dataesr/scientific-paragraphs-categorization huggingface dataset:
These different aspects can be probed by various technologies, including structural determination, genetic editing, metabolomics, various animal models, chemical biology, basic biochemistry, etc. Among them, structurebased techniques are commonly used to improve our understanding of substrate specificity determinants. As such, they bear a great potential to guide the rational design of prospective new drugs. Importantly, these methods are most powerful when integrating experimental information together with data generated in silico  [4, 5]. The experimental determination of SLC 3D structures is challenging due to the inherent difficulty of expressing and purifying membrane proteins in their native state. As a result, about 100 structures of human SLCs have been resolved to this day, and they represent only 25 unique proteins.
As compared to ethanol, DCM has (i) a lower viscosity (~0. 3 / 1. 2 mPa. s), (ii) a higher vapour pressure (~48 / 6 KPa) and (iii) a lower boiling temperature (40 / 80 °C). The physical-chemical properties of DCM allow thus for a higher bubbling of the solvent when it reaches the nozzle, a more effective atomization and a faster solvent evaporation. The droplet evaporation rate is estimated from the reduction of the average droplets size when travelling along the axial path. From the analysis of data at Ti=140 °C and Pi=20 bar, we observe an average droplet size reduction, after travelling for 1 cm between 7 and 8%, with an average diameter reduction from 1. 8 to 1. 65 µm for DCM (Figure  2b ). The droplet velocity mainly depends from the pumping capacity and varies from 50 to 200 m/s with an average value at 160 m/s.
N H N R 1 R 2 R 3 R 4 R 5 R 6 R 7 R 8 1a-o C. Scheme 1. Reagents and conditions: (i) piperidine, EtOH, reflux, 6-8 h. The structure of compounds 1e and 1i were demonstrated by single crystal X-ray diffraction method. According to X-ray crystallography the two compounds are isostructural. They crystallize in P21/c space group with close unit cell parameters (Table  1S , see supplementary data section for full data). The asymmetric part of the unit cell (Figure  2a , 2b) comprises one molecule of 1e and 1i as a crystallographic independent unit, respectively. There are no co-crystallized solvent molecules in both crystals. -o i R 1 R 2 R 3 R 4 R 5 R 6 R 7 R 8 R 1 R 2 R 3 R 1 R 2 R 3 R 4 R 8 R 7 R 6 R 5 R 4 R 5 R 6 R 7 R 8 R 1 R 2 R 3 R 4 R 5 R 6 R 7 R 8 4a: R 4 = CF 3 , R 5 =R 6 =R 7 =R 8 =H 4b: R 4 =OMe, R 5 =R 6 =R 7 =R 8 =H 4c: R 4 = Br, R 5 =R 6 =R 7 =R 8 =H 4d: R 4 =Cl, R 5 =R 6 =R 7 =R 8 =H 4e: R 4 =R 6 =Cl, R 5 =R 7 =R 8 =H 4f: R 4 =R 6 =F, R 5 =R 7 =R 8 =H 4g: R 4 =CH 3 , R 5 =R 6 =R 7 =R 8 =H 4h: R 6 =Cl, R 4 =R 5 =R 7 =R 8 =H 4i: R 4 =F, R 5 =R 6 =R : i) -x, -0.
Acknowledgements The authors acknowledge the  Executive Unit for Financing Higher Education, Research, Development and Innovation (UEFISCDI) ,  Romania , for financial support of this work which is part of the project  PN-III-P4-ID-PCE-2020-0818  (REPAIR). The authors also thank the  CERNESIM Center  within the  Interdisciplinary Research Institute at "Alexandru Ioan Cuza" University of Iasi, Romania  for the infrastructure used in recording NMR experiments.
Such a representation facilitates the comparison between data from different samples. The data are also represented as 3D plots, which help visualizing the features of the scattering curves (Figure  2 ). Selected scattering curves are individually analyzed to assess the morphology and size of the scattering particles. The analysis comprises both comparison of the measured data with theoretical models and analysis of the low q scaling behavior of the scattered intensity I ∼ q -m. For non-interacting particles, the scaling exponent m is related to the fractal dimension of the scattering objects, thereby providing information on their shape. The SAXS data (Figures  1a  and 2a,b ) reveal that Me-EO 45 -CL 30 is molecularly dissolved for T > 20 °C in mixtures with the composition in the range 0.
