dataesr/scientific-paragraphs-categorization huggingface dataset:
Catalyst Characterization XRD analysis was performed using a Phillips PW 1730 (Eindhoven, The Netherlands) with 2θ ranging from 5 to 80 •. The lattice parameters of the structure were refined using the Rietveld method using the software, MAUD (version 2. 93). Structural presentation was realized using the Vesta program. Raman spectra were obtained from 100 to 800 cm -1 using a Horiba Jobin-Yvon (LabRAM HR, Longjumeau, France). The morphology of the sample was visualized by field emission scanning electron microscopy (FESEM) (JEOL JSM-7610plus, Tokyo, Japan). The sample's UV-visible diffuse reflectance spectrum (DRS) was obtained from 200 to 800 cm -1 using a Cary 5000 UV-vis (Agilent, Stevens Creek Blvd, Santa Clara, CA, USA). The photoluminescence spectra were determined using an FL3-DFX-IHR320 spectrophotometer (Horiba, Longjumeau, France) with a wavelength excitation of 342 nm.
In this part, the XRD pattern was refined employing the Rietveld method with the help of MAUD software using the I23 space group. The fitting after refinement is presented in Figure  2. The observed and calculated profiles are suitable for one another, and all experimental peaks are approved Bragg 2θ for the space group I23. Using Rietveld after refinement, both the structural and lattice parameters were calculated, such as the lattice constants, atomic positions, the Sig (goodness of fit), and also various R factors, such as R wp (weighted profile factor), R exp (expected weighted profile factor), and R b (Bragg factor). The obtained results were gathered in Table  1. The goodness of fit, Sig, evaluated the fitting quality of the experimental data; the closer to 1, the more the fitting was good; in our case, it was 1.
76, which is very significant. This showed the excellent quality of our sillenite phase. Compared to our previous study that dealt with the synthesis of BZO using co-precipitation  [36] , the purity of the catalyst that was synthesized using the sol-gel method was higher than the co-precipitation method. This could be confirmed by taking the Sig (goodness of fit) into account as sol-gel was closer to 1 (around 1. 75) and was 3. 21 for coprecipitation, which is significantly high. The average crystallite size of the BZO selenite crystals (59. 46 nm) was determined using Scherrer's equation. The lattice table results enabled us to construct our exact sillenite structure using Vista software and the resulting structure is shown in Figure  2  (inset), representing a total of 66 atoms in a supercell.
Evidence of widespread extracytosolic flavinylation within bacteria As all previously characterized flavinylation systems contain genes that encode for an ApbE enzyme and a substrate that contains an FMN-binding domain, we reasoned that these features are indicative of flavinylation-mediated electron transfer. To identify flavinylation-mediated electron transfer systems, we searched for genes with ApbE (Pfam accession PF02424) or FMN-binding domains (Pfam accession PF04205) within a collection of 31,910 genomes that are representative of the genetic diversity of the prokaryotes  (Parks et al. , 2018; Parks et al. , 2020). We found that 18,965 of bacterial genomes and 238 of archaeal genomes encode an FMN-binding domain-containing protein and/or an ApbE enzyme. To focus the search on extracytosolic electron transfer, we eliminated genes that lacked a computationally predicted signal peptide or lipidation site.
This analysis provides evidence that ~50% of the bacterial (15,095) and ~4% of archaeal (63) genomes possess extracytosolic flavinylation components (Supplementary file 1). A phylogenetic analysis of the resulting dataset reveals that extracytosolic flavinylation components are broadly distributed across bacterial lifethough strikingly underrepresented in Cyanobacteria and the candidate phyla radiation (Figure  2 ). We next took advantage of the colocalization of genes for multi-subunit complexes on the genome to determine the prevalence and phylogenetic distribution of previously characterized flavinylated systems. We devised operational definitions in which the close proximity of a key gene in each system to an FMN-binding-or ApbE-containing gene was used to assign clusters to characterized systems (Supplementary file 2).
