dataesr/scientific-paragraphs-categorization huggingface dataset:
Settings were optimized for detection without saturating the signal. For each set of figure settings were constants. However, since the expression of the Orion-B-Myc-ΔSP protein is lower than the one of the Orion-B-Myc (as shown in the western blot and its quantitation Supplementary Fig. 3i-j ), the levels of red were increased in this particular case in order to get similar levels than in Orion-B-Myc. We used the Imaris (Bitplane) software to generate a pseudo-3D structure of Orion-produced γ axons (Imaris surface tool). We created two 3D surfaces, from regular confocal images, defining the axonal domain (green) and the Orion expression domain (red). Quantitation of immunolabelling. To quantify unpruned γ axons, we established three categories of phenotypes: "none," when no unpruned axons are observed, "weak," when few unpruned individual axons or thin axon bundles are observed in the dorsal lobe, and "strong," when >50% of the axons are unpruned.
For EcR-B1 signal quantitation, we performed five measurements for each picture (intensity 1, …, 5) in the nuclei of GFP-positive cell bodies and the same number of measurements in the background using confocal single slices. The mean of these background measurements is called mean background. We then subtracted intensities of mean background from each intensity value (intensity 1, …, 5 minus mean background) to obtain normalized intensity values. Finally, we compared normalized intensity values between two genetic conditions. We proceeded similarly for Draper and STAT-GFP signal quantitation, but staining was quantified in the astrocyte cytoplasm located in the immediate vicinity of the γ dorsal lobe. Quantitation of intensity was performed using the ImageJ software. To quantify the Myc signal in the γ vertical lobe, we traced a 60 µm line on the Cy3 red Z-stack and used the Plot Profile function of ImageJ to create a plot of intensity values across the line.
5% Tween-20, and 5% milk. The Orion-Myc and tubulin proteins were detected using a mouse anti-Myc antibody (clone 9E10, Abcam) and an anti-tubulin antibody (Sigma, T5168) at 1/ 1000 and 1/10,000, respectively, in PBS, 0. 5% Tween-20, 5% milk, and revealed using anti-mouse Ig horseradish peroxidase (1:10,000) and an ECL kit (Amersham). Band intensities were normalized to the corresponding tubulin band intensity using the ImageJ software. Statistics. Comparison between two groups expressing a qualitative variable was analyzed for statistical significance using the two-sided Fisher's exact test. Comparison of two groups expressing a quantitative variable was analyzed using the two-sided nonparametric Mann-Whitney U test. (BiostaTGV: http://biostatgv. sentiweb. fr/?module=tests). Values of p < 0.
Acknowledgements We thank  Amélie Babled ,  Pascal Carme , and  Dana Bis-Brewer  for help in the EMS mutagenesis, MB developmental studies, and WGS analysis, respectively, and  Oren Schuldiner  for discussions about the Orion expression and function. We also thank  Marc Freeman  for alrm-GAL4 stock,  Baeg Gyeong Hun  for 10X-STAT92E-GFP stock, the  Bloomington Drosophila Stock Center and VDRC  for fly stocks, the  BioCampus RAM-Drosophila facility (Montpellier, France) , the imaging facility MRI, which is part of the  UMS BioCampus Montpellier  and a member of the  National Infrastructure France-BioImaging , supported by the  French National Research Agency  ( ANR-10-INBS-04 ) for help in confocal and image analysis and processing. We acknowledge  BDGP, BestGene ,  GenScript , and  Genewiz  for cDNA clone, transgene service, gene synthesis, and DNA-sequencing, respectively.
Three specific databases were used to identify each set of nanopore reads. The coral 18S rRNA database contains full-length 18S rRNA for 140 scleratinia and 2 Millepora 12. Five 18S rRNA sequences of Symbiodiniaceae (gi:176088, 12247076, 1224077, 148734588 and 12247080) were added in the database in order to detect and remove undesirable Symbiodiniaceae 18S sequences. The ITS2 database contains 432 sequences of Symbiodiniaceae  18  and finally the Greengenes database (v. 13. 5, https ://green genes. lbl. gov) was used to detect 16S rRNA reads. All nanopore reads were mapped to each database with minimap2 (v 2. 0-r191) with the pre-set options "map-ont"  36. For coral identification, the reference sequence that had the most sequences mapped to it was the only one retained in each sample. Then a second round of mapping (same parameters) was done on the selected reference in order to aggregate reads potentially mis-assigned during the first round of mapping.
