dataesr/scientific-paragraphs-categorization huggingface dataset:
Reinterpretation of de Wilde's dataset emphasizes the large proportion of uninterpretable results, as more than half of the recorded changes were considered to be uninterpretable. Future validation studies will need to include a large cohort of patients to increase the number of interpretable points. Moreover, physicians should consider previous published studies with caution, emphasizing the importance of sharing study data in order to reanalyze data by means of new methods. [18] Finally, a more rigorous approach would be to exclude uninterpretable changes from the analysis, but if a study presents an excessively high proportion of uninterpretable changes, these changes could be reinterpreted by a complementary analysis. The degree of overlap between reference values (+/À RM Â RC) of the change might be used to estimate the uncertainly of the change.
Our data comprise imaging (primarily in the R-band) to monitor the evolution of Notes. ( a) OK refers to the number of images good for photometry -those clear within the ρ = 10,000 km aperture in difference images (see text). the coma and the total brightness of the comet and regular spectroscopic observations covering the UV and optical range, which are sensitive to the stronger comet emission bands (e. g. CN). The campaign includes observations from many telescopes 1 , but the largest data set in 2014, while the comet was faint and in southern skies, comes from the ESO VLT. Further observations were made using Gemini South and the Las Cumbres Global Telescope Network (LCOGT) robotic telescopes. Additional results on dust photometry, using observations with the Nordic Optical Telescope (NOT), were published by  Zaprudin et al.
Grism 150I (central wavelength λ c = 720 nm) was used, which gives a broad wavelength coverage (330 -1100 nm) and low resolution (R = 260). From June onwards deeper spectroscopic investigations were performed in visitor mode. Grism 300V (λ c = 590 nm) was used to gain slightly higher resolution (R = 440), and therefore improved S/N in emission bands, when it was clear that the comet was bright enough to get a strong detection of the continuum. The observation geometry for each run is given in table 2. The slit width for all comet spectra was 1. 31. The slit was aligned with the parallactic angle. Solar analogues were also observed during each run, although subtle differences between the different stars observed were noted during the data reduction. To have a uniform data set, the final reduction used average spectra of the solar analogue star HD148642 for the grism 150I data and of asteroid (5) Astraea for the higher resolution data.
Gemini -FLAMINGOS-2 Gemini South was also used for near-infrared (NIR) imaging in JHK s filters, also regularly spaced through the second half of the 2014 visibility window. All NIR data taken each night and in each filter were combined to produce single stacked images of the comet, as it was still relatively faint for imaging at these wavelengths (hence the need for the 8m red-sensitive Gemini telescope). The observing geometry for all Gemini data is given in table 3.
LCOGT Towards the end of the 2014 visibility window we began longterm monitoring programmes using robotic telescopes, primarily to establish a baseline for comparison with the 2015-6 data when the comet would be brighter. The LCOGT network has a unique capability of 24-hour / day coverage of the sky, for well placed targets, and is made up primarily of 1m telescopes deployed in groups of three. For observations of 67P in 2014 we used the southern sites in Chile, Australia and South Africa. While the visibility of the comet was extremely limited from any one site, with the network we could get short observations every 8 hours, weather permitting. Observations from LCOGT ran from October 2nd to 19th and from November 5th to 18th, totalling 518 exposures. Each visit performed two 120s exposures in each of the SDSS griz filters.
Visible data -FORS All visible wavelength imaging observations were reduced using IDL packages from the DanIDL software suite 2  , which perform basic bias subtraction and flat fielding and also allow more advanced steps, such as DIA  (Bramich 2008; Bramich et al. 2013). DIA methods were necessary for the data on 67P taken in 2014, as they were in previous years  (Snodgrass et al. 2013) , due to the crowded star field that the comet was seen against. Where possible, a background template (or reference image) of the field for each night was taken later in the year (i. e. without the comet) to provide subtraction of stars. In some cases this was not possible, especially late in the observing season, in which case one of the images taken on the same night has to be used as the background template, meaning that this template image and images close in time to it are not useful for comet photometry as the comet and its negative imprint from the template image overlap.
