dataesr/scientific-paragraphs-categorization huggingface dataset:
e. , from June to September 2017. The dynamics were weakly nudged by Newtonian relaxation toward ERA-Interim reanalysis data  59. The model configuration of the chemical mechanism is similar to that of Lelieveld et al. 60  , where the comprehensive MOM (Mainz Organic Mechanism)  61  NMHC chemistry representation has been used. Biomass-burning and anthropogenic emissions were prescribed based on the global fire assimilation system  62  and EDGAR, v4. 3. 2  20, 21  database, respectively. Furthermore, the emissions of ethane were subdivided into different source sectors as shown in Supplementary Figs. 2, 5 , and 6. The ethane, propane, n-butanes, and i-butane emissions were scaled by factors of 1. 9, 1. 7, 1. 0, and 0. 43, respectively, to match recent global emission estimates in the literature  4, 15.
A main advantage of PMF is that it can provide the source profile and contribution without any prior knowledge of VOC emission profiles. In this study, PMF was applied to the 50-min data samples of the AQABA campaign for identification and quantification of the major observed VOC sources, using the US EPA PMF 5. 0 software 22 (https://www. epa. gov/air-research). Missing points were replaced with the median concentration of the corresponding species over the entire measurement matrix and they were accompanied by an uncertainty of 4 times the species-specific median, as suggested  22. It should be mentioned here that this is the first application of PMF to data from a moving platform (ship). This might introduce a small bias, despite the fact that the data were filtered for own ship exhaust.
Acknowledgements We acknowledge the fruitful collaborations with the  Cyprus Institute (CyI) , the  King Abdullah University of Science and Technology (KAUST) , and the  Kuwait Institute for Scientific Research (KISR). We are grateful to  Hays Ships Ltd , the ship's captain  Pavel Kirzner , and the ship crew for providing the best possible working conditions onboard Kommandor Iona. We thank all the participants of the AQABA ship campaign and in particular  Hartwig Harder  for the fruitful discussions and day-to-day organization of the campaign, and  Marcel Dorf ,  Claus Koeppel ,  Thomas Klüpfel , and  Rolf Hofmann  for logistics organization and assistance during the setup phase. Uwe Parchatka  is acknowledged for his contribution to the NO x data set. Marc Delmotte ,  Laurence Vialettes , and  Olivier Laurent  are acknowledged for helping with setting up the methane measurements.
Results and Discussion Variety of Mutational Landscapes. Overall, we established the mutational landscapes of 274 MA lines generated in the isogenic BY and/or hybrid SK1/BY wild-type (WT) backgrounds. Strains assessed included WT, 11 single-deletion mutants (hereafter abbreviated by gene name), and 3 double mutants covering various genome maintenance processes. Compared with WT, we analyzed the following mutant strains: pif1Δ, pol32Δ, and rad27Δ (replication), msh2Δ (mismatch repair), mre11Δ, rad51Δ, and tho2Δ (recombination and repair), lig4Δ (nonhomologous end joining), tsa1Δ (oxidative stress response), cac1Δ cac3Δ (nucleosome deposition), and clb5Δ and sic1Δ (cell-cycle progression) (https:// www. yeastgenome. org/). Strain genotypes are indicated in Dataset S1. All of the genes assessed are evolutionarily conserved and most are implicated in human diseases and/or tumor development (Fig.
Some mutational signatures resemble those found in human tumors. (Fig. 1B ) and sequenced after a minimum of 180 single-cell bottleneck passages (see SI Appendix, Materials and Methods and Dataset S2 for individual clones). One passage corresponds to ∼25 generations. Our bioinformatics analyses of the next-generation sequencing (NGS) reads allowed identification of base substitutions (single-nucleotide polymorphisms; SNPs), multinucleotide polymorphisms (MNPs), small (1-to 44-bp) insertions/deletions (InDels), combinations of SNPs and small InDels (complexes), structural variants (SVs), as well as chromosomal ploidy variations and loss-of-heterozygosity (LOH) regions (SI Appendix, Materials and Methods and Fig. S1 ). The coordinates and annotations of the 8,876 de novo mutations identified in this study are reported in Datasets S3-S8.
The number of mutations detected in the parallel MA lines of the same genotype was similar (SI Appendix, Fig. S2A  and Dataset S9), thus excluding clonal effects. Except for a few common homopolymer InDels in msh2 and rad27 backgrounds, all mutations were different from one another. Functionally, 4,103/5,416 (75. 8%) base substitutions were located in a gene-coding region (Datasets S3 and S4), similar to random expectation (76. 5%). At the protein level, 2,879 (53. 2%) modified an amino acid with a presumptive moderate functional impact according to SnpEff annotation  (17) , and 199 (3. 7%) created a premature stop codon. Among these protein-truncating mutations, 58 were located in an essential gene (https://www. yeastgenome. org/) and all were heterozygous, likely phenotypically recessive.
