dataesr/scientific-paragraphs-categorization huggingface dataset:
e. , tail-correction was applied). PLD and VF were calculated using algorithms available in the ZEO++ software. 30 All atomic structures and accessible surfaces were visualized in VESTA  31  and iRASPA 32 software, respectively. Absolute change of PLD and VF is defined as Δ = - X X X (distorted structure) (undistorted structure) (4) where X is considered parameter. Accessible Surface. Accessible surfaces were calculated using iRASPA software  32  with nitrogen as a probe molecule. This surface is an isosurface where energy of interactions between probe and framework is equal to 0 (r = σ LJ ). Practically, it means that the volume inside the pore corresponds only to the positions of the center of mass of adsorbed molecules. Hence, even a very thin channel which connects the neighboring pores indicates the possibility of gas diffusion in the framework.
K. , Japan) for HA or CATSEC 100 and 1000 columns (Eprogen, USA) for DEAE-D. The eluents for HA and DEAE-D were LiNO 3 0. 1 mol. L -1 and acetate buffer 0. 1 mol L -1 (pH = 5) respectively. The injected sample volume for each analysis was 100 μL. The samples for analysis were solutions of HAs of medium and high molar masses and DEAE-D at concentrations of 1 g L -1 , 0. 1 g L -1 and 0. 5 g L -1 respectively, prepared in the corresponding eluents by stirring overnight at 200 rpm at room temperature and filtered through a 0. 45 µm filter units (Sartorius, Germany). The results were treated using Astra 6. 1. 7. 16 ® software package via a data processing Zimm order 1  [47]. The refractive index increment (dn/dC) of 0. 15 mL/g was applied for both HA and DEAE-D  [48, 49]. For DEAE-D, molar mass distribution was fitted using 1st order exponential model.
5 cm -1. Typical experiment leads to the acquisition of hundreds of FTIR https://doi. org/10. 5194/amt-2021-19 Preprint. Discussion started: 16 February 2021 c Author(s) 2021. CC BY 4. 0 License. spectra. To perform the analysis of huge datasets, a home-made software algorithm was written to retrieve NO2 concentrations. Typical detection limits in absorption spectra recorded by co-adding 100 scans (i. e. with an integration time of 5 min) for various gaseous compounds are listed as follows: NO2 (5 ppbv), Ozone (5 ppbv), HONO (10 ppb), CH2O (3 130 ppbv) or HNO3 (10 ppbv).
When NO2 concentration inside the chamber stabilized at 120±5 ppbv, water vapor produced in a small pressurize stainless steel vessel filled with ultrapure water (18. 2 Mohm, ELGA Maxima). The relative humidity (RH) inside the chamber was allowed to increase to ~60% at 23 o C (corresponding to an absolute H2O vapor 165 mixing ratio of ~1. 6%). Under these conditions, as described by  Wang et al. (2011) , a significant gas-phase HONO is systematically observed. As described in the literature  (Finlayson-Pitts et al. , 2000; Lammel et al. , 1995; Spataro et al. , 2014). It is generated through heterogeneous formation on chamber inner surfaces via a complex reaction of NO2 with adsorbed H2O chamber walls. All the instruments (UV-IBBCEAS, FTIR, NitroMAC, NOx analyzer, temperature and humidity sensor, pressure gauge) 170 simultaneously recorded the relevant data (including NO2, HONO, NO and H2O concentrations, temperature and pressure) for data analysis and instrument intercomparison.
Absolute NO2 concentrations obtained by FTIR were used for the determination of cavity mirror reflectivity. Four NO2 injections in the presence of humid air were organized during the four days of experiments. During the last experiment, an injection of formaldehyde (HCHO) was performed to allows the investigation of the sensitivity of the UV-175 IBBCEAS data analysis to the interferences in the UV range. Formaldehyde was prepared by sublimating commercial paraformaldehyde (CH2O)n (Fluka, "extra pure" grade) under vacuum in a glass line and collected at a known pressure in a bulb of known volume. This quantity was then flushed into the chamber with a gentle flow of pure nitrogen. A controlled dilution flow was allowed to the chamber to induce a forced decrease of the sampled concentrations and hence testing the quantification performance of the various analytical devices across a few orders of magnitudes.