In the September data set the K-band data does appear to contain some remaining flux from a background star, resulting in an over-estimation of the brightness of the comet in that instance. Apertures of radius 5 pixels (0. 9 ) were used for all NIR data, which gave a good balance between collecting all the flux from the comet (the frames have a seeing with FWHM ∼ 2-3 pixels) while avoiding remaining background stars. The use of 2MASS stars in the field, also observed with a 5 pixel radius aperture, includes an implicit aperture correction in the calibration. The use of such aperture corrections in calibration (technically only appropriate for point sources) is justified as the comet 3 http://www. eso. org/observing/dfo/quality/FORS2/qc/ zeropoints/zeropoints. html does not appear to be visibly extended in the NIR data; in any case the corrections are much smaller than the final photometric uncertainty.
67P-activity-2014-final phase is observed each night over short periods like this. If real, this event took place a few days before OSIRIS was turned on, meaning that it is quite possible that it would have been missed from Rosetta, as the outburst that OSIRIS did see at the end of April was visible for only a short time  (Tubiana et al. 2015). We do not see any strong evidence for the OSIRIS outburst in the VLT photometry, but we lack observations in late April to compare with the early May data. Although this period is covered by the NOT observations by  Zaprudin et al. (2015) , the S/N of those data do not allow small outbursts to be confirmed. By the time of the potential August event, Rosetta was already close enough to the nucleus that OSIRIS no longer saw the whole comet, so again small outbursts could have been missed.
Data reduction Spectroscopic data from FORS were reduced using IRAF and MIDAS routines, and the results compared. No significant difference was found between the techniques -we report the results using IRAF routines. The 1-D spectrum was extracted from the debiased, flat-fielded, rectified frames, by addition over 20-30 lines. The sky background was taken in clean zones on each side of the comet spectrum. Not all spectra were usable -the fields were crowded and in many cases star spectra overlap the comet. Some spectra were affected by clouds and in some cases the comet was absent altogether. Spectrophotometric standards have been observed with the MOS instead of the long-slit mode in order to have a wide (5 ) slit. Standards stars showed slight differences between the runs, hence a sensitivity curve was computed for each run.
2015) , and also see a decreasing slope with wavelength. The X-SHOOTER slopes are consistent with these results. The shallow NIR slopes are also consistent with the photometry from Gemini, where average slopes in the J -K (1. 2 -2. 2 micron) range are ∼ 2 % / 100 nm in the October data set and near zero (i. e. solar spectrum) in November, around the same time as the X-SHOOTER spectrum. The November Gemini data set contains only J and K band photometry taken 4 nights apart, so the latter slope is relatively uncertain. Fig. 14. Zoom in on visible region of the X-SHOOTER spectrum, showing where gas emission bands would be expected.
Acknowledgements. We thank the referee,  Mike A'Hearn , for helpful comments that improved this manuscript. We thank the observatory staff who made the observations possible, especially the service mode observers. CS received funding from the  European Union Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 268421  and from the  STFC  in the form of an  Ernest Rutherford Fellowship. EJ is a FNRS Research Associate, JM is an Honorary Research Director of the FNRS and CO acknowledges the support of the  FNRS. AF is supported by  UK Science and Technology Research Council  grant  ST/L000709/1. MMK is supported by  NASA   Planetary Astronomy Program  grant  NNX14AG81G. DMB was supported by  NPRP  grant  X-019-1-006  from the  Qatar National Research Fund. This work was based, in part, on observations obtained at the  Gemini Observatory  processed using the Gemini IRAF package, which is operated by the  Association of Universities for Research in Astronomy, Inc.
Ambient measurements The complete set of spectra can be clustered using the software MATLAB version 2013b into different chemical classes of particles. Figure  9a  illustrates four of these clusters and their repartition every 5 min in different size range. These clusters were chosen as example to show different kind of inorganics particles, and one cluster with major carbonaceous ions. The inorganic particles are those containing sulfate and nitrate that are considered as secondary particles and particles containing TiO 2 that are rather considered as primary particle  (Delmas et al. , 2005). It can be observed that nitrosium ion NO + (m/z = 30) is abundant in the first cluster and potassium ion K + (m/z = 39) is abundant in the second cluster. The third cluster represents particles with high signals of carbon, and in the fourth cluster characteristic peak of carbon C + (m/z = 12), C + 2 (m/z = 24), C + 3 (m/z = 36) dominate.
