dataesr/scientific-paragraphs-categorization huggingface dataset:
Pharmacokinetics of PHA 543613 Given the lack of data on the pharmacokinetics of PHA 543613, a study to determine the evolution of the concentration vs time in plasma and in brain was performed to choose the most suitable dosing regimen and to confirm the PHA 543613 cerebral diffusion. PHA 543613 concentration was measured with ultra liquid chromatography (UHPLC UltiMate ® 3000 system, Thermo Scientific Dionex TM , Villebon-sur-Yvette, France) coupled with high resolution mass spectrometry (Orbitrap Q exactive TM , Thermo Scientific TM , Villebon-sur-Yvette, France) in the serum and brain of 4 treated rats after one i. p injection of PHA 543613 at a dose of 6 mg/kg. Blood samples from the jugular vein were collected at 0. 5, 1, 3, 6 and 24 h post injection in heparinized tubes. Blood was centrifuged at 2,000 g, for 20 min at 4°C, plasma was removed and then kept at -20°C.
Evaluation of PHA 543613 dose-effect on neuroinflammation using TSPO quantification by autoradiography First we investigated the potential dose-related effect of chronic 4-day treatment with PHA 543613 on striatum expression levels of TSPO. Rodents received either vehicle (n=5) or PHA 543613 at 6 mg/kg (n=8) or 12 mg/kg (n=9) twice a day. In agreement with results previously obtained (see section 3), the density of TSPO binding sites was measured by in vitro auroradiographic experiment using [ 3 H]DPA-714 (specific activity 2. 1 TBq/mmol ; CEA ; Orsay ; France) as described above. A total of 6 sections per brain were analyzed for each rat. Data from brain sections were collected over 4h with the β-imager™ 2000. Specific binding (expressed in cpm/mm 2 ) from 2 ROIs, i. e. , IL and CL striatum were determined.
Images were acquired with Morpho Strider software (Explora-Nova™, La Rochelle, France) on Leica DM 5500B microscope. Neurons and activated microglia cells were counted with Image J software (Rasband, WS, Image J, US National Institute of Health, Bethesda, Maryland, USA) in 3 areas per striatum for each section and in 2 sections per rat in order to obtain a representative sample of the whole striatum. The number of cells was determined for each rat by calculating the average obtained on the 6 analyzed areas for each hemisphere. Counting was performed by 2 independent operators. The percentage of neuronal loss and of increase of activated microglia in ipsivs contra-lateral hemisphere were calculated as follows: IL-CL x 100.
The tips were then coated with nail polish to reduce solution contact area, and thus faradaic reactions, leaving only the tip apex uncovered. The tip potential, E t , was generally near -150 mV vs. Ag/AgCl. The STM was calibrated using HOPG. All glassware and parts were cleaned daily. Aside from EC-STM studies, other electrochemical studies were performed using an automated electrochemical flow cell deposition system (Electrochemical ALD L. C. , Athens, GA). The E-ALD hardware consisted of a flow cell, solenoid valves, solution reservoirs, pumps, relay box and potentiostat, all controlled using specialized "Sequencer 4" software. Solution reservoirs were purged with nitrogen, and valves and tubing were confined in a nitrogen atmosphere. The flow cell was also of a three-electrode configuration.
The raw data were reduced to the rod profiles using BINoculars 56 according to a previously described procedure. 57 he fits were performed with the ROD code. 58 ll solutions were prepared with reagent grade chemicals and ultrapure water (18 M , obtained from a Millipore-Q system, fed with in-house DI water). Blank and germanium solutions contained 0. 1 M or 0. 05 M KClO 4 (Aldrich, 99. 99% trace metals basis). The germanium solutions also contained 1 mM GeO 2 (Alfa Aesar, 99. 999%, metals basis) in addition to the electrolyte. The solutions were pH 4. 2 -4. 7, though no buffer was present. Raman spectra were obtained using a Renishaw InVia Raman microscope (Renishaw, Inc. , Hoffman Estates, IL) with a 514 nm laser.
