dataesr/scientific-paragraphs-categorization huggingface dataset:
By using investigator triangulation to compare and agree researchers' interpretations, each set of expanded field notes became the work of multiple researchers, thus helping reinforce the validity of the results reported. In addition, researchers from the United Kingdom and the three study countries attended an analysis workshop to reach consensus on interpretations and cross-country comparisons. Systematic analysis of the expanded field notes was conducted using a framework approach to code a priori themes and identify emerging themes in NVivo10 as we sought to examine the actions and factors that catalysed scale-up and the contextual factors enabling and undermining it. Aid effectiveness issues emerged in our data analysis which we related to key principles of aid effectiveness. The emerging themes were categorised by two researchers, separately, using an inductive analytic framework based on the aid effectiveness principles.
Acknowledgements We would like to thank the country researchers in Ethiopia, India, and  Nigeria , who contributed to the data collection for this study. This study was supported by  IDEAS -Informed Decisions for Actions  to improve MNH (http://ideas. lshtm. ac. uk), which is funded through a grant from the  Bill and Melinda Gates Foundation, USA  to the  London School of Hygiene & Tropical Medicine, London, UK. (Gates Global Health Grant Number:  OPP1017031 ).
Sample and data collection Blood samples from 151 dogs were randomly collected from pet clinics in Lahore (N = 50); Rawalpindi/Islamabad (N = 50) and Multan (N = 51), districts of Punjab, during June-December 2014 All of the dogs included in the study were pets, except for stray dogs (N = 2), and informed consent was obtained from pet owners before enrolling them in the study. Sampled dogs included healthy animals as well as those having clinical symptoms including fever (diagnosed with thermometer) pale mucus membrane, haematuria and vomiting (physical examination). Blood samples were collected from the saphenous vein of the animals and immediately preserved in EDTA tubes. A questionnaire was filled at the sampling site in order to gather data (including age, sex, breed, body temperature, deworming, vaccination, mucous membrane status, hydration status, the presence of haematuria and tick infestation) and to report risk factor(s) associated with the prevalence of E.
Acknowledgements This study was supported by the  AMIDEX  project (No. ANR-11-IDEX-0001-02 ) funded by the " Investissements d'Avenir" French Government program , managed by the  French National Research Agency (ANR)  and  Foundation M editerran ee Infection  (www. mediterranee-infection. com). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Authors are grateful to pet owners and venetians who helped us in blood sample collection.
Areas of guidelines Three areas related to HAP were: prevention, diagnosis and treatment with population-specific considerations. Four relevant specific populations were considered in the guidelines analyses (COPD, neutropenia, postoperative and pediatric). An extensive literature research over the last 10 years was conducted based on publications indexed in PubMed TM and Cochrane TM databases. To be considered for analysis, publications had to be written in English or in French. It was decided ahead of the analysis to limit the number of expert opinions and to not produce recommendations that are not supported by literature. The analysis was focused on recent data, according to decreasing hierarchical prioritisation of data from meta-analyses of randomised controlled trials (RCTs) or individual RCTs to observational studies.
R3. 5 -We recommend not prolonging for more than 7 days the antibiotic treatment for HAP, including for non-fermenting Gram-negative bacilli, apart from specific situations (immunosuppression, empyema, necrotising or abscessed pneumonia). GRADE 1À, STRONG AGREEMENT Evidence summary and rationale for the recommendation: There are two meta-analyses comparing treatment durations of 8 days or less to 9 days or more  [128, 129]. Data are only available in the area of VAP. The first of these meta-analyses relies on six RCTs, including a meeting summary, which was not reported here  [130] [131] [132] [133] [134]. This meta-analysis included 508 patients. Mortality (28-day, ICU and hospital), length-ofstay and of mechanical ventilation did not change according to treatment duration. Patients in the short-course group had a mean increase in antibiotic-free days at day 28 of 4.
