dataesr/scientific-paragraphs-categorization huggingface dataset:
Sanger sequencing To validate whole exome sequence results and segregation analysis we performed Sanger sequencing for the candidate variants for the two patients and five healthy family members using the BIGDYE chemistry on an ABI3730 sequencer (Applied Biosystems). Seqscape (Applied Biosystems) and Chromas lite software (Technelysium, South Brisbane, QLD, Australia) were used for sequence analysis and visualization. Genetic testing was done for the two patients and their parents and all available family members at the time of presentation.
The variant segregated with the disease; both parents were heterozygous and all unaffected family members had either the wild type genotype or were heterozygous. Mutations in exon 10 have been previously reported in association with INAD in dogs  [16]. This comports with its role in the pathogenesis of the disease in this family. The effect on mRNA could not be checked however as no cells were available from the patients. According to the latest ACMG guidelines  [17] , this variant has one very strong (loss of function mutation) and three supporting evidence for its pathogenicity (segregation with the disease, multiple computational evidence and specific patients' phenotype). In addition, this variant was absent in Exac and 1000 genome browser databases and has a total allele frequency of 0.
Acknowledgements The authors would like to send their gratitude to the patients and family members who participated in the study. We also thank the members of the DNA and cell bank of the ICM,  Emeline Mundwiller ,  Khalid El Hachimi  and  Delphine Bouteiller  for their valuable contribution as well as the IGenSeq platform of the  Institut du Cerveau et de la Moelle  épinière for genetic studies.
Funding This study was supported financially by funded by the  Agence Nationale de la Recherche  ( SPATAX-QUEST  project, to  Giovanni Stevanin ), the  Verum Foundation and Roger de Spoelberg Foundation  (to Alexis Brice), the  European Union  (Neuromics projects, OMICS call, to  Giovanni Stevanin ) and benefited from the  Programme d'Investissement d'Avenir IHU-A-ICM. MAMS was supported by the  Deanship of Scientific Research, King Saud University, Riyadh ,  Saudi Arabia  via research group project number  RGP-VPP-301. The funding bodies had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
The minor P3 QTL was at the limit of significance when the 93 sub-sampled individuals were used, suggesting that the reduced sample size prevented the detection of this minor QTL. Taken together, our results indicate that the P1 QTL is linked to the SDR. To more precisely locate the three QTL intervals detected using the whole dataset, the decay of pairwise linkage disequilibrium (r 2 ) was estimated for each linkage group (Figure  2C ). An r 2 threshold of 0. 2 was used to determine approximate windows at the QTL positions to search for putative candidate genes. Based on these windows we determined the number of genes present in each QTL interval using both the reference genome of the closely related species Ectocarpus species 7 (strain Ec32)  [18, 31]  and an assembly of the genome of the male parent (RB1;  [32]  (Table  S10 ).
Epistasis analysis An epistasis analysis was carried out to detect potential interactions between the parthenogenesis QTLs. Two analyses were performed, using either all 152 male and female progeny ('full dataset') or the subset of all the 93 male individuals. We observed significant sex by genotype interactions for parthenogenetic capacity. The analysis of the full dataset identified an epistatic interaction between the P2 QTL and the P1 QTL (Figure  3 ). When the same analysis was carried out with only the males, this epistatic interaction was not detected (Table  S9 ). This result indicated that the epistasis was driven by the female-specific region. In Figure  3 , the B allele was inherited from the female parent, and the A allele from the male parent. All females were parthenogenetic (B allele on the P1 locus in Figure  3 ) and therefore their parthenogenetic phenotype was independent of the allele carried at the P2 locus.
In contrast, the phenotype of males depended on the allele carried at the P2 locus. An additional interaction was detected between the P2 QTL and the P3 QTL. In this case, the frequency of P+ individuals was higher when the maternal B allele was present at the P2 locus and the effect was strongest when the P3 locus carried the maternal B allele (Figure  3B ). Several additional interactions were detected between the P2 QTL and markers on several autosomes when the male-only dataset was analysed (Table  S9 ).
