dataesr/scientific-paragraphs-categorization huggingface dataset:
We vary such value from 0 (no IPL procedure is performed, these results are equivalent to the ones obtained by the DMTS-PUL NoIPL ) to 7. For this experiment, a set of positive samples with a size equal to 30 is considered. Generally, as we can expect, we observe that as the number of iterations increases, the F-Measure performances ameliorate. The involved benchmarks are characterized by two distinct behaviours. A first one shared by ArabDigits, ECG5000, HAR and PenDigits. Here, the performances stack and remain stables after three or four iterations of the IPL procedure. Conversely, for Dordgone, seqMNIST and SpeechCommand we see that the performances are still growing as the number of iterations increases. This is probably due to the fact that, while on the former bunch of datasets DMTS-PUL already obtains high level performances (more than 95 points of F-Measure), the second set of test cases exhibit higher complexity/difficulty thus, resulting in general lower absolute performances of DMTS-PUL with room for improvement.
This is probably due to the fact that, while on the former bunch of datasets DMTS-PUL already obtains high level performances (more than 95 points of F-Measure), the second set of test cases exhibit higher complexity/difficulty thus, resulting in general lower absolute performances of DMTS-PUL with room for improvement. Figure5depicts a sensibility analysis of our framework varying the amount of samples to be added to the positive (resp. reliable negative) set at each iteration. We vary such a value from 10 to 50. For this experiment, we set the parameter.
Timing: 5 days The crystallographic structure of Fe II and Zn II complexes can be determined by combining single crystal and powder X-ray diffraction. Single-crystal X-Ray diffraction (SCXRD) 8. Collect Single-Crystal X-Ray diffraction (SCXRD) data at 100 K with a diffractometer, Bruker APEX duo diffractometer with an APEX II CCD detector using Mo-Ka (l = 0. 71073 A ˚) and equipped with an Oxford Cryostrem 700 plus. 9. Obtain the crystal structure solution using SHELXTL and the XP program. Note: Both structures crystallized with high degree of disorders with one molecule of an anionic trimetalic complex, six dimethylammonium cations and five water molecules in the asymmetric unit, being Fe3 and Zn3 isostructural complexes (Figure  4 ). (Fe 3 CCDC deposition number: 1016539 ; Zn3 CCDC deposition number: 2019876).
vi. Plot the c M T product vs. T to obtain Figure  13B. Note: The temperature can be controlled from -80 C to 100 C by using liquid nitrogen as a coolant. This cryostat is placed inside a sample compartment of Agilent 8453 diode array spectrophotometer (l = 190-1,100 nm), see Figure  15. c M = 3dfM 4pfm viii. Set the kinetic mode in the spectrometer software (1 spectra$min -1 ) and manually set the temperature in the cryostat during heating and cooling processes (0. 5 K min -1 -0. 1 K min -1 range scan rate). ix. The exact temperature in the solution was monitored by thermocouple Pt100 controller. CRITICAL:. It is important to monitor the exact sample temperature that correspond to each spectrum to mitigate the difference between the set and sample temperature (up to b. UV-Vis absorption data i.
ACKNOWLEDGMENTS This work was supported by the  European Union  (projects  ERC StG  grant  CHEMCOMP no. 279313  and  ERC CoG  grant  GREENLIGHT_REDCAT no. 648304 ); the  Ministerio de Ciencia e Innovacion for support through Severo Ochoa Excellence Accreditation   2020-2023  ( CEX2019-000925-S, MIC/AEI ) and  Maria de Maeztu Exellence Accreditation  ( MDM-2017-0767 ); the  Spanish Ministerio de Ciencia e Innovacion  through the projects  PID2021-124796OB-I00 ,  PGC2018-095808-B-I00 ,  PGC2018-093863-B-C21 ,  PID2020-112733GB-I00 ,  PID2021-122464NB-I00 , and  PID2020-115165GB-I00 ; the  Generalitat de Catalunya  ( 2017-SGR-1406  and  2017-SGR-1277 ); and the  CERCA Programme/ Generalitat de Catalunya.
