dataesr/scientific-paragraphs-categorization huggingface dataset:
Main experiment We recorded daphnids' behaviour when they had the choice between i) MC-strain vs water, ii) MC-free strain vs water, iii) pure MC-RR vs water, iv) S. obliquus vs water, v) MC-strain vs S. obliquus, vi) MC-free strain vs S. obliquus vii) MC-free strain vs MC-strain, and viii) water vs water as a control. These eight treatments were tested in parallel with eight olfactometers and the tests were repeated 100 times strictly in the same conditions. Thus, we obtained 100 observations of different starved daphnids for each of the eight oppositions of treatments (Fig. 2 ) and our dataset was composed of 800 observations of displacements during 1. 5 h. The water treatment contained pure Volvic (Societé des Eaux de Volvic) water. The density of resource in the treatments with MC-strain, MC-free strain and S.
Statistical analysis Two types of analysis were done: i) comparisons of the distribution of daphnids between the treatments for each choice, and ii) comparisons of the distributions of daphnids between the first and the last choices. We used Fisher's exact test with R software. Fisher's exact test is used in the analysis of contingency tables when sample sizes are small. For the first and last choices, we tested the significance of the deviation from a null hypothesis of equal distribution. For the comparison between the first and last choices, we tested the significance of the deviation of the last choice from the first choice. We set significant differences at a threshold of α=5% and marginal significance at a threshold of α=10%.
Numerical results We consider an aircraft landing by fixing initial and final flight conditions as follow: 0 • ≤ α ≤ +20 • -10 • ≤ χ ≤ +10 • -5 • ≤ μ ≤ +5 • -10 • ≤ φ ≤ +20 • -60 km ≤ x(t) ≤ 0 km -10 km ≤ y(t) ≤ +10 km 0 ≤ t ≤ +10 min 0 • ≤ γ ≤ γ max = f ree 85 m/s ≤ V (t) ≤ V max = f ree 0. 2 ≤ δ x (t) ≤ δ x max = f ree 125000 kg ≤ m(t) ≤ m f = f ree 3500 m ≤ h(t) ≤ h f = f ree V min = 85 m/s represents the aircraft stall velocity. Some of these parameters are kept free. Once the processing steps and calculation efficiency are confirmed, their limit values are found and given. The data used in this optimization model are taken from an Airbus A300 of which the specifications are as follow: • Type : Airbus A300 -600 The three-dimensional analysis is useful in enhancing the reliability of the optimization model which it could be applied in automatic detection of aircraft noise.
The type of aircraft was recorded; it has been collected in real-time for each flight. In this paper, we present data recorded under flight path at a lateral distance of 2 km to the touchdown point. This measurement point corresponds to the certification point of the aircraft. The stability of atmospheric conditions was checked and timetabled. The following numbers show their fluctuations in the intervals where stability criteria are met during measurements. We summarize below meteorological parameters provided by Meteo France: -Wind speed (m/s): 1 -3 -Average temperature ( • C): 15 -35 -Cloudiness (octas): 0 -2 -Humidity (%): 35 -50 -Global radiation (J /cm 3 ): 240 -290 A SIP 95 sound level meter was used to record acoustic data. The measurement system is inspected every two years and approved by the French National Laboratory for testing in accordance with international standards.
Ambient noise, including both an acoustical background and electrical noise of the measurement system was recorded for 10 minutes a day with the system gain set at the levels used for the aircraft noise measurements. The recorded aircraft noise data is acceptable according to international standards. The exclusion criteria of the recorded data are: days on which a strike took place and special weather conditions (gusty winds, stormy rainfall, atmospheric turbulence, etc. ). According to the measurement specifications, we identified and retained 15460 turbojet aircraft approaching the airport in the same conditions representing 84. 5 % (+20 T) of the air traffic (15 % of the air traffic represents propeller aircraft (3-9 T and +20 T) and 0. 5 % others (-3 T and 3-9 T)). In this paper, we analyzed the measured maximum noise levels.
