dataesr/scientific-paragraphs-categorization huggingface dataset:
The results show that they are consistent with the expanded measurement uncertainty of both LT and LS2. By analysing the individual residuals, the higher deviations correspond to a few targets lying on the floor, whose position requires an unfavourable acquisition direction for all the instruments employed. Furthermore, the colour-coded error maps show that the largest errors, in terms of deviation from the reference data, are mainly located at sharp surface gradients, such as the ones corresponding to the edges between the vertical walls of the corners and to the small grooves among the bricks. As evidence, the error distribution associated to results achieved with the 10°-dataset is shown in Figure  7 : the colour scale ranges from -5 mm (violet) to +5 mm (red). These sharp edges are problematic for active laser scanners when the spot diameter is large compared to the structural (lateral) resolution (VDI/VDE 2617) being analysed.
Two experiments are carried out, in order to analyse the software performance in dealing with both outdoor and environmentally controlled conditions for the case of a single 3D image. The results achieved within these two contexts are not general since they are of course influenced by the specific operative conditions affecting each case study, i. e. , datasets, hardware/software means, ambient and operators. Nevertheless, these studies offer a possible reference procedural workflow that can be further applied to different case studies in order to set specifically-adoptable best practices. Aspects of metrological nature should be developed further for the good of the different communities and for market growth. These aspects include defining what the measurand is in a given comparison, how calibration is performed and how often, what the traceability route is that links a measurement value to the SI unit, and, finally how the measurement accuracy of a system is quoted.
These pressure sensors were accompanied by six time-domain reflectometer (TDR) probes (ECH2O Decagon device) to measure the soil water content. TDR is an abbreviation of time-domain reflectometer, which is an electronic instrument that uses the time-reflectometry to characterize the soil properties, such as volumetric water content. The vertical slope surface movement was monitored by a laser displacement sensor (ZLDS100 ZSY Group, with resolution of 0. 03 %FS). Data for each sensor were logged digitally at 70 mhz for the duration of each experiment. The materials for the flume tests were collected from the Wenjia gully, where a huge volume (5. 67× 10 6 m 3 ) of debris originating from the Qingping landslide (5× 10 7 m 3 ) was deposited during the 2008 Wenchuan earthquake and a catastrophic debris flow (4.
> DATABASE CREATION A swimming fish was defined as a fish using active swimming, which is different from fish swept away by the flow. A fish was considered to behave as if migrating upstream when it was swimming with the flood-like tide or against the ebb-like tide with a non-null ground speed. On the contrary, a fish was considered to behave as if migrating downstream when it was swimming with the ebb-like tide or against the flood-like tide with a non-null ground speed. During the three weeks of the experiment, behaviour was recorded for one minute every 20 min. This was done to observe and record all fishes swimming with the current. During each recording event, an operator counted the number of fish migrating upstream, i. e. , the number of fish swimming with the flow during flood tides and against during ebb tides.
> DATA ANALYSES The rhythmic analysis showed if the individuals exhibited cyclic activity, i. e. , the same activity at a regular interval of time. Nevertheless, rhythmic analyses are not suitable to show what the favourite modality is. For example, a diel rhythm shows an activity peak every 24 h, but it is impossible to know if activity occurred during the night or the day. To mitigate this issue, we analysed a second parameter: the activity level, which is the instantaneous number of fish exhibiting a specific behaviour (in this study, swimming upstream). Migration behaviour (the proportion of fish migrating upstream) was analysed using shortterm Fourier transforms (STFT). STFT is based on the usual Fourier transform performed on an appropriate time sliding window  (Allen and Rabiner, 1977).
Mains Objectives of this Study The present study focuses on the temporal changes of the herbaceous vegetation cover in the Gourma region in Mali, where 27 years of field observations of the aboveground herbaceous mass are available. A strong re-greening pattern is observed using both field data and remote-sensing measurements  [17] ; a re-greening that we aim to understand through the analysis of RUE and ANPP residuals. This study addresses the three main following questions: (i) The first methodological goal will be to evaluate the use of remote sensing NDVI data to estimate indicators of land degradation such as RUE and ANPP residuals. The consistency within these two methods (RUE and residuals) will be examined as well. (ii) The second objective is to understand whether the re-greening trends observed over the Gourma region can be explained by rainfall.
