dataesr/scientific-paragraphs-categorization huggingface dataset:
Acquisition times were at least 60 min, and a stabilization time of at least 5 min at each temperature before data acquisition was selected. Longer time acquisition patterns were obtained at some temperatures for structural and refinement purposes. The structure of the low-temperature ordered phases were determined by means of long acquisition time high-resolution X-ray powder diffraction patterns. X-cell software  [45]  was used to index the lattices and a Pawley profile-fitting procedure minimizing the Rfactor (R wp )  [46]  to confirm the space group as well as to refine the unit cell parameters, the zero-shift, the background and peak profile (pseudo-Voigt) parameters. To fully determine the structure, rigid body molecules were built up by replacing the two hydrogens attached to the tertiary carbons in the adamantane molecule by two methyl groups for 13DMA, two Br atoms for 13DBrA and two OH groups for 13DOHA.
Molecular energy minimization with the Forcite module (energy minimization using Dreiding forcefield)  [47]  has been used for the molecular parameters. For the final structural solution, molecules were placed in a general position randomly oriented and through the Powder Solve  [48]  (Monte-Carlo approach), both position and orientation of molecules within the unit lattice were refined. For a fine tuning of all structural data, Rietveld  [49]  refinements were conducted alternatively with energy minimization within the rigidbody constraint, a single overall isotropic displacement parameter and a preferred orientation by using the Rietveld-Toraya function. [50] The used software is included in MS Modelling from Materials Studio. [51]  Density Measurements. Liquid density measurements at normal pressure were carried out for 13DMA from 278 to 335 K using an Anton Paar D5000 densitometer with temperature stability of 0.
Spectra Acquisition Two sample presentation modes were evaluated for the analysis of LTL samples: intact and minced muscles. In intact LTL samples, NIR spectra were collected after thawing at 4 ± 1 C for 24 h. Subsequently, an aliquot of each sample was minced in order to collect NIR spectra data in both intact and minced modes. For each scan mode (intact and minced), two aliquot samples were scanned by fourier transformation near-infrared spectroscopy (FT-NIRS). From each muscle, one minced sub-sample was collected to determine the fatty acid profile through gas chromatography. NIR spectra were collected using the FT-NIRS Antaris II model (Thermo Scientific, Waltham, MA, USA). Samples were exposed in a circular quartz cup spinner (60 mm of diameter) for an electro-magnetic scan in the absorbance mode.
Each spectral measurement was obtained from 32 scans performed at a wave number resolution of 4 cm -1 over the range of 1000 to 2500 nm and corrected against the background spectra of room environment. Absorbance data were collected as log 1/R (R: reflectance), as it results in a more linear response according to analytic concentration  [20] , and 3. 112 data points were recorded per sample. Each intact and minced sample final spectra was obtained by averaging the performed spectra measurements to assess the potential of FT-NIRS prediction.
5 mL/min and at a split ratio of 1:20. The detector temperature was set at 260 • C. The chromatograms were recorded using computing integrator software (Galaxie Chromatography Data System 1. 9. 302. 952; Varian Inc. ). The FAs were identified by comparing the retention time of FAMEs with the standard Supelco 37-component FAME mix (Supelco) and were quantified through calibration curves using nonadecanoic acid (C19:0) (Supelco) as an internal standard. The amount of each fatty acid was calculated on the total of fatty acids detected and expressed as g/100 g of FAMEs, and the different fatty acid groups were obtained: sum of all saturated fatty acids (SFA) detected (C12:0+ C13:0 + C14:0 + C15:0 + C16:0 + C17:0 + C18:0 + C20:0 + C22:0); sum of all monounsaturated fatty acids (MUFA) detected (C14:1 n-5 + C16:1 n-9 + C16:1 n-7 + C17:1 + C18:1 n-9 + C18:1 n-7 + C20:1 n-9 + C20:1 n-7 + C22:1 n-9 + C16:4 n-1); sum of all polyunsaturated fatty acids (PUFA) detected (C18:2 n-6 + C18:3 n-4 + C18:3 n-3 + C20:2 n-6 + C20:3 n-6 + C20:4 n-6 + C20:3 n-3 + C20:5 n-3 + C22:4 n-6 + C22:5 n-3), as well as the quotient of PUFA n-6/PUFA n-3.