Full Factorial Design Modeling The quality of the developed FFD models was analyzed using the software "JMP 13 pro". This method established a mathematical equation (Equation (  1 )) linking four input variables, i. e. , SDBS concentration, kerosene concentration, PEG, and sodium chloride concentration, to four output variables: conductivity (mS/cm), turbidity (NTU), viscosity (mPa. s), and interfacial tension (mN/m). Table  1  presents the outcomes of 19 experiments conducted in the laboratory. It is important to note that the final concentrations of the output variables (conductivity, turbidity, viscosity, and interfacial tension) were used in the analysis. The statistical information required for the development and comprehension of the FFD model is presented in Table  2. Equation (1) represents the relationship between the four input variables, including their interactions, and the four output variables.
Multi-Objective Optimization The primary aim of this study was to identify the optimal concentrations of SDBS, kerosene, PEG, and sodium chloride that result in the best system performance. To achieve this, the study used multi-objective optimization (MOO) to solve the optimization problem. The four objectives were assigned weights, and their weighted sum was considered as a single objective, which was solved using the particle swarm algorithm available in the MATLAB Optimization Toolbox  [16]. The objective functions considered in this study were the minimum conductivity (J 1 ), the minimum turbidity (J 2 ), the minimum viscosity (J 3 ), and the minimum interfacial tension (J 4 ). These objectives were combined into a scalar goal as follows: J = w 1 J 1 + w 2 J 2 + w 3 J 3 + w 4 J 4  (10)  where w 1 , w 2 , w 3 , and w 4 are weighting factors, which can be calculated using the rank sum method  [16, [43] [44] [45].
General information, reagents and chemicals Proton ( 1 H NMR) and carbon ( 13 C NMR) nuclear magnetic resonance spectra were recorded on a Bruker Avance III instrument operating at 500 MHz (Bruker Corporation, Billerica, MA, USA). The chemical shifts are given in parts per million (ppm) on the delta scale. The solvent peak was used as reference values for 1 H NMR (CDCl 3 = 7. 26 ppm, CD 3 OD = 3. 31 ppm, CD 3 COCD 3 = 2. 05 ppm) and for 13 C NMR (CDCl 3 = 77. 16 ppm, CD 3 OD = 49. 00 ppm, CD 3 COCD 3 = 29. 84 ppm). Data are presented as follows: chemical shift, multiplicity (s = singlet, d = doublet, t = triplet, q = quartet, dd = doublet of doublet), integration, and coupling constants (J/Hz). High-resolution mass spectra (HRMS) data were recorded on a micrOTOF spectrometer (Bruker Corporation, Billerica, MA, USA) equipped with an orthogonal electrospray interface (ESI).
Chromatography An Agilent Technologies (Waldbronn, Germany) 1100 Series HPLC system (high-pressure binary gradient system equipped with a diodearray detector operating at multiple wavelengths (220, 254, 280, 360 nm), a programmable autosampler with a 20 μl loop, and a thermostated column compartment) was employed for analytical separations. Data acquisition and analyses were carried out with Agilent Technologies ChemStation Version B. 04. 03 chromatographic data software. The UV absorbance is reported as milliabsorbance units (mAU). Lux Cellulose-1 [cellulose tris  (3,5- dimethylphenylcarbamate)], Lux Cellulose-2 [cellulose tris(3-chloro-4-methylphenylcarbamate)], Lux Cellulose-3 [cellulose tris(4-methylphenylbenzoate)], Lux Cellulose-4 [cellulose tris(4-chloro-3-methylphenylcarbamate)], Lux i- Cellulose-5 [cellulose tris  (3,5-dichlorophenylcarbamate) ], Lux Amylose-1 and i-Amylose-1 [amylose tris  (3, 5 -dimethylphenylcarbamate)], Lux Amylose-2 [amylose tris(5-chloro-2-methyl-phenylcarbamate)], and Lux i-Amylose-3 [amylose tris(3-chloro-5-methyl-phenylcarbamate)] were used as chiral columns (5 µm, 250 × 4.