Each substance is assigned a permanent computer checkable registry number that identifies it in the CAS database and links it to the structure record, the names used for the chemical in the literature, and its Chemical Abstracts index name. Brought to you by | Washington University in St. Louis Authenticated Download Date | 9/22/18 5:43 PM CAS numbers are intended to provide a unique, unmistakable identifier for chemicals. However, a chemical will have different CAS numbers assigned to analogues containing isotopic labels. A stereoisomer will also have a different CAS number from that of an isomeric mixture (whether racemic, scalemic, or comprising other stereoisomers, e. g. epimers or diastereomers). The following examples illustrate the ambiguity that could arise  [14] : (a) The nitrogen mustard bis(2-chloroethyl)methylamine (1) (HN2) is listed in Schedule 1.
Acknowledgements: The SAB thanks Ambassador Ahmet Üzümcü for supporting the Board and providing its output to States Parties to inform their decision making. The SAB expresses its gratitude to Dr. Sarah Clapham, Dr. Jim McGilly and Mr. Matthew Brooks of Dstl, and to Mr. Terry Dance and Mr. Craig Wallbank of the UK National Authority in BEIS, for information and helpful feedback, especially on the change of licensing of scheduled chemicals in the UK. The SAB also acknowledges Ms. Marlene Payva, for her skillful assistance to the Board, the European Union for providing funding for activities of the Board, and the International Union of Pure and Applied Chemistry for its support during the run-up to RC-4 and the three Review Conferences held previously, to which it provided substantial scientific input  [67] [68] [69].
Data The data are from the three waves of the French component of the Generations and Gender Programme 2 survey (10,079 participants between the ages of 18 and 79 in Wave 1, 2005; 6,534 of these participants in Wave 2, 2008; 5,436 of these participants in Wave 3, 2011). The survey was designed specifically to examine key lifecourse events that affect relationships between parents and children and between partners. These events include the birth of children, partnership formation and dissolution, the transition to adulthood and economic activity. The sub-sample selected for this analysis includes 2,016 respondents who participated in all three waves 3 in the birth cohort  1941-1960, i. e. between the ages of 45 and 64 at Wave 1 in 2005. The lower limit of 45 in Wave 1 corresponds approximately to that of an 'ageing worker' in the sense that age discrimination, such as a lack of training and the difficulty of re-finding a job after a spell of inactivity are accentuated (see  Lössbroek and Radl, 2019).
Data From June 6th, 2015 (BJD=2457180. 5) to June 21st, 2017 (BJD=2457925. 5), we collected 128 observations with the HARPS spectrograph  (Mayor et al. 2003; Pepe et al. 2004 ), including the 25 measurements already published in  Berta-Thompson et al. (2015). We chose the high-resolution mode (R=115'000), used the scientific fiber for the target and the calibration fiber for the sky. In practice, sky brightness is low enough and the second fiber is not used by our pipeline. It only serves as a potential a posteriori diagnostic. Exposure times were fixed to 40 minutes, except for one exposure on June 26th, 2016 (BJD=2457566. 5) which was shortened to 1700 sec. Also, note that we discarded a 90th measurement otherwise found in ESO archives. It was just 5 sec and taken on June 11th, 2015 (BJD=2457185.
This choice of prior was modified and not found to significantly affect the results. The eccentricities e of each planet were sampled indirectly via the jump parameters h = √ e cos ω and k = √ e sin ω where ω is the argument of periastron, a choice that reduces bias toward high eccentricities  (Ford 2006). Next, we conduct a model comparison using timeseries cross-validation  (Arlot & Celisse 2010) ; a computationally less expensive procedure than computing the fully marginalized Bayesian likelihood and one that is independent of the choice of model parameter priors. The unique model parameters for each model-including the GP hyperparameters-are optimized on each of the 107 training sets which contain between 20 and the full dataset size, less 1 (i. e. 127), chronologically-spaced RV measurements.
