dataesr/scientific-paragraphs-categorization huggingface dataset:
As a result, P 1 = 1 spectrum presenting s-ATR artifacts has been identified by the operator among the P 0 spectra (Fig. 3  step 6 , Fig. 5. a). 54 spectra (1. 37% of the database) were correlated to the previous spectrum and were therefore excluded from the bilinear problem (Fig. 3  step 7 , Fig. 4. f). Then, a PCA was used to find the number of compounds on the reduced database. Similarly to the previous estimation, p = 4 compounds were found (Fig. 3 step 8  ). Thus, the number of compounds defined before and after SSMS (i. e. , before and after excluding the irrelevant spectra from the database) was the same (Fig. 6. a). In this case, SSMS led to exclude only 1. 37% of the database, which explains why it did not impact on the number of compounds found by a PCA. However, if SSMS had been used to remove more spectra (e.
6. 06% of the database) A high absorbance, thus a low reflectance (A ∼ 1/R) implies that there was an insufficient number of photons hitting the sensor during the acquisition. This occurred in zones assigned to granular silica (compound 1). For such absorbent materials, a higher number of scans would permit to reduce the signal to noise ratio; a longer duration of acquisition (per scan) would permit to collect more photons and perform a reliable measurement. • occurrence of s-ATR artifacts (Fig. 4. f, 1. 37% of the database) Spectra assigned to these artifacts were only found right in the middle of zones where carbonate ettringite (compound 4) was predominant. Looking at one of the spectra excluded from the resolution process by SSMS (Fig. 5. a) and at the spectrum corresponding to carbonate ettringite (compound 4, Fig.
Implications of the use of SSMS and s-ATR acquisitions All in all, a new supervised method has been developed in this work: SSMS combined with ALS. This method permitted to handle a set of 3936 FT-IR spectra to obtain a relevant chemical mapping of compounds present in an ettringite binder. In this work, a PCA on the hyperspectral database led to the same number of compounds with or without the exclusion of the s-ATR artifacts spectra thanks to SSMS. But, without SSMS, the 4 selected spectra and their related maps had no chemical meaning. Moreover, as already discussed, SSMS can also be used to exclude spectra of no interest for a specific study. In this case, the number of compounds found by a PCA would be changed after SSMS. In SSMS, thresholds and a correlation coefficient have to be adjusted for each study.
Since the operator has to intervene in the process, SSMS requires the operator to have enough hindsight and expertise for his study. However, such a requirement holds true for all statistical methods applied on physical problems. On the other hand, the main interest of SSMS lies precisely in the fact that it is based on statistical considerations. Thus, SSMS can be used to identify all kinds of artifacts in all kinds of database without any restriction on material nature and characterization mean; more generally, SSMS may be used for all types of problems with few adaptations. The s-ATR crystal is an interesting set-up for the acquisition of valuable data to map the relative concentrations of compounds in a material. Thanks to this set-up, no relative motion occurred between the s-ATR crystal and the sample all along the acquisition: cross-contamination and successive stamps, experienced in previous studies on materials with similar properties  [18] , were avoided here.
Conclusions A new supervised method, called SSMS, has been developed to deal with the analysis of hyperspectral data. Experimental acquisitions may lead to unexpected biased information, which can have different origins, such as the acquisition technique, the environment, the analyzed sample. To obtain relevant information from the database, it is fundamental to be able to exclude all of these biased data without impacting on the informative ones. This selection is easily carried out with classical filtering methods when the origin and the characteristics of the biased data are known. SSMS is a powerful tool to handle this problem in the general case and exclude biased data when all their sources cannot be predicted. Moreover, SSMS is a preprocessing method, and thus can be coupled with a reliable physical model to obtain quantitative chemical information.
