dataesr/scientific-paragraphs-categorization huggingface dataset:
The rate of sialylated fetuin formation remained constant for at least 5t o6 hwith either D56ST6Gal Io r D56ST3Gal I( Figure  2A ). We also noticedt hat asialofetuin was sialylated much faster by D56ST3Gal It han by D56ST6Gal I: the  formationo fa2,3-sialylated product reached am aximum after 6h incubation, whereas the formation of a2,6-sialylatedp roduct kept on increasing up to 15 h( Figure  2A ). We checked that our recombinant enzymes had negligible transfer activity onto potentialt argets in the medium (data not shown). We then incubated each enzymef or 6h with various concentrations of CMP-Neu5Ac (1 to 100 mm;Figure  2B ). Apparentkinetic parameters were obtainedb yn onlinearr egression analysis of the Michaelis-Menten equation in Graph Pad. The experiment was carried out three times, and the apparent K M values were determined for the donor substrate CMP-Neu5Ac as 2.
These data furthers uggested that D56ST3Gal Ia nd D56ST6Gal Ia re likely promiscuous with respectt ot he CMP-SiaNAl donorc arrying an extended N-acyl group in the C5 position, as previously suggested. [4] aracterizationo ft he a2,3/6-sialyltransferase activities towards the unnatural donor substrate CMP-SiaNAl We developed an in vitro sialyltransferase assay based on desialylatedg lycoproteins as acceptor substrates for probing D56ST3Gal Iand D56ST6Gal Isialyltransferase activities towards the unnatural sialica cid donors ubstrate CMP-SiaNAl. Sialylation reactions were carriedo ut with the cell culture medium of transfected HEK293 cells containing either D56ST3Gal Io r D56ST6Gal I( or no enzyme, mock) with 100 mm CMP-SiaNAl and 50 mgo fa cceptor substrate (fetuin, asialofetuin, or a-1acid glycoprotein).
The glycosidic linkage between sialic acid and acceptor monosaccharide was hydrolyzed with TFA( 100 mL, 0. 1 m), then the mixture was incubated for 2hat 80 8C, and dried in a5301 concentrator (Eppendorf). Derivation of sialic acid was performed for 2hat 50 8Ci nt he dark with DMB (32 mg), b-mercaptoethanol (0. 5 m),N a 2 S 2 O 4 (9 mm),T FA (5 mm, 40 mL). Samples were stored at À20 8Cbefore analyzing. Quantitative analyses were performed in positive ion mode on an amaZon speed ETD ion trap mass spectrometer (Bruker Daltonics) equipped with as tandard ESI source and controlled by Hystar software (ver. 3. 2). The identification of MS 2 fragment ions was based on previously published analyses of DMB-coupled sialic acid by MS/MS. [36] DMB-coupled sialic acid separation was achieved on Prominence LC-20AB micro LC system (Shimadzu).
Acknowledgements We thank  Elodie Richard  and  Dr. C hristian Slomianny  of the  BICel-Campus Lille1  facility for access to instruments and technical advices. Wea re indebted the  Plateforme d'Analyse des Glyco-conjuguØs( PAGØs , http://plateforme-pages. univ-lille1. fr)and to the  Research Federation FRABio (Univ. Lille, CNRS ,  FR 3688 ,  FRABio,B iochimie Structurale et Fonctionnelle des assemblages BiomolØculaires ) for providing the scientific and technical environment conducive to achieving this work. We aree xtremely gratefult oA nne- Marie Mir  for her excellent technicala ssistance using radiolabeled compounds. We greatly acknowledge  Dr. B er -nadetteC oddeville,  Dr. M athieu Carpentier , D r. AgnsD  enys and  Dr. FabriceA llain  for helpful discussions.
8 mm fiber in a system designed for a fiber with an NA of 0. 22. Using a fiber with a larger than expected NA resulted in vignetting on the apertures of various optical devices of the detection subsystem, which probably added significant sensitivity to beam wandering and thus increased calibration instability. In order to eliminate this vignetting, we used the ZEMAX commercial optical ray tracing software (www. zemax. com) to optimize the optical design of the detector subsystem for different optical fibers. For each fiber, the focal length of the collimating L1 and the distance between the source -i. e. , fiber output -and L1 was optimized to obtain a collimated beam throughout the system. The focusing lenses (L2, L3, and L4) were chosen in such a way as to achieve a 5 mm diameter spot centered on the 8 mm diameter PMT photocathodes.
