dataesr/scientific-paragraphs-categorization huggingface dataset:
2009). To identify SNP polymorphisms we applied GATK v. and a GQ (genotype quality) !20. We then used vcflib (https://github. com/vcflib/vcflib), specifically the vcfgeno2haplo module, to generate a revised version of the D. magna reference genome that includes the identified polymorphisms for individual clones. For each of these individual's updated references, we extracted coding sequences using gffread from the gffcompare package (https://github. com/gpertea/gffcompare). We note that the large number of recent paralogs within the D. magna genome  (Orsini et al. 2016 ) could lead to high rates of cross-mapping. However, because these reads will have low mapping quality, the affected genes will be excluded from our analysis.
Annotation was made using the MAKER 2 (Holt and Yandell 2011 pipeline, which included the eukaryotic gene predictors GeneMark-ES 4. 33  [Ter-Hovhannisyan et al. 2008] ), Prodigal 2. 6. 3  (Hyatt et al. 2010) , and Augustus 3. 2. 3 (Stanke et al. 2008). We used protein hints derived from the D. magna genome as well as paired-end, Illumina sequenced RNAseq data derived from the same D. similis clone (NCBI BioProject PRJNA744861).
Daphnia lumholtzi Assembly A single, short-insert PE library was generated for a second outgroup, D. lumholtzi (NCBI BioProject PRJNA744886). Because a high-quality assembly is unlikely to result from such a data set, we applied a reference assisted assembly approach in order to provide additional context for polarizing variants. Specifically, as with reads sampled directly from D. magna, reads from D. lumholtzi were aligned to the D. magna reference and the same procedures were used to generate variant calls using the GATK variant caller. Next, we used the GATK FastaAlternateReferenceMaker approach in order to replace variants ascertained from D. lumholtzi in the D. magna reference genome.
Orthology The MK approach to inferring adaptive fixations requires divergence between two sequences, limiting the analysis to those genes with 1:1 homologs. Although it is, in principle, possible to instead use pairs of paralogs rather than orthologs, such analyses are prone to mis-inference as they violate one of the central assumptions: that constraint is thought constant over the interval that gave rise to both polymorphism and divergence data  (Hahn 2009). Therefore, to identify 1:1 orthologs for analysis, protein sequences of D. magna (v2. 4 GenBank: LRGB00000000), and D. similis genomes were used as inputs for OrthoMCL  (Li et al. 2003) , a fast method for inferring orthologous groups from protein sequences. For further analysis, we retained only those genes that were identified by OrthoMCL as single copy, one-to-one orthologs in both species.
Alignment Alignments of orthologous coding sequences of D. magna and D. similis were made using a custom R script which would initially utilize the R package seqinr  (Charif and Lobry 2007)  to import individual coding sequences for each respective species, followed by identification of the correct reading frame, and finally a codon based alignment using PRANK  (Lo ¨ytynoja and Goldman 2005, 2008). To assess the quality of the alignment procedure, we calculated gene-wise K A , K S , and K A /K S using the codeml function from the package PAML  (Yang 1997 (Yang , 2007)). To further improve the quality of aligned coding sequences we excluded regions that contained stop codons, and very poorly aligned regions. Poorly aligned regions were identified as those with multiple consecutive codons possessing no aligned bases, and regions in which K or K A was > 0.
Focal Gene Classes We defined focal gene classes based on orthology and expression patterns. To identify orthologous sequences of wellcharacterized immune genes from a broad range of systems, we used an additional run of OrthoMCL which included protein sequences derived from D. melanogaster, Caenorhabditis elegans, and Homo sapiens. To identify male and female specific genes, we used RNAseq data derived from the study of  Molinier et al. (2018; NCBI SRA PRJNA533017). Briefly, the data set of  (Molinier et al. 2018 ) is composed of high-coverage paired-end 100 bp Illumina reads derived from our different genotypes (clones) as biological replicates  (Moscow, Russia, 55. 763514, 37. 581667). One library was prepared per genotype and sex, resulting in a total of eight libraries. Quality and adapter trimming procedures were the same as used above for whole-genome DNA sequencing.
