dataesr/scientific-paragraphs-categorization huggingface dataset:
Emission inventories In this study, we use surface emission data from different inventories made available in the ECCAD (Emissions of atmospheric Compounds & Compilation of Ancillary Data) database  (Granier et al. , 2013)  of the French Atmospheric Chemistry Data Centre ESPRI (formerly Ether; http://eccad. sedoo. fr/). The objective is to derive the total acetone flux from the boundary layer into the upper troposphere for different regions and compare this flux with the acetone source strengths derived from the enhancement ratios and CO inventory data. Ideally, we would have preferred to use inventory data of exactly the same years for which CARIBIC data were used in this study  (2006-2008; 2012-2015) , but not all data in the ECCAD database is yet available for the full period. Therefore, we chose the last 6 years with complete data coverage  (2005) (2006) (2007) (2008) (2009) (2010)  as reference period.
This period has a similar duration as the CARIBIC periods and at least covers the first CARIBIC data period. Except for biomass burning emissions, there is currently only one possible inventory for each source type for the given period. Hence, anthropogenic emissions are taken from the MACCity inventory (van der  Werf et al. , 2006; Lamarque et al. , 2010; Granier et al. , 2011; Diehl et al. , 2012)  and biogenic emissions from MEGAN-MACC  (Sindelarova et al. , 2014). For biomass burning emissions we decided to use the GFED3 inventory (van der Werf et al. , 2010) instead of GFASv1. 0 for reasons of easier data handling, as GFED3 data in ECCAD has the same temporal and spatial resolution as MACCity and MEGAN-MACC. Furthermore,  Kaiser et al. (2012)  found that the budgets of GFED3(. 1) are consistent with GFASv1.
0. As we are interested in the total flux of acetone, i. e. primary emissions and secondary production, we also include emission data from the major precursors of acetone and CO. According to  Jacob et al. (2002)  and  Fischer et al. (2012) , the three dominant precursors of acetone are propane (13-22 Tg a -1 acetone), higher alkanes (4-7 Tg a -1 acetone) and monoterpenes (5-6 Tg a -1 acetone). In order to estimate the acetone source from propane oxidation, we use propane emission data from MACCity and GFED3 and a molar acetone yield of 72 %  (Jacob et al. , 2002; Pozzer et al. , 2010). For isobutane and isopentane, we use the "butanes and higher alkanes" data of MACCity and calculate the mass proportion of the two species (5. 7 % for isobutane and 9. 7 % for isopentane) according to the VOC speciation of  Passant (2002)  and  Calvert et al.
(2009). The resulting amount of acetone is derived using the means of the yields suggested by  Jacob et al. (2002)  and  Pozzer et al. (2010) , which are 0. 96 mol mol -1 for isobutane and 0. 72 mol mol -1 for isopentane. G. Fischbeck et al. :  Acetone-CO enhancement ratios in the upper troposphere For the monoterpenes, we use the emission data for the sum of monoterpenes from MEGAN-MACC  (Sindelarova et al. , 2014)  and the relative contributions provided in  Sindelarova et al. (2014)  to calculate the emissions of the following individual monoterpene species: α-pinene, β-pinene, limonene, trans-β-ocimene, myrcene, sabinene and 3-carene. For each species, we derive mean acetone yields based on the available literature. Here, we consider the two main degradation processes of monoterpenes, reaction with OH and O 3 , and weight the yields according to the respective reaction rates (i.
Temporal and spatial distribution of data The analysis of acetone-CO EnR relies on the availability of the simultaneous measurement of acetone and CO in the troposphere. At the time of this study, tropospheric acetone data were available for 105 CARIBIC flights between 20 February 2006 and 13 December 2008 and for 109 CARIBIC flights between 6 March 2012 and 16 July 2015. The gap is due to a larger modification of the instrument and subsequent re-certification. As shown in Fig. 5 , about 90 % of simultaneous tropospheric acetone and CO measurements were carried out in the Northern Hemisphere, mainly in the subtropics and mid-latitudes along the routes between Germany and Caracas/Bogota, Sao Paolo, Chennai, Bangkok and Guangzhou/Hong Kong. Although IAGOS-CARIBIC flights to North America took place frequently, mainly stratospheric air was sampled due to the lower tropopause heights there.
