dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements Authors would like to thank  Dr. El-Eulmi Bendeif  and  Dr. Pierrick Durand  from  "Laboratoire de Cristallographie, Résonance Magnétique et Modélisation " ( CRM2 ),  UMR 7036 ,  Université de Lorraine , for small angle X-ray diffraction measurements and discussion, and also  Mrs Odile Merdrignac-Conanec  from " Verres et Céramiques " team at the  "Sciences Chimiques de Rennes" laboratory ,  UMR CNRS 6226 , ( Université de Rennes I). The TEM microscopy work was carried out within the MATMECA consortium supported by the  ANR  under contract numberANR-10-EQUIPEX-37. It has benefited from the facilities of the  Laboratory MSSMat  ( CNRS UMR 8579 ),  Centrale Supélec , France.
Energy calibration was established by putting the sample between the first and the second ionization chamber and the corresponding metal foil between the second and the third chambers. At least two repeated spectra were taken for each sample to check stability of the material under X-ray irradiation. The IFEFFIT program package  [33]  was used for the XANES (X-ray absorption near edge structure) and EXAFS (extended X-ray absorption fine structure) analysis. High-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) images were acquired using a C3/C5 Nion USTEM spherical aberration-corrected microscope working at 100 keV. Electron energy loss spectra (EELS) were recorded with a modified GATAN EELS system with a back-illuminated charge coupled device camera. Thermogravimetric measurements were performed on a Mettler Toledo TGA/DSC1 Instrument in the temperature range from 25 to 950 °C with a heating rate of 10 K•min -1 in an argon atmosphere.
Acknowledgements This work was supported by the  Slovenian Research Agency  research programmes  P1-0134 ,  P1-0112 , and  P1-0125 , and by  DESY  and the  European Community 's  Seventh Framework Programme  ( FP7/2007-2013 ) under the grant agreement CALIPSO  312284  ( EU Support of Access to Synchrotrons/ FELs in Europe ). Access to synchrotron radiation facilities of  DESY  (project I-20110082 EC and II-20080058 EC) and  Elettra  (project  20140312 ) is acknowledged. We would like to thank  E. Welter  of  DESY  and  G. Aquilanti  and  L. Olivi  of  ELETTRA Sincrotrone Trieste  for expert advice on beamline operation.
Experimental photoswitching In order to provide a larger experimental dataset to compare with this computational analysis, UV/vis spectra and photoswitching experiments were recorded for each of the new photoswitches in acetonitrile. Since the best photoconversions were generally achieved with 355 nm (E-Z) and 532 nm (Z-E) irradiation, these wavelengths were principally used in the switching experiments (see Table  3 ). Azopyrazole E-5pzH could be quantitatively switched to its Z isomer using 355 nm irradiation, while the majority of other compounds were switched to photostationary states (PSSs) containing a mixture of isomers. Z-3pyMe could be near-quantitatively (98%) switched back to its E isomer using 532 nm, while the majority of other compounds gave PSSs containing a mixture of isomers, due to overlapping absorbances between E and Z isomers at this wavelength.
Acknowledgments: The authors thank  Belkacem Otazaghine  and  Benjamin Gallard  for their help. Author Contributions: For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used " Loïc Dumazert  and  Rodolphe Sonnier  conceived and designed the experiments; Loïc Dumazert performed the experiments;  Loïc Dumazert  and  Rodolphe Sonnier  analyzed the data;  Rodolphe Sonnier  wrote the paper. "Authorship must be limited to those who have contributed substantially to the work reported.
5 h. The time at which intestinal fluid was amended was designated as 0 h. Data Analysis. The Freundlich models were used to fit the equilibrium adsorption isotherm data of CIP by GO, rGO and Mont at varying interaction systems (detailed in the SI). The K d (L/g) value is the distribution adsorption coefficient calculated by dividing the adsorbed amount of the sorbate (q e ) by its equilibrium concentration in aqueous phase (C e ), K d = q e /C e.
Characterization Fourier transform infrared (FTIR) spectra were acquired on a Bruker (Billerica, MA, USA) Vertex 80v spectrophotometer equipped with Bruker Platinum ATR diamond system. A total of 64 scans were acquired for each sample at a resolution of 1 cm -1. Raman spectra were recorded on a Renishaw (Wotton-under-Edge, UK) InVia Reflex spectrometer using a monochromatic diode laser (λ = 785 nm) as an exciting light source and a 1200 L mm -1 grating. The spectra were measured on the mould-casted films, from 400 to 1500 cm -1 , with a resolution of 1 cm -1. A total of 20 scans were collected with an acquisition time of 1 s and averaged for every sample. Small-angle X-ray scattering (SAXS) data were collected at the SWING beamline, SOLEIL synchrotron (Gif-sur-Yvette, France)  [62]. The acquisitions were performed in transmission mode, at sample-to-detector distances of 6.