Chemometric Analysis All spectra were processed by chemometric analysis using Unscrambler CAMO ® software. Detection of outliers was performed by observing the spectra plot and by principal component analysis (PCA). Possible outliers were expected to show high residual values and high Hotelling's T2 statistic values. T2 was calculated from the sample scores (samples projected in the PCA model) and indicated the variation of each sample within the model. During the elaboration of the models, outliers were identified and removed. The cleaned data set was then randomly split into four different test sets as follows: (i) Test 1 (80-20%); (ii) Test 2 (60-40%); (iii) Test 3 (40-60%), and (iv) Test 4 (20-80%), where the first number was the percentage of samples used in the calibration tests and the second was the percentage used in the external validation tests.
All calibrations were evaluated in both the full NIR spectra and those reduced into specific regions for each test (1, 2, 3, and 4). Cross-validation with the leave-one-out method was performed to determine the number of factors or latent variables (LVs) in the regression models, avoiding the overfitting, and to validate the calibration model. In this cross-validation process, uncertainty (SECV) and certainty estimators or the determination coefficient (1-VR) were calculated. The predictive ability of the model was analyzed based on the highest value of the determination coefficient (1-VR) and the root mean square error of cross validation (RMSECV). The ratio between the standard deviation (SD) of the set of samples and the SECV (SD/SECV, known as the residual prediction deviation (RPD) index) and the relationship between the interval of composition of the reference data for the collective calibration (Y max -Y min ) and the SECV, known as the range error ratio (RER) index, were calculated since they are considered as statistics indicators with the greatest weight in the precision of a NIRS calibration model  [25].
AKGs 8-11 were also tested in combination with some commonly used antibiotics (Table  2 ). The results showed that synergistic effects could be obtained in some cases, especially when the AKG 8 was combined with gentamicin, and compound 11 was combined with ciprofloxacin and ampicillin. More than four-fold increase of the activity of these antibiotics was recorded on the three selected bacteria, suggesting that the study should be emphasized on such combinations. The overall activity could be considered as important, mainly when viewed that most of the organisms used were antibiotic resistant. This study therefore provides supportive data for the potential use of the studied 1-O-alkylglycerols, in particular AKG 11, as well as in combination with some antibiotics for the treatment of microbial infections.
The precipitation of coffinite would explain the decrease of Si and U concentration in the bulk solution. This mechanism could also trigger the dissolution of the UO 2+x layer by creating undersaturated conditions for UO 2+x at the pellet/solution interface. The surface of the UO 2 pellet was observed regularly by ESEM. Selected micrographs recorded at high magnification highlight the evolution of the UO 2 grains at the solid/solution interface (Fig. 5 ). Selected micrographs recorded at low magnification are presented in Fig. S3  of the supporting data to illustrate massive grain detachment at the pellet surface. These results showed that silicate ions had a deleterious effect on the UO 2 pellet microstructure. As a consequence, the surface area of the pellet in contact with the solution increased through the development of grains roughness and numerous cavities.
6b ). This suggests that the grain indicated by the blue circle may be a neoformed coffinite particle. To determine the structure of this particle, the high-resolution TEM image was analyzed (Fig. 6c ). The d-spacings between the two sets of white lines were 0. 469 nm and 0. 281 nm, respectively, which were identified as the (011) and (121) in coffinite  14, 18. Neither of these two d-spacings belonged to UO 2. The fast Fourier transform (FFT) of the image agreed well with the electron diffraction pattern of this grain, as shown in Fig. 6d. and the formation constant of the hydroxosilicate complex, U(OH) 3 (H 3 SiO 4 ) 3 2-proposed by Mesbah et al. 15  UO 2 (cr) is not allowed to be present in the calculations. Symbol correspond to experimental data at equilibrium (≥ 100 days). Calculations performed by using the Thermochimie database (https ://www.
Conclusion The first evidence of coffinite formation from UO 2 has been obtained at low temperature under conditions relevant for geological disposal of SNF and in uranium ore deposits. In a solution slightly undersaturated with respect to SiO 2 (am) at 25 °C (i. e. [Si] tot = (1. 77 ± 0. 03) × 10 -3 mol L -1 and pH = 9), anoxic conditions provided Eh values in a range that caused the dissolution of UO 2 through oxidative weathering, followed by precipitation of coffinite. In the studied conditions, the precipitation of coffinite was thermodynamically favored as compared with the mixture of UO 2 ⋅2H 2 O (am) and SiO 2 (am). Using current thermodynamic databases, geochemical calculations showed that coffinite coexisted with UO 2 (OH) 3 -predominant species in solution. From a kinetic point of view, the formation of coffinite occurred rapidly and the precipitation of coffinite was unambiguously evidenced after 155 days of leaching at the surfaces of the UO 2 pellet.