In addition, the combined use of SSMS and of a physical model permits to identify the sources of the biased data. Thus, it becomes possible to improve the experimental method (sample preparation, acquisition parameters. ). All steps involved in SSMS are described and justified in this article. The interest and the gain provided by SSMS is illustrated on the analysis of data acquired with a FT-IR microscope using a disregarded set-up (static-ATR). Relevant chemical maps of a complex inorganic material are obtained coupling FT-IR microscopy data with the Beer Lambert law. Maps are analyzed, sources of biased data are identified thanks to SSMS and discussed. Finally, such a supervised preprocessing opens a new route to obtain more reliable quantitative information and to improve the experimental protocols.
Indeed, the method was originally developed for space exploration purposes, to aid in the identification of rocks during in situ exploration where instrumentation is generally limited for technical reasons. It is also a good companion for laboratory investigations, enabling the precharacterisation and selection of the samples best suited to be analysed in detail using potentially slow and expensive methods, or to rapidly monitor changes in material properties. This paper explains the CaliPhoto protocol and is applicable to a wide range of scientific studies. The main part of this paper is thus voluntarily short. Nevertheless, the detailed protocol and different validation tests are given in the Appendices so that any scientist can take advantage of its use. The algorithm (encoded in MATLAB) is available online in the Supplementary Materials of this article and may be used freely for any noncommercial purpose.
e. , a 4:3 ratio rectangle without the logo band). The resolution of the images may also be fixed; here we used a resolution of 1200 pixels × 1020 pixels including the logo band (Figure  2b ). This can easily be made using image processing software, such as GIMP (see Appendix B, Figure  A3  for details). Since it is difficult to control the orientation and homogeneity of the light source, the external and internal white rectangles of the colour plate (see Figure  1 ) are used to evaluate and correct the inhomogeneity of the illumination. This approach is inspired by the standard "plane fitting" data processing used in Scanning Probe Microscopy in order to remove the slope induced by the nonparallelism between the sample surface and the scanning plane (e. g. ,  [11] ). Indeed, in the absence of shadow, the light orientation will form a brightness continuum over the colour plate that can be fitted using a polynomial surface (see details in Appendix B, Figure  A4 ).
• The correction of an image with respect to the reference image remains good, even in low-light environments. It is shown that Δ <3% when the luminance µ = (R + G + B)/3 of the white square in the sample image is higher than approximately 100, and when the image dynamic (i. e. , µ of white square minus µ of black square) is higher than approximately 100. • The "colour" of the light does not play a role in the final correction; for a difference of 54 between the highest and the lowest of the three RGB values of the white square, Δ = 1%. • It is better to use the same camera throughout the whole procedure, even if Δ <2% when using different imaging devices. Finally, the tests show that in "normal" conditions, the method allows the user to obtain a dataset of images in which the difference between the RGB values of colour squares in the colour plate (between two images) is always approximately Δ ≈ 1%.
). Furthermore, by creating a database of CaliPhoto colour vectors (or RGB values) the method can be used to perform preliminary characterisation of an "unknown" material based on analyses of comparable materials using laboratory-based instrumentation. The philosophy is then to link properties obtained using expensive and/or nonportable instrumentation to measurements made by low-cost, highly portable imaging. The principle consists of characterising the materials expected to be found in the field, using laboratory instruments if needed, to make their CaliPhoto image following the process previously described, then to store their RGB CaliPhoto vectors in a database linking these vectors to the different materials or to any other relevant physical parameter(s). By comparison with the database, it would then be possible to identify or determine the physical properties of an unknown material using only a photograph.
The method is resilient: a database can be made and completed at any time and, thus, the characterisation of "unknown" materials is continuously improved and refined with time. Figure  5  illustrates the use of the CaliPhoto method for sample identification and for compositional measurement (detailed results can be found in Appendices E and F). Finally, the only restriction of the method is the fact that it is necessary to associate a database to a specific colour plate. If this colour plate were to be lost or altered, the database would become obsolete. We thus propose to maintain a Master Colour plate in a secure place so that the reference image of a new colour plate can be recalibrated for use with a previously established database (see Appendix G).