DUF2271 and DUF3570 domains of unknown function are ApbE substrates Our initial approach only considered FMN-binding domains as potential flavinylation substrates. However, preliminary analyses identified 17% of genomes (2571 total) within our dataset that encoded an ApbE but no FMN-binding domain-containing protein -implying that some ApbE substrates lack an FMN-binding domain (Figure  3 -figure supplement 1). To identify novel ApbE protein substrates, we examined the genomic context of these 'orphan' apbE genes, looking for gene cluster patterns conserved across multiple genomes (Supplementary file 1). We observed that a subset of orphan apbE genes are associated with DUF2271 -an ~135 amino acid domain of unknown function. In some genomes a single gene encodes a protein with both ApbE and DUF2271 domains (e.
Consistent with DUF3570 serving as a flavinylation substrate, we identified two conserved [S/T]GA[S/T] motifs within ApbE-associated DUF3570s (Figure  3C ). Using the coexpression approach described above, we confirmed that the Chlorobium luteolum DUF3570 was flavinylated in the presence of its cognate ApbE (Figure  3D ). Consistent with both of the identified [S/T]GA[S/T] motifs being modified, we found that replacing serines with alanines at both predicted flavinylation sites was required to abrogate flavinylation (Figure  3D ). These results suggest that DUF2271 and DUF3570 are novel ApbE substrates. Including DUF2271 and DUF3570 within our analyses significantly expanded the number and diversity of predicted ApbE substrates and decreased the number of orphan apbE genomes within the dataset from 17% to 4% (670 total) (Figure  3 -figure supplement 1).
Several lines of evidence suggest that many NapH-like proteins function with respiratory oxidoreductases. Previously characterized NapH-like proteins PceC and NosZ have been shown to be flavinylated and are part of gene clusters for organohalide and nitrous oxide reduction, respectively (Figure  1 ;  Buttet et al. , 2018; Zhang et al. , 2017). These previously characterized NapH-like systems were identified within 1197 genomes within our dataset (Figure  2 ). We also identified NapHlike gene clusters with an extracytosolic nitrite reductase in 133 genomes or an ethanol oxidase in 172 genomes. Thus, while the reactions catalyzed by the majority of NapH-like systems remain unknown, this electron transfer apparatus seems to be modularly employed to facilitate electron transfer to reductases or from oxidases (Figure  4A ).
MsrQ-like systems We identified 1797 flavinylation gene clusters in 1468 genomes that encode an 'MsrQ-like' (Pfam accession PF01794) protein (Supplementary file 1). These clusters are broadly conserved in Actinobacteria and are infrequently identified in other lineages (Figure  2  and Figure  4B ). MsrQ-like proteins are predicted to have six transmembrane helices and two heme-binding sites. MsrQ-like proteins are homologous to MsrQ, the quinone-binding subunit of periplasmic methionine sulfoxide reductase  (Gennaris et al. , 2015). MsrQ-like proteins are also distantly related to eukaryotic proteins that function in transmembrane electron transfer, including NADPH oxidase and STEAP iron reductases  (Zhang et al. , 2013). MsrQ-like gene clusters typically include apbE and an FMN-binding domain-containing gene.
MsrQ-like proteins often contain a C-terminal NAD-binding domain (Pfam accession PF00175, 1437 gene clusters). In other cases, the MsrQ-like gene clusters include an NuoF-like protein (Pfam accession PF10589 , 31 gene clusters), homologous to the NAD-binding subunit of complex I. At least a subset of MsrQ-like proteins thus likely use NAD(P)H as a cytosolic electron donor (Figure  4B ). We also identified 153 MsrQ-like gene clusters that encode a protein homologous to the eukaryotic  ferrous iron transporter VIT1 (Pfam accession PF01988). This association suggests that some MsrQlike systems function as assimilatory iron reductases that facilitate iron uptake through VIT1 (Figure  4B ).