Measurements were performed in 1 mm quartz capillaries which were cooled down from T = 70 °C to T = -20 °C by means of a Linkam heating stage. Before filling the capillaries, the BCP solutions were preheated at 70 °C on a heating plate. A cooling rate of v c = 10 °C•min -1 was applied. The scattered X-rays were simultaneously detected using two CCD detectors, Rayonix LX-170HS collecting the atomic diffraction from the system at wide angles and Rayonix MX-170HS collecting the small-angle scattering. The small-angle detector was placed at a 1 m distance from the sample to access a scattering vector (q) range of 0. 06 < q < 6 nm -1. Automatic data reduction and calibration were performed at the beamline. Multiple analysis cycles were performed for some selected samples (data not shown). The data obtained in the different cycles did not show significant differences, demonstrating the reproducibility of the observed processes.
Analysis of the Scattering Data. The scattered signal of an empty capillary, used as a background, was recorded at different temperatures, -20 °C < T < 70 °C. Background subtraction was automatized by means of a custom-made script. Ethanol was not included in the background for two reasons: first, different capillaries have different diameters, and therefore, subtraction of the ethanol signal could have resulted in negative scattering data at high q; second, the scattering of ethanol is expected to be q-independent at small angles, and hence, its contribution is a constant. The script for the background subtraction operates as follows: the scattering patterns of the empty capillaries and the samples are indexed based on the acquisition temperature. For each sample, the script subtracts the background recorded at the closest temperature.
The temperature differences between the sample and background were always smaller than 1 °C. Comparison or fitting of the scattering data with theoretical form factors and structure factors was performed with SasView 36 4. 2. To provide details about the scattering models used here, the original papers are cited during the discussion. For details about the implementation of these models, the reader is referred to SasView documentation. Some parameters of the scattering models are accompanied by polydispersity indices. These represent the ratio between the average parameter value and the width (i. e. , standard deviation) of the simulated Gaussian distribution. If polydispersity is not indicated, the parameter is assumed to be uniform. Scanning Probe Microscopy. Height and phase characterizations were performed with an NT-MDT Solver Next SPM in the semicontact (tapping) mode using the Bruker silicon tips, RTESPA-150 as well as PEAKFORCE-HIRS-F-A.
For each cylinder, the cross-section was measured at four different locations. Cryogenic Transmission Electron Microscopy. Cryo-TEM samples were prepared on QUANTIFOIL R2/2 (Electron Microscopy Sciences) grids. Grids were glow-discharged for 70 s to increase hydrophilicity prior to sample loading. Vitrification was carried out using an Automatic Plunge Freezer ME GP2 (Leica Microsystems) with 3 μL of the sample. Grid preparation was performed at 95% humidity, and the grids were blotted for 3 s prior to plunging into liquid propane. Cryo-TEM samples were then placed on a Gatan cryo-TEM holder and imaged on a JEOL 2100F TEM using a Schottky-type field emission gun operating at 200 keV. Images were recorded using SerialEM software in the low-dose mode with a Gatan OneView CMOS camera at a 4k × 4k resolution.
Prior to vitrification, samples of PCL 30 -b-PEG 45 (50 mg/mL) were heated up to 70 °C and cooled with an average cooling rate of 20 °C/min. Following cooling, samples were immediately diluted to 10 mg/mL and vitrified. Dilution was necessary in order to image the sample using cryo-TEM. Selected images have been analyzed to determine the size of the spherical micelles and the cross-sectional diameter of the cylindrical micelles. The analysis (see Figure  S4d ,e) was performed on 100 particles per sample; the data in the main text are presented as the average ± standard deviation.
1) • C using a Metrohm 827 pHmeter and the pH was adjusted with solutions of NaOH (0. 1 M and 1 M) and HCl (0. 1 M and 1 M). The Statsoft Statistica 10. 0© software was used in all statistical analyzes and to draw the response surfaces. The obtained results were statistically analyzed with a 95% confidence level, and a student t-test was applied to verify the statistical significance of the adjusted data (Supplementary Information, Tables  S7-S13 ). The regression coefficient (R 2 ), the lack of fit and the F-value obtained from the analysis of variance (ANOVA) were evaluated to determine the model's adequacy.