• Geology: As for space exploration, the method allows easy comparison of samples observed in different places in the field. When associated with a database, it can also facilitate the use of soil colour charts. • Biology: Colour is used as a parameter to pre-identify microbial colonies or to evaluate their reaction to external stresses (sunlight, dehydration, pH, salinity, etc. ). This applies more generally for any living system (the yellowing of leaves, for example). The CaliPhoto may thus be used as a noninvasive and rapid method of monitoring such types of samples. • Materials science: Changes in the physico-chemical characteristics of materials may be associated with a change in colour. The possibility to monitor such changes during specific experiments may be particularly useful in determining reaction kinetics.
Association with a database linking specific properties to CaliPhoto colours may circumvent or limit the systematic use of sophisticated instrumentation. It may help to refine measurements based on colour, such as those obtained using pH paper. • Submarine investigation: Underwater imaging is generally affected by water colour and inherently limited control of the light source. Submarine instrumentation is also limited compared with laboratory instrumentation. The CaliPhoto method may thus also be particularly useful in this setting. By linking physical properties obtained by laboratory analysis to a CaliPhoto database, it could be possible to estimate these properties from images made underwater, without sampling. • Cosmetics and dermatology: The CaliPhoto method may assist in the selection of makeup adapted to specific types of skin.
It may also provide a control for Sun exposure to prevent sunburn. In the latter case, the idea would be to take pictures regularly of the same part of the body to monitor any change in colour. Several studies on various applications of the CaliPhoto method are in progress in field geology and space exploration. In particular, the method will be adapted for the upcoming European Space Agency (ESA)/Roscosmos ExoMars 2020 mission to Mars to assist in the identification of rocks using the Close-Up Imager (CLUPI) camera  [13]. While the CaliPhoto method has many applications for scientific purposes, it could also be used by the general public, for which an app for smartphones and tablets is under development. This implies automation of the method since manual image processing and MATLAB code cannot be used.
Significant work has thus been carried out to integrate the automatic detection of the colour plate and of the sample area, and for automated comparison with databases. Finally, prototypes of apps and specific colour plates are currently under development for cosmetics, paints and decoration, for example, to identify complementary colours of textiles (N. B. in aesthetic cases, the matching percentage uses the Lab colour system to take into account the higher sensitivity of the human eye to green). The method could also be particularly relevant for assisting the colour-blind. Finally, it is important to note that the CaliPhoto method is in line with the long-term vision for future developments in scientific technologies that favour low-cost solutions prior to methods that consume large amounts of resources.
9%. When using the tablet camera throughout (i. e. , to make the reference image of the colour plate, image in (c), and the image to correct) the value of Δ is decreased to 0. 6%, as displayed in (d). The photograph of the colour plate must then be processed in order to obtain the reference image. For this, the perspective must be corrected and the image resized. This can easily be done using image processing software. The example is given in Figure  A3  uses GIMP. The final reference image of the colour plate is obtained after light, brightness and contrast corrections. This image processing, described in Figure  A4 , is performed using mathematical software (MATLAB Code S1), and is as follows: (i). The rescaled and resized image (Figure  A4a ) is imported in MATLAB. (ii). The RGB channels of the image are extracted and converted into double format (Figure  A4b ).
E. 1. Identification using Average CaliPhoto Colour The CaliPhoto method can be used for identifying materials from a database. For such use, wellcharacterised reference samples must be photographed, taking into account the recommendations listed in Appendix D4, and corrected using the CaliPhoto image processing described in Appendix C. The average CaliPhoto colours of the materials are then extracted and stored in a database. An example is given for coloured paper (blue, green, mauve, orange, pink, purple, yellow) in Figure  A10. The database may also include the uncertainty on the colours, given by 256 × Δ. Table  A3  shows the values of Δ ij and Δ for each square and each of the reference sample images after correction. The database created, including uncertainties, is displayed in Table  A4.
It is then possible to identify a material using the same image correction processing and by comparing its CaliPhoto colour to the values stored in the database (see Figure  5 , main text). For that purpose, we defined a matching parameter given by: Mij = 1 -∆ij (A8) The results are displayed in Table  A5. Table  A5. Identification of a sample (orange paper) using a CaliPhoto database. The best match occurs for the orange paper, which has a matching percentage Mij = 99%. The second-best match occurs for the yellow paper which, to the human eye, is not very different from the orange paper.