Sexing of gametophytes was carried out using two molecular sex markers for each sex (FeScaf06_ex03 forward: CGTGGTGGACTCATTGACTG; The ddRAD-seq library was constructed as in  [64]  using HhaI and SphI restriction enzymes (New England Biolabs, https://www. neb. com/). Those enzymes were selected based on an in silico digestion simulation of the Ec32 reference genome  [18]  using the R package SimRAD  [65]. After digestion, samples were individually barcoded using unique adapters by ligation with T4 DNA ligase (New England Biolabs, https://www. neb. com/). Then, samples were cleaned with AMPure XP beads (Beckman Coulter Genomics), and PCR was performed with the Q5® hot Start High-Fidelity DNA polymerase kit (New England Biolabs, https://www. neb. com/) to increase the amount of DNA available for each individual and to add Illumina flowcell annealing sequences, multiplexing indices and sequencing primer annealing regions.
Quality filtering and reference mapping The ddRAD-seq sequencing data was analysed with the Stacks pipeline (version 1. 44)  [26]. The raw sequence reads were filtered by removing reads lacking barcodes and restriction enzyme sites. Sequence quality was checked using a sliding window of 25% of the length of a read and reads with <90% base call accuracy were discarded. Using the program PEAR (version 0. 9. 10,  [66] ) paired-end sequencing of short fragments generating overlapping reads were identified and treated to build single consensus sequences. These single consensus sequences were added to the singleton rem1 and rem2 sequences produced by Stacks forming a unique group of singleton sequences. For this study, paired-end reads and singleton sequences were then trimmed to 100 bp with the program TRIMMOMATIC  [67].
The genome of the male parent of the population (strain RB1) was recently sequenced to generate an assembly  [32]  guided by the Ectocarpus species 7 reference genome published in 2010  [68]. We performed a de novo analysis running the denovo_map. pl program of Stacks. Firstly, this program assembles loci in each individual de novo and calls SNPs in each assembled locus. In a second step, the program builds a catalog with the parental loci and in a third step, loci from each individual are matched against the catalogue to determine the allelic state at each locus in each individual. We then used BWA (Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303. 3997) to align the consensus sequence of the catalog loci to the reference genome and used the Python script "integrate_alignments.
Genetic map construction and QTL mapping The vcf file obtained with the Stacks pipeline was first filtered to keep only loci with maximum of 10% of missing samples and samples with a maximum of 30% of missing data. The program Lep-MAP3 (LP3)  [70]  was used to construct the genetic map. LP3 is suitable to analyse low-coverage datasets and its algorithm reduces data filtering and curation on the data, yielding more markers in the final maps with less manual work. In order to obtain the expected AxB segregation type for this haploid population, the pedigree file was constructed by setting the parents as haploid grandparents and two dummy individuals were introduced for parents. The module ParentCall2 of LP3 took as input the pedigree and the vcf files to call parental genotypes. The module SeparateChromosomes2 used the genotype call file to assign markers into linkage groups (LGs).
Several LOD score limits were tested to obtain an optimal LOD score of 8 giving a stable number of LGs. The module JoinSingles2All was then run to assign singular markers to existing LGs by computing LOD scores between each single marker and markers from the existing LGs. The module OrderMarkers2 then ordered the markers within each LG by maximizing the likelihood of the data given the order. Sex averaged map distances were computed and 10 runs were performed to select the best order for each LG, based on the best likelihood. This module was run with the parameters grandparentPhase=1 and outputPhasedData=1 in order to obtain phased data for QTL mapping. This phased data was converted to fully informative genotypic data using the script map2gentypes. awk distributed with the LP3 program. Identification and mapping of QTL were carried out using the R package R/qtl (version 1.
Read quality was assessed with FastQC (http://www. bioinformatics. babraham. ac. uk/projects/fastqc), and low quality bases and adapter sequences were trimmed using Trimmomatic (leading and trailing bases with quality below 3 and the first 12 bases were removed, minimum read length 50bp)  [67]. High score reads were used for transcriptome assembly generated with the Trinity de novo assembler (ref) with default parameters and normalized mode. RNA-seq reads were mapped to the assembled reference transcriptome using the Bowtie2 aligner  [73]  and the counts of mapped reads were obtained with HTSeq  [74]. Expression values were represented as TPM and TPM<1 was applied as a filter to remove noise if both replicates of both samples exhibit it. Differential expression was analysed using the DESeq2 package (Bioconductor;  [75] ) using an adjusted p-value cut-off of 0.