(  2 ), as shown in Fig. 3(a). With the measured mirror reflectivity R(), the real cavity length d, and absorption cross 200 sections of the target gas from a common database, target gas concentrations can be simultaneously retrieved using a least-squares fit to the experimentally measured absorption coefficient (): HONO  (Stutz et al. , 2000)  and CH2O  (Meller et al. , 2000)  were convoluted with the instrument function of approximate 0. 59 nm (the spectrometer resolution). nNO2, nHONO and nCH2O are the concentrations (number densities) to determine for NO2, HONO and CH2O, respectively. The second-order polynomial term in Eq. (3) represents the variation in spectral baseline which could arise from gas scattering, LED intensity fluctuations, and other unspecified loss processes. The unknown 210 parameters (number densities nNO2, nHONO, nCH2O, a, b and c) can be extracted using a linear algebraic method known as the singular value decomposition (SVD) method.
FTIR spectra Infrared spectra were obtained at a resolution of 0. 5 cm -1 and derived from the co-addition of approximately 200 scans 235 collected over 5 min. Concentrations of the interested species were determined by subtracting pure reference spectra (brought to the experimental resolution of 0. 5 cm -1 ) from spectra of reaction mixtures using home-made software based on matrix algebra. To guarantee the performance of the automatic routine, selected spectra for each experiment were subtracted manually and results were compared. Spectroscopic information used for the FTIR data analysis are given in table 1. HONO absorption was analyzed from its ν3 absorption bands around 1263 cm -1 using the synthetic reference spectrum proposed by 240  Barney et al. (Barney et al. , 2000)  and modified by  Barney et al.
Results and discussion During the intercomparison experiments in the CESAM atmosphere simulation chamber, time series measurements of NO2, 245 HONO and CH2O were simultaneously performed using the UV-LED-IBBCEAS, FTIR spectrometer, NOx analyzer and NitroMAC. Before HONO, NO2 and CH2O intercomparison measurements, a FTIR was used to measure absolute NO2 concentrations between 60 and 120 ppbv for determination of the IBBCEAS cavity mirror reflectivity. The measured mirror reflectivity (R) is shown in Fig. 3  The UV-LED-IBBCEAS spectrometer recorded spectra of the transmitted light intensity with an integration time of 1 s, and 120 such acquisition data were then averaged to produce one datum for I0(λ) or I(λ) (i. e. a net acquisition time of 2 min per 255 datum). The response time of the NitroMAC was 10 min for one measurement of HONO concentration.
Acknowledgments The authors acknowledge financial supports from the  French Agence Nationale de la Recherche (ANR)  under the  CaPPA 380  ( ANR-10-LABX-005 ) contract, as well as the support in the framework of the  CPER CLIMIBIO program  funded by  Nord-Pas de Calais Region and the Ministère de l'Enseignement Supérieur et de la Recherche. CNRS-INSU  is gratefully acknowledged for supporting the CESAM chamber as a national facility (http://cesam. cnrs. fr). European Union's  Horizon 2020 research and innovation program  through the  EUROCHAMP-2020 Infrastructure Activity  under grant agreement  n°730997  is also gratefully acknowledged for distributing freely the ANIR deconvolution software as well as  Mila Rodenas   385  and the  Centro de Estudios Ambientales del Mediterráneo  ( CEAM -Valencia ) for sharing the software and providing the guidance in using it.
This study was designed to optimise an analytical method for characterising TiO2 nanoparticles (NPs) in food additives and pharmaceuticals by inductively coupled plasma-mass spectrometry in single particle mode (spICP-MS). Several parameters, including transport efficiency (TE), were assessed and optimised using the NM-100 reference material. We found that self-aspiration for sample intake and use of the concentration-based method for TE was optimal for characterising TiO2 NPs. No spectral interference was observed with either 49 Ti or 48 Ti isotopes. The optimised Excel spreadsheet developed for this study not only provided additional parameters but gave results closer to the NM-100 reference value than the ICP-MS software. The method was then applied to the analysis of a selection of food samples and pharmaceuticals.
Analysis and data processing Before analysis, the NP dispersions were homogenised by vortex agitation for 5 -10 s. The samples were then analysed by spICP-MS in standard mode using the high sensitivity option (STDS); the intensity data were recorded using the npQuant module of the Qtegra ISDS software (version 2. 8. 2944. 202) and exported to an Excel spreadsheet (Microsoft®) for further processing. A comparison of the optimised Excel spreadsheet and of the capacity of ICP-MS software is presented hereafter. NPs were considered spherical and with a density of 3. 9 g. cm - 3 , which corresponds to the density of the anatase structure  [52].