E. 2. Identification Using CaliPhoto Colour Vectors The identification method can be improved by using more complex parameters to create the database. Indeed, for nonhomogeneous materials, the average colour of two materials may be similar, as illustrated in Figure  A11. The CaliPhoto RGB values stored in the database of coloured papers can be replaced by the newly defined CaliPhoto vectors, and material identification can be performed using Equation (A11). The results of this test are displayed in Table  A6.
IR characterization Fourier-Transform Infra-Red (FTIR) was carried out with a Vertex 70 Bruker spectrometer equipped with an MCT detector and using the Attenuated Total Reflectance (ATR) technique which enables samples to be examined directly. Germanium crystal has, by far, the highest refractive index of all the ATR materials available, and the effective depth of penetration is approximately 1 µm. In order to obtain effective signal/noise ratio, each spectrum was obtained by averaging 400 scans in the wavelength range of 400-4000 cm -1 at a spectral resolution of 4 cm -1. Absorption peaks search was automatically realized using the OPUS 7. 0 software. As scan spectra are of low intensity, all spectra have been normalized to be weighed. The results were compared with IR database or data published in the literature.
Choice of deposition time Another parameter that controls the electrochemical grafting is the deposition time at a given potential. Grafting of FTO electrodes was carried out at -0. 50 V for different deposition times and the total charges (Q) were monitored. An increase in the absolute value of total charges |Q| was observed with an increase in the deposition time (data not shown). The modified electrodes with 5 or 10 minutes grafting were then characterized as detailed previously by CV and EIS in the presence of the electroactive probe ferricyanide (Fig. 3A  and B , supporting information Fig. S1 ). Despite of a visible broaden redox peak at E1/2 = 0. 19V vs SCE corresponding to the signature of Fe(CN)6 3-/4-couple, changes in the CV response of modified electrode are clearly observed when compared to the signals recorded on the bare electrode, consisting in a substantial decrease in the peak current and a significant increase in the peak-to-peak separation.
A comparison with available data from the literature shows that this quantity of grafted molecules, obtained after optimizing the grafting conditions, is in the same order of magnitude that the one estimated by Meyer and al. by UV-visible absorbance of a Ru (II) diazonium dye grafted under imposed potential in CH3CN or aqueous HCl on a parent material, i. e. SnO2  [27]. This value range is moreover different from the values expected for a grafted monolayer which is from 1. 4 to 6. 4 10 -10 mol cm -2  [34] [35]  or 5 10 -10 mol cm -2  [36]. For 4-carboxyphenyl diazonium grafted on a different surface (glassy carbon), Γ values reported in the literature are of 5. 5x 10 -10 mol cm -2 for a monolayer  [16]  and 3 10 -9 mol cm -2 for multilayer  [37]. This feature provides an indication that under the above mentioned conditions, the modification of FTO surface with 4carboxyphenyl diazonium would lead to multilayer formation.
IR characterization To confirm the successful grafting of an organic layer on the electrode surface, the grafted FTO surface was investigated by FT-IR. Fig. 4  shows the FT-IR spectra of the pristine surface and the grafted one which were compared with reported spectra of the literature  [38] [39] [40] [41] [42]  and IR database  [43]. Several well-defined absorption peaks are clearly observed in both spectra. The spectrum of the pristine FTO surface reveals absorption peaks at 615 cm -1 and 520 cm -1 that can be assigned respectively to Eu (TO) and Eu (LO) vibration modes of SnO2  [26] [27] [28] [29]. This oxide exhibiting a cassierite-type structure has four infrared-active modes belonging to A2u and Eu symmetry but both A2u modes appear below 400 cm -1 and could not be seen here. The presence of additional peaks at 780 cm -1 and 682 cm -1 is related to the fundamental stretching vibration of tin hydroxyl which is further confirmed in the insert of Fig.