Acknowledgements We thank  CNR (Consiglio Nazionale delle Ricerche)  (Grant no. :  SAC. AD002. 011 )and  SRNSFG (Shota Rustaveli National Science Foundation of Georgia)  (Grant no. :  CNR-22-259 ) for the  Italy-Georgia Joint Bilateral Agreement , and the  University of Strasbourg , the  Centre National de la Recherche Scientifique (CNRS) , and the  French National Research Agency  (Grant no. :  ANR-21-CE07-0014 ) for financial support.
12 μM), at least the (+)-enantiomer  [74]. Beyond TopoII, two additional targets for rutamarin have been proposed on the basis of a molecular modeling analysis: the protein tyrosine phosphatase 1B (PTP1B) and the retinoid X receptor α (RXRα). Rutamarin would be an inhibitor of PTP1B and a RXRα agonist. The molecular models have been validated experimentally. Rutamarin effectively inhibits the PTP1B enzyme (IC50 = 6. 4 μM), acting as a competitive inhibitor capable of enhancing the insulin-induced translocation of the glucose transporter 4 (GLUT4) in CHO/GLUT4 cells  [78]. In addition, the structure of the furocoumarin bound to RXRα has been solved by X-ray crystallography, as represented in Figure  7  (PDB: 3PCU). The targeting of RXRα with rutamarin triggers an increased expression and translocation of GLUT4.
12 µM), at least the (+)-enantiomer  [74]. Beyond TopoII, two additional targets for rutamarin have been proposed on the basis of a molecular modeling analysis: the protein tyrosine phosphatase 1B (PTP1B) and the retinoid X receptor α (RXRα). Rutamarin would be an inhibitor of PTP1B and a RXRα agonist. The molecular models have been validated experimentally. Rutamarin effectively inhibits the PTP1B enzyme (IC 50 = 6. 4 µM), acting as a competitive inhibitor capable of enhancing the insulin-induced translocation of the glucose transporter 4 (GLUT4) in CHO/GLUT4 cells  [78]. In addition, the structure of the furocoumarin bound to RXRα has been solved by X-ray crystallography, as represented in Figure  7  (PDB: 3PCU). The targeting of RXRα with rutamarin triggers an increased expression and translocation of GLUT4.
Discussion Plants of the Rutaceae family can be found in all territories worldwide. The Ruta L. genus originates the Mediterranean region, including the Mediterranean basin and Macaronesia, with species showing a very variable distribution. Some species are endemic to islands, such as R. corsica DC. in Corsica and R. oreojasme Webb. in the Canary Islands. R. angustifolia Pers. presents a circum-Mediterranean distribution, like its closest phylogenetic neighbor R. graveolens L. [108]. However, today, these plants can be found in all continents, including in Southeast Asia where they are even cultivated  [109, 110]. R. graveolens (garden rue, herb-of-grace) is far more frequently studied for its phytochemical, medicinal, ornamental properties than R. angustifolia which is much less known. For example, the PubMed ® databank includes more than 2500 references with the key word "Ruta graveolens" compared to less than 20 with the key word "Ruta angustifolia".
Data analysis Statistical analyses were conducted with R software (version 3. 6. 1). Data from the different experimental groups were compared performing analysis of variance (AOV) when normality and homoscedasticity conditions were respected (parametric test) otherwise by performing Kruskal-Wallis (KW) test (non-parametric-test) in order to discriminate REE and/or DOM effect on a given variable (biomarker). Tukey HSD  (Miller, 1981)  and the multiple comparisons test from  Siegel and Castellan (1988)  (for parametric and non-parametric tests, respectively) were conducted as post-hoc tests to identify exactly which groups differ from each other. Data normality and homoscedasticity were checked with Shapiro-Wilk and Bartlett tests respectively. In addition, Hedge's g statistic was calculated based on the mean and standard deviation of each variable (biomarker) with the package "metafor"  (Viechtbauer, 2010).