072 and 0. 997 m, for accessing q-ranges (q = 4π sin(θ)/λ, where 2θ is the scattering angle and λ is the X-ray wavelength) from 0. 002 to 0. 2 Å -1 and from 0. 015 to 1. 2 Å -1 , respectively, using a monochromatic beam with a wavelength of 1. 0332 Å (12. 000 keV). For each sample, the acquisition time was optimized in order to obtain high signal without saturating the detector. Once desired acquisition time was selected, 10 backgrounds (air and, in some cases, Kapton (DuPont, Wilmington, DE, USA) films) were collected, masked, integrated and averaged. The same number of acquisitions and treatments were performed for the sample data. All the data treatments were performed at the beamline using FOXTROT  [63]. Due to overlapping q-ranges, q = 0. 15 Å -1 was selected as the merging point and the values below and above are from the data collected at sample-to-detector distances of 6.
Spin-coated films were analysed with a polychromatic light (210 to 1690 nm) using focusing probes. Three points per sample were recorded and for each point, measurements were done at five angles (50, 55, 60, 65 and 70 • source-sample angles, corresponding to 100, 110, 120, 130 and 140 • source-detector angles, respectively) with an analysis time of 20 s per position. The refinement of the data was performed using CompleteEASE (J. A. Woollam, version 5. 13). The Cauchy model was used from 400 to 1600 nm on the hybrid film layer and the substrate was modelled with a 2 nm SiO 2 layer on metallic silicon.
Acknowledgments: Financial support from  The Research Council of Norway  to the projects " Beat the Human Eye " (number  235210 ) and " FASTS " (number  250403 ), as well as for the support to  NTNU NanoLab  through the  Norwegian Micro-and Nano-Fabrication Facility ,  NorFab  ( 197411/V30 ) is gratefully acknowledged. We acknowledge SOLEIL for provision of synchrotron radiation facilities at the SWING beamline. Support from The  Norwegian University of Science and Technology Publishing Fund  is also acknowledged.
Discussion Detailed analysis of the m-SQUID data additionally shows that within the cage two exchange interactions could be present, ferromagnetic and antiferromagnetic; this is consistent with the electrostatic analysis. m-SQUID analysis of the ferromagnetic projection (Fig. 4b  and d ) suggests possible quantum tunnelling between the ferromagnetic ground state and excited states at AE0. 22, AE0. 32, AE0. 42 and AE0. 62 T whilst a crossover is found in the antiferromagnetic projection at AE0. 35 T (Fig. 4a  and c ), suggesting antiferromagnetic interactions. In order to understand these two distinct behaviours at the rst stage, we invoke spin effective formalism 38 (S eff ¼ 1/2) employing pure axial g-tensors e. g. g xx ¼ g yy ¼ 0; g zz ¼ 20 and the projection angles of the m J ¼ AE15/2 state for each Dy(III) ion obtained from the electrostatic analysis.
Acknowledgements MR, WW and YL acknowledge the  EU  for nancial support within the  FP7 FET-Proactive  project  MoQuaS No. 610449  and the  ANR  for  ANR-13-BS10-0001-03  MolQuSpin. We acknowledge the  Karlsruhe Nano-Micro Facility (KNMF)  for X-ray time. Notes and references ‡ Crystal data for 1 [Dy  4 N 12 O 24 C 105 H 192  ]: M r ¼ 2656. 69,monoclinic, T ¼ 180. 15(1)K, a ¼ 28. 1117(11), b ¼ 20. 1279(6), c ¼ 22. 8674(10) Å, b ¼ 105. 985(3) , V ¼  12 438. 7(8 ) Å3  , Z ¼ 4, r ¼ 1. 419 g cm À3 , total data ¼ 41 630, independent reections  11 718 (R int ¼ 0. 0723 ), m ¼ 2. 442 mm À1 , 699 parameters, R 1 ¼ 0. 0723 for I $ 2s(I) and wR 2 ¼ 0. 1870. The data was collected employing a STOE StadiVari 25 diffractometer with a Pilatus 300 K detector using GeniX 3D HF micro focus with MoK a radiation (l ¼ 0.