Spin contamination and basis set superposition errors were monitored and validation calculations can be found in the SI. Solid state calculations of diamond were performed with VASP 5. 4. 1  [12] [13] [14] [15]  using the HSE06 functional  16  with a 550 eV plane wave cutoff. Integration of electron density within ELF basins was performed with the CRITIC2 program  17, 18  using the algorithm proposed by Yu and Trinkle. 19 Statistical analysis was performed with the Statsmodels package version 0. 9. 0. 20 Graphics were generated with Chimera 1. 11. 2 21 and VESTA 3. 4. 1. 22.
General trends of the model Model 4 (Equation  10 ) was used to fit an extensive database (793 datapoints) including the complete set of DFAs using an ordinary least-squares model. Results are shown in Figure  3a  and Figure  3b  with respect to the model terms and q and R eq respectively. The collective Details and diagnostics of the fitting procedure can be found in the SI. Overall, the model fits the data at a semi-quantitative level, which is remarkable considering its simplicity and the variability in the data set. However, it must be noted that the ensemble parameters reported above are not recommended for in-depth analysis: method-specific parameters should be used instead, which lead to R 2 > 0. 99 in most cases, and can be found in the SI for a selection DFAs. (a) BE with respect to T and V (b) BE with respect to q and R eq molecule range from 0.
) PuTf PuFet 26 44 26 20 =. ×. PuTf PuFet Tf Fet [ ] [ ] 1 738 [ ] [ ] (9) At equilibrium, the PuTf ratio by a constant factor of 1. 738. In practice, both proteins were first mixed together in the appropriate ratio, and then a Pu aliquot solution stabilised by NTA was added. The final mixture was analysed by CE-ICPMS. The example given in Fig. 6  shows a co-migration of Pu-protein complexes at pH 7. 0. In order to determine each contribution, additional experiments, either without Fet or without Tf, were performed within the same set of experiments. All results are gathered in Table  2. The slope calculated from the data in Table  2  (1. 81 ± 0. 27) is in excellent agreement with the expected slope (see Fig. 7 ). We can conclude that the chemical equilibria are attained and that the distribution of plutonium between these two proteins is driven only by the binding constants.
CIEF. A Beckman Coulter P/ACE MDQ Capillary Electrophoresis system (Beckman Coulter, USA) equipped with an L2D2 deuterium lamp (Hamamatsu Photonics, Japan) controlled by System Gold Software (Beckman) was used in this study. The cIEF was performed using a 30 cm eCAP neutral capillary (50 µM ID, Beckman) with a 20 cm separation length. The separations were carried out at 25 °C with an optical detection at 280 nm. Capillary conditioning was performed by rinsing the capillary with acetic acid (chemical mobiliser, Sigma-Aldrich) for 5 min at 50 psi, followed by milliQ water (2 min, 50 psi), and then cIEF gel (Beckman) for 5 min at 50 psi. The sequence was concluded with the submersion of both ends of the capillary in milliQ water. The anolyte consisted of 200 mM phosphoric acid (Sigma-Aldrich) and the catholyte consisted of 300 mM sodium hydroxide (Sigma-Aldrich).
Acknowledgements We would like to thank  Jaime Angulo  for welcoming us to his laboratory. Many thanks to  Anne Van der Meeren  for her help in all the administrative and safety procedures and for her precious advice in carrying out these experiments. We gratefully thank  Olivier Grémy  for fruitful discussion. This work was funded by the  French transversal program  " Toxicologie Nucléaire" under project name Inspector.
Acknowledgments Lauriane Giraud gratification was supported by  INP  grant. Sharvina Shanmugathasan  was supported by the Chaire auto-assemblage,  Fundation de Bordeaux/Solvay. The authors would like to thank  E. Khetsomphou  for additional experiments. coacervates ( PAA-DA20 ) after 1 and 12 days. Figure S7: Microscopic image of a solution of PAA-DA15 stabilized by Ca  2+  , dispersed in deionized water after 18 days. Table S1: Quantification of the grafting density from the NMR spectra. Table S2: Microscopic pictures of coacervates loaded with various molecules. Table S3: Sequestration efficiency of fluorescent components determined by fluorescence spectroscopy.