dataesr/scientific-paragraphs-categorization huggingface dataset:
Surface Complexation Modeling. The multisite complexation (MUSIC) model  54  and the geochemical speciation code PHREEQC (version 2)  55  were used for surface complexation calculations. The charge of the goethite/water interface was treated using the three-plane model (TPM) for the electric double layer (EDL). Charges of the adsorbates were distributed among the 0-(H + , metal-bonded PA and silicate), 1-(hydrogenbonded PA, and metal-bonded silicate), and 2-(Na + , Cl -) planes. Singly (≡FeOH -0. 5 ; OH), doubly (≡Fe2OH; OH), and triply (≡Fe3OH  +0. 5  ; O(H)) coordinated oxygens outcrop the goethite surface, depending on the crystal face (Figure  1 ) and pH. The protonation of these species was predicted using a simplified 1-pK model, here neglecting the contributions of doubly-and part of the triply-coordinated oxygens.
ACKNOWLEDGEMENTS This work was supported by the  Swedish Research Council  ( 2020-04853 ) to J. -F. B and the  CNRS  ( PICS 2018-2020 ) to K. H. and J. -F. B. W. C. was supported by the  China Scholarship Council  for a Ph. D. grant, and by  Rennes Métropole (France)  for a mobility grant for an extended research visit at  Umeå University. K. H. is also supported by the  Institut Universitaire de France (IUF).
The mechanism of the photodissolution of the catalyst is ultimately quite complex and the data here reported can only partially clarify it. The organic coating has an active role in the process especially because the carboxylic moieties at the surface are effective ligands for Fe +2 and Fe +3. Moreover, these iron complexes at the surface are not only redox active species able to react with hydrogen peroxide or persulfate, but they are also photoactive species. Note that, the spectrophotometric method used to determine the iron concentration in solution was carried out on filtered solutions and consequently is silent on the concentration and speciation of the iron complexed by organic ligands at the surface of the catalyst. The contribution of the iron released in solution on the initial BPA degradation was evaluated as follows: BPA and H 2 O 2 /S 2 O 8 2-were added to the supernatant solution after removing the heterogeneous catalyst by filtration.
Acknowledgements This work is part of a project that has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No  765860. Authors also acknowledge the financial support for experiments provided by the  Region Council of Auvergne , from the  "Féderation des Recherches en Environnement"  through the  CPER "Environment"  founded by the  Region Auvergne , the  French government ,  FEDER  from the  European Community  and from CAP 20e25 I-site project.
Acknowledgements This work was generously supported by the  Colorado School of Mines Slater Family Research Fund , the  U. S. Bureau of Reclamation  ( R16AC00121 ), the  Colorado Office of Economic Development and International Trade , a  National Science Foundation   CAREER Award  ( 1752531 ), and the  Embassy of France Thomas Jefferson Fund. The authors thank  Dr. John Farnsworth  ( University of Colorado, Boulder ) for helping interpret vortical flow structures. We also thank  Drs. Tony Saad  ( University of Utah ),  Amneet Pal Bhalla  ( San Diego State University ),  Amir Riaz  ( University of Maryland ), and  Drs. Paul Martin  and  Greg Fasshauer  ( Colorado School of Mines ) for aiding our code development. Fig. 22. Downstream variation of ΔT m (a), c m (b), and v m (c) for the cases in Fig.
FUNDING This research was supported by the  Korea CCS R&D Center  ( NRF-2014M1A8A1049273 ) funded by the  Korean government (Ministry of Science and ICT)  to EJ, the  ERC   Starting Grant SOLENALGAE  ( 679814 ) to MB,  HFSP  ( RGP0046/2018 ), GRAL  LabEX GRAL  ( ANR-10-LABX-49-01 ), and  ANR  MetaboLIGHT ( 18-CE20-0006-01 ) to DP.