The mutation frequencies per strain genotype (normalized per clone and passage) are reported in Fig. 1C. Both BY and SK1/ BY wild-type strains accumulated few SNPs, corresponding to a frequency of 0. 11 mutations per clone per passage or 1. 8 × 10 -10 mutations per nucleotide per generation, similar to previous measurements  (18). Not surprisingly, the vast majority were heterozygous (allelic ratio of ∼0. 5) but a few appeared as homozygous (see below). The mutation frequencies and genome rearrangements in the mutant MA lines varied up to 83-fold compared with WT (Fig. 1C  and Dataset S10) and delineated six classes of mutational profiles. The first class, comprising cac1 cac3 (chromatin assembly factors), lig4 (nonhomologous end joining), and pol32 (polymerase δ replication), accumulated few base substitutions, similar to WT (Fig.
1C ). The second class, represented by rad51 (homologous recombination) and tsa1 (oxidative stress), specifically increased base substitutions (20. 5-and 13. 6-fold, respectively) but seemingly via different mechanisms (see below). Distinctively, rad51 more than tsa1 (2. 8 × 10 -2 and 0. 2 × 10 -2 SVs per clone per passage, respectively) enhanced SVs. All were heterozygous intrachromosomal deletions (Dataset S8). Their length varied between 488 and 59,200 nt and most particularly (11/17 cases) occurred between transposable (Ty/LTR [long terminal repeat]) elements and others between repeated homeologous genes (Dataset S8). This is typical of single-strand annealing events, known to be Rad51independent  (19). The third class is defined by msh2 (mismatch repair) that exhibited a strong increase of base substitutions (26.
4fold) and small InDels (495-fold) with a slight excess (58. 7%) of small InDels over base substitutions, as previously observed  (20, 21). Notably, as reported for haploid strains  (22, 23) , there was an excess (81%) of deletions vs. additions within homopolymer tracts. Among all small variants, complex base substitutions were rare (9/2,824) (Fig. 1C  and Dataset S10). The fourth class of mutant represented by clb5 and sic1 (cell-cycle progression), mre11 (double-strand break repair), and tho2 (transcription-coupled recombination) exhibited a slight increase (1. 5-to 3. 6-fold) of base substitutions but also aneuploidies. The fifth class, defined by rad27 (lagging-strand replication and base-excision repair), yielded the broadest spectrum of mutational events. It exhibited an increase of base substitutions (8.
1-fold increase) including a few complex substitution events (76/1,208), small InDels (63-fold increase), mostly located in homopolymers and microsatellites (518/ 564) with an excess of insertions vs. deletions (73%) but also SVs represented by 26 large deletions (62 to 23,614 nt), and two small duplications (520 and 542 bp) (Dataset S8) as well as aneuploidies (7. 8-fold increase) (Dataset S10). Similar to rad51, the SVs in rad27 reached a spontaneous frequency of 4. 3 × 10 -2 per clone per passage. The deletions involved homeologously repeated regions located in cis but fewer (3/26 in rad27 instead of 11/17 in rad51) involved Ty/LTR elements (Dataset S8). The sixth class of mutational profile is represented by pif1, affecting various DNA metabolism functions (https://www. yeastgenome. org/), whose major feature is the rapid and complete loss of mitochondrial DNA (SI Appendix, Fig.
S2B ). Further, pif1Δ MA lines exhibit a slight increase of base substitutions (2. 5-fold) (Fig. 1  and Dataset S10), consistent with the two-to threefold increase of spontaneous mutagenesis previously observed in WT cells lacking mitochondrial DNA (rho0)  (24). Compared with our previous analyses of haploid mutants  (23) , the mutational spectrum and the overall frequencies of SNPs and small InDels per genome in haploid and diploid cells are similar (SI Appendix, Fig. S3 ), indicating no drastic effect of the ploidy variation. To more broadly characterize all of the mutational landscapes, we also examined variation of mitochondrial DNA (mtDNA) and ribosomal DNA (rDNA) copy number. It was substantially variable in the WT and mutant parental strains with 0 to 103 mtDNA copies and 42 to 122 rDNA copies.