PepSY-like systems We identified 3220 flavinylation gene clusters in 3040 genomes that encode a PepSY-like (Pfam accessions PF03929 and PF16357) protein (Supplementary file 1). PepSY-like proteins contain three transmembrane helices and are broadly distributed throughout Gram-negative bacteria (Figures  2  and 4C ). PepSY-like gene clusters frequently encode an ApbE enzyme, the flavinylation substrate DUF2271 (Pfam accession PF10029, 2833 clusters), and a secreted DUF4198 (Pfam accession PF10670, 1500 clusters) protein. Little is known about the structure or function of PepSY-like proteins. The only characterized PepSY-like homolog, Vibrio cholerae VciB (which is not associated with identified flavinylation components), was reported to possess extracytosolic iron reductase activity  (Peng and Payne, 2017)  an -an activity consistent with transmembrane electron transfer activity.
We further identified 1077 PepSY-like genes that have a NAD-binding domain (Pfam accession PF00175), suggesting that a subset of these proteins use cytosolic NADH as an electron donor (Figure  4C ). Several observations implicate a role for identified PepSY-like gene clusters in iron reduction and assimilation. First, a functional connection to MsrQ-like proteins is suggested by our observation that 108 gene clusters contain both PepSY-like and MsrQ-like genes. Second, 167 PepSY-like gene clusters contain a VIT1 (Pfam accession PF01988) ferrous iron transporter (Figure  4C ). Finally, PepSY-like gene clusters have been shown to be repressed by Fur (the primary transcription regulator that responds to iron limitation) in Shewanella oneidensis and Caulobacter crescentus  (da Silva Neto et al.
, 2013; Wan et al. , 2004). Moreover, in some cases, PepSY-like proteins may be actively involved in the extraction of siderophore-bound iron, as periplasmic reduction has been shown to be important for the uptake of siderophore-bound iron and 231 PepSY-like gene clusters encode a TonB receptor (Pfam accession PF03544) related to well-characterized outer membrane siderophore transporters (Figure  4C ;  Liu et al. , 2018a; Manck et al. , 2020).
DsbD systems We identified 285 flavinylation gene clusters in 275 genomes that contain a DsbD protein (Pfam accession PF02683) (Figure  2  and Supplementary file 1). DsbD is part of a well-studied transmembrane protein family that uses cysteine pairs to transfer electrons across the membrane  (Krupp et al. , 2001; Missiakas et al. , 1995). DsbD family proteins generally transfer electrons onto extracytosolic thioredoxin-like proteins, which in turn use a similar thiol-disulfide exchange chemistry to promote extracytosolic redox-dependent activities, such as oxidative protein folding  (Cho and Collet, 2013). The DsbD gene clusters identified in our analyses typically include genes for ApbE, the flavinylation substrate DUF3570 (Pfam accession PF12094, 227 clusters), a thioredoxin-like protein (Pfam accession PF13899, 183 clusters), and a DUF4266 protein (Pfam accession PF14086, 221 clusters).
NQR/RNF-like systems We identified 127 flavinylation gene clusters in 127 genomes, primarily from the Actinobacteria and candidate phyla radiation, with evidence of partial NQR or RNF systems (Figure  2 ). As shown in Figure  1 , the NQR and RNF complexes contain a common core apparatus with two transmembrane electron transfer pathways that together achieve a semicircular electron flow  (Juarez et al. , 2010; Steuber et al. , 2014). A first path takes electrons from the cytosol to the extracytosolic FMN-binding domain, while a second path takes electrons from the FMN-binding domain back to a cytosolic substrate. NQR/RNF-like gene clusters encode for components associated with a single electron transfer pathway and thus likely function for unidirectional electron flow (Figure  4E ). NQR/RNF-like gene clusters encode a protein with an N-terminal membrane domain that is homologous to NqrB/RnfD and a cytosolic C-terminal domain homologous to the NAD-binding domain NqrF (Pfam accession PF00175).