5 mL/min with an injection volume of 25 µL. The column oven and autosampler temperatures were kept at 40 • C and 10 • C, respectively. The wavelength was set at 280 nm using a DAD detector. The obtained chromatograms were analyzed using the PeakFit version 4 software. The SE-HPLC method applied was optimized for proteins quantification. Samples of IL aqueous solutions (with no proteins) were also run in the equipment, showing that they do not interfere with protein quantification. The purity (%Purity RuBisCO ) and yield of RuBisCO (Yield RuBisCO ) were calculated using Equations 3 and 4, respectively. The purity was determined by the ratio between the peak area of RuBisCO (A RuBisCO ) and the area of all peaks of the chromatogram, corresponding to other proteins present in the samples (A Total ).
025 mg/mL). For aqueous solutions of [Ch]Cl at higher concentrations (500 mM and 1 M), better results were obtained at 500 mM where the yield of extraction was 1. 84 mg of RuBisCO/g of biomass. With aqueous solutions of [Ch][Ac], a yield of extraction between 6. 38-8. 45 mg of RuBisCO/g of biomass was obtained. These data reinforce the high impact of the IL concentration on the extraction yield. The good performance of aqueous solutions of  [Ch] [Ac] to stabilize proteins was reported previously by Bisht et al. [39]. The authors studied if it was possible to improve the thermal stability of α-chymotrypsin with cholinium-based ILs, where [Ch][Ac], [Ch][DHP] and [Ch]Cl preserved the structural stability of the enzyme and the enzymatic activity  [39]. The pH value of all IL aqueous solutions and final extracts was also determined, changing with the IL type and suffering a slight increase in the extract when compared to the initial IL aqueous solution.
Funding: This work was developed within the scope of the project  CICECO-Aveiro Institute of Materials ,  UIDB/50011/2020 & UIDP/50011/2020 , financed by national funds through the  Portuguese Foundation for Science and Technology/MCTES. This work was developed within the scope of the project " IL2BioPro ",  PTDC/BII-BBF/30840/2017-and POCI-01-0145-FEDER-030750 (PTDC/EQU-EPQ/30750/2017 ), funded by  FEDER , through  COMPETE2020 ,  Programa Operacional Competitividade e Internacionalização (POCI) , and by national funds (OE), through  FCT/MCTES. This work was financially supported by  Cooperação Portugal/PHC ,  Pessoa ,  2018-2019 N • 441. 00. Data Availability Statement: Not applicable. Acknowledgments:  Ana P. M. Tavares  acknowledges the  FCT  for the research contract  CEECIND/ 2020/01867  and  Ana I.
Wavelength solution using HC spectra alone Two main methods were developed and tested for the wavelength solution based on the HC lamp. The principal conceptual difference between them lies in the way in which the HC lines are identified. The first, method HC1, is analogous to the SO-PHIE/HARPS wavelength solution  (Baranne et al. 1996 ): For each line in the catalogue, the region where it should be located is selected and a Gaussian fit is attempted, with poor fits being discarded. In the second, method HC2, Gaussians are fitted to every peak in the HC spectra, and the best match to the catalogue is identified. The detailed structure of the full routine is as follows. Data identification and reading: The input files are verified via FITS header keys to be extracted two-dimensional spectra (E2DS) corresponding to an HC lamp.
The E2DS files contain the extracted spectrum for a single fibre in the format of a 50 × 4089 array with one spectral order per row, arranged from blue to red. The data and header are read, and the lamp and fibre are identified. If more than one HC file is given, the routine verifies they all correspond to the same lamp and fibre, then the median of the frames is obtained and used as input for the rest of the routine. Calibration set-up: The calibration files that are closest in time to the input file(s) are copied from the calibration database (including the previous wavelength solution). The previous wavelength solution is read and checked for compatibility with the current parameter set-up (degree of the polynomial fits employed, as this varied during development). The correct HC line catalogue (UNe or ThAr) is read in.
The coefficients of the polynomial fits are stored in the header. If the quality controls were all passed, the new wavelength solution is copied to the calibration database, and to the header of the input HC E2DS spectra. Performance tests (discussed in more detail in Sect. 4. 2) showed that while the first method has slightly better internal accuracy than the second, it is much less stable night-to-night. In any case, neither method reaches the expected internal accuracy of < 0. 45 m s -1 budgeted for the SPIRou wavelength solution. The first method is also very sensitive to drifts from the initial wavelength solution (this was particularly highlighted by the earthquake in May 2018, which caused a detector shift of several pixels), to which the second method is more robust. The second method was therefore adopted for the HC wavelength solution, and is the only one available in version 0.
