dataesr/scientific-paragraphs-categorization huggingface dataset:
95 for one topology) (SET: 16. 27% -28 genes; SAT: 66. 9% -115 genes). When taking into account the slightly weaker phylogenetic signal (SH-like values >0. 70), the majority (54. 3 %) of the 1228 genes supported SAT (SET: 23%; SMT: 22. 5%) (Supplementary Table  8 ). Assuming gene tree differences are the result of coalescent stochasticity, we performed coalescence-based analyses (STAR, NJst, MP-EST, ASTRAL-III) of the three datasets to reconstruct a species tree (Supplementary Fig. 4 ). Using 689 loci (12 taxa), all three coalescent methods (STAR, NJst, MP-EST) retrieved a SET topology, whereas both the 2426 loci (4 representative taxa) and the 1578 loci dataset (4 representative taxa + 2 published magnoliids) dataset retrieved a SAT topology. Interestingly, in both the 689 and 2426 loci datasets, the branch supporting the position of Annona in the trio Annona--monocots-eudicots is very short (Supplementary Fig.
95) highlighting different trends in functional annotations according to the topology they supported (P-value < 0. 001, Friedman rank sum test, see Supplementary Fig. 5 ). Briefly, differences among topologies were significant only for Catalytic Activity (p<0. 005, Kruskal-Wallis rank sum test) and Receptor Activity (p<0. 05). We found the "Receptor activity" genes were over-represented (p<0. 005) in the SMT topology (when considering genes giving topologies without support (0<SH<50) relative to the background. To investigate the genomic landscape of incongruent phylogenetic signals, we compared scaffold features in terms of ortholog number and density (Supplementary Fig. 6 ) for the 2426 loci dataset. The 181 scaffold containing orthologs (19%) included an average of ~22 orthologous coding regions (max=799, found in the scaffold_1, see Supplementary Table  10 ), with a density of 1.
Genomic DNA extraction and library preparation The libraries were subjected to the paired-end 150bp sequencing on the Illumina HiSeq 2500 platform. Approximately 900 millions reads were generated from Illumina libraries with different inserts sizes (250bp, 350bp) to provide a first estimation of the genome size, GC content, heterozygosity rate and repeat content. Genomic DNA was isolated from the leaves of A. muricata. For a 20-kb insert size library, at least 20 μg of sheared DNA was required. SMRTbell template preparation involved DNA concentration, damage repair, end repair, ligation of hairpin adapters, and template purification, and used AMPure PB Magnetic Beads. Finally, the sequencing primer was annealed and sequencing polymerase was bound to SMRTbell template. The instructions specified as calculated by the RS Remote software were followed.
Genome annotation Transposable elements in the genome assembly were identified both at the DNA and protein level. We used RepeatModeler to develop de novo transposable element library. RepeatMasker  (Smit et al. 2017 ) was applied for DNA-level identification using Repbase and de novo transposable element library. At protein level, RepeatProteinMask was used to conduct WU-BLASTX searches against the transposable element protein database. Overlapping transposable elements belonging to the same type of repeats were integrated together. Protein coding genes were predicted through combination of homology-based prediction, de novo predictions and transcriptome based predictions: -Structural annotation of protein coding genes and protein domains was performed by aligning the protein sequences to the soursop genome by using TblastN with an E-value cutoff by 1E-5.
The blast hits were conjoined by solar. For each blast hit, Genewise was used to predict the exact gene structure in the corresponding genomic regions. -Five ab initio gene prediction programs, including Augustus (http://bioinf. uni-greifswald. de/augustus/), Genscan (http://genes. mit. edu/GENSCAN. html), GlimmerHMM (ftp://ccb. jhu. edu/pub/software/glimmerhmm), Geneid (http://genome. crg. es/geneid. html) and SNAP (https://github. com/KorfLab/SNAP), were used to predict coding genes on the repeat-masked genomes. -Finally, RNA-seq data were mapped to genome using Tophat  (Kim et al. 2013) , and then cufflinks (http://cufflinks. cbcb. umd. edu/) was used to assemble transcripts to gene models. All gene models predicted from the above three approaches were combined by EVidenceModeler (EVM)  (Haas et al.