The apparent density of each pellet was evaluated by geometrical measurements and compared to the calculated density of UO 2 (d calc = 11 g. cm -3 ). Measurement of the effective density by helium pycnometry allowed the differentiation between the open and closed porosity. The densification rate of the pellet was 93 ± 1% (indicating 7% porosity of which 3% was determined to be closed). The specific surface area of the pellet was too low to be measured using Kr adsorption. Thus, it was estimated from SEM images recorded at low magnification and He pycnometry. SEM images of 92 × 62 µm 2 were binarized using the FiJi software to determine the surface area of the pores in each investigated domain. The pore diameter distribution was evaluated from these images using the "analyse particles" plugin implemented in the FiJi software.
Characterizations of UO 2 pellet. The UO 2 samples were characterized by powder X-ray diffraction (PXRD). PXRD patterns were recorded using a Bruker D8 advance diffractometer with copper radiation (λCu Kα 1,2 = 1. 54184 Å) in a parallel mode and using the reflection geometry. The patterns were recorded between 5° and 100° (2θ) with a step of 0. 02° and a counting time of 3 h. The resulting data were refined using the Fullprof_ suite  38  by applying the Rietveld method and using the Thomson Cox profile function  39. Pure silicon was used as a standard to determine instrumental parameters. Zero shift, unit cell parameters, overall displacement, preferred orientation and anisotropic size model for the microstructural characteristics were considered for all the refinements. The PXRD pattern of the prepared powder showed UO 2+x (fluorite structure-type, space group Fm 3 m) with lattice parameter: a = 546.
X-Ray Photoelectron Spectroscopy (XPS) analyses were carried out with Thermofisher Escalab 250 XI using a monochromatic Al Kα source (hν = 1,486. 6 eV)  43. Due to a charge effect the samples were analysed using a charge compensation flood gun. The instrument was calibrated to the silver Fermi level (0 eV) and to the 3d 5/2 core level of metallic silver (368. 3 eV). The C-1s signal for adventitious carbon was used to correct the charge effect. The C-C/C-H component of C-1s spectra was fixed at 285. 0 eV. The analysis zone was 900 µm diameter spot. The pass energy for overview and high resolution spectra was 150 eV and 20 eV, respectively. The data processing was performed using the commercial Avantage software. For the fitting procedure, a Shirley background has been used. Transmission Electron Microscopy (TEM) characterization carried out using a FEI Tecnai G2 F20 X-TWIN Transmission Electron Microscope operated at 200 kV, equipped with an energy dispersive spectroscopy (EDS) system.
Fast Fourier transformation (FFT) and image filtering were performed using DigitalMicrograph software. The samples after leaching were ultrasonicated in acetone for 30 min at room temperature to separate coffinite particles from the surface of the pellets. The solutions after ultrasonication were dripped onto TEM grids with lacey carbon thin film using pipettes. For each TEM sample, only thin area on the edge of each particle was observed for ideal high-resolution imaging conditions. Modeling of the U speciation in solution. Phreeqc  44  and GibbsStudio  45  codes were used to model the aqueous chemistry of the leaching experiment carried out with UO 2 pellets. ThermoChimie Database vs 10 46,47 was used with some modifications. Selected log K° values used for calculations are summarized in Table  1.
Acknowledgements This project was initiated and partially funded by the  Swedish Nuclear Fuel and Waste Management Co. (SKB). R. C. E and C. W. were supported by funding from the  U. S. Department of Energy, National Nuclear Security Administration, Office of Defense Nuclear Nonproliferation Research and Development  under Contract No. DE-AC02-76SF00515. "Authors acknowledge  Béatrice Baus-Lagarde  and  Bruno Corso  at  ICSM  for the technical support during ICP-MS and XRD analyzes, respectively.
This volume of HCl was sufficient to, within 2 min, drop the pH down to 4. 7, which was a value lower than the pH of the CSL conformation switch  [16]. As a control, the same volume of an iso-osmolar sucrose solution of NaCl was added to the vesicles-containing chamber. PDMS-NBD/calcein and rhodamine-PE were stepwisely imaged using an argon laser line with an excitation/range of emission of 488 nm/500-530 nm (PDMS-NBD/calcein) and 514 nm/600-700 nm (Rhodamine-PE). Images were processed using Fiji/ImageJ software. To calculate the overall fluorescence intensity of loaded calcein immediately before and after (2 min) HCl treatment, 13 images per condition were processed by ImageJ software on the same Region of Interest (ROI). Fluorescence intensity ranged from 0 to 250 and the number of pixels for each intensity was normalized by the total amount of pixels measured.