In addition, comparison between models provided 10 % and 20 % of F C Nonoptimal -F C Opt J Nonoptimal and F C Opt -F C P IM J Opt. This fuel consumption could be in favor of optimal flight path. Models describing engine parameters during flight operations in different conditions are not often published in the open literature. Indeed, in-flight engine database is not provided by engine manufacturers or airline companies. Data on FC and thrust versus aircraft Mach, altitude, throttle settings and power extraction can be correctly modeled because the physics behind it is well established. The output power of the turbojet is quite constant with changes in speed, whereas turbojet provides a constant thrust with speed. Modern aircraft are equipped with engines where the net thrust is reduced with the increase of the speed and the altitude.
Offspecular HREELS data may provide insights on the antisymmetric stretch modes too, and show indeed slightly lower frequencies. In agreement with experiment, the computations give a lower frequency for the anti-symmetric modes compared with the symmetric stretch ones of the Si1a-H bond. The computed Si2a-H(D) stretch mode at 2,020 (1,457) cm À 1 is not observed owing to its weak out-of-plane component. Thus, all observed H(D) experimental modes are accounted for by the vibrational properties of 8 H structure. One should note that the modes associated with atoms Si1a and Si2a of the 10 H structure are similar to those of 8H. No modes are present at the frequencies of 778 cm À 1 for D-exposed or 1,450 cm À 1 for H-exposed 3C-SiC surface as predicted by some of the DFT calculations for vibrations involving H(D) in bridge positions in the third plane  [27] [28] [29].
7 , this leaves reactive dangling bonds inside the nanotunnel, which could be used to trap other species of interest. After nanotunnel opening, the computed properties of the three-nanotunnel structures are in remarkable agreement with a range of experimental data and there is no experimental evidence, which would be in contradiction to the properties computed for these unprecedented void nanostructures. Specifically, the points are as follows: (i) Agreement with HREELS: The computed vibrational frequencies for the nanotunnel 8 H structure with both H and D atoms are in very good agreement with HREELS data as given in Table  1  and illustrated in Fig. 4. The antisymmetric stretch mode of the surface dimers as well as the outof-plane wag mode of the Si2a-H(D) atoms are very well described. The computed Si2a-H(D) stretch mode is not observed, which is reasonable because this motion is mostly in plane and thus expected to be weak in HREELS experiments.
Valence-band SR-PES experiments are performed at 300 K, using the ultrahigh vacuum photoemission experimental station of the TEMPO beam line connected through an ondulator to the light emitted by the third generation synchrotron radiation SOLEIL light source. The diameter of the SR beam and the size of the photoelectrons collected area are 300 mm. Photoemission spectra are measured using a Scienta SES2002 hemispherical electron energy analyser equipped with a fast two-dimensional delay line detector. The overall energy resolution combining the contributions of the soft X-ray beam monochromator and analyser energy selection is, in our experimental conditions, better than 50 meV. The experimental station allows direct in situ atomic H exposures during photoelectron spectroscopy data acquisition up to partial pressures of 10 À 8 mbar.
The Kohn-Sham equations are solved with the all-electron frozen-core projector augmented wave method  64  as implemented in the Vienna ab-initio Simulation Package  [65] [66] [67]  and integrated in the MedeA s computational environment  67. Locally stable equilibrium structures are determined by minimizing energy and forces using a conjugate gradient method. The topmost six layers are relaxed so that the forces on the atoms are o0. 02 eV Å À 1. The three layers at the bottom are kept frozen. The vibrational frequencies are computed using a finite difference method  68  as also implemented in the MedeA s environment  67. In these phonon calculations, the bottom layers are kept frozen and phonon dispersions originating from the vibrations of all other atoms are computed. For the clean 3C-SiC(001)-3 Â 2 surface, comparison between computed DOS and measured one by valence band photoemission is shown in Fig.