0, implying loss of the wild-type allele. This mostly occurred in the msh2, tsa1, and rad27 diploids, representing 2. 3, 6. 6, and 13. 4% of the total frequency of base substitutions and small-InDel mutations, respectively (Fig. 3A  and Dataset S10). In such situations, various types of genomic events, distinguishable by the state of the homologous chromosomes, could be invoked (Fig. 3B ). In msh2, 70/71 cases occurred in full diploid cells and resulted from two identical (18 cases) or two distinct (48 cases) InDels, located within the same homopolymer tract on the homologs (Fig. 3A  and Datasets S3 and S6). It can be explained from the >1-nt length of these motifs and high rate of polymerase slippage within homopolymers during replication  (44). In tsa1, the homozygous SNPs were also mostly found on chromosomes with two copies (54/60 cases) but all were located in nonrepeated nucleotide sequences (Fig.
3A  and Datasets S3 and S4). This was rather similar in rad27, except that 22/163 cases were associated with a change of the local copy number (1 or >2). We hypothesize that along the lineages the heterozygous de novo mutations were rendered homozygous upon a subsequent LOH event. Detection of LOH Signatures in Hybrid Yeasts. LOH can result from mitotic interhomolog recombination, short tract mitotic gene conversions, and/or break-induced replication (BIR) events that are difficult to detect in isogenic strains. To comprehensively detect LOHs, we generated additional WT and mutant MA lines B X X X X X X X X X X X X X O X X X X O Copy number X Fig. 3. Occurrence and potential origin of "homozygous" de novo mutations. (A) Allelic ratio of mutations from MA lines (BY and SK1/BY backgrounds). Sum of heterozygous (allelic ratio ∼0.
5) or homozygous (allelic ratio ∼1. 0) SNPs, small InDels, MNPs, and complex mutations. Copy number is calculated with Control-FREEC  (66). (B) Molecular events leading to de novo mutations with an allelic ratio of ∼1. 0, associated or not with local or chromosomal copy-number variation. from the polymorphic SK1/BY diploid that carries >53,000 constitutive SNP markers, distributed on each chromosome with one marker every 218 bp on average (Dataset S11). Compared with the isogenic and hybrid WT, the mutant MA lines exhibited similar mutation frequencies and specific mutational landscapes (compare Fig. 1  C and D and SI Appendix, Fig. S2A ) but revealed the presence of numerous LOH regions, robustly defined to involve ≥3 adjacent markers (Fig. 4A  and SI Appendix, Figs. S5-S9 ). In WT and pif1, LOHs were rare (0.
09 and 0. 12 LOH per clone per passage, respectively) (SI Appendix, Figs. S7  and S8 ). It was modestly increased in rad51 (0. 18 LOH per clone per passage), while many rose in tsa1 and rad27 (1. 2 and 2. 5 LOHs per clone per passage corresponding to a 12. 7-and 27. 3-fold increase, respectively). In numerous instances, these LOH events involved several chromosomes in the same clone (Fig. 4B  and SI Appendix, Figs. S5A  and S6A ). Considering all of the clones, the LOHs covered a large fraction of the genome in tsa1 and almost all of the genome in rad27 (Fig. 4C ). Regarding the occurrence of homozygous mutations, again this was most frequent in tsa1 and rad27 cells (Fig. 4D  and Dataset S10). Notably, 16/22 in tsa1 and 95/114 in rad27 were located in LOH regions with two copies of the chromosome (Fig.
4  C and E and Datasets S3 and S4), consistent with the hypothesis that along the cell lineage, mutations arose as heterozygous and passively became homozygous as part of a subsequent overlapping LOH event (Fig. 4E ). Among the remaining events, 2 cases in tsa1 and 10 cases in rad27 resulted from the occurrence of a de novo mutation on one homolog and an overlapping de novo deletion on the other homolog (Figs. 3B and 4D and Dataset S4), as frequently found in tumor cells that carry a germline susceptibility mutation and then acquire a secondary somatic deletion on the homologous chromosome  (45). Thus, the highly mutagenic tsa1 and rad27 strains stimulated SNPs and LOH events, a dual signature that accelerates and enlarges the spectrum of genome modifications. Distributions and Mechanisms of Interstitial and Terminal LOHs.
In tsa1 and rad27, the majority of LOHs were interstitial (81 and 76%, respectively; Fig. 4F ), with a length varying from 33 bp to 419 kb and 17 bp to 846 kb, respectively (Dataset S12). The remaining LOHs were terminal, with lengths varying from 659 bp to 1,052 kb in tsa1 and 55 bp to 1,079 kb in rad27 (Dataset S12). Globally, the interstitial LOHs are shorter than the terminal LOHs (SI Appendix, Fig. S10A ), consistent with their origin resulting from gene conversion-like events and/or double cross-overs rather than a single cross-over. The LOH size ranges were similar to those observed in a previous study  (46). In both mutants, the LOHs were from one or the other parental haplotype, with a slight BY vs. SK1 excess genotype (58 and 55%, respectively). Due to the extended polymorphism of the BY and SK1 genomes, this slight bias may result from intrinsic and emerging lethal allele incompatibilities when part of the genome becomes homozygous, a somatic manifestation of the spore inviability observed in the SK1/S288C haploid segregants  (47, 48).