Acknowledgments Support from the  National Science Foundation , DMR # 1410109 , is gratefully acknowledged, in addition to support from the  National Science Foundation  grant  CHE-1214152  and by the  Gordon and Betty Moore Foundation  ( GBMF1225 ). The research was in part carried out through the  Joint Center for Artificial Photosynthesis at the California Institute of Technology , a  DOE Energy Innovation Hub , supported through the  Office of Science of the U. S. Department of Energy  under Award Number  DE-SC0004993 , which provided support for Y. -G. K. and M. P. S. to perform the EC-STM experiments. We thank  Dr. Resta  from the  Synchrotron Soleil, L'Orme des Merisiers , for his contributions to this work.
We report on our OCaml implementation MightyL and some promising experiments on several benchmarks in Section 6. 2 Timed logics vs (alternating) timed automata Timed languages. Let AP be a finite set of atomic propositions, and Σ = 2 AP. A timed word over Σ is an infinite sequence ρ = (σ 1 , τ 1 )(σ 2 , τ 2 ) • • • over Σ × R + with (τ i ) i≥1 a non-decreasing sequence of non-negative real numbers. We denote by T Σ ω the set of timed words over Σ. A timed language is a subset of T Σ ω. Timed logics. We consider the satisfiability and model-checking problem of Metric Interval Temporal Logic (MITL), an extension of Linear Temporal Logic (LTL) in which temporal operators can be labelled with non-singular timed intervals (or [0, 0], which is the only singular interval we allow). Formally, MITL formulae over AP are generated by the grammar ϕ := p | ϕ ∧ ϕ | ¬ϕ | X I ϕ | ϕ U I ϕ where p ∈ AP and I is either a non-singular interval over R + with endpoints in N ∪ {+∞} or [0, 0].
A comprehensive hydrometeorological dataset is presented spanning the period 1 January 2011-31 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km 2 ) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space-time resolution (∼ km 2 , ∼ min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields.
Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0. 17 to 116 km 2 ) at a time resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling.
Thus, the deployment of multi-scale observation systems over a period of several years in medium catchments and the release of the collected datasets as open data with metadata on how the data have been collected and quality-assured, as well as their associated uncertainties  (Weiler and Beven, 2015) , are of crucial importance to address the current limitations of distributed models. High space-time resolution (∼ km 2 , ∼ min) datasets linking meteorological forcing and hydro-sedimentary response are rare in scientific literature because of the high number and diversity of types of sensors required for measuring rainfall and surface hydrology. The already published datasets consist of first-order catchments ("Tarrawarra data set", southeastern Australia:  Western and Grayson, 1998) , catchments where the observation period is exceptionally long ("Reynolds Creek Experimental Watershed", northwestern USA:  Slaughter et al.
, 2001 ; "Walnut Gulch Experimental Watershed", southwestern USA:  Renard et al. , 2008; Stone et al. , 2008 ; "Goodwater Creek Experimental Watershed and Salt River Basin", midwestern USA:  Baffaut et al. , 2013) , or catchments located in snow-dominated mountains ("Reynolds Creek Experimental Watershed", northwestern USA:  Reba et al. , 2011 ; "Dry Creek Experimental Watershed", northwestern USA:  Kormos et al. , 2014). In mesoscale catchments, such datasets are scarce ("Walnut Gulch Experimental Watershed", southwestern USA:  Goodrich et al. , 1997; "Iowa River  Basin", north central USA:  Gupta et al. , 2010) , especially in the Mediterranean region. This study is part of the FloodScale project  (Braud et al. , 2014) , which is a contribution to the HyMeX programme (Hydrological Cycle in the Mediterranean Experiment,  Drobinski et al.