Acknowledgements This work has been supported in part by the  EU-RU. NET European Pilot Project, by  Compagnia San Paolo  and by the  French Agence Nationale de la Recherche  through the  ANR-P2   Nano MetroGraph  Project. P. S. acknowledges the support of the  Consiglio Nazionale delle Ricerche (CNR)  under the short-term mobility programme. The authors are especially grateful to the  SOLEIL  staff for outstanding assistance in synchrotron radiation experiments, and to  Marcin Zielinski  and  Thierry Chassagne  from  NovaSiC SARL (Sophia-Antipolis, France ) and  Lea di Cioccio  and  Thierry Billon  from  CEA-LETI (Grenoble, France)  for providing very high quality single-domain 3C-SiC(100) samples that were essential in the success of the HREELS and SR-PES experiments. All the calculations were carried out using the in-house facilities of  Materials Design , Inc.
e. scattering + absorption), and (iii) the spectral dependence of these optical parameters, calculated in terms of Angström Exponent (AE) or Absorption Angström Exponent (AAE) in the case of optical depth or absorption optical depth, respectively: AAE = log(AOD λ1 /AOD λ2 )/ log(λ 2 /λ 1 ) and AAE (1) = log(AAOD λ1 /AAOD λ2 )/ log(λ 2 /λ 1 ) Subsequent to the data description (ground-based dataset used in our work) in Sect. 2, the results are presented and discussed in two main parts. First (Sects. 3. 1-3. 2), we report AAOD and AAE AERONET level-2 and 1. 5 multi-year observations for different Mediterranean sites. AERONET SSA is analysed in Sect. 3. 3.
Finally, over Barcelona, even if the mean value is near unity, indicating that BC aerosol is the main contributor to absorption, a large range of AAE is also observed, with maxima around 1. 6. In such a case, organic particles could participate to the absorption of solar radiation as suggested by  Shinozuka et al. (2009)  during the MILAGRO experiment. Further analysis is needed to link the calculated AAE with the chemical composition of aerosols over different AERONET sites when such data are available. To conclude, such additional analysis of AERONET level-1. 5 data reveal that, in addition to dust particles, organic aerosols also contribute to shortwave absorption over the Mediterranean. This result demonstrates that current regional climate models treating OC as nonabsorbing over Mediterranean underestimate the total warming effect of carbonaceous particles by neglecting part of atmospheric heating.
Conclusions A multi-year climatology of column-effective aerosol absorption properties obtained over the Mediterranean from AERONET ground-based remote-sensing observations is presented. The focus of this study was on characterizing Aerosol Absorption Optical Depth (AAOD) and Single Scattering Albedo (SSA), and their spectral dependence. The AAOD dataset is composed of daily averaged AERONET level 2 data from 22 stations mainly under the influence of urban-industrial and/or soil dust aerosols. The datasets span 1996-2012, but most data are from the 2003-2011 period. Since AERONET level-2 absorption products are limited to high aerosol load (AOD at 440 nm > 0. 4), which are most often related to the presence of desert dust, we also considered level-1. 5 AAOD data despite their higher uncertainty.
Sun-photometer level-2 data analysis indicates a possible AAE regional gradient, with higher values obtained over the eastern basin (AAE East = 1. 39/AAE West = 1. 33). In parallel, the North-South AAE gradient is more pronounced, especially over the western basin, with AAE North and AAE South of about 1. 22 and 1. 77, respectively. The complementary analysis using level-1. 5 AERONET retrievals with data screened to avoid mineral dust aerosols (i. e. , AOD > 0. 2 and Angström Exponent > 1. 0) show that some Mediterranean sites are affected by organic absorbing aerosols (mean AAE ∼1. 15), especially Rome, Lecce, Burjassot and Athens. The effect is found to be lower for the Barcelona and Forth Crete AERONET sites (mean AAE of about 1. 0). This result highlights that current regional climate models that treat OC as purely scattering over the Mediterranean underestimate the total warming effect of carbonaceous aerosols and neglect part of the atmospheric heating due to particles.
Acknowledgements. This work was undertaken is the framework of the  MISTRALS/ChArMEx program. We acknowledge the AERONET and PHOTONS sun-photometer networks and the PIs of the 22 selected stations and their staff for their work to produce the dataset used in this study. This research has received funding from the  French National Research Agency (ANR)  project  ADRIMED  (contract  ANR-11-BS56-0006 ). Edited by:  T. Wagner The publication of this article is financed by  CNRS-INSU.