Two Maximum Likelihood phylogenetic trees with newly reconstructed sequences and the coral 18S rRNA database were further reconstructed, one with all sequences except Acroporidae and the other with Acroporidae only. For Symbiodiniaceae and the bacterial community the same strategy was used except that all references covered with a minimum of 1% (for ITS2 sequences) or 0. 01% (for 16S rRNA sequences) of all reads mapped were kept for the second round of mapping. In addition for the bacterial community, reads mapped on eukaryote chloroplastic 16S were removed after the first mapping. SAMtools and BCFtools were used to reconstruct consensus sequences for each reference sequence covered with more than 10 nanopore reads with the following programs and options: mpileup -B -a -Q 0 -u; bcftools call -c -ploidy 1;vcfutils.
This phenomenon is most probably due to the conservation of the flow cell for more than 2 months before the run which is longer than ONT specifications. However, given the number of sequencing reads obtained was sufficient to study the ITS2 amplicon, we decided to keep this MinION run for downstream analysis. The identification of 18S rRNA, ITS2 and 16S rRNA sequences was done by the mapping of nanopore reads against specific databases for each marker gene (see the Method section and Supplementary Method S1). Identification of corals, Symbiodiniaceae, and bacterial communities. Corals were identified by both their morphological traits (Supplementary Fig. S1 ) and the analysis of 18S rRNA sequences. A full-length 18S rRNA consensus was obtained for 50 corals covering 10 scleratinia families and the fire coral Millepora.
The coral identification with the 18S rRNA was limited at the genus level for non-acroporid corals because the 18S rRNA sequence is not discriminant at species level for these genera  12  (Supplementary Table  S2 ). A phylogenetic tree was reconstructed confirming the taxonomic identification of these corals (Supplementary Fig. S2 ). The DNA extraction and/or the PCR amplification failed for 10 coral colonies. In these cases, we based our identification on the morphological traits only. In order to identify Symbiodiniaceae diversity in each coral colony, nanopore reads were mapped against a database of 432 Symbiodinium ITS2 sequences  18. Several Symbiodiniaceae species may coexist in a coral colony so we can expect multiple ITS2 sequences per sample. As such, for each sample, ITS2 sequences covered with at least 1% of all nanopore reads aligned were conserved.
At present, this device is the only one able to execute a complete sequencing run under these conditions. A -20 °C freezer is sufficient to conserve reagents for DNA extraction, ONT library preparation, and MinION sequencing, allowing molecular experimentations during long-term expeditions in distant islands in total autonomy. In addition, several new developments ongoing by ONT to lyophilize sequencing reagents will be useful improvements to enable room temperature storage of reagents for several months. The bioinformatic pipeline developed in this article can be run on a simple laptop without internet access, so long as reference databases are prepared and downloaded before the expedition. The method described in this study will significantly improve the capability of local surveys and enable researchers in remote locations to make informed and effective sampling and experimental decisions while in the field.
We have observed that the combination of low sequencing depth and high error rate limits the detection and the precise assignment of rare sequences. The low sequencing depth in this study was due to the difficult conditions under which the sequencing was conducted, in particular the high temperature (~ 32 °C). The problem of low sequencing depth is amplified by the difficulty in identifying the correct barcode at each side of the amplicon due to the high error rate. Taken together, the number of de-multiplexed reads is sometimes the limiting factor for the diversity analysis but the current error rate is by far the main challenge to assign correctly each read to a specific taxon. We aimed to address this problem through the generation of consensus sequences from reads aligned to each sequence of the database.
Acknowledgements This project has been funded through the  Tara Pacific consortium ,  France Genomique  grant number  ANR-10-INBS-09 , and the  Genoscope/CEA. We are keen to thank the commitment of the people and the following institutions and sponsors who made this singular expedition possible:  CNRS ,  CSM ,  PSL ,  KAUST ,  Genoscope/CEA ,  ANR-CORALGENE , agnès b. , the  Veolia Environment Foundation ,  Region Bretagne ,  Serge Ferrari ,  Billerudkorsnas, AmerisourceBergen Company, Lorient Agglomération, Oceans by Disney , the  Prince Albert II de Monaco Foundation, L′Oreal, Biotherm ,  France Collectivites ,  Kankyo Station ,  Fonds Francais pour l′Environnement Mondial (FFEM) ,  Etienne Bourgois ,  UNESCO-IOC , the  Tara Foundation  teams and crew. Tara Pacific  would not exist without the continuous support of the participating institutes.