Alternative respiration was inhibited by adding 2 mM SHAM (salicylhydroxamic acid), while the cytochrome pathway (complex III) was inhibited by adding 5µM myxothiazol. To assess the relative contribution of the cytochrome pathway, respiration was first measured in the absence of inhibitors (total dark respiration) before alternative respiration was inhibited by adding SHAM. Cytochrome dependent respiration was then inhibited using myxothiazol and the residual respiration determined in relation to the uninhibited state. The contribution of alternative respiration was determined by reversing the order of inhibitor addition (myxothiazol followed by SHAM)  (Bailleul et al. , 2015). NAB1 sequence analysis. Chlamydomanas reinardtii NAB1 protein (Cre06. g268600. t1. 2) was blasted against C. vulgaris protein database  (Cecchin et al.
, 2019)  and C. sorokiniana protein database (https://greenhouse. lanl. gov/greenhouse/). Protein domains were obtained and aligned with Scanprosite tool of Prosite database  (de Castro et al. , 2006; Sigrist et al. , 2013). Sequence alignment was visualized with Clustal Omega  (Goujon et al. , 2010; Sievers et al. , 2011). Experimental replication and statistical treatment. All the experiments herein reported were performed at least three times. Errors are reported as standard deviations. Statistical significancy was tested by Tukey's test. FIGURE LEGENDS.
X-ray Diffraction For all samples, oriented slides were prepared by drying a clay suspension on glass slides at room temperature following contact with the organic solution. X-ray diffraction (XRD) patterns were then recorded using a Bruker D8 diffractometer equipped with an MHG Messtechnik humidity controller coupled to an Anton Paar CHC+ chamber. Intensities were measured with a SolXE Si(Li) solid-state detector (Baltic Scientific Instruments) for 4 s per 0. 04 • 2θ step over the 2-50 • 2θ Cu Kα angular range. The divergence slit, the two Soller slits, the antiscatter, and resolution slits were 0. 3 • , 2. 3 • , 0. 3 • , and 0. 1 • , respectively. Samples were kept at 23 • C in the CHC+ chamber during data collection. A constant flow of mixed dry/saturated air maintained a 40% relative humidity (RH) during data collection after an initial equilibration at ∼97% RH.
This system was coded ZnPc-BZA (Scheme 3). All the calculations related to the molecular geometry optimization, electronic absorption spectra and molecular orbitals were performed with the package Gaussian 09, rev. D. 01  54. To determine the interaction between the dye and the semiconductor (TiO 2 ), systems were computed after grafting the dye on a TiO saturating the oxygen dangling bonds. The geometry of the complex is partially optimized, where TiO 2 is frozen to retain the anatase-phase structure, and the dye with the anchoring group (-COOH) approaching to a titanium atom are fully optimized. The interaction between the fragments is monodentate meaning that one -O(OH) interacts with one titanium atom. The complex was optimized at the DFT level of theory with the D3 Grimme´s dispersion correction using the Quantum ATK package  55.
In addition, the popular nucleus independent chemical shift (NICS) and its z-component  62  (NICS zz ) have been measured in strategic positions, these indexes are especially reliable for π-aromaticity analysis  [62] [63] [64] [65]  and allows quantifying the magnetic response due to ring currents. These calculations were performed using Gaussian 09 in conjunction with AIMAll software  66  and MICD module planes were plotted using VisIt software  67. Additionally, the delocalization criteria  68  have been applied using the recently proposed AV1245 index  69  , specially designed for macrocycles such as porphyrinoids, whereas the multi-center index  70  (MCI) and para-delocalization index  71  (PDI) have been used to analyze the six-membered rings (6MR). Finally, the geometric criteria has been evaluated using the Harmonic Oscillator Model of Aromaticity 72 (HOMA), these indexes were calculated using the Multiwfn program  73.