SNP and indel detection method Draft genomes sequences are available for the parent strains RB1 and EA1  [32]. Using Bowtie2, we aligned the EA1 genome against the RB1 genome and generated an index with sorted positions. The program samtools mpileup  [76]  was used to extract the QTL intervals and call variants between the two genomes. The positions of variants between the two genomes were identified and filtered based on mapping and sequence quality using bcftools  [72]. The annotation file generated for the RB1 genome was then used to select SNPs and indels located in exons of protein-coding genes for further study (bcftool closest command). The effect of polymorphism on modification of protein products was assessed manually using GenomeView  [77] , the RB1 genome annotation file (gff3) and the vcf file for each QTL region.
GO term enrichment analysis A Gene Ontology enrichment analysis was performed using two lists of genes: a predefined list that corresponded to genes from all three QTL intervals and a reference list including all putative genes in the mapped scaffolds based on the Ec32 reference genome and that had a GO term annotation. The analysis was carried out with the package TopGO for R software (Adrian Alexa, Jörg Rahnenführer, 2016, version 2. 24. 0) by comparing the two lists using a Fisher's exact test based on gene counts.
Epistasis analysis Epistasis analysis was carried out with the R package R/qtl (version 3. 3. 1). Two analyses were performed, one with the full data set (female and male genotypes generated with RAD-seq method) and the second with only the male individuals. For both analyses, the scantwo function from R/qtl were used with the model "binary" as the phenotypes of the individuals is either 1 (P+) or 0 (P-).
46r  [79]  (13 zygotes for the P-male parent and 14 zygotes for P+ male parent). For all datasets, the assumption of normality (Shapiro test) and the homoscedasticity (Bartlett's test) were checked. The latter's assumptions were not met for zygote length, and consequently statistical significance differences at each time of development was tested with a non-parametrical test (Mann Whitney U-test, α=5%).
"Lod. add" measures the improvement comparing with the additive model. This measurement indicates evidence for at least one QTL assuming no interaction. "Lod. av1" measures the increase when the additive model with QTLs on chromosomes j and k is compared to the single QTL model with a single QTL on chromosome j and k. This measurement indicates evidence for a second QTL assuming no epistasis. Table  S10. Summary of the sequencing methods and raw data obtained. Table  S11. Predicted functions, expression patterns and polymorphisms of genes in the QTL intervals. Expression data in transcript per million (TPM) for P-(male) versus P+ (female) gametes were obtained from strains belonging to the Ectocarpus siliculosi group (Ectocarpus species 1). Information about the type of polymorphism in the parental strains of E.
ACKNOWLEDGEMENTS We thank  Drs A. Andrew Pacheco  for discussions, and  Lina Bird  and  Peter Chovanec  for preliminary experiments. We thank  Dr William Miller  for genomic DNA of C. jejuni RM1221. We greatly appreciate all assistance from  Dr Maissa Gaye  for preliminary LC-MS experiments and  Dr Gabriel Filippelli  for preliminary ICP-OES experiments. Partial support of this work from  PA CURE ,  DOE  ( DE-FG027ER64372 ) and  National Institute of Health  ( GM061555  to PB) is gratefully acknowledged.
These may be controlled for solar tracking during daytime or to obey other user-defined time-variable controls. The measurement campaign spreads from 18 October 2015 to 24 October 2016 and thus covers a full year. It encompasses 41 monitored rain events, 12 of which were recorded with a 1 min time step, among which 11 exhibit complete and reliable sets of data linked to the incoming and redistributed rain amount, as well as to the tilting angle of the panels.
Data collection and model development were performed in the frame of the Sun'Agri2B project that links the Sun'R SAS society with Irstea and other academic or nonacademic partners. Author contributions. YE performed most of the experiments and developed the model, under the supervision of BC and GB. AM contributed to the first stages of the experiments and model development while CD and FL helped in handling the metrological and technical parts of the work. Competing interests. There are no known competing interests based on scientific grounds. However, there may be conflicts of interest on commercial grounds with societies other than Sun'R SAS also engaged in agrivoltaic activities.