The atomic factors for the 249 nm line were determined through a King plot analysis 32 using the data for the 324. 7540 nm line ?. Using values of M 324 = 1413(27) GHz u and F 324 = -779(78) MHz fm -2 obtained from the same reference, we find M 249 = 2284(24) GHz u and F 249 = 439(80) MHz fm -2. The extracted radii are in excellent agreement with those measured in the 324 nm transition (see Table  I ), although a factor of 2-4 less precise due to the lower value of F 249 as compared to F 324.
Acknowledgements We acknowledge the support of the ISOLDE collaboration and technical teams, and the  University of Jyväskylä  for the use of the injection-locked cavity. This work was supported by the  BriX Research Program  No. P7/12  and  FWO-Vlaanderen (Belgium)  and  GOA 15/010  from  KU Leuven ,  FNPMLS ERC Consolidator Grant  no. 648381 , the  Science and Technology Facilities Council  consolidated grant  ST/P004423/1  and continuation grant  ST/L005794/1 , the  EU Seventh Framework  through  ENSAR2  ( 654002 ), and by the  Office of Science, U. S. Department of Energy  under Award Numbers de-sc0013365 and de-sc0018083 ( NU-CLEI SciDAC-4 collaboration ). We acknowledge the financial aid of the  Ed Schneiderman Fund at New York.
(2009) , and provide it in Table 1. To this end we retrieved fully reduced mediumresolution (R ∼ 700) Spitzer archival spectra from  Pontoppidan et al. (2010)  or from the online CASSIS database  (Lebouteiller et al. 2015 ) and used the same wavelength ranges as in  Banzatti et al. (2019)  to compute the mean flux densities at the relevant wavelengths. The CASSIS database only offers low-resolution Spitzer spectra of MP Mus and V836 Tau, so we use the wavelength ranges adopted in  Furlan et al. (2009) , appropriate for the lower spectral resolution. Finally, the highresolution Spitzer spectrum from TWA3A is of poor quality, with a large discontinuity between the short and long wavelength modules. Hence, for this source we use the Spitzer IRAC and MIPS photometry closest to the 13 and 31 µm wavelengths to calculate the spectral index in Table  1.
g. ,  Najita et al. 2010; Szulágyi et al. 2012; Espaillat et al. 2013). Regardless of the EUV spectrum, centimetric radio data demonstrate that the EUV luminosity impinging on the disk surface is too low to reproduce the observed [Ne II] 12. 81 µm luminosities  (Pascucci et al. 2014). This means that Ne atoms are ionized by 1 keV hard X-ray photons via the Auger effect. X-rays are also likely to heat the gas in the same region, although it remains unclear whether they are the dominant heating source. A prediction from static disk models is that the [Ne II] 12. 81 µm luminosity should scale almost linearly with L X in the X-ray-heated disk layer (e. g. ,  Hollenbach & Gorti 2009; Aresu et al. 2012). While several of the data points fall on the predicted relation (see Figure  4 ), the current dataset cannot confirm the existence of a correlation between L [NeII] and L X.
81 µm fluxes obtained from the Spitzer/IRS medium-resolution spectra (slit width 4. 7 ) with those recovered with the much narrower slits of VISIR 1 (∼ 0. 4 ) and 2 (0. 75 ) for the targets in Table  1. Except for TWA3A, V4046 Sgr, S CrA, T CrA, TY CrA, and VV CrA, all Spitzer [Ne II] fluxes can be found in the following papers:  Pascucci et al. (2007) ;  Güdel et al. (2010); and Rigliaco et al. (2015). TY CrA was not observed with Spizer/IRS. For the other five sources we retrieve reduced Spitzer spectra from the online CASSIS database  (Lebouteiller et al. 2015)  and, following  Rigliaco et al. (2015) , we fit a Gaussian profile when the [Ne II] transition is detected (for V4046 Sgr and T CrA) or calculate a 3σ upper limit when it is not detected (for TWA3A, S CrA, and VV CrA). The left panel of Figure  12  compares the Spitzer (blue) and VISIR (black) fluxes (circles) or upper limits (downward triangles) for each source.
