manfredi Di Lorenzo  (for helping collect field data),  Maria Benedetti  (for preliminary statistical analyses),  Christian Vaglio  and  Nucleo Subacqueo Carabinieri di Bari  for assistance during field work ( Commander Ugo Adorante  and his team:  Pietro Di Pinto ,  Gianfranco Simonini ,  Carlo Del Console ,  Fabrizio Pichierri ,  Gianni Sgariglia ,  Roberto Ciccacci ,  Mauro Bellini ).
Model derivation The description of the rim and sheet breakup requires a model for the deformation of the drop into an expanding sheet of radius R and thickness h. Previous models have considered a sheet with uniform thickness  (Gelderblom et al. 2016). However, from the MEK data it is clear that the sheet thickness has a radial dependency (see e. g. figure  4 ). Therefore, we employ here a slightly more sophisticated model that has previously been used for the sheet formed by an impact on a pillar  (Villermaux & Bossa 2011) : R(t) -R 0 R 0 = 3 We d t τ c 1 - √ 3 2 t τ c 2 , (4. 1) with We d = E k ,d E k ,cm We, (4. 2) where E k ,d /E k ,cm is the ratio of the deformation to the propulsion kinetic energies, which depends on the laser-beam profile  (Gelderblom et al. 2016). The rescaled Weber number We d is only based on the fraction of the kinetic energy that is actually used for deformation.
Ligaments form earlier for larger Weber numbers and always form before the sheet starts retracting (t r < t max ). The maximum number of ligaments observed over t t max is found to increase with increasing We d as illustrated in figure  11 (a-d  ) with tin. This observation is confirmed by plotting N r versus We d in figure  11 (e). For MEK drops neck breakup takes place much earlier than for tin and interacts with the formation of the rim ligaments. Therefore neck breakup in MEK drops limits the range in We d for which reliable measurement of N r can be obtained. However, the two measurements we obtained are in quantitative agreement with the tin data at the same Weber number.
The fastest growing Rayleigh-Taylor mode is given by k r ∼ (-R ρ/γ) 1/2 ∼ We 1/4 d /R 0 , identical to the characteristic wavenumber of the Rayleigh-Plateau instability. Using again the early-time expansion of (4. 1) we find R/R 0 ∼ We 1/2 d t/τ c , which leads to N r ∼ R(t r ) k r ∼ We 3/8 d. (5. 2) Figure  11  (e) shows that (5. 2), with a prefactor of 4. 4, is in good agreement with the tin data. Although the We d dependence cannot be verified on the sole basis of the limited MEK data, the MEK data available is found to follow the scaling (5. 2) with the same prefactor as the tin data. Hence, we conclude that the difference in rim breakup between MEK and tin is completely captured by the rescaled Weber number We d that accounts for the different driving mechanisms, in particular the effect of the plasma dynamics on the expansion the tin sheets.
In addition, the timescale of the breakup becomes shorter as We is increased (t/τ c = 0. 30 and 0. 12 in (c) and (e), respectively). Hole nucleation in MEK is always preceded by corrugations with a high k corr on the sheet surface. However, no direct relation between k corr and k s is found. Only a few holes pierce a corrugated area, such that k corr k s. The corrugations can however be used as an indicator for the areas where holes are likely to nucleate. We verified this concept with an image-analysis algorithm that is sensitive to spatial frequencies much larger than the hole density, as shown in figure  13 (a). From the data of approximately 100 experimental realisations we obtain the probability density function (PDF) of hole nucleation in the radial direction (figure  13 c ). Not surprisingly, the quantitative analysis recovers a bimodal Gaussian distribution with two preferred areas for hole nucleation as already identified visually in §3: the neck and centre region, which are marked in figure  13 (b).
Comparison between model and experiments Figure  17  compares the scaling for the breakup time (6. 14) with experimental data of the centre breakup for the tin and MEK drops. As the kinetic-energy partition E k ,d /E k ,cm differs between the tin and MEK experiments, the shows the breakup time t s rescaled by E k ,d /E k ,cm to allow for a direct comparison. Both the MEK and the tin data sets show good agreement with the predicted We -1scaling, over respectively one and two decades in Weber number. Strikingly, the absolute time at which the MEK and the tin sheets break differs by almost an order of magnitude, as was already observed in figure 5 in §3. 2. This difference can be explained by a difference in the initial noise level from which the instability grows. Assuming a prefactor of order unity in (6.