This method is more suitable and accurate for small samples (n = 3)  (Cline, 2019). Differences in median values between groups were considered statistically significant when the 95 % CI excluded zero. Relationship between two variables was evaluated by performing a linear regression test of Pearson (when data normality is respected) otherwise Spearman using the whole data set for each variable (n = 60-120 individuals). A difference was considered as statistically significant in case of a p-value <0. 05. A principal component analysis (PCA) was performed to compare biological effects observed in the different experimental groups. The criterion of Kaiser-Meyer-Olkin  (Kaiser and Rice, 1974)  was calculated (KMO = 0. 72) and confirmed that the used dataset was suitable to run factorial analysis.
Acknowledgements We gratefully acknowledge technical assistance from the  Pôle de compétences en biologie environnementale  and the  Pôle de compétences en chimie analytique environnementale, ANATELo ,  LIEC laboratory ,  UMR 7360 CNRS -Université de Lorraine. The authors specifically thank  Maximilien Beuret ,  Danièle Pauly  and  Marie Zaffino  for their contributions and  Bert-Jan Groenenberg  for providing the DOM stock solution.
This work was supported by the French National Research Agency through the ECOTREE project [ANR-16-CE34-0012] and the national program "Investissements d'avenir" [ANR-10-LABX-21-01/RESSOUR-CES21] with financial support by the ZAM LTSER Moselle for the thesis of Nicolas Lachaux. CRediT authorship contribution statement Nicolas Lachaux: Conceptualization, Data curation, Formal analysis, Investigation, Validation, Visualization, Writing -original draft. Alba Otero-Fariña: Validation, Formal analysis, Investigation, Data curation, Writingreview & editing. Laetitia Minguez: Validation, Formal analysis, Investigation, Data curation, Visualization, Writing -.
Acknowledgment We thank  Taglit R/V team -Shahar Gan-El ,  Meir Yifrach , and  Ziv Mor  for field assistance. This study was funded by the  Israel Science Foundation, PI-NGL  (grant #  ISF 1471/18 ), the  US-Israel Binational Science Foundation (BSF) Prof. Rahamimoff Travel Grant for Young Scientists  to IS (grant #  0378745 ) and the  University of Palermo  ( CON 0037 ).
6-NA air objective (Olympus LUMPlanFL N). The sample was illuminated with a white light source (Hg lamp) coupled through Olympus U-MSWB2 cube (with excitation filter within 450-480 nm and emission at 500 nm) to excite and reveal fluorescence emitted from the deprotonated FITC probe, occurring for pH higher than ca. 6 (Fig. S1 ). [1] A digital USB color camera (UI-3080CP Rev. 2, IDS with CMOS 2456×2054-pixel detector) collected the fluorescence emitted from the solution. FL images are recorded at a speed of 2 frames per second (fps) with 500 ms accumulation time. Data analysis was done on selected regions of interest using Python.
Later, we located identical particles on SEM and EDX images (vide infra) using similar procedure of fitting to a 2D-gaussian distribution to further perform the alignment of insitu RM and ex-situ SEM/EDX images with a pixel precision. All reflectivity maps were normalized by the intensities from the first reflectivity image and converted to the change of the thickness of surface films according to the Fresnel model described below. The image analysis was performed using Python scripts. Examples of image analysis, as well as the original data, are available in the Zenodo repository (https://doi. org/10. 5281/zenodo. 7963186) under a Creative Commons Attribution 4. 0 International license. Description of the Fresnel model for the conversion of reflectivity changes to the changes of surface film thickness.