Acknowledgements. This study was conducted within the frame of the  SunAgri2b  project, supported by the  Provence-Alpes-Côte d'Azur and Rhône-Alpes regions, CAPI, BPI France ,  Communauté de Communes Pays d'Aix ,  Grand Lyon , and the  Agence Nationale pour la Recherche et la Technologie. The experimental platform was co-funded by  Irstea ,  Région Île-de-France and Paris Entreprises. The first author is a PhD student and a member of both the  Sun'R SAS  society and the  OPTIMISTE research team of Irstea Montpellier, France , to which all co-authors also belong. OPTIMISTE stands for Optimization of the Piloting and  Technologies of Irrigation, Minimization of InputS , and Transfers in the Environment and is one of the research teams in the " G-Eau " joint research unit that addresses water management, actors and uses.
An allelopathic effect was noticed and a toxin production by C. watsonii was assumed and included in the model. Calibration was carried out with experimental data where cell densities and nitrate concentrations were measured. The predictions of the mathematical model accurately represented the experimental data. The model therefore highlighted the interactions within this artificial ecosystem. The model confirms that D. salina growth was limited by nitrate concentration and did not consume dissolved organic nitrogen produced by C. watsonii from its diazotrophic activity. D. salina and C. watsonii were competing for light, which favored D. salina and limited C. watsonii when grown in cocultures. The model supports the hypothesis that C. watsonii produced toxins enhancing D. salina mortality in the cocultures.
But interactions within these natural ecosystems are still poorly understood and are affected by the environment. A photosynthetic marine ecosystem composed of the microalgae Dunaliella salina and the nitrogen fixing cyanobacteria Crocosphaera watsonii was therefore studied. A model was designed to represent the competition for light and the interactions with nitrogen between these two microorganisms. An allelopathic effect was noticed and a toxin production by C. watsonii was assumed and included in the model. Calibration was carried out with experimental data where cell densities and nitrate concentrations were measured. The predictions of the mathematical model accurately represented the experimental data. The model therefore highlighted the interactions within this artificial ecosystem.
m -2. s -  ), and Q max and Q min are respectively the maximum and minimum nitrogen cellular quota (mol N. cell -1 ). The calculated µ d was doubled in order to fit the day/night cycle and reach the appropriate average growth rate in 24h. Other parameters estimations. The light extinction coefficients were estimated from preliminary D. salina and C. watsonii monocultures experiments to make the model fit the data. The minimal and maximal nitrogen intracellular quota were obtained from simulations of preliminary experiments. However, the toxin production rate by C. watsonii, the half-saturation constant for toxin and mortality rate for D. salina were estimated from the cocultures experimental data since nothing is known about the toxin productivity and impact. gen consumption for the two microorganisms in monocultures.
ACKNOWLEDGEMENTS The authors would like to thank  Sophie Marro ,  Sophie Rabouille ,  Amélie Talec  and  Meng Zhang  for their help and comments. This work was supported by the  ANR Phycover  ( ANR-14-CE04-0011 ) and the  Inria Project Lab Algae  in silico. M. Caia benefited from an  INRA  funding.
Before the measurement all catalysts were degassed at 350 • C for 3 h. The specific surface area of each catalyst was obtained by the Brunauer-Emmett-Teller (BET) method. X-ray photoelectron spectroscopy analyses (XPS) were recorded on a Thermo ESCALAB 250 electron spectrometer with a monochromatized Al K␣ X-Ray source (1486. 6 eV) and passing energy of 40 eV. C1 s (binding energy 284. 8 eV) of formed carbon was used as a reference. XPS spectra were deconvoluted using XPSPEAK 41 program by the curve fitting after the Shirley-type background subtraction. Finally, temperature-programmed reduction (TPR) experiments were conducted in a commercial BELcat unit with TCD detection. Catalyst (ca. 0. 1 g) were loaded into a U-shaped tube and ramped from room temperature to 1173 K (10 K/min), using a reducing gas mixture of 5% v/v H 2 /Ar (50 cm 3 /min).
Model Validation The model has been validated using High Molecular Weight PolyEthylene under compressive unixial loading from the literature  [10]. The results of the modeling are presented in figure  2. A good agreement is observed between experimental results and the numerical prediction over a wide range of strain rate. This model have been introduced in the Finite Element software ABAQUS/Explicit through the writing of a VU-MAT subroutine. The aim is to simulate the high-velocity impact of a polymer particle against metallic substrate.