The data and header are read, and the lamp and fibre are identified. Fibre correspondence between the HC and FP files is checked. If more than one HC file is given, the median of the frames is obtained and used as input for the rest of the routine. Currently, providing more than one FP file is not supported. This option was chosen as allowing for multiples of each file type increased set-up complexity, and the FP spectra are generally bright everywhere while the HC lines can be weaker. Calibration set-up: Previous calibration files are copied from the calibration database (including the blaze file and the previous wavelength solution). The previous wavelength solution is read and checked for compatibility with the current parameter setup (order of the polynomial fits employed). The correct HC line catalogue is read in.
Impact of previous calibrations The wavelength solution is the last step of a long calibration sequence. This made its development particularly challenging as changes upstream frequently meant large modifications in the data that proved destabilising for the wavelength solution, especially in the earliest versions of the DRS. As the DRS has evolved, this has somewhat ameliorated. Nevertheless, the previous calibrations can still impact the wavelength solution. In order to explore the performance of the wavelength solutions alone, therefore, the tests presented in the rest of this section are all carried out with the HC and FP files extracted using a single set of input calibrations. We found that fixing the input calibrations introduces large drifts between the wavelength solutions for different nights, of the order of ∼ 10-50 m s -1 ; however, they are easily calibrated out by subtracting the night-to-night median RV difference.
Acknowledgements. The authors wish to recognise and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. This work was supported by the  Programme National de Planétologie (PNP)  of  CNRS/INSU , cofunded by  CNES. We acknowledge funding from  ANR of France  under contract number  ANR-18-CE31-0019  (SPlaSH). This research made use of matplotlib, a Python library for publication quality graphics (Hunter 2007); SciPy (Jones et al. 2001-); IPython package (Pérez & Granger 2007); Astropy, a communitydeveloped core Python package for Astronomy (Astropy Collaboration et al. 2018, 2013); NumPy ( Van Der Walt  et al. 2011); Astroquery (Ginsburg et al.
Acknowledgements The authors thank  Elkem Silicones©  for providing raw materials and funding for MP's and JD's PhD projects. DC thanks the  FUI ECOMAT  for funding her post-doctorate. JR and VM also thank  Roger Spitz  for enlightening discussions and  Franck Collas  for his DSC expertise,  Sébastien Norsic  for his technical support as well as  Carlos Fernández de Alba Encinas  for his HR-MAS NMR expertise.
Cell Culture L-6 cells from rat skeletal muscle were obtained from the American Type Culture Collection (Rockville, MD, USA). Cells were seeded in 75 cm 2 flasks for tissue culture and 0. Influence of EA and EAPA on cell viability on A549 cells in a dose-dependent response by MTT assay. Cells were seeded into 96-well plates (1 × 10 4 cells/well) and allowed to adhere for overnight. Cells were treated with increasing concentrations of EA and EAPA (50-300 µM) separately for 24 h; ethanol was used as control. Data represent mean of ± S. D. from three independent experiments and were performed in triplicates. p < 0. 05.
The compatibility of a solvent and a solute can be evaluated by determination of the relative energy difference (RED) between these compounds and this is estimated by calculating their distance in the parameter space defined by the axes dd, dp and dh. Table  2  shows the values of the Hansen parameters and average RED of some lipids vis-à-vis hexane and MeOx. The lower the value of RED, the stronger the proximity between the solvent and the solute. The data in Table  2  show that according to the Hansen parameters, which characterise a method based on the rule "like dissolves like", 2-Methyloxolane is a solvent closer to most lipids than hexane, except for waxes. That means that in theory, n-hexane is not the best solvent for the dissolution of oils and that MeOX molecules interact better with most of lipids molecules.