For each split of the data the testing set is the single measurement taken after the final measurement in the training set. The lnlikelihood (ln L) of the testing data given each model optimized on the training set are then computed. Over the 107 splits of the data we compute the median and median absolute deviation per measurement of each model's ln L. Table  1  reports the resulting ln L ratio for various pairs of competing models where each model's ln L is calculated by scaling the median ln L per measurement from cross-validation to the full dataset size of 128 measurements. We find that the 3 planet model is greatly favoured over the 2 planet model with a > 8σ greater ln L. Furthermore the 3 planet + GP model has a marginally better ln L to the 3 planet model (i. e. 0. 3σ higher ln L).
Acknowledgements. We are grateful to our referee for comments that significantly improved our manuscript. XB, JMA and AW acknowledge funding from the  European Research Council  under the  ERC Grant  Agreement n. 337591-ExTrA. RC and RD acknowlege financial support from the  National Research Council of Canada  and the  Institute for Research on Exoplanets. NCS acknowledges the support by  Fundação para a Ciência e a Tecnologia (FCT, Portugal)  through the research grant through national funds and by  FEDER  through  COMPETE2020  by grants  UID/FIS/04434/2013&POCI-01-0145-FEDER-007672  and  PTDC/FIS-AST/1526/2014&POCI-01-0145-FEDER-016886 , as well as through Investigador FCT contract nr. IF/00169/2012/CP0150/CT0002. JAD gratefully acknowledges funding from the  Heising-Simons Foundation 's 51 Pegasi b postdoctoral fellowship.
The  MEarth Team  gratefully acknowledges funding from the  David and Lucille Packard Fellowship  for Science and Engineering (awarded to D. C. ). This material is based upon work supported by the  National Science Foundation  under grants  AST-0807690 ,  AST-1109468 ,  AST-1004488  ( Alan T. Waterman Award ), and  AST-1616624. E. R. N. is supported by an  NSF   Astronomy and Astrophysics Postdoctoral Fellowship. This publication was made possible through the support of a grant from the  John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the  John Templeton Foundation. This research has made use of the  NASA Exoplanet Archive , which is operated by the  California Institute of Technology , under contract with the  National Aeronautics and Space Administration  under the  Exoplanet Exploration Program.
AOD retrieval AOD is defined as the negative natural logarithm of transmission, normalized to the vertical path length, m = 1, through the atmosphere; its error becomes proportional to the relative error in calibration and inversely proportional to the length m of a slant path. The current GAW specification  (WMO, 2005)  calls for an AOD uncertainty of 0. 005 ± 0. 01/m, thus requiring a calibration uncertainty of 1 %. This specification is similar to the uncertainty required for satellite AOD retrievals of 0. 015 over land and of 0. 010 over the ocean in order to make a meaningful statement concerning the aerosol climate effect  (Chylek et al. , 2003). Measurements of solar irradiance were nominally taken each full minute by the participant's data acquisition systems, typically yielding 500 observations per cloudless day.
The number of instruments that submitted AOD retrievals for each of those wavelengths is summarized in Table  2. Ångström exponents were derived from optical depths at 500 and 865 nm (29 instruments). Values of atmospheric pressure, precipitable water, relative humidity and temperature readings were made available to all participants by the MeteoSwiss weather station located at PMOD/WRC with a 10 min resolution. Total ozone column content measured with a double Brewer spectroradiometer at PMOD/WRC was available as well. This common auxiliary database was available to all participants in order to avoid AOD-related discrepancies introduced by uncertainties linked with the abovementioned parameters. Several of the participating radiometers were calibrated at various sites within a few months prior to FRC-IV.
MFRSR instruments. SURFRAD network MFRSRs are calibrated on site using a robust estimate for V 0 s from Langleys based on at least 1 month or more of data in representative conditions  (Augustine et al. , 2003). MFR_US_2 and MFR_US_3 were calibrated using only the data from the FRC-IV; MFR_US_1 and MFR_DE_1 also used the data from FRC-IV for calibration following slightly different modified procedures to determine V 0 s because of the short duration of the campaign. SPO2 instruments. The Australian Bureau of Meteorology SPO2s (Middleton Solar) were removed from a highfrequency clear-sun Australian (Longreach) station where they were calibrated in situ for 2 years using the methods described in  Mitchell et al. (2017) , prior to participating in the FRC. PSR instruments. PSR instruments were absolutely calibrated at the PMOD/WRC laboratory during the campaign.