In practice, this means that for each hourly waypoint of the trajectory, the assigned EnR is duplicated and the coordinates of the sample location are exchanged by the ones of the waypoint. This domain-filling technique is also known as trajectory mapping and has been applied elsewhere for similar in situ datasets  (Stohl et al. , 2001; Osman et al. , 2016). In Fig. 8 , the resulting geographical distribution and frequency of EnRs duplicated this way is shown for a 5 • × 5 • grid. We are aware that back trajectories have limited reliability; however, random trajectory errors should be negligible in our case, with respect to the large number of trajectory-mapped EnRs. The assignment of EnRs to source regions is done as follows. In a first step, longitude-latitude boxes are defined for the regions of interest.
4. 1 and Fig. 4 ). The seasonality is less pronounced (in descending order) above Europe, Southeast Asia and East Asia. In contrast to the mean EnRs, individual low EnRs are observed throughout the year in all regions, as can be seen from the overlap of the lower whiskers in Fig. 9. Low EnR in summer might be an indication of rapidly ascended plumes from sources with low acetone-CO emission ratios, such as smouldering fires and other incomplete combustion processes (see Table  1 ). Figure  10. North American emission rates of (a) acetone and (b) CO according to the ECCAD inventory database, averaged over the time period 2005-2010. (c) Mean EnRs derived from IAGOS-CARIBIC measurements are compared to ECCAD total emissions volume ratios (TERs) of acetone and CO with and without consideration of biomass burning (BB).
Summary and conclusions In this study, we give a major update on enhancement ratios of acetone and CO in the upper troposphere. We present a new method to detect coherent correlations that are physically more meaningful than correlations based on spatially or temporally distant measurements. We apply this method to the IAGOS-CARIBIC dataset of acetone and CO and utilize the concept of enhancement ratios for interpretation. In former studies, free-tropospheric acetone-CO enhancement ratios were often compared directly with emission ratios of individual sources, although enhancement ratios are only equivalent to the emission ratio when measured at the source. For EnRs higher than the ERs, the authors assumed secondary production of acetone in the plume. We show, using a box model, that an increase in EnR is not inevitably caused by secondary production of acetone, but strongly depends on the initial quantities of acetone and CO in the plume.
Dilution rates from other studies indicate that common enhancements are rapidly mixed in the PBL and rather contribute to the PBL background than being directly transported into the free troposphere. We conclude that an uplift of these air masses leads to tropospheric EnRs that can be seen as a chemical signature of the boundary layer air, therefore rather reflecting larger regional source patterns than distinct emissions from single point sources. As the sources vary by season, we investigate the seasonality of EnR and find that in the Northern Hemisphere mid-latitudes they are on average 2. 3 times larger in summer than in winter. Given the coverage and representativeness of the IAGOS-CARIBIC dataset, it is also possible to investigate regional differences in EnR and its seasonality. We compare the seasonality of EnR observed over North America, Europe, East Asia and Southeast Asia and find the same behaviour for all four regions, but with varying degrees.
We assume that these differences are mainly caused by regional differences in acetone and CO sources and therefore enable the comparison of EnR with emission estimates of inventories. The monthly ratios of the total acetone and CO bottom-up source estimates lie well within the standard deviation of mean EnR observed over the respective region and show the same seasonal course as EnR. We calculate regional acetone fluxes by using well-constrained CO emission data and monthly averaged EnR. For North America, we estimate a mean annual acetone flux of 53 × 10 -13 kg m -2 s -1 and for Southeast Asia 185 × 10 -13 kg m -2 s -1 , reflecting the dominance of biogenic acetone emissions that are larger in tropical to subtropical Southeast Asia. With our EnRbased approach, it will be also possible to estimate regional acetone fluxes for other regions in the future.
Data availability The CARIBIC data and relevant information are available from the CARIBIC website (http: //www. caribic-atmospheric. com) upon signing the CARIBIC data protocol and by contacting the CARIBIC coordinator (andreas. zahn@kit. edu). The trajectory data are available from the website http://projects. knmi. nl/campaign_support/CARIBIC/ (van Velthoven, 2016). The underlying emission inventory data are available via the ECCAD database (http://eccad. sedoo. fr/) (Granier et al. , 2013)  upon signing the data protocol. Appendix A: Detailed description of emission data in Fig. 10  The strongest source of acetone in North America is direct biogenic emission with an annual mean of ∼ 31 × 10 -13 kg m -2 s -1 and a strong maximum in July/August (∼ 70 × 10 -13 kg m -2 s -1 ). The second largest source is secondary production from precursors.