2008 ) into a non-redundant set of gene structures. Then we filtered out low quality gene models: (1) coding region lengths of ≤150 bp, (2) supported only by ab initial methods and with FPKM<1. Functional annotation of protein coding genes was evaluated by BLASTP (evalue1E-05) instead of two integrated protein sequence databases -SwissProt and TrEMBL. The annotation information of the best BLAST hit, which is derived from database, was transferred to our gene set. Protein domains were annotated by searching InterPro (https://www. ebi. ac. uk/interpro/) and Pfam (https://pfam. xfam. org/) databases, using InterProScan and Hmmer, respectively. Gene Ontology (GO) terms for each gene were obtained from the corresponding InterPro or Pfam entry. The pathways, in which the gene might be involved, were assigned by blast against the KEGG database (https://www.
genome. jp/kegg/), with an E-value cutoff of 1E-05. The tRNA genes were identified by tRNAscan-SE  (Lowe and Eddy 1996)  with eukaryote parameters. The rRNA fragments were predicted by aligning to Arabidopsis thaliana and Oryza sativa template rRNA sequences using BlastN at E-value of 1E-10. The miRNA and snRNA genes were predicted using INFERNAL by searching against the Rfam database (http://rfam. xfam. org/).
Coalescence phylogenetic analyses We selected the following 12 representative plant species (Supplementary (Cinnamomum kanehirae and Liriodendron chinense). We reconstructed phylogenetic trees using the same method with three datasets : -orthologs identified in the 12 representative plant species, maximizing the number of species ; -orthologs identified in the quartet (Annona muricata, Arabidopsis thaliana, Amborella trichopoda and Oryza sativa), maximising the number of loci ; -orthologs identified in the previous quartet, plus Cinnamomum kanehirae and Liriodendron chinense, maximizing the magnoliids representation ; For each dataset, we used OrthoMCL  (Li et al. 2003)  to define gene family clusters among different species. An all-against-all BLASTP was first applied to determine the similarities between genes in all genomes at the E-value threshold of 1e-7.
Then the Markov clustering (MCL) algorithm implemented in OrthoMCL was used to group orthologs and paralogs from all input species with an inflation value (-I) of 1. 5. The sequences from each family containing one single ortholog for all species were aligned using mafft and a phylogenetic reconstructed using PhyML  (Guindon et al. 2010 ) with a GTR+I+G model with 4 substitution categories and 100 bootstrap replicates. The species trees were then built for each dataset with MP-est, NJ-st and STAR as implemented in the Species Tree Webserver  (Shaw et al. 2013 ) and ASTRAL-III  (Zhang et al. 2018 ) using default parameters.
Gene family expansion analysis The species tree from the dataset maximizing the magnoliids representation was used to analyze the Gene family expansion/contraction along the branch of the species tree with CAFE  (De Bie et al. 2006 ), with correction for potential assembly and annotations mistakes. We dated the ASTRAL-III tree with treePL 114-146Ma  (Massoni et al. 2015) ). One representative sequence from each family was used for downstream annotation as above. GO-terms were retrieved for annotated in expanded families using PANTHER (http://www. pantherdb. org/).
Identification of WGD events in A. muricata and during early angiosperm divergence KS-based age distributions were constructed using wgd  (Zwaenepoel and Van de Peer 2019). In brief, the paranome of magnoliids and one-vs-one orthologs comparisons were constructed by performing all-againstall protein sequence similarity searches using BLASTP with an E value cutoff of 1 × 10-10, after which gene families were built with mcl  (Altschul et al. 1997; Stijn Marinus van Dongen 2000). Each gene family was aligned using mafft  (Katoh and Standley 2013)  and KS estimates for all pairwise comparisons within a gene family were obtained through maximum likelihood estimation using CODEML  (Kohlhase 2006 ) of the PAML package  (Yang 2007 ). Gene families were then subdivided into subfamilies for which KS estimates between members did not exceed a value of 5.