Study Area The Gourma region is located in north-eastern Mali, south of the Niger River. The exact area considered in this study extends from 14. 5 to 17. 5°N and from 2. 2 to 0. 8°W, and will be referred to hereafter as the -Gourma window‖. Field observations of aboveground herbaceous vegetation mass are available from 1984 to 2010. The Gourma is a pastoral region, land under cultivation representing less than 5% of the surface. The vegetation is mainly constituted of annual herbaceous plants, the woody plants covering less than 3% of the surface. Twenty-one sites of 1 km 2 have been used in this study, which were measured every year for 27 years, at least when the field campaigns could be performed (some temporal gaps in the dataset do exist, but sites irregularly measured apart from these gaps have not been used).
ANPP Estimation Dardel et al. [17]  analyzed the time series of ground ANPP averaged at the Gourma window scale in relation to the GIMMS-3g time series, using peak mass as a proxy for ANPP. In this study, ANPP estimation is further refined. First, more severe criteria are used to select sites without significant temporal gaps (thus selecting 21 sites over the 38 available in the database). For instance, sites with only a few years of measurements available (either because the site monitoring was abandoned or because it started lately) are set aside. Second, for some sites which are sampled more often than others (mostly because of their ease of access), several measurements per year are performed. It is thus possible to detect when the mass goes through several maxima during the growing season.
Most of the years, a rain gauge could be associated with every vegetation site, meaning that there was a gauge with good quality data close enough, typically within 10 km of the vegetation site. The Gourma average JJASO rainfall was compared to the simple average of the two long-term stations of Gourma-Rharous (station from Direction Nationale de la Mé té orologie du Mali, DNM) and Hombori (SYNOP station from DNM Mali). Also, to evaluate the use of satellite-based rainfall datasets in estimating RUE or ANPP residuals, we included the TARCAT v2. 0 dataset from the TAMSAT Research Group (Tropical Applications of Meteorology using SATellite data and ground-based observations, Maidment et al. [46] ). TARCAT provides rainfall estimates from 1983 up to today with a spatial resolution of 0. 0375°, based on Meteosat thermal infra-red data and calibrated with ground-based rain gauge data.
The NDVI GIMMS-3g Dataset The NDVI-3g dataset is produced by the Global Inventory Modeling and Mapping Studies (GIMMS) group from data collected with the AVHRR (Advanced Very High Resolution Radiometer) sensors, which have been carried out by polar-orbiting meteorological satellites from the NOAA (National Oceanic and Atmospheric Administration), and are currently flying onboard the MetOps 1 and 2 satellites. The GIMMS-3g dataset extends the widely used GIMMS dataset, which is available over the 1981-2006 period  [41]. NDVI-3g data are provided globally from 1981 to 2012 with a 1/12° spatial resolution and 15-days maximum value composite images  [47]. The GIMMS-3g NDVI is produced using a similar processing scheme than for the GIMMS dataset. NDVI data are calculated from the AVHRR channel 1 (red, 550-700 nm) and channel 2 (near-infrared, 730-1000 nm) reflectances.
Calibration of the channel 1 and channel 2 reflectances is performed using the atmospheric Rayleigh scattering over oceans method of Vermote and Kaufman  [48] ; calibration of the NDVI itself is performed using the technique of Los  [49] , which relies on spectrally invariant targets such as desert areas, and finally artificial trends due to orbital drift are corrected using the empirical mode decomposition/recomposition (EMD) technique of Pinzon et al. [50] , which separates the trends due to a varying solar zenith angle from the overall signal. No atmospheric correction is applied, except for the aerosol content due to the volcanic eruptions of El Chinchon (1982) and Mt Pinatubo (1991). In the GIMMS-3g dataset, another stage was implemented in the processing because of the dual gain introduced in the late 2000s with the first AVHRR/3 instrument.