Acknowledgements We acknowledge financial support by  Agence National de la Recherche (ANR)  through the program  Vision-NIR  ( ANR-17-CE05-0037-02 )  Région des Pays de la Loire  for the project LUMOMAT and  ECOS Sud-CONICYT (Chili). We thank the financial support of  ANID/CHILE  under the following projects:  FONDECYT 1171719  (G. C. -J. ) and 1180565 (X. Z. ),  FONDECYT  Postdoctoral  3180119  (R. P. -R. ) and  ECOS C19E03  (G. C. -J. , X. Z. ). M. Z. -A. is grateful for the graduate fellowship awarded by the  Vicerrectoría de Postgrado (VIPO)  of  USACH/CHILE , and Y. H. -R. is grateful for the PhD Program in Molecular Physical Chemistry from  University Andres Bello/CHILE. Powered@NLHPC: This research was partially supported by the supercomputing infrastructure of the NLHPC ( ECM-02 ) of the  Universidad de Chile.
Net power production In the dynamically positioned wind turbine concept, part of the electric power generated by the wind turbine P T (equation 5) is used to power the propellers P P (equation 13). The remaining net power production P net is stored in an energy storage system. Thus, P net = P T -P P. (15) 2. 6. Velocity and power prediction program A velocity and power prediction program has been developed in Matlab. It solves the equilibrium equation described in section 2. 1. It allows evaluating the rotational velocity of the propellers, their power consumption, the wind turbine power generation and the net power production.
Acknowledgements Antonio Madureira is grateful to the  Conseil Regional des Hauts-de-France  and  University of Artois  for the Ph. D. grant support. The  TEM facility in Lille (France)  is supported by the  Conseil Regional des Hauts de France  and the  European Regional Development Fund (ERDF). We thank  Dr. St ephane Menuel  for the synthesis of cationic cyclodextrins,  Pr. S ebastien Saitzek  for DRX analyses,  Dr. C ecile Machut  for ICP analyses,  Dr. Nicolas Kania ,  Dr. J eremy Ternel  and  Dominique Pr  evost for the technical assistance.
In the absence of an experimentally determined structure and given the high accuracy recently achieved in 3D modeling by AlphaFold and RoseTTAFold, it is interesting to question the prediction of the iron-sulfur binding site structures in proteins produced by these programs. Hence, here I analyze several 3D models of enzymes, including tRNA sulfuration enzymes and sulfidases, for which no homologous structure had been solved, to know if the amino acids forming the putative cluster-binding site are already positioned, in the apo-structure, to bind the cluster. For clarity, I use the term "structure" for proteins with experimentally determined structure, deposited at the Protein Data Bank (PDB), and "3D model" when the coordinates are calculated by AlphaFold or RoseTTAFold.
Enzymes, which catalyze U34-tRNA sulfuration in archaea (named NcsA) and the cytosol of eukaryotes (named Ncs6, Ctu1), belong to subtype II  [37, 38]. In contrast, enzymes, which synthesize s 2 U34-tRNA in bacteria, named MnmA, represent a different class that possesses a PP-loop motif and only one central D/CXXC motif  [39]. TtuA  [28, 29] , TtcA  [36, 40] , NcsA/Ctu1 (Bimai et al. , in preparation, PDB code 6SCY), as well as MnmA from Thermus thermophilus and Escherichia coli  [30, 31] , were shown to use the central CXXC + C motif to bind a [4Fe-4S] cluster. In all of these enzymes, the PP motif (Figure  1 ) is used to bind ATP to activate the target base.
Subsequent spectroscopic, sitedirected mutagenesis and enzymatic experiments indicated that EcMnmA binds a [4Fe-4S] cluster coordinated by Asp99, Asp102, and Cys199, which is necessary for catalysis  [31]. Accordingly, a [4Fe-4S] cluster can be modeled in the structure of apo-EcMnmA, based on the superposition of EcMnmA with Methanococcus maripaludis NcsA (MmNcsA) (Bimai et al. , in preparation, PDB code 6SCY) because the three catalytic residues Asp99, Cys102, and Cys199 of EcMnmA occupy equivalent positions to those of Cys142, Cys145, and Cys233 that bind the [4Fe-4S] cluster in MmNcsA (Figure  3B ). Interestingly, like in TtTtuA (Figure  2 ), Asp99 and Cys102 in EcMnmA, and Cys142 and Cys145 in MmNcsA belong to an α-helix, whereas Cys199 in EcMnmA and Cys233 in MmNcsA belong to a highly flexible loop.