In order to retrieve the AOD, an absolute extraterrestrial solar spectrum is used. Microtops instrument. The instrument was calibrated by direct comparison with a calibrated Cimel/AERONET instrument from June to August 2015. COFOVO instruments. The four instruments are calibrated through direct comparison with the National Renewable Energy Laboratory (United States) secondary reference spectroradiometer  (Tatsiankou et al. , 2013). AOD is retrieved by matching absolute irradiances at the six measuring wavelengths with a radiative transfer model. During the intercomparison, AOD data delivered by the operators of the participating radiometers were evaluated using common comparison software. The comparison was based on AOD results only, as each operator/group used their own algorithm normally used for standard radiometer operation.
4 ). Correlation coefficients (CCs) among the triad and all other instruments were better than 0. 9 for all instruments and wavelengths, with the exception of three instruments, only at 865 nm. In the case of the Cimel, PFR and POM, CCs were higher than 0. 98 in all cases. The normalized standard deviation in Fig. 4  describes the instrument-measured AOD variability compared to that of the reference (triad). Most of these ratios were well within the 0. 8 to 1 area, with the exception of a single PFR instrument, which provided data for only one comparison day. Overall, statistics at 368, 412 and 500 nm showed an excellent agreement for all instruments, while at 865 nm the instrument scatter within the Taylor diagram space is higher. However, the agreement can still be considered quite good, as seen when examining Fig.
Cloud flagging The FRC campaign was a unique opportunity to compare the different cloud-screening algorithms used by each instrument/group. McArthur et al. (2003)  reported on instrument/network-related cloud-flagging differences using measurements from a 3-month campaign. The use of such algorithms can lead to significant differences, while the selection of threshold values to filter out the retrievals could lead to large deviations when comparing AOD retrievals from instruments with different cloud-flagging algorithms. For our comparison, we have used one of each of the main types of instruments and compared the number of available retrievals (PFR, POM, SPO, MFR and Cimel instruments). More specifically, we have chosen to examine the instruments of each type with the larger dataset on these 5 days.
MFR. The technique used for MFRs is described in  Michalsky et al. (2010). A coarse filter is used on 10 min of data; this examines differences first from the 20 s sample to the 20 s sample and then over the entire 10 min interval. This is followed by a second similar filter but using allowance of variability that is scaled to the approximate value of the AOD. If the 10 min span passes both tests, the test is repeated after advancing one 20 s sample. Duplicate points from processing all of the data are discarded. We have used the tool developed by  Heberle et al. (2015)  to visualize the coincidence of the instrument datasets that provided 1 min AOD (SPO, MFR, PFR and POM) by plotting Venn diagrams (Fig. 7 ). Cimel instruments were not included due to the lower AOD-measuring temporal resolution.
All instruments only detected cloudless conditions during 25 % of the common measurements. The SPO seems to have the most values that do not appear in common with other instruments (4. 9 % solo, and 18 % in common with only one other instrument) and the POM the least (0. 1 and 0. 8 %). When considering measurements defined as cloudless from at least three out of four instruments, the SPO has the largest number of coincident measurements (69. 9 %) followed by the PFR (69. 2 %), MFR (59. 9 %) and POM (36. 3 %). The POM has the smallest dataset, only retrieving AOD from 40 % of all possible (at least one instrument provided cloudless AODs) measurements. In order to investigate measurements when only one instrument provides cloud-free minute measurements while all other instruments are marked as cloud-flagged (as an example in Fig.
AOD retrieval differences For the present intercomparison, no common procedures were used for the removal of gas-phase constituents or Rayleigh scattering; cloud screening, solar position, timing and calibration methodology were at the discretion of the network operators. Datasets from each sun photometer network were corrected for these factors independently. Figure  9  identifies some of the possible discrepancies that may result when considering NO 2 , ozone, Rayleigh scattering, other trace gases and H 2 O in the atmosphere  (Thome et al. , 1992)  at 500 and 870 nm during FRC-IV. One reference day (30 September 2015) was chosen for this comparison exercise. The slant optical thicknesses of various trace gases and Rayleigh scattering were obtained from Cimel, PFR, POM and SPO instruments and individually compared.