The multi-annual variations of ET in the merged synthesis products display realistic responses. They are also consistent with previous findings of a global increase in ET between 1989 and 1997 (0. 13 mm yr -2 in our merged product) followed by a significant decrease in this trend (-0. 18 mm yr -2 ), although these trends are relatively small compared to the uncertainty of absolute ET values. The global mean ET from the merged synthesis products (based on all data sets) is 493 mm yr -1 (1. 35 mm d -1 ) for both the 1989-1995 and 1989-2005  products, which is relatively low compared to previously published estimates. We estimate global runoff (precipitation minus ET) to 263 mm yr -1 (34 406 km 3 yr -1 ) for a total land area of 130 922 000 km 2. Precipitation, being an important driving factor and input to most simulated ET data sets, presents uncertainties between single data sets as large as those in the ET estimates.
e. computed with LSMs within a global model assimilating mostly atmospheric observations). The general main geographical structures related to the principal climatic regimes are present in all products, but relatively large differences in the absolute values among some of the products were observed  (Mueller et al. , 2011b; Jimenez et al. , 2011). Even though a large number of ET data sets are currently available and have been analyzed in these studies, a global benchmark for ET is missing. Such a benchmark data set would be useful for several purposes. Land-surface modellers and hydrologists often use ET to validate their model output, because it is one of the main components in the land water and energy budgets as well as a key driver for droughts (e. g. Sheffield et al. , 2012; Seneviratne, 2012).
However, the behavior of the LandFlux-EVAL data sets with respect to ET trends or multi-annual variations has not yet been investigated. Knowledge of the temporal changes of ET is important since it is a major component of the global water cycle. As the variability of water vapour is negligible at the global scale, the rates of precipitation and evaporation are similar. Within a changing climate, changes in the hydrological cycle are expected, but very difficult to determine. Observations indicate that precipitation over land increased by about 2. 4 mm per decade from 1900 to 1988  (Dai et al. , 1997, excluding  North Africa in their analysis). Extending the analysis to the entire 20th century indicates a similar large trend (reduced by about 25 %,  New et al. , 2001). Increases of land evaporation over these periods are therefore expected.
Besides precipitation and temperature, radiation is an important forcing for ET. Studies on trends in radiative forcing do not agree well. Wild and Liepert (2010)  for example noted a brightening since the 1990s, while  Romanou et al. (2007)  found a slight dimming. An evaluation of radiation data sets can be found in e. g. Troy and Wood (2009)  or  Jimenez et al. (2011). The benchmark synthesis products presented in this study are used to assess the interannual variations of ET on the global scale and encompasses the largest number of ET products to date. Besides the evaluation of the temporal variability of the benchmark products and the underlying single data sets, the present study also compares these to precipitation, which is one of the most important drivers of ET, especially in soil-moisture-limited regions (see, e.
Merged benchmark synthesis products of evapotranspiration We present here new multi-year merged synthesis products based on the analyses of existing land ET data sets that were available to us at the time of writing and fully cover one or both of the two studied time periods. A first product spans the time period 1989-1995 and includes 40 data sets, while the second is available for the longer time period 1989-2005 and includes 14 data sets (Table  1 , all data set categories). Consistent with a previous analysis  (Mueller et al. , 2011b) , the type of data sets included can be classified as diagnostic data sets, LSMs and reanalyses (see Sect. 1). Besides the two merged synthesis products based on all types of data sets, merged synthesis products from each of the individual data set types are also produced (see Table  1 ).
, 2006). In GLEAM, the calculation of ET is based on the Priestley-Taylor equation and the Gash analytical model of forest rainfall interception  (Miralles et al. , 2011b). The model discriminates the different evapotranspiration components, i. e. interception, bare soil evaporation, transpiration and sublimation, and ET is coupled to soil moisture  (Miralles et al. , 2011a). Note that not all diagnostic estimates separately calculate these components or account for all of them, which leads to large differences especially in the Amazon region. The forcing data for GLEAM were all obtained from remote sensing products and synthesis of rain gauges (CPC, see Appendix A). All WaterMIP simulations are driven with the same forcing data set (WATCH forcing, see  Weedon et al. , 2011) , but the employed forcing variables and time steps differ.
Overview of ET data sets, including their ET scheme or land-surface schemes (LSS), along with the number of soil layers, precipitation forcing data set and atmospheric forcing variables. Model names with a star are classified as global hydrological models (GHMs, see text). Forcing variables are P : precipitation; T : air temperature; W : wind speed; Q: specific humidity; R: radiation; SP: surface pressure. "na" denotes either not applicable or information currently not available. Note that GS-VISA and GS-CLMTOP cannot strictly be classified as aerodynamic approaches, since they include a carbon cycle and photosynthetic control on transpiration. Models with an x are included in the 1989-2005 merged synthesis product. Note that PT-JPL was referred to as UCB in  Mueller et al. (2011b). information on all other data sets, the reader is referred to  Mueller et al.