Strains, growth and media composition Galdieria sulphuraria SAG21. 92 and 074G were obtained from the Culture Collection of Algae at Göttingen University (SAG) and were grown in sterile 2xGS modified Allen medium, pH 2. 0, containing 20 mM of NaNO 3 , and 5 mM of inorganic phosphate (K 2 HPO 4 and KH 2 PO 4 in a 2/1 ratio  (Allen, 1959) ) at 42°C without or with organic substrates as indicated in the text. The concentration of organic substrates was selected on the basis of data reported in literature  (Oesterhelt et al. , 2007). More precisely, glucose was employed at the concentration of 25 mM, as in  (Oesterhelt et al. , 2007). The concentration of all the other organic compounds was adjusted to reach the same carbon atom concentration (150 mM). G. sulphuraria was grown either in 250 mL flasks (50 mL culture volume), in an incubator (Infors, Switzerland, continuous light, 30 µmol photons m -2 s -1 , 42°C, 100 rpm) or in a photobioreactor  (Multicultivator, Photon System Instruments, Czech Republic).
The Proline software  (Bouyssie et al. , 2020)  was used to filter the results (conservation of rank 1 peptides, peptide identification FDR < 1% as calculated on peptide scores by employing the reverse database strategy, minimum peptide score of 25, and minimum of 1 specific peptide per identified protein group). Proline was then used to extract the MS1-based intensities values of protein groups from unique peptides. Proteins identified in the reverse and contaminant databases (i. e. trypsin or keratin), and proteins identified with only 1 peptide with a score <40 were further discarded from the list. Proteins identified in only one or two conditions were kept for analysis without statistical treatment. Proteins identified in all three conditions were submitted to statistical differential analysis using ProStaR  (Wieczorek et al.
The aqueous phase was transferred to a new reaction tube and the organic phase was re-extracted with 400 µL of ice-cold deionized water. Aqueous phases of each sample were combined and lyophilized overnight. After resuspension in 500 µL of 50% methanol 50 µL were dried in a glass inlet for analysis by GC-MS and IC-MS. For GC-MS analysis the samples were prepared and analyzed as described  (Gu et al. , 2012)  and  (Shim et al. , 2020). Identification of metabolites was performed with MassHunter Qualitative (v b08. 00, Agilent Technologies) by comparing spectra to the NIST14 Mass Spectral Library (https://www. nist. gov/srd/niststandard-reference-database-1a-v14) and to a quality control sample containing all target compounds. Peaks were integrated using MassHunter Quantitative (v b08. 00, Agilent Technologies).
For relative quantification, all metabolite peak areas were normalized to the peak area of the internal standard ribitol. For IC-MS a combination of a Dionex ICS-6000 HPIC and a high field Thermo Scientific Q Exactive Plus quadrupole-Orbitrap mass spectrometer following the method described in  (Schwaiger et al. , 2017)  and in Methods S1. Data Analysis was conducted using Compound Discoverer (version 3. 1, Thermo Scientific). Setting parameters for the untargeted metabolomics workflow and peak annotation criteria are described in Methods S1.
Labelling experiments with 13 C-glucose Cells were cultivated in 250 mL Erlenmeyer flasks (50 mL culture volume) for four days under continuous light at 60 µmol m -2 s -1 , 40 °C and ambient air (0. 04% CO 2 ). U-13 C 6 -glucose (Cambridge Isotope Laboratories Inc, Tewksbury, Massachusetts) was added at day 4 in a final concentration of 25 mM and the irradiance was increased to 100 µmol m -2 s -1 either under ambient or elevated (2%) CO 2 conditions. 1-2. 5 x10 8 cells were harvested 1, 4, 12, 24, 36, 48 and 60 hours after glucose addition as described above. Metabolites were extracted and measured by IC-MS as described above. Data analysis was conducted with Compound Discoverer (version 3. 1, Thermo Scientific) and the standard workflow for stable isotope labelling from Compound Discoverer was chosen.