The annotation of the LOH breakpoint regions did not localize to specific functional elements except in pif1, where they often were in proximity to an LTR/Ty region and/or the rDNA locus (SI Appendix, Fig. S10B ). Thus, after only 25 single-bottleneck passages, the stimulation of LOH created mosaic diploid genomes (Fig. 4C  and SI Appendix, Figs. S5A  and S6A ) that reached 4. 7 to 28. 9% homozygosity per clone in tsa1, and 26. 6 to 60. 7% in rad27. The formation of terminal LOHs is a hallmark of BIR (49, 50), whereas both terminal and interstitial LOHs can result from mitotic cross-over recombination and/or gene conversion. Since BIR specifically depends on the activity of POL32 and PIF1 (51-54), we examined the effect of deleting these genes in the tsa1 mutant (Dataset S1). Similar to tsa1, the tsa1 pol32 and tsa1 pif1 SK1/BY MA lines displayed increased base substitutions (13.
In both mutants, the accumulation of heterozygous mutations (SNPs and small InDels) appeared essentially regular; in tsa1, 15/25 passages yielded one or two de novo mutations and 7/25 passages yielded three or five mutations; in rad27, 7/25 passages yielded one or two mutations but a majority of passages (15/25) yielded three to nine mutations. These multiple mutation events did not necessarily arise within one cell division, since in our experimental protocol, each bottleneck passage corresponds to ∼25 generations (Fig. 5  and Datasets S13 and S14). Also, note, 3/16 tsa1 pol32 clones (C12, D12, O12) that exhibited an LOH in both the MSH2 and PMS1 regions showed a higher number of de novo mutations (34, 30, and 46 mutations, respectively) compared with 19 mutations on average in the other clones.
This can be explained by the presence of the MLH1-D161 homozygous allele from BY and PMS1-K818 homozygous allele from SK1, previously reported to confer a mismatch repair-deficient phenotype in haploid strains  (56). This case illustrates the occurrence of a secondary mutator phenotype occurring during the clonal drift. Along the lineages, several de novo heterozygous mutations (2/ 45 and 9/90 in tsa1 and rad27, respectively) chronologically became homozygous in a single-bottleneck passage as a consequence of an overlapping LOH, while others (1/45 and 6/90 in tsa1 and rad27, respectively) were eliminated in favor of the WT allele (Fig. 6  A and B, Datasets S15 and S16, and Movies S1 and S2). This opposite outcome is explained by the occurrence of an overlapping LOH mediated by an interhomolog recombination event, followed by the segregation of the nonsister chromatids carrying both WT or mutant alleles in the daughter cells (Fig.
Materials and Methods Strains and Mutation Accumulation Lines. Mutation accumulation lines were obtained from BY or BY/SK1 diploid mutants carrying homozygous deletions of the genes listed in Fig. 1A. The details of the strain constructions are described in SI Appendix and the complete strain genotypes are listed in Dataset S1. All strain constructions were checked by PCR, Southern blot, or Sanger sequencing. Proper gene deletions were confirmed by the lack of read coverage upon whole-genome sequencing of the parental and MA lines. Generation of Mutation Accumulation Lines. The mutation accumulation lines were obtained as described in ref. 23. Briefly, 4 to 16 colonies of each diploid parental strain were subjected to 12 to 100 single-cell bottlenecks (Datasets S2 and S10). One single-cell bottleneck is performed by picking one colony of average size and streaking it to obtain individual colonies on a YPD plate (1% yeast extract, 2% peptone, 2% dextrose), incubated for 3 d of growth at 30 °C.
Mutation Calling, LOH Detection, and Mutational Signatures. Illumina wholegenome sequencing was performed on parents and mutation accumulation lines. Paired-end reads were aligned on the R64-1-1 S288c Saccharomyces Genome Database reference sequence (https://www. yeastgenome. org/). Our analysis pipeline outlined in SI Appendix, Fig. S1  allowed the detection of all kinds of mutations and genome rearrangements and ploidy variations. The base-substitution mutational signatures were extracted using the R/Bioconductor MutationalPatterns package  (63). In the hybrid strains, the LOH regions were detected by genotyping the 53,523 polymorphisms that distinguish the BY and SK1 strain backgrounds (Dataset S11). The LOHs were robustly defined as regions showing at least three consecutive homozygous markers of the same haplotype (see details in SI Appendix).