, 2016). However, because the radiosonde measurements are made at a distance of 30 km, the profiles do not agree well all the time, especially in the lower levels. This is a main reason why we did not use the radiosonde data as a source for external calibration of the lidar profiles such as done during DEMEVAP. External calibration of the lidar WVMR profiles was achieved with two types of auxiliary measurements: relative humidity measurements from PTU sensors and ZWD data derived from GPS measurements following the methodology described in  Bock et al. (2013). It can be questioned whether the portion of atmosphere between these measurements and the first valid lidar range bin (33. 75 m) would introduce a significant bias in the calibration. To evaluate this effect we estimated the mean vertical gradient in WVMR from simultaneous humidity measurements from PTU sensors at two different heights (15 and 25 m).
Acknowledgements. The authors gratefully acknowledge  Licel GmbH  for fixing the instrumental problems on the transient recorder and the  IGN-LOEMI  staff ( Olivier Martin ,  Yann Le Borgne ) for participating in the nighttime measurements during the Saint-Mandé campaign. The authors would like to express their thanks to  David Whiteman  and a second anonymous reviewer for their constructive comments that helped improve the manuscript. This work was developed in the framework of project  VEGA  and supported by the  French national program LEFE/INSU. Edited by:  Ulla Wandinger Reviewed  by:  David Whiteman  and one anonymous referee.
Water contents were recalculated from laboratory measurements (weighing, drying, density measurements) considering a full saturation state for all samples. This correction was implemented due to the fact that desaturation of samples during core drilling and sample handling can lead to an overestimation of calculated porewater concentrations. In addition to the determination of porewater contents, out diffusion enabled to give rough estimates of the pore diffusion coefficient by modelling the experiment with a transport code (HYTEC 5 in this study).
Pore diffusion coefficients Out diffusion experiments were modelled using the transport code HYTEC and assuming that diffusion is dominating the solutes transport through the rock samples. Sample swelling prevented the possibility to get proper values of diffusion coefficients for each of the tested samples. Estimated pore diffusion coefficients for chloride in a sandy facies of the Opalinus Clay are presented in Figure  3. With an imposed accessible porosity of 5. 4%, pore diffusion coefficients were respectively estimated to 5•10 -10 m²/s and 1. 2•10 -9 m²/s for diffusion perpendicular and parallel to bedding. These values correspond to an anisotropy ratio of 2. 4, which is lower than the value of 4 reported by  6. The discrepancy could be due to sample heterogeneity or different experimental procedures, added to uncertainties due to cracks induced by sample unconfining and swelling.
[(UO2)4Ba2(R-chdc)6(H2O)8] (8). R-H2chdc (17 mg, 0. 10 mmol), UO2(NO3)2•6H2O (35 mg, 0. 07 mmol), Ba(NO3)2 (26 mg, 0. 10 mmol), methanol (0. 2 mL), and demineralized water (0. 6 mL) were placed in a 10 mL tightly closed glass vessel and heated at 150 °C under autogenous pressure, giving light yellow crystals of compound 8 in low yield within two months. Crystallography. The data were collected at 150(2) K on a Nonius Kappa-CCD area detector diffractometer  46  using graphite-monochromated Mo K radiation ( = 0. 71073 Å). The crystals were introduced into glass capillaries with a protective coating of Paratone-N oil (Hampton Research). The unit cell parameters were determined from ten frames, then refined on all data. The data (combinations of -and -scans with a minimum redundancy of at least 4 for 90% of the reflections) were processed with HKL2000.
47 Absorption effects were corrected empirically with the program SCALEPACK. 47 The structures were solved by direct methods with SHELXS  48  or by intrinsic phasing with SHELXT,  49  expanded by subsequent difference Fourier synthesis and refined by full-matrix least-squares on F 2 with SHELXL-2014. 50 All non-hydrogen atoms were refined with anisotropic displacement parameters, with restraints being applied for some badly resolved parts, particularly the ammonium counterions in 3, or solvent molecules. Two-and threecomponent twinning in 1 and 8, respectively, was detected with TwinRotMat (PLATON  51  ) and was taken into account in the refinement. In compound 3, one of the H2NMe2 + cations was given an occupancy factor of 0. 5 for charge equilibrium and also to retain acceptable displacement parameters.
Some coordinated or free water molecules in compounds 2-4, 6 and 7, as well as NMP molecules in 4, were given half-occupancy in order to retain acceptable displacement parameters and/or to account for too close contacts with their image by symmetry (some of them being further disordered in 4 and 6). The hydrogen atoms bound to oxygen or nitrogen atoms were retrieved from difference Fourier maps when possible, but none was found for compounds 2, 4 and 5; the carbon-bound hydrogen atoms were introduced at calculated positions. All hydrogen atoms were treated as riding atoms with an isotropic displacement parameter equal to 1. 2 times that of the parent atom (1. 5 for CH3, with optimized geometry). Crystal data and structure refinement parameters are given in Table  1. The molecular plots were drawn with ORTEP-3  52  and the polyhedral representations with VESTA.