5406 Å). The measurements were carried out in a Bragg-Brentano geometry with a step-scan technique and a 2y range of 10-701. Data were acquired by using a Lynx Eye detector in continuous scanning mode with a step size of 0. 0381 and a time step of 0. 15 s. The mean crystallite size domain (t) along the film growth direction and the lattice parameters of the samples were determined by using the full profile fitting Pawley method. 77 The Pawley method was carried out using the program-suite TOPAS from Bruker. Raman spectra of the samples were collected using a Renishaw InVia micro Raman spectrometer with an argon ion laser (514 nm), with a laser power of 0. 13 mW and a spectral resolution of about 3 cm À1. Electrical characterization and Hall effect measurements were performed on TiO 2 and Ta:TiO 2 films deposited on soda-lime glass in a four-point probe configuration with a Keithley K2400 source/measure unit as a current generator (from 100 nA to 10 mA), an Agilent 34970A voltage meter, and a 0.
For the modelling of the optical properties of Ta:TiO 2 films, we employed a combination of Lorentz, Lorentz-Gaussian and socalled PSEMI oscillators, along with a Drude-type contribution to take the doping-induced free carriers into account. PSEMI oscillators are parameterized functions widely employed to model the optical response of crystalline semiconductors. 79, 80 he oscillator parameters of the undoped TiO 2 , and the Ta:TiO 2 , layers, as well as the thickness of all the optical layers, were carefully fitted in order to achieve the best agreement between the experimental data and the simulated SE spectra. The thickness of the SiO 2 native oxide was assessed by SE measurements on a bare substrate and was found to be around 2 nm.
WAXS and SAXS Characterization In situ WAXS and SAXS experiments were carried out in two conditions: on relaxed samples (=1) and on strained samples (=2. 5). The first set of experiments (=1) was carried out on a GANESHA 300XL+ system from JJ X-ray 1 in the X-ray lab at DSM Materials Science Center in the Netherlands. The in-situ experiments on strained samples (=2. 5) were carried out at the PETRA III beamline P03 at Deutsches Elektronen-Synchrotron (DESY) in Hamburg. The technical details of the scattering experiments are summarized in Table  1. The 2D scattering data were integrated using the software tool FIT-2D  19. All data were corrected by subtracting background scattering. In situ WAXS and SAXS experiments were carried out for two sets of samples: samples that were pre-fatigued and pristine samples.
Digital Image Correlation (DIC) DIC is a technique which allows measuring displacement fields by matching a reference with a deformed image. Here, the Correli-LMT software  20  , which represents the displacement field by the same kind of mesh as in finite element methods, was used. The final displacement is evaluated using an algorithm that minimizes the difference in the gray levels between the matched images, while imposing some level of regularity to the solutions. The objective adopted for this analysis corresponds to a pixel size of 7μm and the mesh size was x chosen as 16 pixels. In this condition the spatial resolution of the DIC analysis (minimum distance between two adjacent estimates of displacement) was 112 m. Since the datapoint associated by convention to a distance of 0 mm from the crack tip is indeed the closest available point, this spatial resolution should also be considered as an uncertainty on the distance of such point from the crack tip.
Acknowledgements The PhD work of  Giorgia Scetta  was jointly funded by the  French ANRT  and the LRCCP. We are grateful to  Dr. Matthias Schwartzkopf  for the access to P03 DESY beamline,  Dr. Dario Cavallo  for his support on interpretation of X-Ray Data. We are indebted to  Dr. Matthias Gerst ,  Dr. Elke Marten , and  Mr. Stephan Dohmen  from  BASF AG  for kindly providing the TPU samples. We thank  Stephane Delaunay  for injecting the samples and  Mohamed Hanafi  for the chemical characterization.
Acknowledgements Feudjio Memenfo is thankful to the  French Government  for financing her works through the  Cultural Cooperation and Action Service (SCAC)  scholarship. She is also indebted to  Laurence Burylo , research engineer at  National Graduate School of Engineering Chemistry of Lille (ENSCL ) for X-ray diffractometry analysis and  Jean-Noël Staelens , laboratory technician at UMET. The author also thanks  Nicolas Blanchemain , Professor at  University of Lille  for facilitating the access to bacteriological analysis.
It consists in sampling N independent realizations w i , i = 1,. N with the following sampling procedure: • Step 1: Initialization of Monte Carlo weights w i = 0 and w ðqÞ i ¼ 0 for q 2 N, scattering counter j = 0, emission location r = 0 and emission direction u = e x (see  Fig 1). • Step 2: Wavelength λ is sampled according to the incident spectrum p i (λ), and the extinction coefficient k λ = CE λ is interpolated from spectral database. • Step 3: A first extinction length l is sampled over [0, +1[ according to the Bouguer extinction probability density function p L ðlÞ ¼ k l e À k l l and the location is updated: r = r + l u. • while 0 � r � e x � L (location is inside the slab) do Step 4: Bernoulli test: uniform sampling of a realization ξ over [0, 1] • if ξ < F (scattering event) then Step 4a.