As explained above in the description of LAAP-ToF-MS, the flight time of an individual particle between the first and second scattering lasers is used to determine its velocity and associated vacuum-aerodynamic diameter. For the given beam separation distance of 11. 5 cm between the two scatterings lasers the particle velocity was determined and plotted against the aerodynamic particle diameter (Fig. 11 ). The experimental data were fitted with a first order exponential decay curve. The smallest PSL particles that can be precisely size-calibrated have a diameter of 350 nm. However, the fitting equation depicted in Fig. 11  can serve to roughly estimate the size of atmospheric particles with an aerodynamic diameter smaller than 350 nm.
In other words, the spectrum obtained relates to a single, real particle, but the size information does not. Hence, the E (%) should decrease because the data of one single particle is recorded instead of two. In order to study the effect of a concentration higher than C max on the E (%), ferric sulfate particles (450 nm) were generated at 5 different concentrations between 50 and 1200 particles cm -3. The higher level 1200 was chosen according to the value of C max found at 562 particles cm -3 for particles with diameter of 450 nm. The influence of particle concentration on the detection efficiency was assessed by comparison of the obtained RSD values based on at least three independent measurements. Concerning the scattering efficiency E (%), it was expected that it decreases, but the RSD between the different concentrations is lower than the RSD between the repetitions for the same concentration, so the E (%) is considered constant.
Acknowledgements. This work is a contribution to the LABEX SERENADE (no. ANR-11-LABX-0064 ) funded by the " Investissements d'Avenir", French Government program  of the  French National Research Agency (ANR)  through the  A*Midex  project (No. ANR-11-IDEX-0001-02 ). The authors gratefully acknowledge the support of this work by  French National Agency of Research  within the  ANR-10-EQPX-39-01. Edited by:  P. Herckes.
Acknowledgements We would like to thank  P. -Y. Lagrée  for his help in reviewing the literature on granular simulation,  R. Narain  for sharing his code, and anonymous reviewers for their insightful feedbacks. This work was supported in part by the  LabEx PERSYVAL-Lab  ( ANR-11-LABX-0025-01 ) funded by the  French program Investissement d'Avenir.
Luminal Digestive Enzymes and Fecal Bacteria Possess Limited Activity on 3/15ADON We first evaluated the capacity of secreted digestive enzymes present in the upper part of the intestinal tract to deacetylate 3/15ADON. Results showed that pepsin and pancreatic enzymes (pancreatin, trypsin, lipase) possessed very limited activity on 3-and 15ADON (around 10%-15% of deacetylation after 210-270 min incubation at 37 ˝C) (Figure  3 ). Increasing further the incubation time did not significantly improve the deacetylation, only 15%-20% of the initial concentration of 3/15ADON (100 µM) being hydrolyzed after 24 h of incubation at 37 ˝C (data not shown). Similarly, fecal bacteria obtained from human donors displayed no activity on 15ADON and limited activity on 3ADON with only 22. 6% ˘15. 9% of deacetylation after 6 h incubation (Figure  4 ).
The Deacetylation Activity Is Present in the S9 Fractions But Is Not Due to CES1 or CES2 Next, we evaluated the activity of commercial pooled S9 fractions obtained from human small intestine, liver and kidneys on 3-and 15ADON. Results found with S9 fractions corroborated data obtained with human cells and tissues (Figure  7 ). Only small intestinal and liver S9 fractions had significant activity on 3/15ADON, whereas renal S9 fraction had minor activity, if any.
The Deacetylation Activity Is Present in the S9 Fractions But Is Not Due to CES1 or CES2 Next, we evaluated the activity of commercial pooled S9 fractions obtained from human small intestine, liver and kidneys on 3-and 15ADON. Results found with S9 fractions corroborated data obtained with human cells and tissues (Figure  7 ). Only small intestinal and liver S9 fractions had significant activity on 3/15ADON, whereas renal S9 fraction had minor activity, if any. Once again, deacetylation activity of S9 fractions on 3ADON was largely higher than the activity on 15ADON with specific activities of 1250; 1791 and 33 pmol•min -1 •mg -1 and 166; 208 and 16 pmol•min -1 •mg -1 for intestinal, hepatic and renal S9 fractions on 3ADON and 15ADON, respectively. Then, we evaluated the involvement of CES in 3/15ADON deacetylation.