H2NMe2][(UO2)4Rb3(R-chdc)6(H2O)1. 75] (3), [(UO2)4Rb4(R-chdc)6(NMP)0. 5(H2O)3. 75]0. 5NMP 0. 25H2O (4) and [(UO2)4Rb4(R-chdc)6(H2O)1. 5]0. 5H2O(5), which all contain the enantiopure ligand and crystallize in the Sohncke space groups C2, P21 and R32, respectively. The asymmetric unit in 3 contains four uranium and three rubidium atoms, and six complete ligands (Figure3). All uranyl cations are tris-chelated, and the U-O(oxo) bond lengths, 1. 746(14)-1. 789(15) Å, and the U-O(carboxylate) bond lengths, 2. 404(16)-2. 520(15) Å [average 2. 46(3) Å], are as usual. The pseudotetrahedral cage is here also less distorted than in 1, with UU distances in the range of 6. 2016(11)-6. 3775(14) Å. A search of the Cambridge Structural Database (CSD, Version 5. 38) 57.
[ H2NMe2][(UO2)4Rb3(R-chdc)6(H2O)1. 75] (3), [(UO2)4Rb4(R-chdc)6(NMP)0. 5(H2O)3. 75]0. 5NMP 0. 25H2O (4) and [(UO2)4Rb4(R-chdc)6(H2O)1. 5]0. 5H2O(5), which all contain the enantiopure ligand and crystallize in the Sohncke space groups C2, P21 and R32, respectively. The asymmetric unit in 3 contains four uranium and three rubidium atoms, and six complete ligands (Figure3). All uranyl cations are tris-chelated, and the U-O(oxo) bond lengths, 1. 746(14)-1. 789(15) Å, and the U-O(carboxylate) bond lengths, 2. 404(16)-2. 520(15) Å [average 2. 46(3) Å], are as usual. The pseudotetrahedral cage is here also less distorted than in 1, with UU distances in the range of 6. 2016(11)-6. 3775(14) Å. A search of the Cambridge Structural Database (CSD, Version 5. 38) 57.
In summary, we demonstrated a fiber laser pumped, passively CEP stabilized 3 µm OPA, which delivers 8 µJ pulses with the duration of 85 fs. This system is potentially tunable in the 2. 4 -3. 6 µm range. Finally this middle infrared ultrafast source has been designed for solid state physics in the non-perturbative regime. Further development will shorten the pulse to few cycle with a CEP stability control, and an increase of the energy to 50 µJ. With the present characteristics, our first demonstration of HOH in ZnSe by a fiber laser pumped OPA shows how fiber lasers based systems are already very promising tools for future work such as band structure investigation  [31] , strong field Bloch oscillations, or HOH dynamics beyond the band gap of semi-conductors. Funding. Laserlab-Europe IV ILAT (EU-H2020 654148), the ANR (ANR-10-IDEX-03-02), the ANR-ASTRID (ANR-15-ASTR-0005) and ELI-ALPS GOP-1.
X-ray Studies The X-ray diffraction intensities of single crystals of compound I were measured at the Kurchatov Centre for Synchrotron radiation, while the dataset for II was collected with Bruker APEX DUO diffractometer. The structures were solved by direct method and refined in anisotropic approximation. Hydrogen atoms were calculated from a geometrical point of view, and were then refined with restraints applied for their displacement parameters and C-H (O-H) bond length. The crystal data for compounds I and II are summarized in Table  2  (see also the ESI). Crystallographic data for I and II were submitted to CSD (CCDC 1481141 and CCDC 1481142) and can be obtained free of charge using web request from http://www. ccdc. cam. ac. uk/request. The main difficulty in the refinement of compounds I and II was to reveal the exact chemical composition of these structures.
Acknowledgments: This work was partially financially supported by the  Ministry of Education and Science of the Russian Federation  (the Agreement number  02. a03. 21. 0008 ), the  RFBR  (projects  16-29-05180  and  16-03-00254 ),  RFBR-CNRS  (project  16-53-150008 ), the  French Embassy in Moscow , the  Balard Foundation , and  Université de Montpellier.