This is also true for Rubisco activase (Gasu_19410, dataset S1-2), an enzyme that was shown to be important under low CO 2 in Chlamydomonas  (Pollock et al. , 2003). These findings are also corroborated by metabolite analysis (Fig. 4a ). The amounts of the oxygenation product of Rubisco, 2-phosphoglycolate are highest under photoautotrophic conditions, lower in mixotrophic conditions, and very low in heterotrophic conditions. Glycine accumulates, likely due to a higher reduction potential inside the mitochondrial matrix under mixotrophic conditions, which will reduce the rate of oxidative decarboxylation of glycine by glycine decarboxylase. Consequently, the glycine to serine ratio was inverted compared to photoautotrophic conditions. The amounts of glycerate and 3-phosphoglycerate under mixotrophic conditions are mimicking those in heterotrophically grown cells (Fig.
Microalgae and media composition Galdieria sulphuraria SAG21. 92 and 074G were obtained from the Culture Collection of Algae at Göttingen University (SAG) and was grown in sterile 2xGS modified Allen medium, pH 2. 0, containing 20 mM of NaNO3, and 5 mM of inorganic phosphate (K2HPO4 and KH2PO4 in a 2/1 ratio,  (Allen, 1959 )) at 42°C. The medium and flasks were sterilized in an autoclave for 20 min at 121 °C in order to prevent any contamination. For the experiments with different organic carbon sources, the 2xGS modified Allen media was supplemented by adding filtersterilized concentrated organic substrate solutions as indicated in the text. The concentration of organic substrates was selected on the basis of data reported in literature  (Oesterhelt et al. , 2007). G. sulphuraria was grown either in 250 mL flasks (50 mL culture volume) in an incubator (Infors, Switzerland, continuous light, 30 µmol photons m -2 s -1 , 42°C, 100 rpm) or in a multicultivator (Photon System Instruments, Czech Republic).
The 20 most intense ions from the preview survey scan delivered by the Orbitrap were fragmented via collision-induced dissociation in the LTQ after accumulation of 1e5 ions (maximum filling time: 50 ms). Database searches and quantificationData were processed automatically using the Mascot Distiller software (version 2. 7. 1. 0, Matrix Science). Peptides and proteins were identified using Mascot (version 2. 6. 0) through concomitant searches against Uniprot (Galdieria sulphuraria taxonomy, July 2019 version), classical contaminants database (homemade) and their corresponding reversed databases. Trypsin/P was chosen as the enzyme and three missed cleavages were allowed. Precursor and fragment mass error tolerance were set, respectively, to 10 ppm and 25 mmu. Peptide modifications allowed during the search were: carbamidomethylation (fixed), acetyl (protein N-terminal, variable) and methionine oxidation (variable).
Acknowledgments GC, DL, AW, GF, MT, SB and MF acknowledge funds from the  ANR (French Research Foundation) 'Momix' (Projet- ANR-17-CE05-0029 ). GC and GF also acknowledge support of the  LabEX GRAL ,  ANR-10-LABX-49-01  financed within the  University Grenoble Alpes graduate school (Ecoles Universitaires de Recherche) CBH-EUR-GS  ( ANR-17-EURE-0003 ). DDB acknowledged a PhD grant from  CEA. J. D. was supported by the  ATIP-Avenir program. CR and MC acknowledge the  ARC grant  ( DARKMET proposal ) for Concerted Research Actions ( 17/21-08 ), financed by the  French Community of Belgium (Wallonia-Brussels Federation). This project received funding from the  European Research Council :  ERC Chloro-mito  (grant no. 833184 ) to GC and GF. Metabolite analyses were supported by the  CEPLAS Plant Metabolism and Metabolomics laboratory , which is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) under Germany´s Excellence Strategy -EXC-2048/1project ID 390686111.