Jacob et al. (2002)  and  Fischer et al. (2012)  assumed that propane is by far the dominant precursor of acetone on a global scale followed by higher alkanes and monoterpenes. Here, we consider propane, isobutane and isopentane, seven individual monoterpene species and methylbutenol (MBO) as precursors of acetone. Methylbutenol is emitted by pine trees native exclusively to North America (e. g. Harley et al. , 1998; Kim et al. , 2010)  and is therefore considered as a regional source. As MBO emission data are not available in the ECCAD database, we scale the monthly monoterpene surface emissions in a way that annual MBO emissions equal the estimate of 2. 2 Tg by  Guenther et al. (2012). Based on the available literature, we derive and apply a mean molar acetone yield of 0. 46 for the oxidation of MBO.
1 ± 3. 1) Tg is in excellent agreement with the (6. 0 ± 3. 1) Tg derived when using 10 times the measurement uncertainty of CO as threshold. In a second reanalysis, we use a threshold of 15 ppb to test the sensitivity of the result to a higher threshold (results, see Table  B1 ). Increasing the threshold to such an CO enhancement reduces the dataset for North America by ∼ 75 %, leading to the situation that there is not enough data for November and December, although North America is the region with the best coverage (see Table  7 ). The mean of the monthly EnR decreases from 21. 3 to 18. 4 ppt ppb -1 , which can be explained as follows. The exclusion of events with CO enhancements of 10-15 ppb puts more emphasis on the events with high-CO enhancements, but the high-CO enhancements are not completely compensated by high-acetone enhancements; i.
e. the EnRs of this subset are lower. Nevertheless, the means for all three requirements are still in the standard deviations of each other. When changing the threshold to significantly lower CO enhancements, the monthly mean EnRs increase. However, in such a situation it becomes impossible to our mind to distinguish between an increase caused by shifting the weight of certain EnRs and an increase related to the temporal evolution of EnRs, which we discussed in Sect. 4. 1. Consequently, we can only investigate the sensitivity in respect to higher CO Table  B1. Results of three different cut-off requirements (top row) applied to the dataset for North America. For each month and cut-off requirement, the number of unique EnRs (n), the mean EnR and standard deviation in ppt ppb -1 and the resulting acetone source (S Ac ) in Tg are provided.
The means and standard deviations for all months (last row) are based on the monthly values. enhancements. Thresholds higher than 15 ppb are not feasible with regard to the number of such events in our dataset. Appendix C: Detailed description of emission data in Fig. 11  Biogenic emission dominates throughout the year with a minimum in January (∼ 64 × 10 -13 kg m -2 s -1 ) and a maximum in May (∼ 154 × 10 -13 kg m -2 s -1 ). Biomass burning emissions peak in the late dry season (January-April) and contribute to an annual maximum of acetone emissions in March (∼ 208 × 10 -13 kg m -2 s -1 ) being twice as large as the maximum acetone flux of North America. For the same reason, CO emissions (Fig. 11b ) peak in March. However, besides the large contribution of biomass burning (37 %), other anthropogenic sources make up the greatest part (48 %) of the total CO flux (∼ 131 × 10 -11 kg m -2 s -1 ), which is 7 times larger than the maximum CO flux of North America.
Acknowledgements. The authors wish to thank  Lufthansa ,  Lufthansa Technik  and all CARIBIC partners for their ongoing support of the  IAGOS-CARIBIC laboratory. We especially acknowledge  D. Scharffe  for supplying the CO data and  A. Rauthe-Schöch  for supplying the merge files. We thank  T. Gehrlein ,  S. Heger ,  C. Koeppel ,  A. Petrelli ,  D. Scharffe  and  S. Weber  for their commitment in operating the CARIBIC container. We acknowledge the  NCAR Atmospheric Chemistry Division (ACD)  for providing the  TUV Radiation Model. We thank the  Centre National d'Etudes Spatiales (CNES)  and the  Centre National de la Recherche Scientifique (CNRS) -Institut National des Sciences de l'Univers (INSU)  for distributing the emission inventory data in the ECCAD database. ECCAD is part of the  ESPRI Data centre (formerly Ether ) and the emission database of the  GEIA (Global Emissions InitiAtive ) project, which are gratefully acknowledged.