P19-associated iron assimilation A gene cluster that includes the ferrous iron-binding protein P19 (Pfam accession PF10634) and the FTR1 (Pfam accession PF03239) iron transporter has previously been shown to encode a mechanistically uncharacterized system involved in iron assimilation  (Chan et al. , 2010). We identified 260 P19 gene clusters, mostly in Gram-positive bacteria, that contain a gene with an FMN-binding domain (Figure  5 -figure supplement 1A and B and Supplementary file 1). Interestingly, many Gram-negative P19 gene clusters lack an FMN-binding gene but contain an additional thioredoxin-like gene  (Liu et al. , 2018b; Figure 5-figure supplement 1B). The role of the FMN-binding/thioredoxin-like protein in these systems has not been defined but, similar to other assimilatory iron reductases, could engage in redox chemistry to facilitate iron uptake.
Fumarate reductase-like oxidoreductases Fumarate reductase-like enzymes (members of the Pfam accession PF00890 enzyme superfamily) are a group of evolutionarily related proteins that catalyze a variety of redox reactions -though phylogenetic analyses suggest that substrates for many members of the superfamily remain unknown  (Jardim-Messeder et al. , 2017; Light et al. , 2019). We observe that fumarate reductase-like enzymes often contain an FMN-binding domain (3070 proteins encoded by 2979 distinct gene clusters in 1236 genomes) or are part of gene clusters (±2 genes) that contain an FMN-binding domain (189 gene clusters in 171 genomes) (Supplementary file 1). Several characterized fumarate reductaselike enzymes (including fumarate, urocanate, and methacrylate reductases) are extracytosolic and function in respiration  (Bogachev et al.
Gene cluster analyses provide some insight into the basis of multi-flavinylated protein electron transfer. We find that multi-flavinylated proteins are often associated with established transmembrane electron transfer components and thus likely receive electrons through conventional mechanisms (Figure  6C ). We observe that some clusters contain large unannotated proteins with putative cell wall-binding domains -such as SLH (Pfam accession PF00395), Rib (Pfam accession PF08428), FIVAR (Pfam accession PF07554), or LysM (Pfam accession PF01476) -and are thus likely involved in redox chemistry within the cell wall or at the cell surface (Figure  6D ). We also identified 157 clusters that encode a multi-flavinylated protein and additional proteins with FMN-binding domains (Figure  6D  and E ).
Functional annotation Protein sequences were functionally annotated based on the accession of their best Hmmsearch match (version 3. 3) (E-value cut-off 0. 001)  (Eddy, 1998)  against the KOfam database (downloaded on February 18, 2020)  (Aramaki et al. , 2020). Domains were predicted using the same Hmmsearch procedure against the Pfam database (version 33. 0)  (Mistry et al. , 2021). SIGNALP (version 5. 0) was run to predict the putative cellular localization of the proteins using the parameters -org arch in archaeal genomes and -org gram +in bacterial genomes (Almagro  Armenteros et al. , 2019). Prediction of transmembrane helices in proteins was performed using TMHMM (version 2. 0) (default parameters)  (Krogh et al. , 2001).
DUF2271 and DUF3570 sequence analyses Sequences of flavinylation-associated DUF3570 and DUF2271 proteins were aligned using EMBL-EBI Clustal Omega Multiple Sequence Alignment  (Madeira et al. , 2019). Sequence logos of the flavinylation sites shown in Figure  3  were generated in R using the 'ggseqlogo' package  (Wagih, 2017).
Acknowledgements We thank  Daniel Portnoy  and  Dominique Missiakas  for providing critical feedback on the manuscript. RM and JFB acknowledge funding support from the  Chan Zuckerberg Biohub  and the  Innovative Genomics Institute at University of California, Berkeley. RR-L acknowledges funding support from the  National Academies of Sciences, Engineering, and Medicine (Ford Foundation  Fellowship). SHL acknowledges funding support from the  National Institute of Allergy and Infectious Diseases of the National Institutes of Health  ( K22 AI144031 ).