The FloodScale project  (2012) (2013) (2014) (2015)  fits into the EOP and encompasses SOP1  (Ducrocq et al. , 2014) , which took place from 5 September to 6 November 2012 and was dedicated to heavy precipitation and flash floods. This study focuses on nested scales that range from the hillslope to the medium catchment scale, all belonging to the Cévennes -Vivarais Mediterranean Hydrometeorological Observatory (OHMCV)  (Boudevillain et al. , 2011). It is located in Ardèche, in a region with a high gradient in annual rainfall (e. g. Molinié et al. , 2012 ). The observation system was operated by different teams from various countries during SOP1 and the EOP: IGE, IRSTEA Lyon, EPFL, Wageningen University, LaMP and Météo-France. The dataset includes precipitation and weather data, soil moisture data, runoff and soil erosion data, hydrologic and suspended sediment response data, surface water quality data, and GIS data.
This allows documenting the upper ends of stagedischarge rating curves that are generally extrapolated at high values. The paper presents the acquired datasets to make them accessible to the scientific community and make their use easier and wider. The authors are convinced that the published datasets can serve as a benchmark for hydrological distributed modelling applied to the Mediterranean area. The paper is organized as follows. Section 2 presents the location of the studied catchment and its context (geology, climatology, land use, pedology). Section 3 describes the observation system (instruments and measured variables) and is organized into three subsections: (i) hydrometeorological data, (ii) spatial characterization data, and (iii) hydrological and sediment data. Finally, in Sect.
This offers the opportunity to address the issues of the definition of the scales of variability in rainfall and the origins of this variability that are still open questions within the hydrometeorological community  (Fraedrich et al. , 1993; Fabry, 1996; Krajwesky et al. , 2003). The rain gauges are distributed over 11 main locations with a mean interdistance of about 2 km. At some locations, several rain gauges are clustered with interdistances of 10 to 500 m as seen in the inset maps of Fig. 4. All rain gauges are identical and consist of a Précis Mécanique tipping bucket of 0. 2 mm (model 3039) with a collecting area of 1000 cm 2. Each rain gauge is connected to a HOBO or Campbell data logger. A first step of the data quality control consists of comparing the total rain amount recorded by the tipping bucket-HOBO system with that collected at the outlet of the rain gauge with a 30 L plastic tank.
Other meteorological data Most of the meteorological variables originate from one of the operational surface observing networks of Météo-France. Six stations are located in the Auzon catchment or its close vicinity. All of them continuously provide hourly measurements. The measured variables at each station differ depending on the network to which each station belongs. There are four types of networks for Météo-France stations present in this study: the "aeronautical synoptic" network (including LANAS-SYN), the RADOME-RESOME network with automatic stations also known as the Automated Regional Network (including BERZEME-RAD), the network of automatic stations surveyed in real time (including ALBA-SA and ESCRINET) and the network of automatic stations examined in delayed time (including AUBENAS-SA et MIRABEL-SA).
Spatial characterization data Characterization data are used to define the topography, pedology, geology, land use, landscape and hydrological properties of the Auzon catchment. These data provide the fine-scale detail required for modelling and hydrological assessment. The coordinate system of reference used in this study is the Réseau géodésique français (RGF) 1993 (official in France, based on IAG-GRS80 ellipsoid, very similar to WGS 84). The projection is Lambert conique conforme. Table  3  presents the main GIS descriptors available for the region of interest in this study.
GIS descriptors For the Claduègne catchment, a 1 m bare-earth digital elevation model (DEM) was derived from an aerial lidar dataset acquired in 2012 and processed by Sintégra  (Braud et al. , 2014). For the Auzon catchment, the 25 m DEM released by IGN France in 2008 is available. A combination of these two latter DEM was performed using ArcGis based on re-sampling and interpolation to produce a 5 m DEM over the Auzon catchment from which the catchment boundaries were derived using TAUDEM D8 incorporated in ArcGis. A map (scale 1 : 50 000) of the geology of the region including the Auzon catchment was released by the Bureau de Recherches Géologiques et Minières (BRGM) in 1996 and digitalized in vector format from 2001  (Elmi et al. , 1996). A map (scale 1 : 100 000) of the pedology of the region including the Auzon catchment was released by INRA  (Bornand et al.