X-ray diffraction determination of the nickel powder The crystal structure and phase analysis of the Ni powder in the first stage of the reactor was characterized by powder XRD. The XRD patterns of the Ni powder shown in figure  2  were indexed to monoclinic Ni according to the JCPDS database no. 04-0850  [21]. The average crystallite size of Ni sample was calculated by using the Debye-Scherrer formula given in equation (3. 1): d = kλ β cos θ , ( 3. 1) where d is the crystallite size, k is 0. 89 (CuK), λ is the wavelength of the X-rays (λ = 1. 54178 Å), θ is the Bragg diffraction angle, and β is the full width at half maximum (FWHM). The average crystallite size d before and after reaction calculated from the diffraction peaks was found to be approximately 8. 013 and 9. 158 nm, respectively.
Acknowledgements. We thank all the funders who supported this work and thank  Dr Hao Yin  of the  University of Science and Technology of China  for his suggestion. We are also grateful to the two anonymous reviewers who provided comments that substantially improved the manuscript. Y. -h. L. thanks the  Instrument Physics Centre of the University of Science and Technology of China  for providing GC-MS, Raman, XRD and SEM analyses for this study.
The rotating 3 mm-thick disc has a diameter of either 33 mm or 18 mm depending on the lubrication regime. It was also made of same AISI 52100 steel and polished to a surface roughness below RMS 2. 6 nm in order to get a very low surface roughness after the deposition of DLC coating. Contact at the sliding interface was in the shape of line under moderate Hertzian pressure of about 70 MPa. Lubrication was provided by a few droplets (0. 01 ml) of the lubricant on the disc at room temperature. The sliding speed was varied in a range of 0-0. 1 m/s for the tribological experiments. The XAS and HRPES measurements were carried out at station ANTARES of the SOLEIL synchrotron radiation source facility, France. The absorption data was acquired in the total electron yield (TEY) mode by collecting electron emission from the sample and were normalized to the signal from a gold covered grid recorded simultaneously.
The resolution of the beam line is 50 meV at the CK-edge. Data analysis was performed after background correction and subsequent decomposition into several Gaussian peaks. The HRPES analysis was performed at the same experimental station suing 350 eV and 700 eV incident photon energies. The chemical compositions, thickness and chemical bonding states inside and outside the scar were systematically investigated. In order to avoid beam damage to the samples, no ion beam sputtering was performed on the investigated samples. The photoemission spectra were obtained at a Room Temperature of the sample using a hemispherical analyser Scienta R4000. The high-resolution core level spectra were acquired at 20 eV pass energy and 50 meV energy increments. For the correction of binding energy of samples, the C1s core level peak was calibrated to the gold 4 f peak occurring at 84 eV.
Results and Discussion The electrical characteristic of the simple bridge was measured in the 300-390 K range (Figure  1a ). R(T) curve was fitted using a polynomial of degree 9 and was implemented into the COMSOL simulation software. Electro-thermal analysis has been performed assuming only heat transfer conduction mechanisms. At low bias current the electrical resistance has an ohmic behaviour. At high current, I-V curves are non-linear due to self-heating in the non-linear behaviour sensor in R(T), see Figure  1b. The electrical resistance R of the 75 × 75 µm 2 suspended bolometer was measured as a function of temperature T between 240 and 340 K. The maximum value of dR/dT was found to be 72 Ω•K -1 at 320 K and the maximum TCR was of 1. 9 × 10 -2 K -1 , similar to literature  [6]. The thermal conductance was measured from current versus voltage and R(T) characteristics.
The X-ray photoelectron spectroscopy (XPS) measurements were carried out in an ultrahigh vacuum (UHV) spectrometer described elsewhere  [36]. The Al Kα line (1486. 6 eV) of a dual anode X-ray source was used as incident radiation. Survey and high resolution spectra were recorded in constant pass energy mode (44 and 22 eV, respectively). Since the C 1s peak contains contribution of organic residuals related to the synthesis of the materials it cannot be used to correct the binding energy scale, as is typically done with adventitious carbon. Therefore, we have used F 1s (from HF) and N 1s (from DMF) as internal standards of TiO 2 and MOF respectively to correct the BE scale of the presented XPS spectra. Spectra fitting was performed with the CasaXPS software using Ti 2p and Zr 3d line shapes recorded on TiO 2 and NH 2 -UiO-66 samples as reference peaks.