Reads were mapped to the same D. magna reference assembly as above (NCBI database; Assembly name: daphmag2. 4; GenBank assembly accession: GCA_001632505. 1, Bioprojects accession: PRJNA298946), but included this time the associated annotation file (in GFF) format, as well as a genome annotation with 26,646 genes, using the RNA-Seq aligner STAR  (Dobin et al. 2013). The raw counts (number of mapped reads per transcript per sample) were obtained with the software featureCounts  (Liao et al. 2014). We analyzed differential gene expression using DESeq2 (version 1. 10. 1) implemented in R  (Love et al. 2014). Raw read counts were used as input data, and the subsequent analyses used the normalizations of read counts as performed by DESeq2. The male versus female comparison was carried out with a two-factor design taking into account clone identity and sex.
Population Genetics We used a modified set of python scripts (https://github. com/tatumdmortimer/popgen-stats), which relied primarily on the EggLib (De Mita and Siol 2012) python library to calculate gene-wise p A and p S , as well as generate the MK tables (P N , P S , D N , and D S ) to be used in subsequent analysis. For our SNIPre like analysis, which requires counts of synonymous and nonsynonymous codon sites, we used a perl script from SNAP v. 2. 1. 1  (Korber 2000)  to calculate these values based on mutational opportunity using the Nei and Gojobori method (https://www. hiv. lanl. gov/content/sequence/SNAP/perlsnap. html). To derive an estimate of F ST for synonymous and nonsynonymous sites (F ST;s and F ST;N , respectively) we used p A and p S estimates, and calculated F ST ¼ ðp Ij À p Tj Þ=p Tj , where j represents a separate calculation for both synonymous and nonsynonymous sites  (Weir 1996, eqn.
Data Availability All D. magna reads used for the present analysis are available under BioProject accession number PRJNA480405. Reads associated with D. lumholtzi and D. similis are available at BioProject accession numbers PRJNA744886 and PRJNA744861, respectively. All scripts used for the present analysis and simulation are available at https://github. com/ peterdfields/Fields_etal_2022_MBE.
Generation of artificial microRNA constructs The artificial microRNAs (amiRNAs) targeting Chlamydomonas Cr-FAX1 and Cr-FAX5 transcripts were designed with the WMD3 Web tool  (Ossowski et al. , 2008). The resulting oligonucleotides CrFAX1-amiFor, CrFAX1-amiRev, CrFAX5-amiFor, CrFAX5-amiRev (Supplementary Table  S1 ) directed against the second exon of the respective FAX sequence (see Figure  1A ), were annealed by boiling and slowly cooling-down in a thermocycler. The resulting DNA constructs were SpeI-subcloned into the pMS539 plasmid vector, which harbors the inducible NIT1 (nitrate reductase 1) promoter  (Schmollinger et al. , 2010). Screening for correct constructs was done as described by  (Molnar et al. , 2009)  and verified by sequencing. One microgram plasmid DNA was transformed into strain cw15-325 using the glass beads method  (Kindle, 1990).
Among the FAX-protein family in Arabidopsis, Cr-FAX1 shows highest similarity to At-FAX1 (26% aa identity) and Cr-FAX5 is most likely related to At-FAX5 (32% identical aas). Names, gene codes (AGI, Phytozome), and protein IDs (UniProt) are as follows: Cr-FAX1 (Cre10. g421750, A8ICM7), At-FAX1 (At3g57280, Q93V66), Cr-FAX5 (Cre08. g366000, A8J403), At-FAX5 (At1g50740, Q9C6T7), At-FAX6 (At3g20510, Q9LJU6). Note that our Cr-FAX1 and Cr-FAX5 correspond to CrFAX1 and CrFAX2, described in  (Li et al. , 2019) , respectively. (B, C) Structural modelling of Cr-FAX1 and Cr-FAX5 (Phyre2;  Kelley et al. , 2015)  revealed high similarity to the structure of human TMEM14C and TMEM14A proteins (confidence 99. 7-99. 9%). Depicted are 3D models of (B) Cr-FAX5 versus TMEM14C (PDB entry c2losA) and (C) versus TMEM14A (PDB entry c2lopA; right) generated by FirstGlance in Jmol (firstglance.