Ex-situ scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDX) surface analysis of identical locations Identical locations of optical images were retrieved in secondary electron images during SEM analysis with the aid of grid marked on the Al6061 surface. SEM and EDX analyses were performed on a Gemini SEM 360 from Zeiss, with an acceleration voltage of 10 kV and 5 kV correspondingly, and 60 µm aperture window. Spectra and elemental mappings were processed using the AZtec software. The alignment to a pixel precision of optical and SEM/EDX images were performed with the automated feature-based algorithms implemented in OpenCV library, described in detail in ref  [10].
Ex-situ atomic force microscopy (AFM) Atomic force microscopy (AFM) experiments were performed using the NT-MDT AFM Instruments, installed on a dynamic anti-vibration device. Imaging of Al6061 surface was performed in air using standard tapping AFM mode, with Al-coated silicon probes from Nanosensors (cantilevers 40 ± 10 N/m spring constant and 290 ± 10 kHz resonance frequency). The pyramid-shaped tips had a radius of curvature of less than 10 nm. Topographic images were recorded at scan rates of 1 or 0. 5 Hz. Image processing (flatten, plane fit, edge, and profiles, etc. ) was performed with the WSXM processing software. At least three different areas of each sample were scanned, and typical images were presented. Values of nanoparticles height and size were determined.
SI-2 Finite Element Method (FEM) simulations of particle crosstalk The FEM model was built in a 3D geometry with COMSOL Multiphysics 5. 5 software (1) to simulate the steady-state pH distribution and (2) to simulate the transients of Al(OH)3 dissolution/precipitation in the case of galvanic corrosion of Fe-and Si-rich particles dispersed in Al matrix of Al6061 alloy. The geometry of simulated area (Fig. S4 ) was chosen to mimic the particle positioning observed in in-situ RM experiment: Si-rich particle is represented by a 2 µm in diameter disk (2D) while Fe-rich particles are 3 small disks (2D) of 1 µm in diameter located on the same side relative to Si-rich area, all positioned at the bottom of the simulation box in the shape of hemisphere. Note that we do not aim to reproduce the exact conditions (particle sizes, shapes, and positions) since in any case, other parameters (local potential and current distributions) were not accessible experimentally.
′ = 10 -33 and  ′′ = 0. 257 were retrieved from the database of chemical equilibrium software [9] while  ′ = 4. 5×10 27 mol/(m 2 s) and  ′′ = 1. 0×10 10 mol/(m 2 s) were chosen empirically to provide the best fit of experimental data on the evolution of surface films (Fig. 2b  in the manuscript). The initial concentration of {() 3 } was set to 3. 1×10 -4 mol/m 2 that corresponds to the experimentally measured (vide supra) 10 nm surface oxide/hydroxide layer, taking into account the density of Al(OH)3 as 2. 42 g/cm  3. Finally, the input fluxes of OH -and Al 3+ were multiplied by an empirical parameter p that equaled to 0 between 0 s -20 s then 0. 23 between 20 s -53 s and 1. 0 between 53 s -120 s. In this way, we provided the transition between different regimes of surface film evolution observed experimentally in Fig.
Acknowledgements This work was partially financially supported by the  Agence Nationale de la Recherche  ( ANR) Jeunes chercheuses, jeunes chercheurs, ANR JCJC, program  ( OCTAWA  project,  ANR-22-CE29-0010-01 ). L. G. acknowledges the  Ecole normale supérieure Paris-Saclay  for funding. The authors acknowledge the  ITODYS-LISA XRD facility , the  ITODYS SEM-EDX facility , the  Ile-de-France region ,  and initiative d'excellence (IDEX) program  for financial support of the  AFM-Beam-Rex  platform. The authors also gratefully thank  Sophie Nowak  and  Xiaonan Sun  for discussions on the XRD data and implementation of AFM experiments.