Immunoblotting Protein samples of whole cell extracts (0. 5 µg chlorophyll or 10 µg protein) were loaded on 4-20% SDS-PAGE gels (Mini-PROTEAN TGX Precast Protein Gels, Bio-Rad) and blotted onto nitrocellulose membranes. Antisera against LHCSR1 (AS14 2819), LHCSR3 (AS14 2766), ATPB (AS05 085), CAH4/5 (AS11 1737) were from Agrisera (Vännäs, Sweden); previously described was antisera against C. reinhardtii PSBS  (6). ATPB was used as a loading control. An anti-rabbit horseradish peroxidase-conjugated antiserum was used for detection. The blots were developed with ECL detection reagent, and images of the blots were obtained using a CCD imager (ChemiDoc MP System, Bio-Rad). For the densitometric quantification, data were normalized with ATPB.
Flux ranges The solution of the linear programming problem in Eq. (  2 ), above, is the maximum growth, i. e. flux value of the strain and condition-specific biomass reaction,  4"+ 5,'. Flux variability analysis (FVA) allows determining the minimum and the maximum value of flux that a given reaction can carry while ensuring maximum flux through the biomass reaction  (87). These values can be obtained by solving the following linear program for a given reaction. The flux through the condition-specific biomass reaction was set to 99% of the optimum to avoid numerical instabilities. To conduct FVA, we solved the following linear programs: 𝑧 ",678(69:) 5,' = max(min) 𝑣 " s. t. 𝑁𝑣 = 0 𝑣 12+3+# !"#$%& = 𝑧 12+3+# !"#$%& ' (3) 𝑣 !"# 5,' ≤ 𝑣 ≤ 𝑣 !() 5,'  4"+ =  4"+ 5,' * 0. 99 Moreover, we sample 5000 feasible steady-state flux distributions from the flux cone of the strain and condition-specific models by applying the function gpSampler from the COBRA toolbox  (88).
At t=1h cells either continued being sparged with air (labelled "air"); or sparged with air and supplemented with 10 mM sodium acetate (labelled "acet); or bubbled with air enriched with 5% CO2 (labelled "CO2"), always at 600 µmol photons m -2 s -1. The time of addition of acetate or CO2 is highlighted in green on the x-axis. Samples were taken at t= 0, 1h, 2h, 3h, 5h and 9h. (n = 3 biological samples, mean ± s. d. ). The statistical analyses (two-way ANOVA tests) of log10 transformed mRNA data shown in panels (A), (B), (D) and (E) are presented in Data S1. 3, S1. 4, S1. 5 and S1. 6 respectively.
Acknowledgments We are grateful to  Dr. Konomi Fujimura-Kamada  for performing experiments to validate the dark induction of LHCSR3 in the Minagawa lab; to  Claire Remacle  for sharing the icl and icl-C strains and  Pierre Cardol  for the dum11 strain. We thank  Eric Soupene  for valuable insights in the RHP1 induction conditions. We thank  Dimitra Karageorgou  for performing preliminary experiments in the project and  Gilles Curien  for fruitful discussions on aspects of microalgae metabolism.
Funding: The authors would like to thank the following agencies for funding: The  Human Frontiers Science Program  through the funding of the project  RGP0046/2018  ( DP, GV, YY, ARG, PR, ES-L, ZN, AK ); the  French National Research Agency  in the framework of the  Young Investigators program   ANR-18-CE20-0006  through the funding of the project MetaboLight (DP, GV, YY); the  French National Research Agency  through the funding of the  Grenoble Alliance for Integrated Structural & Cell Biology GRAL  project  ANR-17-EURE-0003  ( DP, MAR-S, GV, YY ); the  French National Research Agency  in the framework of the  Investissements d'Avenir program   ANR-15-IDEX-02 , through the funding of the " Origin of Life " project of the  Univ. Grenoble-Alpes (DP, GV, YY)  ; the  Prestige Marie-Curie  co-financing grant  PRESTIGE-2017-1-0028  (MAR-S); the  International Max Planck Research School  ' Primary Metabolism  and Plant Growth' at the  Max Planck Institute of Molecular Plant Physiology (MA, ZN) ; the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Sklodowska-Curie  grant agreement no.