AS09 481) was purchased from Agrisera (Sweden), α-Cr-ABCA2, directed against the ER-localized ABC transporter ABCA2  (Jang et al. , 2020)  was provided by Prof. Y. Lee, α-Lhcb4 for detection of thylakoid CP29 chlorophyll a/b binding protein of PSII from higher plants has been described previously  (Duy et al. , 2007). For the detection of N-terminal peptides in mature Cr-FAX1 and At-FAX1 proteins, peptide sequencing of SDS gel slices of the same size as of the respective bands stained by antisera was carried out. To this end, a tryptic digest of PAGE separated proteins and mass spectrometric analysis was performed as described in  Rütgers et al. (2017)  on a TT6600 Instrument (AB Sciex). MS data analysis was performed with MaxQuant software v 1. 6. 0. 1 using default settings including phospho-STY variable modifications and searching against proteins from Arabidopsis thaliana and Chlamydomonas reinhardtii derived from the UniProt database.
The combined organic phases were then evaporated under a gentle stream of N 2 and re-dissolved in a mixture of chloroform/ methanol (2:1, v/v) and kept at -20 °C until further analysis. TAGs and polar lipids were quantified using a densitometry method after being separated from each other using Thin Layer Chromatography (TLC) techniques. An ATS5 autosampler (Camag Switzerland) was used to deposit lipid extracts to a silica TLC plate made of silica gel 60 F254 (Merck KGaA, Germany). Lipid classes were then separated by developing the plate in an ADC2 automatic developing chamber (Camag) using a hexane/diethyl ether/acetic acid (17/3/0. 2, v/v/v) solvent mixture for TAG analysis or acetone/toluene/water (91/30/8, v/v/v) solvent mixture for polar lipid analysis. TLC plates were thoroughly dried under the hood, before being dipped for 6 s in a solution containing CuSO 4 reagent (20 g CuSO 4 , 200 ml methanol, 8 ml H 2 SO 4 , 8 ml H 3 PO 4 ), heated at 141 °C for 30 min on a TLC plate heater and finally scanned using a TLC Scanner 3 with WinCATs software (Camag).
Chlamydomonas contains four FAX proteins with distinct structural features When we examined publicly available databases, we identified four FAX-like proteins in Chlamydomonas reinhardtii (Table  1 ). According to TargetP 2. 0 predictions  (Almagro Armenteros et al. , 2019) , the proteins encoded by Cre10. g421750 and Cre08. g383300 are in chloroplasts and possess cleavable, N-terminal transit peptides of 54 and 37 amino acids (aa), respectively. In contrast, the protein corresponding to Cre08. g366000 is expected to hold an N-terminal signal peptide of 29 aa for the ER, and no prediction for subcellular targeting of the gene product from Cre09. g387838 was possible (Table  1 ). All four Cr-FAX proteins are annotated to belong to the FAX/TMEM14 protein family (PANTHER "transmembrane protein 14" subfamily, PTHR12668) and contain the FAX-like Tmemb_14 domain (Pfam entry PF03647) with four conserved α-helical domains (Figure  2  and Supplementary Figure  S2A ).