, 1999, for  Cimel; custom set of ozone coefficients for SPO) were adopted. The Rayleigh scattering coefficients by  Bodhaine et al. (1999)  are used by all networks except SPO, which used those by  Bucholtz (1995). Pressure was measured (845. 7 hPa) by the PFR control box, while it was fixed and corrected for altitude (z) for the POM (840 hPa) using the following formula:  (1) Finally, water vapor is only taken into account by POM instruments using a fixed value for the summer season and additionally corrected for altitude using the following formula based on data in  Gueymard (1995) : w = 2. 9816 • exp(-0. 552 • z), (2) where w is the precipitable water in centimeters and z is the altitude in kilometers. The method for deriving the corresponding H 2 O optical depth is also adopted from  Gueymard (2001).
AOD differences of about 0. 01 at 500 nm that can be easily related to the instrument calibration uncertainties can considerably affect such calculations during low AOD conditions. Hence, this campaign reaffirms that for cases of mean AOD 500 < 0. 1, the calculation of AE becomes highly uncertain. Investigating the sources of differences among different instruments, we compared all parameters included in the AOD retrieval algorithm as provided by the different participating institutes. All individual differences (Rayleigh, NO 2 , ozone, water-vapor-related optical depths and air mass calculations) amounted to less than 0. 01 in AOD at 500 and 865 nm. Different cloud-flagging algorithms can affect the AOD datasets as different instruments/networks use different techniques. During a day with sporadic appearances of high and mid-level clouds (which was deliberately chosen as a "difficult" task for such algorithms), results from different cloudflagging algorithms limited the AOD comparison datasets between two instruments from 40 to 90 %, depending on the pair of instruments used, compared to the maximum number of cloudless data points calculated by all instruments.
As AOD from algorithm differences was quite small, the results of the comparisons of this instrument group are considered to have been very successful as differences are in most cases well within the calibration and overall instrument AOD uncertainties. The rest of the instruments also showed reasonable agreement with few exceptions. MFR instruments experienced additional uncertainties concerning the diffuser-based measurements. SIM instruments also performed quite well when considering the radiative-transfer-based processing algorithm. In addition, spectral-AOD-retrieving PSR instruments also performed well, especially at the two higher wavelengths. Finally, Microtops AOD data were in most cases within reasonable agreement with the reference triad but additional technical issues such as the handheld-based sun-pointing and the smaller integration time (compared with other instruments) of the direct sun measurement led to enhanced scatter of the results.
Detailed morphological descriptions of each site have been performed in order to identify the main drivers that determined their formation and degradation. These microanalyses are completed by the characterisation of the palaeoenvironmental records and other geomorphological proxies from the surrounding areas. The aim of the geomorphological analysis of the rockshelters lies in determining the varied origins and the evolutionary processes of their deposits, as well as establishing a basic typology and the extent to which their conservation and visibility is possible. These data are important to determine the distortion that the conservation/disappearance of deposits can create in the available information. As well as in archaeology, an important effort in the study of palaeoenvironmental sequences covering the Late glacial and the Early-Mid Holocene has been performed for the Ebro Basin and the Pyrenees during the last decades  (Aranbarri et al.
These sequences cover all the different biogeographical regions within the study area. The chronological evaluation analysis has been performed using a reference database including 425 14 C dates that span from 5000 to 13000 BP (5650 to 15750 cal BP) from 80 archaeological sites. It has been compiled by means of an exhaustive bibliographical search. The only selection criterion considers their accuracy: a standard deviation of less than a century was required. Despite the lack of anthracological determination for most of the dated samples in our database, we believe that the debate surrounding short life vs. long life samples is no longer relevant in this case  (Barceló, 2008; Williams, 2012; Drake et al. , 2016). The correlation coefficient of charcoal vs. other material samples in our database is 0.