MatLAB implementation By rearranging the energy balance equations (3), (  11 ), (  14 ) and (16), a system of coupled equations is obtained. The system of equations is then solved in MatLAB with the ordinary 'fsolve' function. The coefficients C and D are defined by rearranging the free terms of the energy balance equations above. ⎧ ⎪ ⎨ ⎪ ⎩ C 1 T g + C 2 T p -D 1 = 0 C 3 T g + C 4 T p + C 5 T a -D 2 = 0 C 6 T p + C 7 T a + C 8 T f -D 3 = 0 C 9 T a + C 10 T f -D 1 = 0 (23) where C 1 = M g c g dt + h g-e,CV A g + h g-e,RD A g + h gap A g + h g-p,RD A g (24) C 3 = -h gap A p -h p-g,RD A p (27) C 4 = M p c p dt + h gap A p + h p-g,RD A p (28) C 5 = -h p-a,CD A p (29) D 2 = M p c p dt T p + A p (ατ ) p G irr (1 -η EL(T ) ) (30) C 6 = -h a-p,CD A a (31) C 7 = M a c a dt + h a-p,CD A a + h a-f A ch + h a-e,CD A a (32) C 8 = -h a-f A ch (33) D 3 = M a c a dt T a + h a-e,CD A a T e ( 34 ) C 9 = -h a-f π DL 2 (35) C 10 = M f c f dt + h a-f πDL 2 + 2 ṁc f (36) D 4 = M f c f dt T f + 2 mc f T fi (37) The fsolve function solves the equations for each individual timestep and gives a vector solution for [T p T g T a T f ].
2 • C. The monthly summer sun hours are 278. 8 and 222. 0 for Bucharest and Strasbourg respectively, while the winter sun hours are 72. 6 and 54. 5  (WMO, 2019). The variation of the weather during the day was used as an input into the numerical model in order to assess in real time the temperatures inside the panel. The input is: solar irradiation (G [W/m 2 ]), ambient temperature (Tamb [ • C]) and wind speed (W [m/s]). The yearly profile with hourly resolution for each parameter was obtained from Meteonorm Database for both Bucharest, Romania and Strasbourg, France. The meteorological conditions of a typical day are presented in the figures below. Fig. 4a  and b  show the daily weather conditions for Strasbourg and Bucharest respectively from 8:00 to 20:00, with an hourly time resolution, while Fig.
5a  and b  show the winter weather conditions. Given the fact that the simulations were run for one day, it is important to note the sensitivity of the chosen data on the results of the numerical simulations. This means that the specific day which was chosen from the Meteonorm yearly database is of crucial importance and given the significant day to day variation of the weather, a random day can be misrepresenting the seasonal climate. In this case, the same data was chosen for both cities, making sure no extreme condition occur and the two weather conditions are comparable at the given time. The representative winter day is 3rd of January and for the summer is 12th of July. Daily simulations were carried out for a typical summer and winter day in Bucharest, Romania and Strasbourg, France, from 8:00 to 20:00, with the weather data including ambient temperature, wind speed and irradiation, discussed in the previous section.
Conclusion and perspectives This study proposed an explicit numerical model of a PVT collector based on the heat balance equations between each layer. The model has been validated by numerically recreating a panel that has been experimentally studied in the literature, and the results show good accordance. Next, the model was applied in two case studies for the climates of Bucharest, Romania, and Strasbourg, France. The input consists of ambient temperature, wind speed and global irradiance, which were obtained for both locations from the Meteonorm Database. Simulations were run for representative summer and winter days, from 8:00 to 20:00. The results show the temperature of each layer at any particular time, and it can be observed a slightly higher temperature of the working fluid in Bucharest during the summer, and in Strasbourg during the winter.