Among the FAX-protein family in Arabidopsis, Cr-FAX1 shows highest similarity to At-FAX1 (26% aa identity) and Cr-FAX5 is most likely related to At-FAX5 (32% identical aas). Names, gene codes (AGI, Phytozome), and protein IDs (UniProt) are as follows: Cr-FAX1 (Cre10. g421750, A8ICM7), At-FAX1 (At3g57280, Q93V66), Cr-FAX5 (Cre08. g366000, A8J403), At-FAX5 (At1g50740, Q9C6T7), At-FAX6 (At3g20510, Q9LJU6). Note that our Cr-FAX1 and Cr-FAX5 correspond to CrFAX1 and CrFAX2, described in (Li et al. , 2019) , respectively. (B, C) Structural modelling of Cr-FAX1 and Cr-FAX5 (Phyre2; Kelley et al. , 2015)  revealed high similarity to the structure of human TMEM14C and TMEM14A proteins (confidence 99. 7-99. 9%). Depicted are 3D models of (B) Cr-FAX5 versus TMEM14C (PDB entry c2losA) and (C) versus TMEM14A (PDB entry c2lopA; right) generated by FirstGlance in Jmol (firstglance.
All the catalysts were prepared keeping a 20 wt. % metal loading. The characterization was performed using XRD, transmission electron microscopy (TEM), CO stripping and cyclic voltammetric (CV) measurements. Physicochemical characterization. -The SnO 2 -C proportion was confirmed by thermogravimetric analysis (TGA) performed on a Q600 TA Instruments SDT2960 under synthetic air using a 10 °C min -1 heating rate from 20 to 900 °C. The X-ray diffraction patterns of the catalysts were obtained with an X-ray diffractometer (Bruker -D2 Phaser) operating with Cu Kα radiation (λ = 0. 15406 nm) generated at 30 kV and 10 mA. The parameters were kept constant during the analysis: 2θ range = 20°-90°, and step = 0. 025°s -1. The catalysts composition phase was achieved by fitting the experimental angular range of interest to the pseudo-Voigt function per crystalline peak with the Profile Plus Executable refinement program (Siemens AG).
Crystallite size was estimated from Debye-Scherrer equation, and the unit cell parameters were determined using the least-squares method by UFit. exe v1. 3-1992 software. Energy-dispersive X-ray spectroscopy (EDX) was performed in a Leica Zeiss LEO 440 to check the homogeneity of the local elemental composition in each prepared material. Additionally, surface morphology was investigated with a high-resolution transmission electron microscopy (HRTEM) using a TECNAI G2F20 electron microscope in bright and dark field modes coupled with EDX analysis. X-ray photoelectron spectroscopy (XPS) was used to probe and characterize the surface and oxidation states. Analyses were performed on a Kratos Axis Ultra DLD spectrometer equipped with a monochromatic Al Kα X-ray source (1486. 6 eV) operating at 15 kV and 10 mA (150 W).
The analysis spot size is approximatively 300 μm × 700 μm and the pass energy is 20 eV for recording high resolution spectra. The XPS data were calibrated by using the C1s (C-C) peak binding energy (B. E. ) at 284. 6 eV, and the spectra were fitted with CasaXPS software (version 2. 3. 17). Shirley background has been chosen and asymmetric Gaussian-Lorentzian profile functions were used to fit the spectra. The base pressure of the instrument was 9 × 10 -8 Pa and the sample powder was pressed in a copper holder of 3 mm diameter and introduced into the preparation chamber after being outgassed overnight.
Acknowledgments The authors thank  CAPES and CNPq  for financial support. "This study was financed in part by the  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES) -Finance Code 001. "The collaborative program  CAPES/COFECUB  under grant n°914/ 18 are gratefully acknowledged. The authors also acknowledge the  European Union (ERDF) , " Région Nouvelle-Aquitaine " and EDF (M-2021-2) for their financial supports.
02 ° step angle. Rietveld refinements using XRPD data were carried out using TopasAcademic software. 27, 28 The background (shifted Chebyshev), sample height, lattice parameters, peak profiles (pseudo-Voight), atomic positions and atomic displacement parameters (a parameter for each atom type) were refined, as well as a correction for absorption due to surface roughness. 29 nsity functional theory (DFT) calculations were carried out using the projector-augmentedwave method  30  encoded in the Vienna ab initio simulation package (VASP)  31  and the generalized gradient approximation (GGA) of Perdew, Burke and Ernzerhof  32  for the exchange-correlation functionals. To deal with the structural disorder at the O(4) site, a (1×2×1) supercell is adopted which led to a disorder-free structure. 33, 25 Full geometry optimizations were carried out using a plane-wave energy cutoff of 550 eV with ƙ-points meshes (3×7×6) in the irreducible Brillouin zone.