, 1977). In addition, the Ardèche soil database at scale 1 : 250 000 produced by Sol-Conseil and Sol Info Rhône Alpes provides a vector map of the region synthesizing a large amount of information on soil (soil class and unit, horizon, thickness, etc. ) and bedrock. Very high resolution images were acquired and processed to provide detailed land use maps: 5 m resolution satellite images (QuickBird images) taken in 2012 for the Claduègne catchment and 30 m resolution satellite images (Landsat) taken in 2013 for the Ardèche catchment. The orthophotography database released by IGN France in 2009 provides aerial images of the Auzon catchment at a resolution of 0. 5 m. In addition, vector data of the drainage network, catchment boundaries, instrument locations, administrative boundaries and road network are available.
Hydrological and sediment data Almost all the instruments deployed in the field to measure the soil and surface water compartments were installed for research purposes. There was virtually no hydrological observation before 2011 in the Auzon catchment, except the water erosion plots and a site for soil moisture measurement (SMOSMANIA network). Most of the instruments were installed in the framework of the FloodScale project and the HyMeX EOP  (2011) (2012) (2013) (2014). The instruments are located mainly in the Gazel and Claduègne sub-catchments (Fig. 3c ), where it was decided to put the major efforts.
At the Gazel and Claduègne stations, different physico-chemical variables of the surface water are measured continuously: temperature, conductivity and turbidity. Generally, for all inter-flood periods (marked by very low turbidity) the turbidity value was set to 0 during the procedure of data quality control even if there was a value different from 0 in the raw data. Indeed, the turbidimeters used in this study are designed for a high turbidity range (typically 1000 to 10 000 ppm) and are not capable of accurately measuring low turbidity (typically less than 50 ppm). Sequential samplers, triggered by the data logger, collect water and suspended sediment samples when threshold values of water level and turbidity are exceeded. The suspended sediment concentration (SSC), which represents the mass of solid divided by the volume of liquid (expressed in g L -1 ), is estimated by measuring the volume    allows for the index velocity method to be applied  (Levesque and Oberg, 2012).
A sequential sampler containing 24 bottles of 1 L capacity sampled water and eroded particles within the H flume. When critical thresholds of water depth or water depth variation were exceeded, the data logger triggered the sampling of water and eroded particles. Thus, the time intervals between each two samples were irregular, depending on the shape of the hydrograph. SSC were estimated following the procedure given above in the section "Hydrometric stations". While the discharges were available continuously, the sediment fluxes were only calculated for the times where SSC values were available. Many samples were analysed using a laser diffraction particle size analyser (Malvern Mastersizer/E) to characterize the particle size distribution. More details about the description of the plots, the topographical data available, and the monitored runoff and erosion events are given by  Grangeon (2012)  and  Cea et al.
Areal rainfall estimation Areal rainfall estimations are important for water budget assessment and the understanding of the internal catchment behaviour. Geostatistical techniques (rain gauge ordinary kriging, as well as merging of radar and rain gauge data through kriging with external drift) were used to obtain quantitative precipitation estimates (QPEs). The uncertainty of these QPEs was calculated using the methodology presented by  Delrieu et al. (2014). The QPEs were produced for a wide range of spatial and temporal resolutions (15-360 min, 1-300 km 2 ) for a 30 km× 32 km window encompassing the Auzon catchment in order to assess the effect of adding highresolution rainfall data on the quality of the QPE for small scale hydrology applications. Rainfall estimates and error structure were compared for four scenarios with varying rain-fall datasets (operational rain gauges, operational + research rain gauges, operational rain gauges + radar, all data) for the 25 largest rainfall events of 2012 and 2013.
8 ). Figure  6a  and b illustrate the added value of radar data to capture the spatial structure of rainfall even if, as for this case study (Fig. 6c  and d ), QPE error standard deviation may be sometimes larger than for ordinary kriging. Boudevillain et al. (2016)  showed that, in general, QPE errors are significantly reduced with the technique of kriging with external drift. The data presented in this section are made available in the public dataset associated with this paper.