Numerical model To check the accuracy and the range of validity of the approximate analytical solution, full nonlinear simulations are carried out using a finite-volume methodology. OpenFOAM software has been utilized to discretize and solve the governing equations  (Pimenta & Alves 2017). The equations solved are conservation of mass, assuming incompressibility, and momentum: ∇ • U = 0, (4. 1) Re ∂U ∂t + U • ∇U = -∇P + β∇ 2 U + ∇ • τ p , (4. 2) where Re is the Reynolds number (i. e. Re = ( ρ Ri ω ã)/ η, and ρ is the density of the fluid). Here, components of the stress tensor are calculated using a so-called log-conformation approach for the Oldroyd-B constitutive equation  (Fattal & Kupferman 2004 ; Afonso, Pinho & Alves 2012; Pimenta & Alves 2017) (already provided in its more standard form relating stress and rate-of-deformation tensors in (2.
However, it should be noted that the velocity profile for Oldroyd-B fluids generates a normal-stress distribution that consequently influences the pressure distribution, which is different from the Newtonian case. In figure  4 , and all of the other results relating to the contours of the velocity and the streamfunction, the moving wall is the vertical left-hand sidewall. To check the accuracy of the derived zeroth-order solution (δ = 0), a comparison between numerical simulations and the analytical solution is carried out (as shown in figure  4 ). In numerical simulations, flow distributions for three different aspect ratios Λ * (Λ) = 0. 2 (0. 25), 0. 5 (1) and 0. 909 (10) with both ANSYS Fluent and OpenFOAM software have been simulated. The geometry consists of three stationary walls and one moving wall.
Acknowledgements The authors would like to express their gratitude to  Professor G. McKinley  ( MIT, USA ) for a series of valuable suggestions. S. L. acknowledges funding from the  Institut Universitaire de France. R. J. P. gratefully acknowledges funding from the  EPSRC (UK)  through grant no. EP/M025187/1. Finally, we would like to sincerely thank one of the anonymous referees for suggesting the use of a polar cylindrical coordinate system and their independent derivation of the base-flow solution.
cantly higher in the Ugi products if compared to the Passerini products (see ESI Table S1 †). Moreover, SEC traces did not reveal any major change in hydrodynamic volume upon further modification of filter paper, resulting in very high molecular weights between 177 and 225 kDa (Table  2 , Fig. 3 ) and thus no significant degradation of the cellulosic backbone. The slight decrease of the molecular weights of the Passerini and Ugi products compared to succinylated filter paper could be ascribed to a different swelling behavior. However, comparison of the SEC data should remain within the Passerini and Ugi products, not with succinylated cellulose, due to the highly different solubility (and thus hydrodynamic volume and swelling behavior) of the samples. The thermal properties of the Passerini and Ugi products were investigated by DSC and TGA.
Characterization techniques Elemental composition of the samples was analyzed by energy dispersive X-ray spectroscopy using an EDX Bruker X Flash Detector 4010 attached to a SEM microscope (FEGSEM, Hitachi S4800, 20 kVHitachi4800). The analyses were carried out on powder samples. An acquisition time as long as 10 minutes was used to record each spectrum, in order to obtain reliable quantitative results. EDS analyses were also performed at the TEM in order to confirm these results at the nanometer scale. Laboratory X-ray diffraction patterns were recorded on a PANalytical X'Pert Pro diffractometer equipped with an X-Celerator detector. Data were collected over an angular range of 10 to 70 º2θ using 0. 05º steps. Raman spectra (200-2000 cm -1 ) were recorded on a Lab-RAM Horiba Jobin Yvon spectrometer equipped with a CCD detector and a diode-pumped solid state laser (785 nm) at 5 mW.
All samples were analyzed during 100 s of exposure time using a 100 μm aperture hole. High-intensity and high-resolution synchrotron powder diffraction (SPD) data were carried out on the 11BM beamline at the Advanced Photon Source, Argonne National Laboratory, US. Data were collected at room temperature on a spinning sample (60 Hz) over the 0. 5-50° 2θ range with a 0. 001° step using a λ = 0. 412708 Å wavelength. The X-ray absorption spectra (XAS spectra) were recorded at the BM25 beam line (SPLINE) of the ESRF synchrotron (Grenoble, France). The spectra were acquired at room temperature at the Mo K-edge (19. 8-20. 8 keV) and Eu L3-edge (6. 8-7. 8 keV) in transmission mode using self-supported wafers of the powder samples prepared using the optimum weight to maximize the signal-to-noise ratio in the ionization chambers (log I0/I1z1).