Data processing optimisation The data obtained by spICP-MS can be processed using the npQuant module, which is part of the QTegra platform of the ICP-MS used. The main advantage of the npQuant module is that it allows fast data processing, but it should be stressed that this module has limitations in terms of the parameters available, lacks flexibility and provides no information on data processing protocols. It was therefore decided to develop an in-house spreadsheet that could be optimised for this study based on the spreadsheet previously described by  Peters et al. (2015)   [54]. The modifications made are presented in Table  1. The daily results for the key parameters obtained from analysis of the NM-100 material were statistically compared with results for those same parameters from the ICP-MS software using a Student's paired t-test (n=15, p=0.
05) (SM Table  A4 ). The in-house spreadsheet and ICP-MS software provided similar results only for ionic sensitivity and size limit detection, while a significant difference was observed for TE assessment. It is difficult to justify the difference observed for the TE calculation given the impossibility of knowing how it is calculated by the ICP-MS software, although we know that it is based on the theory presented by  Pace et al. (2011)   [37]. This may explain the differences between the TiO2 diameters obtained, with diameters provided by the in-house spreadsheet being systematically greater than those obtained with the ICP-MS software. It is worth noting that the average diameter obtained with the in-house spreadsheet (158 ± 11 nm, n=15) was closer to the JRC value (162. 4 ± 4. 3 nm)  [49]  than that obtained with the ICP-MS software (130 ± 12 nm).
These results reveal the benefits in developing one's own in-house spreadsheet for spICP-MS data processing. The advantages and drawbacks of these two data processing systems are described in more detail in SM Table  A5. But generally speaking, although the ICP-MS software is able to process data directly and quickly, until such time as it becomes more efficient and provides open access to information on the data processing protocols used, an in-house spreadsheet is advantageous because our results were closer to the NM-100 reference value while offering additional parameters. Our in-house spreadsheet was consequently used to characterise TiO2 NPs in the real samples analysed (see SM spreadsheet for for NPs samples).
Food sample analysis The spICP-MS method developed in this study for TiO2 NP characterisation was used to analyse a selection of 11 food samples (Table  2 ). The NPs were extracted according to the protocol described in section 2. 3. 2. To analyse samples of frozen desserts and pastries, only a fraction was taken for extraction and further analysis (SM Table  A1 ) so the results in terms of NP concentration are not reported because of the lack of representativeness of the whole sample. The dilution was optimised for each data acquisition replicate, and the number of particles detected varied between 600 and 1600, which corresponds to about 25-100 x 10 3 particles/mL with a TE of 2%. The analysis of each parameter was thus assessed based on at least 3600 particles (600 x 6 replicates). Concerning the data comparison related to 48 Ti and 49 Ti isotopes, 48 Ti provided a lower sLOD, which is in agreement with Bucher et Auger (2019)  [55].
Conclusion This study reports the optimisation and application of a novel analytical method for characterising TiO2 NPs in foodstuffs and pharmaceutical samples by spICP-MS. Firstly, this work focused on assessing the most accurate method to determining transport efficiency, which is one of the main experimental parameters in spICP-MS. To process the spICP-MS data, we then optimised an in-house spreadsheet to assess a panel of parameters (e. g. nanoparticular fraction and the most frequent diameter) for characterising NPs, and compared it with data provided by the ICP-MS software. This in-house spreadsheet provided a more accurate average diameter for TiO2 NPs in the NM-100 reference material. The method was also applied to the analysis of a selection of foodstuffs and pharmaceuticals likely to contain E171, hence demonstrating the suitability of the spICP-MS approach for the comprehensive characterisation of NPs in such samples.
We use an end-to-end model of the instrument to simulate high-contrast observations performed with HARMONI, based on realistic observation scenarios and observing conditions. We then analyze these data with the so-called "molecule mapping" technique combined to a matched-filter approach, in order to disentangle companions from the host star and tellurics and increase the signal-to-noise ratio of the planetary signal. We detect planets above 5σ at contrasts up to 16 mag and separations down to 75 mas in several spectral configurations of the instrument. We show that molecule mapping allows here to detect companions up to 2. 5 magnitudes fainter compared to state-of-the-art classical high-contrast imaging techniques based on angular differential imaging. We also demonstrate that the performance is not strongly affected by the spectral type of the host star, and we show that we reach close sensitivities for the best three quartiles of observing conditions at Armazones, which means that HARMONI could be used in near-critical observations during 60 to 70% of telescope time at the ELT.