The relaxed structure was used for calculations of the electronic structure. The COHP (Crystal Orbital Hamilton Population) analysis was carried out in the framework of the LOBSTER software. 34, 35, 36 e reflectance of the sample was measured from 200 to 900 nm using a PerkinElmer Lambda 650 spectrophotometer. The photocurrents were collected using an electrochemical device (Autolab PGSTAT204, Metrohm) coupled to a LED module (LED driver kit, Metrohm). LEDs (450, 470, 505, 530, 590 and 627 nm) with low spectral dispersion are used. These LEDs are calibrated using a photodiode to determine the density of the luminous flux received by the sample. The photoelectrochemical measurements were performed in standard three-electrode cell (Magnetic Mount Photoelectrochemical Cell (Redox. me®), including Ag/AgCl and Pt wire acted as reference electrode and counter electrode, respectively.
20 I-Site  (ULNE),  University of Lille  and  University of Kent  are thanked for cotutelle funding ( S. Al Bacha ). Durham University  is thanked for hosting research visit. Dr. Donna Arnold  is thanked for helpful discussions. This study was supported by the  French government  through the  Programme Investissement d'Avenir (I-SITE ULNE /   ANR-16-IDEX-0004  ULNE) managed by the  Agence Nationale de la Recherche  (Project  ANION-COMBO ). X-Rays Diffractometers are funded by  Région NPDC, FEDER ,  CNRS  and  MESR. The regional computational cluster supported by  Lille University, CPER Nord-Pas-de-Calais/CRDER, France Grille CNRS  and  FEDER  is thanked for providing computational resources. DIM 1: " Energy efficiency" of UArtois  is thanked for its help in photocurrents measurements.
As a consequence, the 0. 50 ML domain is wider on Pt 3 Sn(111) due to the higher adsorption energies of O atoms for this coverage on Pt 3 Sn(111) than on Pt(111) (Figure  2 ). Two very thin domains of stability are also observed on the Pt 3 Sn(  111   100 ) from the previous published data by Sangnier et al. [12]  is recalled in Figure  S6. As for Pt 13 /Al 2 O 3 (100) system, the phase diagram of the supported Pt 10 Sn 3 cluster shows a large diversity of stable O contents, revealing a smoother transition from zero coverage to 1. 85 ML. This diversity is not observed for the ideal Pt(111) and Pt 3 Sn (111) surfaces (Figure  S4  and 6b ) which reflects that the clusters exhibit more numerous types of sites subject to many reconstructions. Indeed, the clusters are ductile enough to accommodate many O-contents upon reconstruction contrast- ing with the more rigid surfaces.
Computational details DFT calculations with periodic boundary conditions were performed by using the Vienna Ab initio Simulation Package (VASP)  [43]  with the generalized gradient approximation Perdew À Burke À Ernzerhof exchange correlation functional. [44] A kinetic cut-off energy of 400 eV was used for the expansion of the plane waves, while core electrons were described with the projected augmented wave method (PAW). [45] The total electronic energy convergence criterion was set to 10 À 6 eV and all geometries were optimized until forces on atoms allowed to relax were lower than 0. 02 eV/Å. A Gaussian smearing with σ = 0. 02 eV was used for the supported Pt 10 Sn 3 O n clusters. The charge transfer was estimated via the Bader charge analysis  [46]  at the same level of theory. The model of the Pt 10 Sn 3 cluster supported on the γ-Al 2 O 3 (100) dehydrated surface was described previously in detail  [19]  (Figure  S1 ).