Calculation of Rain Use Efficiency and ANPP Residuals Two time-series of Rain Use Efficiency are calculated as the ratio of spatially averaged ANPP field and ANPP sat , respectively, to annual rainfall, over the Gourma window. These time-series are referred to as -RUE field ‖ and -RUE sat ‖. The ANPP residuals method is also applied to both field observations and satellite estimates. First, a linear regression between ANPP estimates (field or satellite) and annual rainfall is calculated, providing the -predicted ANPP‖ (field or satellite) time series. ANPP residuals are then calculated as the difference between observed ANPP and predicted ANPP, and are referred to as -field residuals‖ and -satellite residuals‖ for field observations and satellite data, respectively. Temporal trends over the period 1984-2010 are calculated using Ordinary Least-Square regressions for each of these datasets (RUE field , RUE sat , field residuals, satellite residuals).
ANPP and Rainfall Over the 1984-2010 period, satellite-derived ANPP and field-derived ANPP vary in a very consistent way (Figure  3a ). The temporal variations of both ANPP field and ANPP sat show a recovery of plant production after the 1984's drought, characterized by an increasing trend and a strong interannual variability. Field ANPP explains 65% of the iNDVI variance (Figure  3b ), which is slightly higher than the 56% reported in Dardel et al. [17]  for the correlation between peak biomass and NDVI over 1984-2011. Improvements in the estimation of ANPP field , together with the use of a remote-sensing proxy for ANPP sat which is closer to the Monteith production model (iNDVI instead of the average over August-September), are most probably causing this. The agreement between the two datasets is better during the 2000-2010 period (r 2 = 0.
71, p = 0. 0001) than during the 1984-1995 period (r 2 = 0. 48, p = 0. 018). When Equations (  1 ) and (  2 ) are applied to estimate ANPP from MODIS and GIMMS-3g over 2000-2010, the temporal profiles of the three ANPP datasets are very similar and the explained variance reaches 87% for MODIS and 67% for GIMMS-3g (see Appendix B). Whether ANPP is estimated from field data or from satellite GIMMS-3g NDVI data, it is highly correlated with the JJASO rainfall, which, in both cases, explains 76%-77% of the variance (Figure  4a, b ). The overall consistency of the three datasets, each of which could be impaired by quality issues, therefore strongly supports the use of satellite NDVI archive for long-term monitoring of dry lands.
When RUE and ANPP residuals are based on satellite-derived ANPP (instead of ANPP field ), results also support a non-significant trend over 1984-2010 (Figure  5b, d ). However, the temporal profiles of RUE sat lack the succession of high and low RUE anomalies detected with RUE field , and the interannual variability does not correspond well to the one of RUE field , except when the MODIS data are considered (see Appendix B). These results are still valid when TAMSAT or the two-stations rainfall datasets (Hombori and Gourma-Rharous) are used instead of the Gourma rain-gauge network co-located with each vegetation site: no significant trends over the whole 1984-2010 period are detected for field-or satellite-derived RUE (or residuals), and similar slight differences in the shape of field and satellite RUE (or residuals) temporal profiles are found (see Appendix A).
57, 0. 57, 0. 59 for ANPP field , ANPP sat and rainfall respectively). The second principal component explains 6% of the total variance, and the coefficients (0. 71, -0. 70, 0. 01) indicate that it depicts the differences between ANPP field and ANPP sat. Therefore, over the Gourma region we find no conflict between the RUE approach and the ANPP residuals method, both in terms of temporal trends and when looking at their relationship with rainfall. Both data sources (i. e. , field data and satellite observations) give consistent results, indicating that long-term satellite datasets can be used to monitor RUE (or residuals) over long time periods.
The strongest relationships are usually established when average ANPP is estimated along large climatic gradients. For example, r 2 as high as 0. 89 was reported for climatic means ranging from 200 to 800 mm•yr -1 in North America in Muldavin et al. [56] , or 0. 90 for a 200-1200 mm•yr -1 gradient in Sala et al. [57]. The correlation based on interannual variability is usually much lower (Diouf and Lambin  [36] : r 2 = 0. 41; Evans and Geerken  [30] : r 2 = 0. 50 to 0. 77, depending on the method used to estimate rainfall; Prince et al. [8] : r 2 = 0. 52; Muldavin et al. [56] : r 2 = 0. 56 to 0. 66). Spatial averaging tends to increase the correlation: Nicholson et al. [34]  found a correlation of 0. 85 (r 2 ) between Sahel-averaged NDVI and rainfall, for years 1982-1993. For our dataset, the variance explained by rainfall for both ANPP sat (76%) and ANPP field (77%) is, therefore, in the upper values of the literature range.