14) we find for the noise level of the MEK sheets η 0 /R 0 = 1. 2×10 -2 and for tin η 0 /R 0 = 1. 3×10 -3. The noise level for MEK is hence much larger than the thermal noise, which is expected to be of nanometre scale  (Eggers & Villermaux 2008 ). Unfortunately we are not able to determine the noise level from an independent experiment. However, we can qualitatively explain the difference between MEK and tin. As discussed in §2. 2, the MEK drops are subject to a much rougher beam profile and are furthermore propelled by vapour pockets bursting from their surface, while the tin drops interact with a smooth beam and plasma cloud. As a result, the initial noise in the MEK system is expected to be of macroscopic scale and much larger than for tin. These differences being accounted for by the parameter η 0 /R 0 , the two data sets obtained with different liquids at vastly different length scales both confirm scaling (6.
The radii R(tr) and R(ts) are determined from (4. 1) and the scalings (5. 1) and (6. 14) for the breakup time in the rim ( ), neck ( ) and centre region ( ). The prefactor are those obtained from the experimental MEK data in figures 10 and 17. The maximum radius Rmax ( ) follows from the sheet kinematics (4. 1) for tmax /τc = 2/ √ 27 with an energy partition for MEK of E k ,d /E k ,cm = 1. 8. The radius R frag ( ) is an estimate for the extent of the cloud of fragments ( ) that originate from the rim breakup (see text). EUV lithography applications. To access the different regimes one can either vary the Weber number by tuning the laser-pulse energy or the radial expansion of the sheet by adjusting the timing of the main laser pulse.
Figure18. Overview of the drop fragmentation regimes and radial expansion in terms of the Weber number. The parameter range of stable liquid sheets () is separated from the unstable domain () where rim breakup and sheet breakup occur. The radii R(tr) and R(ts) are determined from (4. 1) and the scalings (5. 1) and (6. 14) for the breakup time in the rim ( ), neck () and centre region ( ). The prefactor are those obtained from the experimental MEK data in figures 10 and 17. The maximum radius Rmax ( ) follows from the sheet kinematics (4. 1) for tmax /τc = 2/ √ 27 with an energy partition for MEK of E k ,d /E k ,cm = 1. 8. The radius R frag () is an estimate for the extent of the cloud of fragments ( ) that originate from the rim breakup (see text).
(1991) , respectively, but in the range of  Bottini et al. (2016). In our dataset, specimens larger than 11 μm are often present. However, a size increase or decrease over time, as observed by  Bralower et al. (1991) ,  Clémence et al. (2010)  and  Bottini et al. (2016)  has not been observed in this study from the middle Norian to the early Rhaetian. These observations could suggest that a significant size variation did not occur before the middle Rhaetian but later, close to the end-Triassic mass extinction.
Acknowledgements This research was supported by the  Austrian Science Fund (FWF) : project number  P 29497-P29  to  Sylvain Richoz  and « RESPECT » (A major evolutive Revolution: the  Emergence and Spreading of PElagic Calcifiers in the late Triassic) PICS-CNRS  project to  Silvia Gardin. Gerald Auer  and  Dorothee Hippler  are acknowledged for their help in the early scientific discussions and  Franz Tscherne  for his assistance during sample preparation for SEM. The detailed and constructive comments of two anonymous reviewers and of guest editor  Yadong Sun  were very helpful during the revision of this manuscript.
Details on the calibration can be found in Sultan et al. [25, 26]. Among the different calibrated varieties, we selected 90-day varieties, which are short duration crops, insensitive to the photoperiod and selected to maximize the mean yield under optimal fertility conditions. This optimal scenario in a farming situation, associated to intermediate seeding practice (neither too early nor too late with respect to the rainy season) allows us to better capture the effects of climatic constraints although it tends to overestimate simulated yields under historical years in West Africa compared to FAO data  [25, 26]. Since accumulated growing degree days were used to estimate the duration of the different crop development stages in the SARRA-H model, the duration of the crop might vary with temperature changes.
Indeed, Sultan et al. [25]  found that a 4 • C warming would shorten the crop duration of such a 90-day cultivar by 11% in the crop model. As for SARRA-H version, five meteorological inputs are needed with SARRA-O (maximum and minimum temperatures, downwelling shortwave radiation, precipitation, and potential evapotranspiration (Penman-Monteith)  [27]. In this study, ET 0 is computed by Hargreaves formula  [28]. Moreover, for the crop yield simulated by SARRA-H, it was showed that Penman-Monteith and Hargreaves formula obtain closed values with the use of in situ weather data and that Hargreaves equation is robust when it is used in dry climate  [28]. Soil depth and soil water holding capacity were defined based on the Harmonized World Soil Database (FAO/IIASA/ISRIC/ISSCAS/JRC, 2012). The first planting is usually carried out as soon as possible, just after the first heavy rains, from the northern part, where the situation is more humid, to the southern part the planting date can extend throughout more than one month.