In the present work, we estimate the capabilities for direct exoplanet detection of HARMONI, by generating realistic simulations of observations performed with its high-contrast module and analyzing them with the molecule mapping technique. First, we introduce in Sect. 2 the high-contrast module of HARMONI. The simulation model of the instrument, i. e. , simulations of the adaptive optics, coronagraphic images and the injection of fake objects and noises, is described in Sect. 3. We then describe the setting of the simulated observing sequence and the astrophysical parameters of the injected objects in Sect. 4. In Sect. 5 we explain how we analyze the simulated data using the molecule mapping framework. We present the results in Sect. 6, and we conclude in Sect. 7.
Photometry The last part of the simulation takes as input the high-contrast images simulated as described in the previous section. The goal of the photometry module is to apply realistic photometry to the science images, inject fake planets into the data and finally apply the various noise sources induced by the detection process. This module relies heavily on the HSIM tool v300 3   (Zieleniewski et al. 2015) , which has been developed as a generic simulation tool for the HARMONI instrument. For technical reasons, HSIM is however not yet compatible with the HARMONI-HC module, so our high-contrast simulations do not use directly HSIM but instead use the same inputs as HSIM (transmission files, thermal background estimates, detection noises, etc). The input models for the stellar photometry are the BT-NextGen PHOENIX models  (Allard et al.
To avoid superposition, this set of 110 companions is split into four complementary datasets independently created and analyzed, with separation increments of 50 mas and position angle increments of 72 • , as presented in Fig. 3. We generate these four datasets for ten different star-to-planet contrasts ∆H or ∆K (depending on the spectral configuration) going from 9 to 18 mag. We simulate this for each one of the six spectral configurations of the HARMONI-HC module described in Table  1 , and for the two types of companions. This amounts to a total of 480 different simulations for the reference cases. The results will be presented in Sect. 6.
Acknowledgments We are grateful to the  « Institut de Chimie des Substances Naturelles » (ICSN ,  UPR CNRS 2301 ) for a PhD grant (AL), the  Centre National de la Recherche Scientifique (CNRS) , the  Ministère de l'Enseignement Supérieur, de la Recherche et de l'Innovation (MESRI) , to  Loic Toupet  ( Institut de Physique ,  UMR CNRS 6521 ,  Univ Rennes 1)  for X-ray analysis of 18, to  Julie Hémez  and  Laurence Arzel  ( CEISAM, UMR CNRS 6230 ) for HRMS analyses.
Optical Microscopy Photographs were taken with a Nikon Eclipse LV100 optical microscope, equipped with a Nikon Digital sight DS-Ri1 camera, or with a Nikon SMZ-10A binocular optical microscope equipped with a Sony Power HAD camera. Both microscopes possess a pair of cross polarizers. The software used to exploit the results is Nikon NIS Elements D V3. 1. To perform temperature-regulated microscopy, a hot/cold stage chamber Linkam THMS 600 was used.
X-ray Powder Diffraction (XRPD) XRPD measurements were carried out on a Bruker D8 Discover apparatus using the Cu Kα radiation (1. 54 Å). The samples were scanned from 3 to 30 • 2θ angles, with a 0. 02 • step (2 s duration). The detector slit was set at 0. 2 mm. The analyses were done using quartz as internal standard. The software used to exploit the results is Bruker DIFFRAC. EVA V4. 1.
Single-Crystal-X-ray Diffraction (SC-XRD) The crystal structures were determined from single-crystal diffraction on a Bruker SMART diffractometer equipped with an APEX detector (with Mo Kα1 radiation: λ = 0. 71073 Å). The cell parameters and the orientation matrix of the crystal were preliminarily determined using SMART Software (Bruker). Data integration and global cell refinement were performed with SAINT Software, (Bruker). The structures were solved by direct methods (SHEL-XS). Anisotropic displacement parameters were refined for all non-hydrogen atoms using SHEL-XL available with the WinGX package [20].