In order to increase the number of orthologous sequences used and to assess the influence of the data matrix configuration ("less genes x more species" vs "more gens x less species"), we generated orthologous sequences set for a restricted number of species representative of the major clades in angiosperms (namely Magnoliids -A. muricata, Monocots -O. sativa, Dicots -A. thaliana, and A. trichopoda). This set of genes contained 2426 orthologous coding genes found in the 4 species in single copies, and was analysis in the same way than describe above for the 689 loci dataset. We then explore the genomic landscape of incongruence loci by comparing the scaffold containing genes supporting a given topology for the second dataset. Heatmaps for several parameters (i. e. the number of genes, their density and their relative abundance compared to the background (the entire set of orthologs) were generated using the heatmap.
2 function from the gplots package in R (R Development Core Team 2010). A linear regression ("lm" function in R) was used to confirm the portion of genes supporting a given topology was independent of the scaffold length (p-values > 0. 2 for each comparison). supporting the topology in the scaffold" / "total number of genes with support >0. 70 for this topology in the dataset") found in each scaffold ; d: difference between the density of genes supporting a given topology and the density of orthologous genes in the scaffolds (aka the background).
Acknowledgements Genome sequencing, assembly and annotation were conducted by the  Novogene Bioinformatics Institute, Beijing , China; mutual contract No. NHT161060. This work was supported by funding through the  Guangxi Province One Hundred Talent program  and  Guangxi University  to JSS, and the  China Postdoctoral Science Foundation  (grant number  2015M582481  and  2016T90822 ) to DDH. The basis for this manuscript was laid down during the 2015 dialogue seminar on Annonaceae under the  Joint Scientific Thematic Research Programme (JSTP)  funded by the  Netherlands Organisation for Scientific Research and the Chinese Academy of Sciences  (grant number  045. 011. 020 ). TLPC was supported by the  Agence Nationale de la Recherche  (grant  AFRODYN :  ANR-15-CE02-0002-01 ) and acknowledges the  IRD itrop South Green Platform at IRD  montpellier for providing HPC resources that have contributed to the research results reported within this paper.
, 2010). As such, the IMF Consultative Group on Exchange Rate Issues (CGER) methodology consists in using these three approaches (IMF, 2006). 16 BACE combines the averaging of estimates across models, with classical ordinary leastsquares (OLS) estimation which comes from the assumption of diffuse priors. I thank the authors for making their original GAUSS code available: http://www. nhh. no/Default. aspx?ID=3075 17 Terms of trade, government spending, foreign direct investment, net foreign assets, official development aid, relative productivity, openness, and investment. 18 To save space, the BACE results are displayed in Table  C. 1 in the online appendix (Supplementary material). We follow the methodology proposed by Moral-Benito (2012) for the implementation of the BACE analysis in the panel data context.
Selected indicators The real effective exchange rate is the dependent variable. It is calculated as the weighted average of real bilateral exchange rates against trade partners (CPIbased). The devaluation is assessed by changes in the nominal effective exchange rate. Those multilateral measures give a more accurate picture of nominal adjustments as they reduce a considerable bias owing from the use of the bilateral exchange rates vis-à-vis the US dollar: indeed a country's currency could depreciate against the US dollar, while appreciating against trading partners' currencies. Both real and nominal effective exchange rates are from the Bruegel's database. 21 r set of macroeconomic indicators includes variables intended to reflect the economic environment as well as the macroeconomic policies implemented along with the devaluation.