VISIR [Ne II] detections and upper limits. Note-Negative EW values are used to indicate upper limits. Disk inclinations are provided for sources with a [Ne II] detection to evaluate de-projected centroid velocities. References are given for the disk inclination, the continuum flux density (Fcont) for VISIR 2 data, and the [Ne II] properties for VISIR 1 data. bDatasetacquired on 26-11-2017, the emission is also detected in the 28-12-2017 dataset at a slightly lower S/N c Highly inclined disks, see Section 3 and Appendix B for details on the re-assignments. dSR21 and V4046 Sgr were observed in two and four slit orientations, respectively. The [Ne II] emission is detected in all exposures with similar shape and intensity. Here, we provide results from the first exposures, slits oriented N-S. Histograms showing the distribution of [Ne II] HVC (green) and LVC (purple) detections in comparison to that of non-detections (grey) for the sources in Table1.
and are necessary to test our proposed evolutionary scenario. ACKNOWLEDGMENTS Based on observations collected at the European Southern Observatory under ESO programme 198. C-0104. I. P. , U. G. , and S. E. acknowledge support from a Collaborative NSF Astronomy & Astrophysics Research grant (ID: 1715022, ID:1713780, and ID:1714229). This material is based on work supported by the National Aeronautics and Space Administration under Agreement No. NNX15AD94G for the program Earths in Other Solar Systems. The results reported herein benefitted from collaborations and/or information exchange within NASAs Nexus for Exoplanet System Science (NExSS) research coordination network sponsored by NASAs Science Mission Directorate. R. D. A. , G. B. , and C. H. acknowledge funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 681601).
58 19 25 TCha 42. 0 -4. 0 75 -5. 09 LVC 20,18 26 MPMus 15. 9 -4. 4 30 -5. 48 LVC 21,14 27 Sz73 60 -99. 0 48 -5. 08 HVC 22,18 28 Sz102 <-5. 40 18 29 V853Oph 26. 5 -35. 8 54 -5. 66 HVC 5,19 30 DoAr44 <-5. 7 14 31 RXJ1842. 9-35 <-5. 83 14 References-1. this work (using Spitzer/IRS spectra from either the CASSIS database or from Pontoppidan et al. 2010); 2. Simon et al. (2017); 3. Rigliaco et al. (2015); 4. Loomis et al. (2017); 5. Tripathi et al. (2017); 6. McClure et al. (2015); 7. Kellogg et al. (2017); 8. Pontoppidan et al. (2011); 9. Francis & van der Marel (2020); 10. Rosenfeld et al. (2013); 11. Vaňko et al. (2013); 12. Boersma et al. (2009); 13. Whelan et al. in prep. ; 14. Sacco et al. (2012); 15. Andrews et al. (2016); 16. Pascucci et al. (2011); 17. Hendler et al. (2020); 18. Pascucci & Sterzik (2009); 19.
Acknowledgements We gratefully acknowledge the financial support provided to the PIVOTS and the  CAPEL-MIP  projects by the  Region Centre -Val de Loire  ( ARD 2020 program  and  CPER 2015 -2020 ) and the  French Ministry of Higher Education and Research  ( CPER 2015 -2020  and public service subsidy to  CNRS and University of Orleans ). This operation is also co-funded by the  European Union. Europe is committed to the  Center-Val de Loire region  with the  European Regional Development Fund.
The root mean square for A and S reduction considering the full dataset is respectively 210. 5 and 24. 5 kHz, using 26 parameters for A reduction and 23 for S reduction. Here we only provide the fitting results using the reduction S. In order to compare our parameters with the ones from  Hahn et al. (2004) , we refitted these data using reduction S. Results can be found in Table  1. Some of the new measurements are in Table  2. Figure  1  shows an example of an observed spectrum. Higher numbers of lines in the experimental spectrum compared to the predicted one come from excited vibrational states. The complete version of the global fit Table (S1) is supplied at the CDS. The fitting files useable with SPFIT, namely. lin (S2),. par (S3), which contain the measured lines and the spectroscopic parameters respectively, and the prediction.
Sources We conducted a search for cyanoketene in a variety of astronomical sources. The observational details of these datasets have all been presented elsewhere (see Table  3 ); only a brief   Fig. 1. Predicted (in red) and observed (in blue) rotational spectrum of NC-CH=C=O between 236. 9 and 241. 3 GHz. The low-frequency region of the spectrum shown here is dominated by a series of R-type transitions, J = 44-43, while the high-frequency region is dominated by a series of Q-type transitions, K a = 5-4. The slight inconsistency between predicted and observed spectrum intensities is due to source power and detector sensitivity variations. Notes. ( a) Except where noted, the source is assumed to fill the beam. ( b) For these interferometric observations, the intensity is given in mJy beam -1 rather than mK.