Ecosystems Resilience The fact that no trend of RUE or ANPP residuals are found either from field data or satellite data demonstrates the resilience of ecosystems in the Gourma region, at least at that aggregated spatial scale. In other words, no degradation could be detected using these indicators. However, Wessels et al. [32]  suggested that a 30% to 40% decrease in ANPP is needed to be detected with a 16-year-long time series. Here, we used a 23-year-long dataset spanning a 27-year-long period. Similar simulations than the ones performed by Wessels et al. [32]  (not detailed here) suggest that a degradation of 20% to 30% may be detected with our time series, provided they do not occur at the beginning or end of the series. Keeping these limits in mind, we can conclude that in situ observations and satellite-based estimates of ANPP support the conclusions that the pastoral Gourma fully benefited from the rainfall increase over the last three decades, showing a global pattern of vegetation regeneration after the droughts, when the data are spatially aggregated.
Consequently, in situations where local degradation and erosion occur over a small fraction of a landscape, on patches surrounded by otherwise resilient re-greening ecosystems, both a stable RUE and an increasing run-off coefficient can be observed. Since increasing run-off coefficient is observed in many places in the Sahel and since the present study gives more confidence in RUE observed from space, which is often stable  [27] , we propose that divergent indicators of degradation may co-exist in the Sahel as soon as shallow soils are present, especially if their detection is complicated by a typical patch size smaller than the resolution of the remote sensing dataset.
High resolution imagery (such as Landsat or airborne images) could be used to assess whether these eco-hydrological changes are affecting a larger extent of the region. and 0. 72 (Table  A1 ). Yet, the correlations between ANPP and rainfall are higher with rainfall from the in situ network. As a result, it seems that a simple dataset from either the SYNOP stations or the TAMSAT datasets could be used to infer the general patterns of RUE and residuals over the Sahel, albeit with less precision than with dense network gauge data.
Acknowledgments We thank the anonymous reviewers for their in-depth analyses, very valuable remarks and suggestions. This work was funded by  ANR ESCAPE  ( ANR-10-CEPL-005 ) and used data from Service d'Observation AMMA-CATCH and from  DNM Mali. First author was funded by the  CNES  ( Centre National d'Études Spatiales ) and by the  Midi-Pyré né es Region. We thank  Jim Tucker  and  Assaf Anyamba  for making the GIMMS-3g data available, and  Marielle Gosset  for helpful discussions on TARCAT. Finally, we thank all the people involved in the field measurements all over the years.
PROCEDURE Random selection of university students was not possible at the various institutions in Lebanon due to administrative challenges, thus a convenient sample of students was recruited for this study. A trained field worker approached students outside their classrooms during break hours and explained the study objectives. Students who expressed interest and provided their oral consent were handed a self-administered anonymous questionnaire that included questions related to sociodemographic, anthropometric, dietary, and lifestyle behaviors. On average, the questionnaire was completed by participants within approximately 20 min. At the end of the process, the completed questionnaires were placed in closed boxes and sent for data entry. During the data collection process, the anonymity of the students was guaranteed.
ANTHROPOMETRIC DATA Students involved in this study self-reported their weights and heights; however, measurements were conducted by a trained field worker on a subsample of individuals (N = 618) using standardized techniques and calibrated scales. A comparison of self-reported versus measured anthropometrics allowed us to calculate equations for corrected reported weights and heights for males and females. The following equations were used for measuring corrected weights and heights: for males [corrected weight = (1. 003*reported weight) and corrected height = (0. 959*reported height) + 7. 59] and for females [corrected weight = (0. 942*reported weight) + 3. 14 and corrected height = (0. 943*reported height) + 9. 42]. A corrected body mass index (BMI) was subsequently calculated as corrected weight in kilograms over corrected height squared (in square meter).