The MUSE data NGC 6397 was observed during MUSE commissioning, lasting from July 26nd to August 3rd, 2014. 23 MUSE pointings were arranged in a 5 × 5 mosaic with two missing frames, covering roughly 300 × 300 on the sky. The exposure times ranged from 25s to 60s per individual observation, accumulating about 4 min per pointing on average. This limitation was set to avoid saturation effects of the brightest cluster giants as the original studies in Papers I & II focused on the stars themselves. In total, we obtained 127 exposures with a total integration time of 95 min. Including overheads, the observations took about 6 h. While the seeing varied below 1 , the central pointings were recorded at a seeing of 0. 6. The data reduction was done using the official MUSE pipeline (in versions 0. 18.
1, 0. 92, and 1. 0) described in  Weilbacher et al. (2012). See Paper I for detailed information on the MUSE observations of NGC 6397. The resolving power of the MUSE instrument ranges from ∼ 2000 at 4650Å to ∼ 4000 at 9300Å. The data consists of roughly 19,000 spectra of ∼ 12,000 individual stars. Even at a resolution of ≈ 100 km s -1 , most of the strong DIBs are resolved, due to their eponymous broad profiles. However, we are strictly limited by the resolution of our data with regard to resolving individual velocity components in the narrow absorption lines of neutral species such as K I or the Na I D doublet. The observed field is strongly dominated by cluster member stars. We expected comparably few foreground stars toward the position of NGC 6397 below the Galactic disk. For an adjacent field of the same angular size, the GAIA archive of Data Release 1 contains ≈ 100 stars brighter than 18th magnitude (see Gaia  Collaboration 2016 , Fabricius et al.
UVES data We used a high resolution spectrum from VLT/UVES in the direction of NGC 6397 of one of its cluster members to verify the results we derived from low resolution MUSE data and to provide a reference spectrum for interstellar absorption. A marker in Fig. 1 , about 200 arcsecs from the cluster center, reflects the position of star NGC 6397-T183. This star lies outside of our map and also outside of the cluster's core region, but since it is relatively close on the sky, its spectrum should give useful indications on the velocity components present in this direction. We retrieved a high resolution UVES spectrum from the ESO archive 1. At a slit width of 0. 3 , the UVES spectrum has a resolution of R ≈ 115, 000 and a S/N of ∼ 50. The UVES data for the nearby B-Type star 2  in the top panel of Fig.
GASS data on H I To further study the gas kinematics of the neutral ISM toward NGC 6397 (including the more diffuse warm neutral phase that is not traced by Na i absorption) we used publicly available H i 21cm data from the Galactic-All Sky Survey (GASS;  McClure-Griffiths et al. 2009; Kalberla et al. 2010 ; see https://www. astro. uni-bonn. de/hisurvey). The GASS survey was carried out with the 64m radio telescope at Parkes. The spectral resolution is 0. 82 km s -1 at an rms of 57 mK per spectral channel (∆v = 0. 8 km s -1 ), while the beam size of the data is ∼ 16 , thus providing a rough estimate of N(H I ) as the effective FWHM of the beam is larger than the MUSE FOVs. If one assumes that the gas is optically thin, the column density of H I can then be obtained from the brightness temperature T (v) per velocity bin from the GASS data: N H = 1.
82 × 10 13 T (v) dv atoms cm -2 , (1) leading to a total column density of log[N(H I )] = 21. 1. As this is observed in emission, gas beyond NGC 6397 could contribute to the total budget. The low galactic latitude of -11. 06 • for NGC 6397 suggests that all observed H I is in the foreground of the GC. The 21cm brightness temperature profile toward NGC 6397 is shown in the top panel in Fig. 2. The radio data clearly displays the main component at rest as well as the much weaker blue shifted component at v helio = -26 km s -1.
Modeling of the stellar population and telluric correction Each of the stellar spectra were PSF-extracted simultaneously from the single data cubes. The process is described and successfully applied in Paper I. In Paper I every extracted stellar spectrum of the globular cluster was fitted with a template spectrum based on PHOENIX models 3. The stellar templates were scaled with a polynomial as linear fit to account for reddening and hypothetical flux calibration inconsistencies in the commissioning data. Furthermore, an individual telluric model was fitted to each spectrum, though we expect a rather homogeneous sky background for each MUSE field of view. Paper I describes this process in great detail. The telluric absorption lines were fitted with models of varying H 2 O and O 2 /O 3 abundances  (Husser & Ulbrich 2014).