8% ethanol. In comparison with the particle obtained in the presence of water (Figure  9a ), the vacuole occupies a more important fraction of the crystal. The software "Material Studio" was used to refine the lattice parameters (Table  1 ) is confirmed that the salt crystallized in an orthorhombic system with a space gro Figure  10b  shows a projection along the 'a' axis of the structure. The polar periodic bond chains propagate along the 'a' axis, forming a polar column (Figure  10a ). The rest of the crystal structure is definitively hydrophobic. In the partial solid solution domain, the substitution of one IBU enantiomer by the other disrupts the quality of the single crystals but not that much the crystal lattice. It is likely that the R enantiomer existing in the matrix of the ss-S-IBU/S-αMBA results from the inversion of the methyl moiety by the hydrogen atom; this minimizes the steric hindrance.
The software "Material Studio" was used to refine the lattice parameters (Table  1 ). It is confirmed that the salt crystallized in an orthorhombic system with a space group P2 1 2 1 2 1. In the case of the upper limit in composition of the solid solution, the 'c' axis increases more than the other parameters. The C*-CH3 covalent bond in IBU and the 'c' axis are 19. 3 • only apart (see SI Figure  S6 ). This crystallographic data is thus consistent with the partial substitution of S-IBU by R-IBU by means of inversion between both the methyl and the hydrogen in the alpha of the stereogenic carbon. The software "Material Studio" was used to refine the lattice parameters (Table  1 ). It is confirmed that the salt crystallized in an orthorhombic system with a space group P212121. In the case of the upper limit in composition of the solid solution, the 'c' axis increases more than the other parameters.
The C*-CH3 covalent bond in IBU and the 'c' axis are 19. 3° only apart (see SI Figure  S6 ). This crystallographic data is thus consistent with the partial substitution of S-IBU by R-IBU by means of inversion between both the methyl and the hydrogen in the alpha of the stereogenic carbon. Table  1. Comparison between the lattice parameters of the ss-S-IBU/S-αMBA with a composition of X R-IBU/S-αMBA = 0. 14 (powder), the single crystal (X R-IBU/S-αMBA ≈ 0. 18), and the pure salt S-IBU/S-αMBA (powder). Data obtained from the software Material Studio.
Chromatography The liquid chromatography system used was the 1220 Infinity II set from Agilent (Santa Clara. CA. USA) including a quaternary pump, mobile phase degasser, 96 vial sample injector, column thermostat, and diode array UV detector. A personal computer drove the chromatographic system and handled data with the OpenLab CDS ChemStation software (Agilent). Acetonitrile solutions of all racemic samples were made at a concentration of 2 mg/mL. One microliter of each individual solution was injected for each analysis. Table  1  lists the characteristics of the chiral columns used  [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23]. Except for the NicoShell column (3 mm i. d. ), the AZYP columns were all 4. 6 mm internal diameter columns packed with superficially porous (SPP) 2.
Differentiation of HL60 cells HL60 cells were used to determine pro-differentiating activities of studied compounds. After initial screening the concentration ranges were established for each compound. 1,25D was tested at concentrations 0. 032-100 nM. Compounds 4a, 4b and 2Z were tested at concentrations 0. 032-500 nM, while 3a, 3b and 2E were applied at concentrations 4-50 µM. The cells were exposed to the compounds for 96 h and then the expression of monocyte/macrophage differentiation marker CD14  [46]  was studied using flow cytometry. Percentages of CD14-positive cells were read out using Becton Dickinson Accuri C6 software. Results are presented in Fig. 5. EC50 values were estimated from dose-response curves using GraphPad Prism 7 software. Effective molar ratios (EMR) for each compound in comparison to 1,25D for CD14 antigen are presented in Table  2.
At 10 nM concentration 4a was significantly stronger than 1,25D in activating expression of CD14 gene in the same cells (Fig. 7d ). Three independent experiments were performed, and in every experiment each measurement was done in triplicate. Points on the graph represent means (±SEM) of all measurements. The nonlinear regression curves were fitted to the obtained means using GraphPad Prism 7 software for a one-site binding model.
Docking procedure The proposed LCA ligands were built, using the three-dimensional structure of 1,25D, obtained from the crystallographic structure of 1,25 D in complex with hVDR (PDB code: 1DB1)  [29]. Modifications to the ligands were carried out with the builder mode of Pymol and the editing tool provided by the Chem3D software. Docking studies to predict the affinity of each ligand for the VDR LBD were made using the Gold software (version Suite 5. 4). A modified structure of VDR LBD, with inclusion of hydrogens and missing gap regions, was used as the  protein. The binding site of the protein was set automatically with a 6 Å radius. Docking was performed in 25 independent genetic algorithm (GA) runs. In each run, a maximum of 125,000 GA operations were performed in a single population of 100 individuals.