Acknowledgements We thank  Frauke Alves  and  Julia Bode  from the  Max-Planck-Institute of Experimental Medicine in Göttingen  for the supply with the Herceptin therapeutic drug. We also want to thank  David Fernandez  and  Amagoia Ametzazurra  from  Progenika Biopharma  for providing the serum. This research was supported by the  European Commission   FP7   NAMDIATREAM  project ( EU NMP4-LA-2010-246479 ), and the  German Research Foundation  ( DFG grant   PA 794/25-1 ).
ACKNOWLEDGEMENTS We thank our referee,  David Neufeld , for his careful reading of our manuscript and his enlightening suggestions. This work was mainly supported by the  ANR SILAMPA  ( ANR-12-BS09-0025 ) and  USTH (University of Science and Technology of Hanoi). This work was also partly supported by the  French program Physique et Chimie du Milieu Interstellaire (PCMI)  funded by the  Conseil National de la Recherche Scientifique (CNRS)  and the  Centre National d' Études Spatiales (CNES). We thank  Guillaume Pineau des Forêts ,  Benjamin Godard  and  Thibaut Lebertre  at  LERMA/Observatoire de Paris -Paris , as well as all the members of the  Department of Astrophysics (DAP) at the Vietnam National Satellite Center (VNSC)  for helpful suggestions and comments. We also thank prof. Stephan Jacquemoud  for a careful reading of the manuscript.
It is planned to operate the Pierre Auger Observatory until at least the end of 2024. An upgrade of the experiment has been proposed in order to provide additional measurements to allow one to elucidate the mass composition and the origin of the flux suppression at the highest energies, to search for a flux contribution of protons up to the highest energies and to reach a sensitivity to a contribution as small as 10% in the flux suppression region, to study extensive air showers and hadronic multi-particle production. With operation planned until 2024, event statistics will more than double compared with the existing Auger data set, with the critical added advantage that every event will now have mass information. Obtaining additional composition-sensitive information will not only help to better reconstruct the properties of the primary particles at the highest energies, but also improve the measurements in the energy range just above the ankle.
Except for the six models mentioned above, some types of machine-learning models, such as deep learning, artificial neural network, and support vector machine, have been used for photograph aesthetical evaluation and prediction  [57] [58] [59] [60] [61] [62]  Although the machine-learning models are black boxes, they are more convenient for model building because of their availability and generality with the development during the last decades. Nearly, all software programs for machine learning, such as MATLAB, Weka, and Enterprise Miner, provide neural network toolbox.
Overweight and obesity are more commonly defined using body-mass index (BMI). According to the US Centers for Disease Control and Prevention (CDC),  8  for children and teenagers of the same age and sex in US datasets, overweight is defined as a BMI at or above the 85th percentile and below the 95th percentile, obesity is defined as a BMI at or above the 95th percentile, and severe obesity is defined as a BMI above the 96th percentile. For calculations, an imperial and metric online calculator based on US datasets is available on the CDC website. Given that BMI is related to age, the diagnosis of obesity using the BMI calculation is a lot easier than using height-to-weight ratios. Another definition of obesity that is age and sex specific and based on BMI was introduced by the International Obesity Task Force (IOTF) in 2000.
Clinical examination might reveal wheezing, dyspnoea, or tachypnoea at rest, and is completed with ambient air pulse oximetry. Lungfunction tests might be done depending on the severity of obesity and type of planned surgery. Uncontrolled asthma requires specialist advice and preoperative optimisation. Gastro-oesophageal reflux is present in 13% of children who are obese and 20% of children who are severely obese, whereas it is only present in 2% of healthy children (no data available for children who are overweight). 30 Nevertheless, obesity per se is not a risk factor for pulmonary aspiration,  31  and preoperative fasting does not need to be modified, even when gastrooesophageal reflux is present. 32 Furthermore, evidence to support the use of preoperative H2-receptor antagonists is sparse.
Search strategy and selection criteria We searched the PubMed database with no beginning date restiction to May 31, 2017, using the search terms "obesity" or "overweight" and "children" or "paediatrics". Those entries were associated with "anaesthesia", "perioperative", "cardiovascular", "metabolic syndrome", "gastrointestinal", "psychological", "obstructive sleep apnoea syndrome", "pharmacology", "anaesthetics", "postoperative complications", "equipment", and "surgical positioning". Studies published in English and French were considered. Studies were excluded if done in adult patients and if a more recent article exploring the same topic was found.