Observations and data accumulation The data presented in this paper are from an ongoing IRC+10216 Q-band (31-50 GHz) spectral survey within the framework of the Nanocosmos 1  project. The line survey accumulated 780 h of on-source observing time at each frequency in 250 observing sessions from May 2019 through the end of January 2023, with the 40 meter antenna of Yebes Observatory (IGN, Spain), (which we refer to as Yebes 40m throughout this paper). During this observational period, several improvements to the Nanocosmos equipment and the telescope were made. This large antenna now provides a main beam efficiency from 0. 6 at 31 GHz to 0. 43 at 50 GHz, and a beam size from 56 ′′ to 36 ′′ between those frequencies. Although the experimental setup was described in detail by  Tercero et al. (2021) , the most relevant information for this work is the use of a receiver consisting of two high-electron-mobility transistor (HEMT) cold amplifiers covering the 31.
0-50. 3 GHz band with horizontal and vertical polarizations. The backends are 16×2. 5 GHz fast Fourier transform spectrometers (FFTSs), with a primary spectral resolution of 38. 1 kHz, providing the whole coverage of the observed band in both polarizations. The observing mode was position switching with an off position at 300 ′′ in azimuth. The reference position used for IRC+10216 has been J2000 RA 09h47m57. 36s Dec +13º16 ′ 44. 4 ′′. The HPBW of the antenna at 39. 2 GHz is 45 ′′. Pointing corrections were obtained by observing the SiO masers of R Leo, and errors were kept within 5 ′′. The intensity scale of the final calibrated data is the antenna temperature (T * A ) corrected for atmospheric absorption using the ATM package  (Cernicharo 1985; Pardo et al. 2001). Calibration uncertainties are estimated to be within 10%.
Results Line identification for this study made use of the catalogs MADEX  (Cernicharo 2012) , CDMS  (Müller et al. 2005) , and JPL  (Pickett 1998). As of January 2023, the MADEX package contained 6464 spectral entries corresponding to the ground and vibrationally excited states, together with the corresponding isotopologues, of 1765 molecules. The new data of IRC +10216 have an unprecedented sensitivity level (see Fig. 1 ), reaching σ values as low as 0. 15 mK on the T * A scale for a spectral resolution of 229 kHz. The new data show a forest of unidentified lines, of which over 250 have been assigned to HC 9 N in nν 19 vibrational states from n = 1 up to 7. After a clear identification of these features it has been possible to detect several new molecules, such as C 7 N -  (Cernicharo et al.
We consequently focused our search on IRC+10216 as the intensity of the lines in TMC-1 is expected to be very low. A series of 15 lines was found in perfect harmonic relation with J u from 52 up to 71. These lines are shown in Fig. 2  and their line parameters are presented in Table  1. A fit to the observed frequencies yields B = 299. 8728 ± 0. 0013 MHz and D = 1. 14 ± 0. 18 Hz. The standard deviation of the fit is 86 kHz. Remijan et al. (2023)  have recently reported, using line stacking techniques and lower frequencies, the detection of a new molecule in TMC-1 with B = 299. 8713 MHz and D = 1 Hz (fixed value) that they assign to be C 10 H -. The rotational constant is in close agreement to the one we derived for our series of individually detected lines in IRC+10216. In fact, if we fix the distortion constant to 1 Hz, as the above authors did for the stacked data of TMC-1, the derived rotational constant for our series of IRC +10216 lines would be 299.
3 MHz (Etim & Arunan 2017) and 311 MHz  (Arnau et al. 1993 ) depending on the level of theory used in the calculations. The species HCCNC and HCCCCNC have been observed in TMC-1  (Cernicharo et al. 2020b ). Hence, HC 6 NC and HC 8 NC could also be present in TMC-1. However, HCCCCNC is not observed in IRC +10216, and HC 6 NC is not observed toward TMC-1 with the QUIJOTE line survey, nor toward IRC +10216 in the current ultrasensitive data set. Consequently, there is little chance that HC 8 NC is the carrier of our lines. Similar arguments apply to other possible isomers of HC 9 N. We therefore conclude that the most plausible carrier of our 15 lines is C 9 N -or C 10 H -, and discuss these two possibilities in detail in the following section.