We measured the deacetylation activity of S9 fractions and human cells in the presence of benzil (100 µM). Results showed that benzil had only limited inhibitory effect on the conversion of 3/15ADON into DON by S9 fractions, i. e. , 8% to 24% inhibition (Table  1 ). Similarly, benzil (at 100 µM) caused a limited and none significant inhibition (i. e. , 10%-20%) of the deacetylation of 3/15ADON by human cell lines (data not shown). To confirm that CES were actually inhibited by benzil, we monitored the activity of cells and S9 fractions on para-nitrophenyl acetate (pNPA), a chromogenic substrate of CES. Results showed that cell lines and S9 fractions were all able to efficiently cleave pNPA, confirming that high levels of CES were present even in the cells and S9 fractions with limited activity on 3/15ADON (i.
e. , A498 and T84 cells and renal S9 fraction) (Table  2 ). Importantly, benzil at 100 µM caused a dramatic inhibition of the deacetylation of pNPA ranging from 83% to 96% inhibition depending of the system tested confirming its ability to inhibit CES activity (Table  2 ). Finally, we tested the activity of commercial recombinant human CES1 and CES2 on 3/15ADON. Although recombinant CES1 and CES2 displayed strong benzil-sensitive activity on pNPA (Table  2 ), we failed at observing any deacetylation activity of these enzymes on 3/15ADON, even after 24 h of incubation of 3/15ADON with 5 µg/mL of CES1/2 (data not shown).
Based on data of Table  3 , Figure  8  proposes an overview of the hydrolytic fate of 3/15-acetyl-deoxynivalenol in humans, with the contribution of each compartment considering that total 3/15-ADON deacetylation activity is the sum of specific activities of digestive enzymes, fecal bacteria, small intestinal, hepatic and colonic tissues. Table  3. Specific activity of digestive enzymes, fecal bacteria, cell lines, explants and S9 fractions on 3/15ADON. Specific activities were calculated from deacetylation kinetics and are expressed as pmol of 3/15ADON that disappeared (or pmol of DON formed) per minute and per mg of protein (n = 3). In the case of pepsin, the rate of formation of DON was not determined (ND) due to the presence of a contamination peak (present in the pepsin solution) at the retention time of DON.
1 min. The detection wavelength was set at 237 nm allowing the best signal/baseline ratio for simultaneous detection of the three DON forms in the incubation mediums. Under these conditions, DON and 3/15ADON were clearly separated, the retention time being around 2. 7 min and 5. 7 min, for DON and 3/15ADON, respectively (Figure  9 ). Quantification was based on calibration with the corresponding standard using Millinium Software (Waters, Saint Quentin Falavier, France).
The input of SModelS consists of an SLHA file  [87] , containing particle spectrum and decay tables, together with SUSY production cross sections, which we have computed with micrOMEGAs v4. 1. 7. For strong production of sparticles we have also applied next-to-leading-order and next-to-next-to-leading-log (NLO+NNLL) QCD κ-factors, which have been computed with the nllfast package  [88] [89] [90] [91] [92] [93] [94]. Note that due to the presence of many states below the TeV scale, and in particular of a very light LSP, for some regions of parameter space the coloured sparticles possess a large number of possible decay.
However, gluino searches generally rely on a large number of jets in the final state. These signal regions can be easily fed also from gluino decays different from the standard assumptions, in particular decays into heavier neutralinos. We have then used the recast  [98]  CMS gluino search  [99] , implemented in the package MadAnalysis5, which relies on an opposite sign dilepton final state, more than 4 jets and more than 2 b-tag jets, together with a large E miss T. This search sets a 95% CL exclusion when more than 4 events fall in its unique signal region. We have simulated gluino pair production with MadGraph5 v1. 5. 11  [100]. Parton showering, hadronization and decay of unstable particles have been performed with the package Pythia v6. 4  [101] , while the MadAnalysis5 tuned version of Delphes v3.