Diffuse reflectance from the sample was collected by a 2" diameter, 2" focal length lens and relayed to a monochromator (Oriel Cornerstone 130) to select the probe wavelength. Time-resolved intensity data was collected with a Si photodiode (Hamamatsu S3071). Data at times faster than 3. 6 ms was recorded by an oscilloscope (Tektronics DPO3012) after passing through an amplifier box (Costronics), whereas data slower than 3. 6 ms was simultaneously recorded on a National Instrument DAQ card (NI USB-6251). Each kinetic trace was obtained from the average of between 100 -250 laser pulses. Acquisitions were triggered by a photodiode (Thorlabs DET10A) exposed to laser scatter. Data was acquired and processed using home-built software written in Labview. Experiments were carried out in diffuse reflectance, since the materials were highly light scattering.
IChem is as uite of tools consisting of about 50 000 lines of computer code written in C ++,d ecomposed in nine modules, for detecting and comparing molecular objects (proteins, ligand-binding cavities, ligands, protein-liganda nd proteinprotein complexes) frequently manipulated in structure-based computational chemistry (Table  1 ). Herein we describe four of the most frequent andi mportant uses. For deeper investigation of all modules, the reader shouldr efer to the publicly availableuser guide. [1] etting the scene:pdbconv. Areasonable start to any structure-based design project is the retrieval of experimentally determined protein structures from the Protein Data Bank (PDB),  [2]  aw eb resource that currently stores over 134 000 entries. Unfortunately,P DB structures cannot be used directly,a s many important features (e.
g. ,p rotonation and ionization states, atom types andb ond ordersf or organic molecules) are missing. The pdbconv module of the IChem toolkit automates the preparation of ready-to-use protein-ligand structures. The processf irst assignsaspecific class to each residue name (Table  2 ). It then appliesac orrect atom type to every heavy atom, generates the corresponding covalent bonds, and selects strongly bound water molecules while removing bulk water. The process relies on ap redefined list of all possible residues with the corresponding templates for every HET record of the PDB file. Correct atom types and3 Dc oordinatesa re provided for every template by converting, with Corina,  [3]  PDBS MILES strings into the corresponding MOL2 file. The residue list (Table  2 ) assignst he encountered HETrecord to one of the 12 possible residue classes (cofactor,i on,l igand, metal, modified aminoa cid, nucleic acid, organometallic, prosthetic, standard amino acid, sugar,u nwanted, water).
Please note that molecules originating from crystallization buffer ("un- Fingerprinting protein-ligand interaction patterns Grim Converts protein-ligand interaction pattern in graphs DetectPPI predictbiologically relevantP PIs  [a]  [a] Protein-proteininterfaces. Table  2. HET residue classes in IChem, exemplifiedbyo ne residue. HET  [a]  Te mplate  [b]  Updated  [c]  Class  [d]  ACO The ORCID identification number(s) for the author(s) of this article can be found under: https://doi. org/10. 1002/cmdc. 201700505. wanted" class) are automatically identified and discarded. O nce atom types have been properly defined for every molecule type (protein and accessory molecules, solvent, ligand), any third-party tool (e. g. ,P rotoss)  [4]  can be used to finally add the missing hydrogen atoms while optimizing both the ionization and tautomeric state of each molecule of the PDB entry.
Working with predefined residue lists and molecular templates provides both advantages and drawbacks. Them ain advantage is au niform treatment of all chemical components of aP DB entry with ap resumably correct atom typing. As am ain drawback, the procedure requires an updated residue list and thus fails in case of an ewly released PDB entry. W et herefore propose regular updates along every new release of the inhouse developed sc-PDB database of druggable protein-ligand complexes. [5] etecting ligandable cavities: Volsite. Volsite is at ool to automatically detect cavitiesa tt he surfaceo famacromolecule of interest, and predict its structurald ruggability. [6] It can be run in two modes depending on whether coordinates of a bound ligand are given (ligand-restricted mode) or not (full unrestricted mode).
Detecting biologically relevant protein-protein interfaces: detectPPI. P rotein-protein interfaces (PPIs) represent challenging but very promising targets for drugd iscovery. [15] Hence, PPIs describe av ast unexplored biological space for which small molecular weight modulators  [16]  are expected to offer very high potency ands electivity profiles. Although mainly discoveredb yb iophysics-driven fragment-based approaches, computational chemistry is expected to playamajor role in designing the future PPIm odulators,  [17]  notably upon relying on the huge structurali nformation already available in the Protein Data Bank. To discriminate biologically relevant from crystallographic artifacts, computational methods are needed to rapidly detect PPIs and predict their biological relevance from astructuralpoint of view.