Acknowledgements This work is part of the " RatiOnAl Design for CATalysis " ( ROAD4-CAT ) industrial chair, project  IDEXLYON  funded by the  French National Research Agency  ( ANR-16-IDEX-0005 ) and the  Commissariat-General for Investment (CGI)  within the  framework of Investissements d'Avenir program  ( "Investment  for the future"). Calculations were performed using HPC resources from  GENCI-CINES  (Grant  A0020806134 ) and from  IFP Energies nouvelles  ( ENER440 ). The authors thank PSMN (Data Center) in Lyon for CPU time and assistance, the  CPER/SYSPROD 2015-2022  project ( N°2019-AURA-P5B ).
Materials and methods The simulator was built using the Matlab© environment. Experimental measurements (testing steps) were performed to extract the equivalent parameters of the models for the solar cells and the batteries. In practice, 10 AltaDevices unit solar cells (GaAs) were tested under standard test conditions (STC) using illumination from a Xe lamp normalized at 1000 W/m 2. The temperature was stabilized at 25 C with a Peltier set-up. The cell was connected to the acquisition device, and the voltage-current curve was collected on a linked computer. Parameter extraction was performed with Matlab©. A repeatable process was performed with the 10 cells. In the energy storage unit, 32 rechargeable unit cells (18650 Li-ion cells) containing the drone's battery pack were electrochemically tested using a VMP potentiostat/galvanostat (Bio-Logic SAS, Seyssinet-Pariset, France).
Irradiance on the wings' surface The simulator was composed of three main modules: the photovoltaic generator, the energy storage unit (Li-ion batteries), and the energy management system (EMS). The simulator flowchart and EMS algorithm developed in this work are shown in Figs. S2a  and S2b , respectively. Prediction of the drone's energy parameters in flight was performed using a pre-established flight plan. The latter was composed of GPS coordinates: Longitude λ ecef , Latitude φ ecef , and inclination angles of the Sun α and β relative to the ground. Note that altitude was not considered, since the UAV flies 100 m above ground level (hence, there is negligible effect of altitude on irradiance). The flight plan was completed by the Sun's irradiance, obtained from the satellite database SoDa Helioclim  [18] , and the Euler angles of the drone: yaw, ψ rotation around the Z axis; pitch, θ rotation around the Y axis; and roll, φ rotation around the X axis.
Results and discussion At this stage of the study, it was necessary to validate the simulator under real flight conditions. Data were therefore extracted from a long endurance flight (flight time of 12 h on July 7, 2020) performed by the XSun drone (Fig. 7 ). The simulation was run with the exact input of the UAV during the flight, specifically: Euler angles (ψ, θ, φ) from the flight; irradiance during the day, from the satellite database of SoDa Helioclim  [18] ; and ambient temperature during the day, from the MERRA 2 database  [32]. Note the drone flew at a constant speed of 15 m/s, producing an air flow able to cool the panels on the wings. Moreover, the gallium arsenide cells showed quite good performance with respect to temperature  [33] , as exemplified by the stability of the equivalent parameters shown in Fig.
ORR and OER Electrochemical Performances Cyclic voltammetry (CV) and linear sweep voltammetry (LSV) tests were performed using a potentiostat/galvanostat Autolab PGSTAT 302N (EcoChimie B. V. , Utrecht, The Netherlands), controlled by the NOVA v2. 1 software. The cell used for electrochemical measurements consisted of 3 electrodes: a modified glassy carbon rotating disk electrode, RDE (Metrohm, Utrecht, The Netherlands, 3 mm of diameter) as working electrode, an Ag/AgCl (Metrohm, Utrecht, The Netherlands, 3 mol dm -3 KCl) as the reference and a carbon rod (Metrohm, Utrecht, The Netherlands, 2 mm of diameter) for ORR or a platinum wire (d = 0. 6 mm, 0. 5 m, 99. 99+%, Goodfellow) for OER as the counter electrode. Before being modified, the electrode underwent a cleaning process (see the Supplementary Materials file for more details).