This work utilizes the residuals of the above mentioned template matching and sky fitting procedures. Once the stellar templates and telluric absorption lines are subtracted, the only features that remain are hypothetical stellar lines not represented in the models, potential misfits of stellar templates, and absorption features of the interstellar medium along the line of sight toward NGC 6397. As a Fig. 3. Steps of data processing. In black the data for one of the brightest stars in the field with a S/N ∼ 120. In red the best fit to the data including the telluric absorption line fit as well. In blue below the fitting residuals to scale with the plotted spectrum. The enlargement windows to the left, highlight the region around the DIBs 5780,5797 and the Na I D doublet. On the right hand side, the zoom illustrates the success of the telluric absorption line fit.
Improving S/N by tessellation For the general analysis, the individual residual-spectra, were coadded with error weighting into Voronoi bins of equal S/N. The applied Voronoi algorithm is based on the procedure presented in  Cappellari & Copin (2003). Voronoi binning is a special kind of tessellation that solves the problem of preserving the maximum spatial resolution of general two-dimensional data, given a constraint on the minimum S/N. This automatically leads to somewhat homogeneous S/N per bin with varying bin-sizes. The uneven spacing of the stars as well as the strong variation in brightness of neighboring stars leads to varying shapes (but always convex) of the individual bins. As each spectrum was extracted from the 23 MUSE data cubes which were reduced to the same wavelength grid, no resampling of the individual spectra was required for this step.
The line strengths for each doublet was fitted as a free parameter to use the ratio as sanity check as well as probe for density variations as mentioned in Sect. 4. 2. 1. K I 7664 sits directly on a strong telluric absorption band, while K I 7699 is hardly affected by this (see also Fig. 3  and Fig. 13 ). At an equivalent width of ≈ 50 mÅ, both features are extremely weak and seen at the MUSE resolution the absorption lines show a absorption depth of merely 1-2% of the continuum level. We are confident that the fit of the sky model is sufficiently stable and accurate to recover the information on the stellar flux and interstellar absorption in those regions of the spectrum. The inset in Fig. 4  shows the distribution of the slope for 5,000 bootstrap realizations of the dataset quantifying the correlation in a more robust way than the correlation coefficient of 0.
Location and size of the absorbing cloud The high-resolution UVES spectra as well as the radio data for H I indicate that we observe one dominant absorption component toward NGC 6397. The component blueward of the main feature is more than an order of magnitude weaker in H I. Our Sun and nearby stars reside in a region of ionized material referred to as the Local Bubble  (Frisch et al. 2011 and references therein). The edge of the Local Bubble can be traced by the onset of Na I and Ca II absorption, indicators of colder material. According to  Sfeir et al. (1999)  or  Welsh et al. (2010)  this edge begins anywhere from 65 to 250 pc depending on the observed direction. Within the Local Bubble, isolated clouds of warm, partially ionized gas are observed  (Redfield & Linsky 2008; Malamut et al.
DIB correlations Correlations between individual DIB strengths have been used to identify features that respond similarly to differences in the diffuse cloud environment. Identifying such correlating subsets of DIBs provides a valuable spectroscopic constraint on the identity of the carrier(s). Ádámkovics et al. (2005)  point out that any group of features arising from a particular carrier, or set of chemically related carriers, must maintain the same relative intensities in all lines of sight. Directly comparing DIB equivalent width ratios within the same observations avoids the potentially complicating factor of normalizing individual DIB equivalent widths which is a crucial source of systematics when comparing data of different sightlines. While the measurement on the combined data reproduces that relationship exactly, the observed trend of our 31 spatial measurements within the physical absorber shows a slope of almost exactly one.
Furthermore, the correction for O 2 works remarkably well, as demonstrated by the tight correlation in Fig. 4 , which gives us confidence in the result for DIB 6283 as well. Figure  13  shows the difference of the two extreme cases in the data set: two exposures for which the sky model contained the strongest and the weakest O 2 while other telluric model parameters remained similar. The modeled absorption for O 2 varies within a few percent only and affects DIB5780, 5797 and DIB 6283 in an almost identical manner, whereas the effect for K I 7664 is about twice as strong and less than half as strong for K I 7699. The strength of the telluric feature blending with DIB 6283 is of the same order of magnitude but a little weaker than the DIB itself for this particular target with considerably high extinction.
Acknowledgements. Many thanks to  Dan Welty  and  Scott Friedman  who generously provided data of DIB and ISM measurements in private communication. We also thank the referee for the thorough reports improving the flow of the paper. AMI acknowledges support from the  Spanish MINECO  through project  AYA2015-68217-P  and the  Agence Nationale de la Recherche  through the  STIL-ISM  project ( ANR-12-BS05-0016-02 ). This work has made use of data from the  European Space Agency (ESA) mission Gaia  (https://www. cosmos. esa. int/gaia),processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www. cosmos. esa. int/web/gaia/dpac/consortium).