Improvement in the quantification of flood hydrographs and reduction of their uncertainty The Gazel-Claduègne-Auzon experimental data were also used to develop a methodology to quantify and reduce the uncertainty of flood hydrographs. This methodology is based on the non-contact stream gaugings performed during the onalert campaigns (see "Hydrometric stations" in Sect. 3. 3. 1) and on the BaRatin framework  (Le Coz et al. , 2014). At the Auzon hydrometric station, during the 2014 campaign, 11 LSPIV gaugings could be performed through the automated station. They were completed by 10 SVR gaugings. These   gaugings have higher uncertainties than the traditional dilution or velocity-area methods, but have the advantage of being feasible safely even under hazardous, high flow conditions. These gaugings were incorporated as observations in the BaRatin methodology, which was further developed by adding the propagation of stage uncertainty and rating curve uncertainty to discharge time series  (Horner, 2014; Branger et al.
Distributed physically based soil erosion modelling The impact of model simplifications on soil erosion predictions was tested by applying the GLUE methodology to a distributed event-based model at the hillslope scale  (Cea et al. , 2016). In this paper the authors analysed how the performance and calibration of a distributed event-based soil erosion model at the hillslope scale is affected by different simplifications on the parameterizations used to compute the production of suspended sediment by rainfall and runoff. Six modelling scenarios of different complexity were used to evaluate the temporal variability in the sediment flux at the outlet of a 60 m long cultivated hillslope. The six scenarios were calibrated within the GLUE framework in order to account for parameter uncertainty, and their performance was evaluated against experimental data registered during five storm events.
Data availability As an example of the kind of data made available in this paper, Fig. B1  in Appendix B shows an overview of rainfall, discharge and turbidity for the entire record (period 2011-2014) at the Claduègne hydrometric station. The measurement period is characterized by a wide variety of water conditions: a dry year in 2012, a wet year in 2014 and an intermediate year in 2013, as well as some intense rainfall events in spring 2013, autumn-winter 2013-2014 and autumn 2014. Note that the 4 November 2014 flood is a 5-10-year return period flood for the Claduègne River (this return period was roughly estimated from archive photos and interviews with residents and farmers who live and work near the river). All the public datasets presented in this study are listed in Tables  5  and 6.
In addition, all the datasets under the "associated scientists" status of the HyMeX data policy (http://mistrals. sedoo. fr/HyMeX/Data-Policy/ HyMeX_DataPolicy. pdf) presented in this study are listed in Table  7. Data collected by a specific instrument and a network of instruments are listed in Tables  5  and 7 , while the GIS descriptors are listed in Table  6. This granularity, also chosen for the DOI attribution (see the column "DOI" in Tables 5, 6, and 7), enables each individual dataset to be associated with a principal investigator who is very familiar with the data and who will be an essential resource for any user in case of need. The added-value dataset corresponding to the results of the rainfall re-analysis (QPE) for the   (Boudevillain et al. , 2016)  based on the merging of operational radar and rain gauge data has been added to Table  5  as it represents a useful dataset for many hydrological studies.
All the individual datasets listed in Tables 5, 6, and 7 have a specific metadata record (see URL links in corresponding tables) in the HyMeX Database (http: //mistrals. sedoo. fr/HyMeX/) maintained by the ESPRI/IPSL and SEDOO/Observatoire Midi-Pyrénées in France. The metadata record includes many fields, amongst which the dataset name, the period of observation, the principal investigator in charge of the dataset, a description of the data, the geographic coordinates of the instruments, a description of the instruments and the measured variables, the format of the data and the status of the data. The metadata record also has a "data access" section. For the public datasets (Tables  5  and 6 ), a simple registration (name, affiliation, email) is necessary to create an account (http://mistrals.
sedoo. fr/User-Account-Creation/). This simple registration generates an automatic e-mail with login and password which enables direct access to public data. For the additional datasets under "associated scientists" status (Table  7 ), the validation of the HyMeX data policy (http://mistrals. sedoo. fr/HyMeX/ Data-Policy/HyMeX_DataPolicy. pdf) is necessary to access the data. There are two options. 1. (1) The user had registered previously for access to public data only. In this case, he/she must go to his/her account (http://mistrals. sedoo. fr/Your-Account/) and complete the HyMeX registration application.