1: Scattering counter is incremented: j = j + 1. Step 4a. 2: Scattering direction u is sampled according to the isotropic phase function. Step 4a. 3: Wavelength λ is sampled according to the luminescence spectrum p L (λ) and the extinction coefficient k λ = CE λ is interpolated from the spectral database. Step 4a. 4: Extinction length l is sampled over [0, +1[ according to the Bouguer extinction probability density function p L ðlÞ ¼ k l e À k l l and the location is updated: r = r + l u. end.
Samples are maintained at the desired temperature for 5 min before the measurement. Emitted photons are collected during 50 ms with an sCMOS Camera (Andor Zhyla 5. 5) for each temperature steps, while keeping constant all other parameters such the incident illumination (6 mW), the grey scale, or the dynamic range  (16 bits). The total intensities emitted from the nanocrystals are then extracted with imageJ software. PL of the Yb 3+ ,Er 3+ -doped α-La(IO3)3 nanocrystals is clearly observed on the optical micrograph as illustrated within Figure  3. The transmitted wavelengths of the FITC cube ranges from 510 and 550 nm (>80%) with a maximum at 525 nm (95%), and enables to collect the main emission spectra of the nanocrystals with two main emission peaks at 522 and 544 nm (Figure  1 ). Large aggregates identified in dark field (dark clusters within Figure  3a ) correlated with fluorescent cluster on FITC-micrograph, as the one highlighted by the arrows to give an example (Figure  3b ).
Data evaluation For the XAS analysis, the QEXAFS data were read-in, split and energy calibrated using the JAQ Analyzes QEXAFS software (version 3. 3. 49v5. 4). 47 For EXAFS data, the data of 5 minutes recording was averaged and further evaluation was performed using the Demeter software package (version 0. 9. 21). 48 After normalization, background reduction and Fourier transformation (k-range showing the analysis regions. (c) Overview on the catalyst test sequence and conditions with a reference lean lightoff step (10 K/min in 1000 ppm CO, 500 ppm C3H6, 1% H2O and 8% O2 in He), a catalyst activation with 10 reductive pulses (3% CO, 1% H2O and 1% O2 in He) and a second light-off of the activated catalyst. The pulse length and the activation temperature were varied as follows: 30 s pulses at 250 °C, 5 s pulses at 250 °C and 5 s pulses at 350 °C.
d: Overview on the applied characterization techniques and whether they were used spatially resolved. from 3. 0-9. 0 Å -1 ), the EXAFS data was fitted using structural models based on bulk Pt (ICSD 41525) and bulk PtO2 (ICSD 4415) and refined using the ARTEMIS software. 48 Two single scattering paths for Pt-Pt (from bulk Pt; interatomic distance=2. 807 Å) and Pt-O (from bulk PtO2, interatomic distance=2. 070 Å) were considered for the fit, which was performed k 1 , k 2 and k 3weighted in R-space (1. 00-3. 00 Å). An amplitude reduction factor of 0. 858 was determined by fitting the experimental EXAFS data for a Pt foil with a structure model based on bulk Pt and used for all fits (further details in Tables S1-S4 and Figures S6-S13 in the supporting information). Transient XAS data was evaluated using a MATLAB script performing merging (for light-offs: 60 spectra were averaged, resulting in one spectrum every 30 s; for the pre-treatment: 4 spectra were averaged, resulting in one spectrum every 2 s), smoothing, energy calibration, normalization, background subtraction and the linear combination analysis (LCA) in a range from 11534 eV to 11634 eV.
For the LCA, the as-prepared Pt/CeO2/Al2O3 catalyst in oxygen and after a H2 temperature programmed reduction at 400 °C were used as references. For plotting, the time resolved spectra were averaged and normalized using a python script based on Larch 49. Time resolved IRT data was evaluated using the IRBIS 3 software (version IRBIS 3. 1 professional 50 ).
ACKNOWLEDGMENT This paper is dedicated to  Professor Enrico Tronconi  in honor of his outstanding contributions towards a better understanding of the behavior of catalytic reactors. The authors gratefully acknowledge the  German Federal Ministry for Economic Affairs and Energy (BMWi :  19U15014B ) and the  French National Research Agency  ( ANR-14-CE22-0011-02 ) for funding the DEUFRAKO collaboration ORCA. The DFG is thanked for financial support of infrastructure at  KIT  ( INST 121384/16-1 ,  INST   121384/73-1 ,  INST   121384/73-1 ) and  DESY  for beamtime at the P64 beamline. Moreover, the work was funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) -Project-ID  426888090 -SFB 1441. D. Zengel ,  G. Cavusoglu  and  D. Doronkin  ( ITCP/IKFT, KIT ) are appreciatively acknowledged for assistance during operando XAS experiments as well as  J.