2 , the absolute ET trend change is very small and the interannual variations nearly vanish. The reason for the large IQRs and standard deviations are the large differences in the absolute ET values of the single data sets. The IQRs and standard deviations based on the yearly anomalies of the underlying data sets (i. e. setting the mean of all data sets to zero before calculating the statistics), which is the quantity shown in  Jung et al. (2010) , are much smaller (can partly be seen also in Fig. 3 ). Note also that we consider more estimates than in the previous analyses from  Jung et al. (2010). The ET anomalies from all long merged synthesis products are shown in Fig. 3  (top left). The comparison reveals a very similar temporal evolution of ET in all four merged synthesis products. Therefore, in the remainder of this study, only the merged products based on all data set categories (long and short) will be analyzed.
Single data sets The temporal variations of the 14 single data sets contributing to the long merged synthesis products are shown in Fig. 3  (top right and bottom panels). In these analyses of single data sets, we excluded unrealistically high ET values, setting a threshold of 4560 mm yr -1 (12. 5 mm d -1 ). The LSMs (bottom left) and reanalyses (bottom right) are more consistent amongst one another in their yearly variations than the diagnostic data sets (top right). The ET time series of all LSMs and reanalyses peak between 1997 and 1999. Some of the diagnostic data sets peak in other years, such as 2001 in the case of PRUNI and 2000 in GLEAM and AWB. The trends for the two time periods  1989-1997 and 1998-2005  are listed in Table  3. The merged product as well as 5 single data sets display a significant negative trend (italic font) for  The reason for this could be that we calculate the trends over a shorter time period compared to  Jung et al.
Precipitation forcing The 1989-1995 global mean land ET of each data set contributing to the synthesis product (short) is plotted against precipitation in Fig. 5. The precipitation value was taken from the forcing data of the respective ET data set as listed in Table  2. If precipitation was not available (for some Table  4. Mean ET of merged synthesis products 1989 -2005 (long), 1989 -1995 (short), mean precipitation 1989 -2005 (average of CRU, GPCC, GPCP and CPC)  and  ET and precipitation trends 1998-2005  in climate regions. Slope of trends (Theil-Sen) and significance (italic font, Mann-Kendal) estimated as for Table  3. diagnostic data sets), the average of four currently available observational data sets (CRU, GPCP, GPCC and CPC) was taken. Global mean values of these four precipitation data sets range from 730 to 803 mm yr -1.
Conclusions The intensity of the hydrological cycle determines the water availability and influences the climate system in various ways. Despite these important implications of possible changes in the hydrological cycle and with that, in ET, a global benchmark ET data set has long been missing. In the framework of the LandFlux-EVAL initiative (www. iac. ethz. ch/url/LandFlux-EVAL), several ET data sets based on observations (diagnostic data sets, LSMs and reanalyses) have been evaluated in previous studies  (Mueller et al. , 2011b; Jimenez et al. , 2011) , focusing on multi-annual means and seasonal cycles. The present study further investigates ET data sets. Global merged benchmark synthesis products of ET are derived and trends are analyzed in single LandFlux-EVAL data sets as well as in the merged ET products.
In addition, it is still unclear whether this signal corresponds to a long-term trend or decadal variability. Finally, because of the reliance of all ET data sets on atmospheric input data sets, the influence of spurious trends in these data sets cannot be excluded. Large uncertainties in absolute values of ET are found, which can partly be related to uncertainties in precipitation. Precipitation is one of the main drivers for ET in waterlimited evaporation regimes and overall in forests where interception can be large. As a consequence, it belongs to one of the main forcing variables for ET used in most diagnostic data sets and LSMs. Indeed, the spread in ET data sets is smaller than the spread in the corresponding precipitation data sets in our global analyses as well as in most climatic regions, which indicates that ET, as expected, is not only constrained by precipitation, but also by other variables such as radiation.