Machine status ThomX project has been approved and financed in the framework of the EQUIPEX program of the French National Research Agency (ANR-10-EQPX-51). After a first study phase a Conceptual Design Report has been provided  [28]  summarizing the main aspects of the scientific case, the accelerator complex, the lasers and the users' X-line. This phase was followed by a detailed study of the expected parameters and of all the technical systems of the machine leading to the publication of the Technical Design Report  [19]. In parallel, an important decision was taken concerning the infrastructure. ThomX will be integrated with another EQUIPEX accelerator project of the Orsay campus, ANDRO-MEDE, in the former "IGLOO" building creating the new IGLEX research platform. After the studies period in 2015, the infrastructures civil works started in 2016 and was finished in middle of 2017.
First experiments The commissioning of the light source will take some time, estimated to few years. During the first phase, the X-ray beam will not be stable and good enough to be used for reliable data acquisition. Moreover, during this phase, the machine will be permanently tuned to improve its performances and so the X-ray beam characteristics may be changed too. It is planned to use the first phase to take over the X-ray line and all its equipments. Then ThomX will be ready to achieve first X-ray experiments as soon as a stable X-ray beam will be delivered. The first experiments planned on ThomX are the characterization of the X-ray beam in terms of flux, size and position, stability over time, angular spectrum and flatness (homogeneity). Later experimental validation of the beam will be performed with standard experiments as X-ray diffraction on a calibrated powder, X-ray fluorescence of well-known materials, X-ray imaging of a phantom (medical calibrated sample) and phase contrast imaging of the phantom.
OBJECTIVES The primary objective of the study is to (semi-)quantitatively assess  The second group was defined to compare techniques for assessing amyloid status in their role and ability to predict cognitive decline. First, the BP ND will be used to assess the validity and possible bias within the SUVR measurement in those subjects who have dynamic scans. Next, the relationship between traditional global amyloid PET measures (Centiloid, SUVR, and BP ND ), regional level data and available systems for staging amyloid burden  [34] [35] [36]  will be assessed. Finally, data combined from AMYPAD PNHS and PCs will be used to determine the cross-sectional and longitudinal agreement between brain amyloid status classification methods (PET quantification and visual assessment, as well as CSF). As a result, the optimal methodology to obtain (cross-sectional and longitudinal) (semi-)quantitative measures of amyloid burden that robustly predict cognitive decline will be determined.
DATA HARMONIZATION As a multi-center study, AMYPAD PNHS must ensure optimal data harmonization in many levels of the data collection process. With respect to imaging, both the PET acquisition protocols and the core MR sequence (3D T1w) are the same across centers, and the scanners are qualified by IXICO prior to study commencement to ensure harmonized data quality. Exceptions to this are scans collected from PCs that entered AMYPAD PNHS with historical scans, in which case the historical protocol is maintained for longitudinal consistency and a posteriori harmonization is performed. With respect to the remaining measurements, these will be more heterogeneous due to the inclusion of multiple PCs. Especially with respect to cognitive measures, PCs may differ due to distinct goals or experience with specific assessments.
Therefore, the harmonization of non-imaging data will be a major endeavor in AMYPAD PNHS, which will leverage the expertise of external partners and collaborators with previous experience. 39 The final strategy for harmonization of each variable will be made openly available on AMYPAD's website, providing clarity to users and potential support for future initiatives aiming to perform similar analyses. As an initial step, cognitive assessments will be analyzed per cognitive domain and z-scored to improve comparison across tests. A list of original variables available from PCs is available on the website and will be updated as new PCs join the project.
43, 44 AMYPAD understands that the accumulation of amyloid plaques is a necessary but not sufficient step in the development of Alzheimer's dementia. Thus, the study purposely aligns itself with cohorts that collect extensive assessments in a pre-dementia population to enable the assessment of a variety of risk factors and biomarker interactions and contribute to the understanding of this complex disease, also beyond amyloid pathology. Nonetheless, the increased availability of larger longitudinal datasets of cognitively unimpaired subjects has already resulted in the compilation of an initial but growing evidence on the role of amyloid burden as a predictor of early cognitive decline, also independently from or corrected for other factors. 9, 10, 45 In fact, early accumulation of amyloid plaques in specific regions of initially amyloid-negative healthy adults has also been linked to subclinical amyloid-related decline in episodic memory.