CHARACTERISTICS OF THE SUBJECTS A total of 3307 university students with complete data were included in the analysis; 60% were females (N = 1969) and the remaining 40% were males (N = 1332). The average age of participants was 20 years, ranging between 17 and 37 years. Differences were detected between male and female university students with respect to their reported income status, distribution between public and private universities, and across various fields of studies. A higher percentage of males were in private universities and reported higher income levels compared to females. Furthermore, a higher percentage of males were classified as overweight or obese, based on the corrected BMI, compared to female university students in our sample (38 versus 10%, respectively, p < 0. 001) (see Table  1 ).
Neutron reflectometry Neutron reflectometry measurements were performed on FIGARO, a horizontal time-of-flight neutron reflectometer at the Institut Laue-Langevin (Grenoble, France). 18 By using a wide wavelength interval, ranging from 2 to 20 Å, and a fixed incidence angle of 0. 621, we probed simultaneously the momentum transfer, q ¼ 4p sin W l (I) from 0. 007 to 0. 07 Å À1. The time-of-flight mode allowed us to follow the change in reflectivity of a deuterated monolayer at the air-water interface simultaneously over the whole q-range with respect to the time of the oxidation reaction. A high flux configuration involving a chopper pair of 7% dl/l, collimation slits of 7% dW/W and a 20 Å frame overlap mirror allowed useful data acquisition times as short as 1 s. The reproducibility of the incident flux was estimated as o0.
g. ref. 32). Based on the estimated volatility of octanoic acid methyl ester, we would also expect this candidate to be lost into the gas-phase. The somewhat lower volatility of nonanoic acid and azelaic acid methyl ester indicate that these compounds could remain on the surface of an aqueous droplet. To determine which products may be produced during the investigated surface reaction, we tested the surface activity of some promising candidates in situ by ellipsometry. Fig. 3  shows ellipsometry data of spread monolayers of nonanoic acid and the methyl esters of azelaic acid and octanoic acid. All three products are shown not to be stable at the air-water interface, i. e. they must be solvated into the aqueous sub-phase or lost to the gas phase. 9-Oxononanoic acid methyl ester is unfortunately not commercially available and is the only previously reported product that could not be tested (compare Scheme 1 and Table  2 ).
Acknowledgements This work was supported by the  Royal Society  (grant no. 2008/R3 ) and  NERC  (grant numbers  NE/G000883/1  and  NE/F007116/1 ). We thank the  Oxford Isotope Facility  for synthesising d-methyl oleate,  Dr Geoff D. Brown ,  University of Reading , for carrying out a detailed NMR analysis of the d-methyl oleate sample, the  Institut Laue-Langevin (Grenoble, France)  for allocations of neutron reflectometry beam time on FIGARO and the NEATNOx studentship funding for FS for this work, the Partnership for Soft Condensed matter for access to the ellipsometer and Brewster angle microscope, and  Simon Wood  for expert technical assistance.
Experimental design Four year-old Q. pubescens saplings were grown into 6 L pots, containing natural soil from a national experimental Downy oak forest (https://o3hp. obs-hp. fr/index. php/fr/). Greenhouses were built with transparent polycarbonate plates (Ombrex) which allowed ,90% of the photosynthetic photon flux density (PPDF) to pass through. Environmental greenhouse conditions (air temperature and relative humidity) were recorded with HOBO devices (U12-012 HOBO data logger, temp/RH/light/ext channel). Water withholding started in April, one week before measurements took place, and stopped late November, during leaf senescence. Saplings were divided into three groups corresponding to three watering treatments: (i) control (C), where saplings were watered to reach and maintain soil field capacity, (ii) mild stress (MS), and (iii) severe stress (SS) where saplings received 20% and 10% of soil field capacity respectively.
Chlorophyll fluorescence Fluorescence was measured on the non-destructive set of plants after isoprene emission collection was performed. Fluorescence of three fully expanded leaves of each sapling was studied and results were averaged. Measurements were performed using a portable Hansatech Fluorescence Monitoring System (FMS 2) allowing computer-assisted data acquisition. The variable to maximum fluorescence ratio (Fv/Fm) was measured in the non-energized state after darkness adaptation of about 30 min using a leaf clip holder for adapting leaves to darkness. Fv/Fm is a reliable indicator of the maximal potential efficiency of excitation capture ) and severe (???e???) water stressed. Note that 70% of isoprene emissions were mostly measured under standard conditions (refer to materials and method for details).