We do not propose benchmark points for region 1B for two reasons. First, the characteristics of the Higgs sector are quite similar to the ones of region 1A when the decay pattern h 2 → h 1 h 1 is closed (recall in fact that in region 1B the h 1 mass is between 70 and 90 GeV). Secondly, and more importantly, the lighter gluino in this region is likely to be tested with early data from LHC Run-  conventional search channels. In summary, the Run-2 of the LHC at higher energy and luminosity will further probe region 1 through stop, slepton and gluino searches, while new Higgs decay channels involving light pseudoscalar and/or scalar bosons can provide characteristic signatures of an extended Higgs sector. Moreover, peculiar signatures from stop decays could also characterise the light singlino scenario.
[96, 123] ) where standard stop searches loose sensitivity, causing therefore a poor exclusion limit. The second is that for higher values of the stop mass, around 400 GeV, the same analyses loose sensitivity since the stop decays do not fulfill the simplified model assumptions. In particular, the branching ratios Br( t → χ± 1 b) and Br( t → χ0 1 t) are both suppressed. The reason is that the coupling of the stop to the singlino is small, hence other decay channels into heavier neutralinos are favoured despite the reduced phase space, causing therefore a reduction of the exclusion power of the experimental analyses. The two previous statements about the non exclusion of such light stops have been checked via the CMS search  [96]  available in the MadAnalysis5 Public Analysis Database  [124].
Acknowledgments DB thanks  Ursula Laa  for useful discussions regarding the use of SModelS. This work was supported in part by the  LIA-TCAP of CNRS , by the  French ANR , Project  DMAstro-LHC ,  ANR-12-BS05-0006 , by the  Investissements d'avenir, Labex ENIGMASS. The work of AP was also supported by the  Russian foundation for Basic Research , grant  RFBR-15-52-16021-CNRS-a. The authors acknowledge the support of  France Grilles  for providing cloud computing resources on the  French National Grid Infrastructure.
Conversely MadAnalysis5 is a multi purpose package designed for the analysis of events generated at parton level and/or reconstructed level with the inclusion of parton showering and detector effects. In this work we have exploited the MadAnalysis5 Public Analysis Database, i. e. a list of implemented and validated experimental searches, with which one can recast the experimental limits set by ATLAS and CMS in a generic model or in a particular model configuration. Clearly the approach of MadAnalysis5 is more general, since it does not rely on any simplified model assumption, but it has the drawback of being somewhat more time consuming, given the need to generate events with a Monte Carlo generator for each model point that one wants to test. In this paper we will use a combination of both tools to check the limits set by LHC Run-1 in the nMSSM, using MadAnalysis5 especially to set bounds on the gluino mass.
Epifluorescence microscopy analysis of RNA in virions FISH-stained viral particles were imaged using a wide-field Leica DM6000 upright microscope equipped with a 100x PL APO 1. 4-0. 7 oil-objective (Leica) and a Coolsnap HQ charge-coupled device camera (Roper Scientific) at Montpellier Rio Imaging (MRI) facilities. Dual-color images were acquired with the excitation and emission filter sets of green fluorescent protein (GFP) and Cy3. Around 10 fields of view were captured for each preparation. The center position of fluorescent spots was identified by their local maxima intensity using a manually defined threshold in ImageJ software. Red-green spots were considered colocalized if the distance between their centers was below three pixels (∼200 nm). To calculate the percentage of WT-lacZ gRNA (red spots) that colocalized with an MS2-tagged RNA (green spots), the number of red spots that colocalized with a green spot was divided by the total number of WT-lacZ gRNA, assuming that each virion contains two copies of viral RNA  (19).
Total internal reflection fluorescence microscopy (TIRFM) of cells TIRFM of FISH-stained cells was achieved using a TIRF microscope (based on an inverted TE Eclipse microscope (Nikon)) equipped with a Plan Fluor 100×/1. 49 NA TIR objective (Nikon) and an EMCCD camera (ImagEM) and controlled using MetaMorph software (MRI facilities). Dual-color imaging of MS2-AF488 and lacZ-Cy3 labeled RNA was achieved by exciting with 491 nm and 561 nm lasers, respectively, and appropriate filters were selected to separate green and red emissions (500-520 nm and 600-660 nm, respectively). The green and red channels were aligned prior to imaging using two-color fluorescent beads of 200 nm diameter (Thermo Fisher Scientific). Imaging was performed on cells that exhibited similar fluorescence intensities in the red and green channels upon episcopic illumination, to ensure similar expression of both plasmids.