Data availability The original contributions presented in the study are included in the article and in the Supplementary information and supplementary dataset files. Further inquiries can be directed to the corresponding author Other supplementary materials for this manuscript include the following: level by comparing MS 2 fragment spectra using mzCloud (ddMS2) (match factor 50) and MS 1 level ChemSpider (by formula or exact mass). Highest identification level via an in-house MS 2 spectral library and retention time was established using mzVault. QC-based batch normalization was performed with QC sample injection every 5 samples during the sequence. Differential analysis, determination of pvalues, adjusted p-values, ratios, fold change, were also calculated using Compound Discoverer.
Oesterhelt C, Tischendorf G, Lederer F. 2002. Characterization Proteins involved in photosynthesis, central metabolism and respiration were selected from the complete proteomic dataset (see Supplementary Dataset S2) and used to build Wieczorek S, Combes F, Lazar C, Gianetto QG, Gatto L, Dorffer A, Hesse AM, Coute Y, Ferro M, Bruley C, et al. 2017. DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics. Bioinformatics 33(1): 135-136. Xu F, Hu HH, Cong W, Cai ZL, Ouyang F. 2004. Growth characteristics and eicosapentaenoic acid production by Nannochloropsis sp. in mixotrophic conditions. Biotech Lett 26(1): 51-53. Yoon H, Hackett JD, Ciniglia C, Pinto G, Bhattacharya D. 2004. A molecular timeline for the origin of photosynthetic eukaryotes. Molecular Biology and Evolution 21(5): 809-818.
Yoon H, Hackett JD, Pinto G, Bhattacharya D. 2002. The single, ancient origin of chromist plastids. Proc. Nat. Acad. Sci. USA 99: 15507-15512. Yoon HS, Ciniglia C, Wu M, Comeron JM, Pinto G, Pollio A, Bhattacharya D. 2006. Establishment of endolithic populations of extremophilic Cyanidiales (Rhodophyta). BMC Evolutionary Biology 6(1): 78. Dataset S1: of a non-thermophilic strain of the red algal genus Galdieria isolated from Soos (Czech Republic). European Journal of Phycology 37: 477-483.
Attempts to quantify the action of water as refrigerant In this section, we look at where the mechanisms schematized in Figures  2  and 3  can lead on the basis of thermodynamics characteristics typical of the water cycle, namely, the 333. 55 KJ/Kg latent heat of ice melting, the 2,447 KJ/Kg latent heat of evaporation at 14°C, the 2. 11 KJ/Kg/°C specific heat capacity of solid ice and the 4. 184 KJ/Kg/°C specific heat of water, various factors with minor effects like salinity, CO2 dissolution in ocean and cloud liquid water, dusts, etc. being neglected  (Engineering Tool Box, 2003). To estimate and compare rAHR and eAHR in terms of Joules, the following data available for year 2018 were used: -14°C, the average temperature of Earth's surface determined from multiple land and ocean local measurements (NOAA; 2021), a value considered common to low atmosphere and ocean surface water; -0.
Acknowledgement The author is indebted to CNRS and University of Montpellier for providing access to local facilities in the framework of an Emeritus CNRS Research Director position. I am also indebted to the Editor-in-Chief of Earth's Future because he first accepted the submitted version after reviewing but faced complains later on and had to deny the acceptance on the basis of the reports of 5 extra reviewers. As I was not given the chance to reply to reviewer's reports although many comments and criticisms were disputable, the rejected submission was revised and the point-by-point reply at the origin is available as supplementary file or on e-mail request from readers who would like to appreciate the consistency of the reviewing and of the work. The author does not have any conflict of interest or specific funding to declare.
60 he one-electron wave-functions were expanded in a basis of plane waves with 450 eV cutoff for the kinetic energy. Atomic relaxations were performed until the maximum force acting on any atom was below 0. 05 eV ÅÀ1. Simulations of the STM images were performed within the Keldysh-Green function formalism  61  as implemented in the localised-basis set code FIREBALL,  62  where both sample and tip contributions are explicitly accounted for.