Canavanine Mutator Assay. To measure the rate of mutations in the CAN1 gene, the occurrence of canavanine-resistant colonies in BY haploids was measured as previously described  (64). The fluctuation test assays were performed from five independent cultures. The mutation rate was calculated using the bz-rates (65) tool (http://www. lcqb. upmc. fr/bzrates). Reported mutation rates are the average of at least three experiments. Data Availability. Illumina whole-genome sequencing read (. fastq files) data reported in this work have been deposited in the National Center for Biotechnology Information (NCBI): Sequence Read Archive (PRJNA659115 and ERP123805), under the accession numbers detailed in Dataset S2. ACKNOWLEDGMENTS. We thank A. Londono-Vallejo and all laboratory members for stimulating discussions.
We also thank the reviewers for helpful suggestions. Research at the Institut Curie was funded by the "Ligue contre le Cancer" to A. G. N. The ICGex NGS Platform was funded by ANR-10-EQPX-03 (Equipex) and ANR-10-INBS-09-08 (France Génomique Consortium) grants from the Agence Nationale de la Recherche ("Investissements d'Avenir" program). We thank the Bioinformatics Platform of the Institut Curie for the sequencing read mapping. Research in the S. P.
In this sense, an experimentally validated mesoscale (tens of μm) physical model can easily give access to these properties, allowing a deeper understanding of the system under analysis. The importance of physicochemical 3D mesoscale models then starts to be recognized. [23] [24] [25] [26] [27] [28] [29] [30] [31] [32]  Nonetheless, with the currently available hardware technology, they can still be computationally too expensive for their systematic use in experimental data analysis. The described scenario calls for faster approaches combining experiments and models. The blooming Artificial Intelligence (AI) field promises to accelerate the manufacturing optimization by revealing patterns hardly recognizable by "classical" analysis methods. [14, [33] [34] [35] [36] [37] [38]  As they do not rely on physical models, the feasibility of this approach depends on the capability to generate high quality datasets (from experiments, physical models or both of them simultaneously) complete enough to describe the battery manufacturing, which most likely represents the limiting step to develop AI models.
Takagishi et al. recently reported a machine learning (ML) approach in which the datasets were built by randomly generating in silico electrode mesostructures composed of only AM particles coupled with a zero-dimensional electrochemical model to calculate the charge/discharge specific resistance. [39]  Even if the above-mentioned approach allows to build rapidly a large dataset (2000 electrode mesostructures), its main drawbacks are the complete lack of link between the generated electrode mesostructures and the experimental manufacturing conditions, as well as the concerns about the reliability of the randomly generated electrode mesostructures. Furthermore, the approach reported by these authors does not consider the carbon-binder domain (CBD), whose heterogeneous distribution throughout the electrode was demonstrated to have a major importance in the performance of LIBs.
Computational methodology The workflow used along this work constitutes a part of the overall methodology presented above (cf. Figure  1 ), and it is schematized in Figure  2  for the specific case of the electrode calendering. First, experimental results are used to determine the relationship between the porosity after the calendering (  ) in terms of the electrodes properties prior the calendering (its composition, porosity (  ) and thickness) and the process parameter (calender pressure). An experimental dataset of 54 electrodes encompassing 14 different initial/calendering conditions was constructed. The initial conditions were measured by averaging the results obtained by analysing 29 different not calendered electrodes, as reported in Section S1a. Afterwards, a polynomial fitting of these results is performed to mathematically link   to the electrode properties and the process parameter analysed (Figure  2A ).
The accuracy of the fitted model is of 97%, as discussed in more detail in Section S1 in the Supporting Information. The equation found through the above-mentioned polynomial fitting was implemented in an in house data-driven electrode mesostructure generator based on Matlab ® programming language (Figure  2B ). Starting from a fixed initial simulation box (x  y  z, 50  50  100 µm 3 ), and as a function of the calendering conditions chosen, the electrode porosity and thickness (z dimension) after the calendering are calculated through interpolation of the mathematical expression derived in the previous step, allowing to rapidly build larger datasets respect the experimental one. The x and y dimensions were maintained constant. Afterwards, the new simulation box is filled stochastically with AM and CBD phases based on the electrode composition and the experimental AM particle size distribution, as it can be seen in the representative electrode mesostructures for different AM compositions shown in Figure  S5 , in the Supporting Information.