The electrospinning voltage was kept constant at 25 kV and the solution flow rate at 1 ml/h. The air in the electrospinning chamber was set to a temperature of 21 ± 1°C with a relative humidity of 38 ± 2 %. To measure the surface potential, a non-contacting electrostatic voltmeter ESVM (Trek Model 347-3-H-CE) connected to a computer for data acquisition was used. The measurement is based on a field-nulling technique for non-contacting voltage measurement achieving direct current stability and high accuracy, with no need for fixed probe-to-surface spacing. The technique allows an accurate measurement of the surface potential of stationary or moving surfaces. The measurement range is 0 to ± 3 kV with an accuracy of 0. 1% of the full range. The probe of the voltmeter (end-view probe model 6000B-7C with a speed of response of 4.
Acknowledgements The authors are grateful to the  French National Research Agency  for the financial support of this work (Project  MimHeart  project  ANR-15-CE08-0010-02 ). We thank  China Scholarship Council (CSC)  for the financial support of the PhD student. We also thank  Christophe Mélart ,  Michel Wolf  and  Thierry Djekriff  for their help in the electrospinning set up.
015 mg precision. 280 mm thick monocrystalline silicon (100) wafers (Neyco S. A. ), cut in rectangles of 32 Â 24 mm 2 , were used as substrates. They were supported vertically by two custom-made substrate holders placed in the isothermal region  [26]. The films thickness was estimated by ellipsometry, with a Semilab SE-2000 instrument, operating between 250 and 1000 nm wavelength range, using a constant incidence angle of 70. The measurements were performed by probing 3 points vertically along the surface's center of each sample. The spectroscopic ellipsometry data were simulated and fitted in the 250e1000 nm wavelength range using the Semilab SEA software. The calculated results were collected for a linear regression R 2 fit of over 0. 99. Water content was evaluated using the Bruggeman effective medium approximation (BEMA) model, applying a three components medium, including SiO 2 , void and H 2 O.
RBS was performed at a 166 detection angle with 2 MeV a particles. Oxygen concentration was measured through the 16 O(d,a 0 ) 14 N nuclear reaction using incident deuterons of 0. 9 MeV and emitted alpha particles detected in the previous configuration at a 166 angle. ERDA measurements were performed with 2. 8 MeV alpha beam. The sample was positioned at 15 grazing incidence angle and the recoiled hydrogen atoms were collected at a scattering angle of 30. The composition of the films was obtained by simulation of the RBS, NRA and ERDA spectra using the SIMNRA  software  [33]. A polycrystalline silicon wafer with a top layer of 213 nm SiO 2 film and a-Si(H þ ) hydrogen standard at 2. 19 Â 10 17 H/cm 2 , a carbon and a SiC polycrystalline films were used for the energy calibration of the detector  [34].
Upon acquisition, the obtained spectral data were further processed by removing substrate signature and correcting the baseline. Finally, absorbance values were normalized by each film thickness, since SiO 2 peak intensities are affected by the thickness of the film in transmission mode  [9, 36]. Nanoindentation tests were carried out using an Ultra-NanoIndenter apparatus from CSM Instruments (Anton Paar) with a Berkovich diamond indenter. For nanoindentation, the load was gradually increased until a maximum value of 0. 5 mN, at which the load was maintained for 30 s, and then decreased down to zero. The loading and unloading rate was 1 mN/min. The system has typical load and displacement resolutions of 0. 25 mN and 0. 1 nm respectively. Elastic modulus and hardness were calculated from the load vs.
Acknowledgments The present work was funded by the  French Agence Nationale de la Recherche (ANR)  under the Contract  HEALTHYGLASS ANR-17-CE08-0056. It was co-funded by the  European Union , the  R egion Centre-Val de Loire and The French Minister of Research (MESRI-DRRT). The authors are indebted to  Elodie Chauvet  and  Charbel Roukoss  from  TESCAN Analytics  for the AFM, XPS and ToF-SIMS measurements,  Claudie Josse  from the  French 'Centre de Microcarat erisation Raymond Castaing', Toulouse , for the FIB preparations of the films, and  Simon Ponton  (CIRIMAT) and  Domingos de Sousa Meneses (CNRS-CEMHTI)  for their guidance in IR-spectroscopy analysis and interpretation.