Conclusions The general problem of high power radio frequency injection during low absorption operations in tokamaks was here described in the case of JT-60SA. Expected loads and EC stray amount have been qualitatively and quantitatively estimated and the main features of a system capable of prompt detection of high level of EC was here proposed, aiming at machine protection. An example of a similar system now operating on TCV tokamak during EC wall conditioning experiment was also given, with indications and guidelines to provide a conceptual design proposal as a next step. This activity is carried out in the framework of the EUROfusion Consortium and is a part of the WPSA work package and the authors gratefully acknowledge members of the JT-60SA Integrated Project Team for data exchange and fruitful discussions.
The status of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and the International Reactor Physics Experiment Evaluation Project (IRPhEP) was last discussed directly with the international nuclear data community at ND2013. Since ND2013, integral benchmark data that are available for nuclear data testing has continued to increase. The status of the international benchmark efforts and the latest contributions to integral nuclear data for testing is discussed. Measurements found in the IRPhEP Handbook offer additional means to support integral nuclear data validation. Select benchmark configurations that have been added to the ICSBEP and IRPhEP Handbooks since ND2013 are highlighted.
The variety in measurements beyond criticality offer additional means a e-mail: john. bess@inl. gov to support validation of computational simulations and integral nuclear data  [3]. Twenty-five countries have contributed to these two projects: 22 to the ICSBEP and 20 to the IRPhEP. Contributing countries include the following: Argentina, Belgium, Brazil, Canada, People's Republic of China, Czech Republic, France, Germany, Hungary, India, Israel, Italy, Japan, Kazakhstan, Poland, Republic of Korea, Russian Federation, Serbia, Slovenia, South Africa, Spain, Sweden, Switzerland, United Kingdom, and the United States of America. A primary purpose of the ICSBEP and the IRPhEP is to provide extensively peer-reviewed integral benchmark data that can be utilized by the international nuclear data community for testing and improvement of nuclear data files.
Highly enriched uranium data An evaluation of the Oak Ridge National Laboratory (ORNL) Oralloy (Oak Ridge Alloy) Sphere [HEU-MET-FAST-100, ORSPHERE-FUND-EXP-001] was completed. Oralloy is a highly enriched uranium (HEU) metal alloy, approximately 93. 2 wt. % 235 U, manufactured for use at ORNL. ORSphere was a very precisely measured, HEU alloy spherical assembly. Benchmark specifications are provided for two critical configurations, worth measurements, delayed neutron fraction, surface material worth coefficient, prompt neutron decay constant, relative fission density, and relative neutron importance measurements. The experiments had been performed to recreate GODIVA I experiments with greater accuracy. The third in a series of ORNL space reactor mock-ups (see Fig. 3 ) was evaluated [HEU-COMP-FAST-004, SCCA-SPACE-EXP-003].
This experiment consisted of beryllium-reflected arrays of UO 2 (93. 15 wt. % 235 U) fuel pins, stainless-steel-clad, to support the validation of reactor physics methods and calculations for the Medium-Power Reactor Experiments (MPRE) space power reactor design. Evaluated experimental data for the graphite-reflected configuration includes two critical configurations, spectral characteristics, various material worth measurements, axial/radial fission rate measurements and cadmium measurements. Only two critical configurations have been currently evaluated for the beryllium-reflected series. Ongoing efforts to evaluate potassium metal worth, as the simulated reactor coolant, are underway for inclusion in future editions of the ICSBEP and IRPhEP Handbooks.
Intermediate enriched uranium data The quantity of intermediate enriched uranium (IEU) benchmark experiments is rather paltry compared against the plethora of available HEU and low enriched uranium (LEU) experiments. The critical conditions for an unreflected, 37 wt. % enriched 235 U, 69. 2-cmdiameter sphere of UO 2 F 2 was evaluated and reported in [IEU-SOL-THERM-005]. This experiment is similar to one of U(93. 2%)O 2 (NO 3 ) 2 solution inside the same sphere [HEU-SOL-THERM-013] and another with 233 UO 2 (NO 3 ) 2 solution [U233-SOL-THERM-001] that were previously evaluated. Calculations with ENDF/B-VII. 0 and -VII. 1 nuclear data libraries of the IEU benchmark are approximately 0. 5% low but within the 1σ benchmark uncertainty of ± 0. 0065 k. The prior evaluation of the Idaho National Laboratory (INL) Neutron Radiography (NRAD) Reactor when it was converted from HEU to 20 wt.