IChemPIC  [18]  was designed to address this need. The detectPPI module uses the general IChem functions (molecule reader,i nteraction detection) to detect the interface, identifies the corresponding IPAs and generate af ixedlength property vector (Figure  5 ) as input for aR andom Forest classifier previously trained on aset of 400 PPIs (200 biologically relevant,2 00 irrelevant interfaces). IChemPIC is equally robust to detect both classes with the same accuracy,i ndependently on the size of the PPI. [18] nterestingly,t his new IChem module can be used at ah igh throughout to detectb iologically relevant PPIs at the PDB  scale. Alternatively,t he method can be used on-line (http:// bioinfo-pharma. u-strasbg. fr/IChemPIC) by just specifying the PDB three-letter code. In conclusion, IChem is as uite of softwared edicated to the analysisa nd comparison of three-dimensional molecular objects.
Acknowledgements We thank the  Centre National de la Recherche Scientifique (CNRS) ,t he Alsace Region,a nd the  Institut de Recherches Servier  for PhD grants to F. D. S. and J. D. Part of this work was supported by the  MEDALIS Drug DiscoveryC enter  ( LABEX ANR-10-LABX-0034_Medalis ). AlthoughJ. D. 'sa ffiliation is currently  Eli Lilly ,a ll presented results pertain to work prior to such affiliation.
In practice, this free tool developed under linux is very useful but requires much RAM, which was problematic until the development of 64-bit computer system architectures. Concerning the large application of OOF, Langer et al. [2]  used this code to perform FEM calculations in order to estimate the macroscopic properties of materials from their microstructure. Kulkarni et al. [3]  completed their own experimental works with FEM calculations of the effective thermal conductivity and Young's modulus performed on artificial micrographs, in the case of partially stabilized zirconia thermal barrier coatings (PSZ TBC coatings): The results calculated were somewhat overestimated in comparison with experiments. Similarly, Wang et al. [4]  performed calculations on real cross-section micrographs of coatings to estimate the effective thermal conductivity and Young's modulus of similar PSZ TBC coatings.
Loading Case Applied Formulas Set 1 κ y = ∅ y H W 1 30 Set 2 κ x = ∅ x W H 1 30 Set 3 E x = F x H 1 ε Set 4 E y = F y W 1 ε Set 5 ν xy = F y F x H W E x E y Set 6 ν yx = F x F y W H E y E x Set 7 α x = F x H 1 E x Set 8 α y = F y W 1 E y As mentioned above, the use of OOF requires a lot of RAM (the more the better). Thus, in the present work, an alternative approach was used. This approach consisted of the development of an interface called TGA_TO_ANSYS allowing the conversion of a TGA image into an ANSYS Parametric Design Language (APDL) script. All calculations performed in the present study were thus obtained with the ANSYS solver requiring less RAM than OOF. In practice, different strategies were tested in order to implement the TGA_TO_ANSYS interface:.
Al12Si alloy is quite conventional so that its properties are available in most databases. The case of EKONOL polyester (not so different from XYDAR, another polyester used in abradable coatings) is a little trickier so that the considered references are provided. 0. 4  [23]  59  [24]  1440  [24]  * From NHT measurements performed on coatings  [22].
e. , by SEM for example). In practice, this pore network induces a lowering of the properties of the AlSi phase of the coating. The reader is thus informed that the mechanical properties shown in Table  4  represent an upper limit. However, the experimental result reported in  [22]  (i. e. , 7 GPa measured with a bending test) is only slightly below the calculated value of E x (7. 6 GPa as shown in Table  4 ), so the data may be considered as consistent. The strategy applied in future works will implement a two-magnification level method for this type of application (i. e. , the case of composite coatings). A first calculation will be performed on high resolution SEM micrographs zooming in on individual phases. The results of the calculations performed at this high magnification level will then be used as input data for calculations performed at the lower magnification level (such that of Figures  1  and 2 ).
The gas flow rates were controlled using Brooks mass flow controllers. Raman spectroscopy. The nitric acid-treated SCCNTs supports were characterized using Raman spectroscopy to estimate the ratio of graphitic to defective carbon of the supports. A Renishaw inVia Raman Microscope equipped with a coherent Argon ion laser was used for the analysis. Each sample was analyzed at three different spots to ensure homogeneity of the sample. Ten accumulations with a 30 s acquisition time, 25 mW power of a laser line at 488 nm were used for each analysis. The measurement range from 800 to 2000 cm -1 was used for analysis. The data analysis was conducted using the method described by Knauer et al. 60  According to this method, a multi-component baseline fit and deconvolution was used: bands at 1580 cm -1 (G-band), 1350 cm -1 (D 1 -band), 1620 cm -1 (D 2 -band), and 1200 cm -1 (D 4 -band) were fit with Lorentzian peaks while the contribution at 1500 cm -1 (D 3 -band) was fit with a Gaussian peak (Supplementary Fig.