As part of her thesis work, Anne-Gaëlle Sicaire also compared the degree of affinity of MeOx for lipids with the one of various solvents such as cyclopentyl-methyl-ether (CPME), dimethyl-carbonate (DMC), isopropanol, ethanol, ethyl-acetate, p-cymene and d-limonene using Cosmos-RS, a powerful software program that simulates the electronic states on the surface of molecules in order to predict their interactions  (Sicaire et al. , 2015b). The result of these simulations also led to classifying MeOx as the solvent having the best characteristics for solubilizing common fatty substances. These data have been confirmed by experience, the solvents being compared in a Soxhlet apparatus for measuring the extraction kinetics, yields and oil quality. With the kinetics data obtained by extracting rapeseed prepress cakes and the characterization of the material particle size, Sicaire determined the diffusivity coefficients (D eff ) of MeOx and hexane, obtaining the respective values of 12.
| INTRODUCTION The nuclear magnetic resonance extracted data (NMReDATA) format  [1]  was introduced recently for reporting and exchanging nuclear magnetic resonance (NMR) data of small molecules. This text-based format maintains a good readability for humans and can be easily interpreted by computers, contrarily to chemical drawings and the associated NMR data tables published by scientific journals as portable document format (PDF) documents. The NMReDATA were thus designed to facilitate the communication between producers and users of scientific findings in the field of structural organic chemistry. In this paper, we demonstrate how this is done in practice, showing how NMReDATA support the NMRbased discussion of proposed molecular structures using a diverse set of tools. We also provide a free access to a set of test data.
These files are given to illustrate the features of the format and to serve as a didactically sound reference point for future users eager to understand its fine details, as a complement to https://nmredata. org/ wiki/NMReDATA_tag_format. They can also serve as a test set for software handling NMReDATA files. It is important to emphasize that the NMReDATA format is not limited to a specific vendor, even though the example uses the Bruker software suite. The format can capture one-and two-dimensional spectra and contains a set of NMR features (i. e. , assignment, chemical shifts, and couplings) with a chemical structure representation and thus is independent of the instrument used to generate the data. The NMReDATA file can be combined with raw data in both the time and frequency domains for any type of NMR spectrometer in the NMR record.
| DATA ANALYSIS PROCESS In this section, we show how the NMReDATA format improves the structure verification workflow for NMRbased investigations of small molecules. The outcome of this workflow can ultimately be used for direct deposition of the resulting standardized data associated with a scientific journal article as well as registration and deposition of the data to relevant repositories. As example for the workflow, we will use the published NMR data from 5αcyprinol sulfate (found in PubChem at https://pubchem. ncbi. nlm. nih. gov/compound/160665 with CID:160665). [3] he NMR record and the NMReDATA file can be authored using either instrument vendor software or third-party data processing applications. So far, Bruker, Mestrelab and Advanced Chemistry Development (ACD)/Labs have included NMReDATA file creation into their software suites.
Bruker allows the export of NMReDATA files from its Topspin software via the CMC-se Structure Elucidation Module. [4] The Mestrelab Mnova software suite  [5]  and the ACD/Spectrus Processor  [6]  are NMR processing software suites that support multiple instrument vendor formats, including Agilent, Bruker, and JEOL. Both feature tools for structure elucidation and spectra assignment, allowing for the export of NMReDATA files with the results. Ultimately, we intend to gain a wide-ranging support for NMReDATA by vendors as well as third-party software suppliers and journals. The role of software suppliers is to ensure that the NMReDATA files can be generated, read, edited, and written, whereas journals will be requested to accept the format for supplemental materials, permanent data deposition, and also to promote format adoption.
As the specification of the NMReDATA format is fully open, the different software suites can be used in any desired combination, thereby easing comparison of data sets generated with different tools. An overview of NMReDATA supporting software introduced can be found in Table  1. An up-to-date version is maintained at https://nmredata. org/wiki/ Compatible_software. Some of the tools described here are freely available for use, and some are open source.
| Data preparation The NMR spectra of the example compound were acquired using a 500 MHz Bruker Avance III HDX spectrometer and processed using Bruker TopSpin version 4. 0 software. The complete list of 1-D and 2-D NMR spectra acquired for the compound is reported in Hahn et al. [3]  comprising 13 C and 1 H 1D and 1 H-1 H correlation spectroscopy (COSY), 1 H-  13  C heteronuclear multiple bond coherence (HMBC),  1  H-1 H nuclear Overhauser effect spectroscopy (NOESY), and other spectra. The initial NMR record was produced using the CMC-se module of the TopSpin software by Bruker. Figure  1  shows the files of the NMR record and the NMReDATA file produced by TopSpin. Once the data have been processed and the initial NMReDATA file has been created, the outcomes of numerous NMR postprocessing software applications can be added to the NMReDATA file and saved in a single format.