22  capture the nature of the fiscal policy implemented along with the devaluation, we include the fiscal balance. Most specifically, we include the exogenous component of fiscal balance estimated as the residual of fiscal balance 21 Data availability mainly motivated the recourse to the Bruegel's database. Indeed, while IMF and WB databases include data on effective exchange rate, these latter do not cover a number of the countries in this paper. 22 We include few macroeconomic indicators to limit endogeneity and simultaneity problems. regressed on GDP (simple reaction functions). Indeed, raw data on fiscal balance are not only endogenous to the business cycle but also a bad proxy of discretionary policies. Since an overvalued real exchange rate is usually the result of an inconsistent fiscal policy -manifested by increasing fiscal deficits, the improvement in the fiscal balance by helping to limit the real exchange rate's appreciation, can only enhance the effects of a devaluation.
1 -Continued from previous page : a: Updated by adding current account balances in the last years where data on net foreign assets were not available. Data relative to current account balance are from WDI database. b: We modified the original scale. IFS: International Financial Statistics (International Monetary Fund) WDI: World Development Indicators (World Bank) WEO: World Economic Outlook (International Monetary Fund)Table A. 2 -Selected countries and devaluation episodes Successful devaluations correspond to underlined episodes. " * " indicates the devaluation episodes retained for the robustness check.
Introduction: The purpose of this study (Tilak Study No: TIL-001) was to evaluate the medical modules on the mobile medical application OdySight and compare them to the gold standard tests for visual acuity, contrast sensitivity, and Amsler Grid. Methods: A total of 120 eyes were evaluated in an open-label, single-arm, prospective, singlesite study during which participants performed monocular, gold standard tests for measuring visual acuity (Sloan Early Treatment Diabetic Retinopathy Study [ETDRS] letter chart at 40 cm testing distance and ETDRS letter chart at 4 m testing distance [40-cm and 4-m ETDRS, respectively), contrast sensitivity (Pelli-Robson contrast sensitivity chart [Pelli-Robson test] ), and metamorphopsia/scotoma (Amsler Grid) followed by the respective modules on Ody-Sight (also monocular).
During this study, both the distance between the device and the patient's eye and room illumination were controlled by the examiner. Results: A Bland-Altman analysis demonstrated that there was no disagreement between the results of the OdySight visual acuity module and both the 40-cm Sloan ETDRS and 4-m ETDRS tests, with a very low level of bias (0. 53 and -1. 53 letters, respectively). The same analysis of contrast sensitivity showed a broader disagreement between the results of the Ody-Sight module and those of the Pelli-Robson test. A McNemar test indicated that there was no significant difference between results obtained by the OdySight Amsler Grid module and those obtained by the paper version for the detection of metamorphopsia and scotoma (p = 1. 0 for both).
OdySight OdySight is a mobile medical video game available on a smartphone or tablet by prescription only. It contains a puzzle game as well as medical modules to test monocular vision (near visual acuity, contrast sensitivity, and the detection of metamorphopsia and scotoma via a digital Amsler grid). A unique, patented technology using the front camera of the smartphone ensures that the tests are performed at a standardized distance (40 cm/15. 7 in. between the participant's eye and the device) and with adequate ambient light, as measured by the device (note: these features were not used during this study). The results from the visual tests are sent via a secure server to an online dashboard which the physician can access in real time (Fig. 1 ). Alerts are sent to both the participant and physician when there is a significant decline in vision.
Study Design In order to assess the validity of the medical modules on OdySight, we conducted an open-label, single-arm, prospective, single-site study at the Quinze-Vingts National Ophthalmology Hospital, in Paris, France (ClinicalTrials. gov Identifier: NCT03457441). The research followed the tenets of the Declaration of Helsinki of 1964, as revised in 2013, and approval of the experimental protocol was obtained from an ethics committee (Comitede Protection des Personnes Ile-de-France VII, France, n°18-005). Informed consent was obtained from each participant prior to any examination. Participants in the study met the following key inclusion criteria: age C 18 years; best corrected visual acuity (BCVA) between 0. 0 and 1. 0 logMAR; ability to recognize letters of the alphabet and to read French; ability to correctly distinguish body laterality; and affiliated with or beneficiary of the French healthcare system.
Participants were excluded if: they presented with a pathology that was considered by the investigator to be capable of affecting the quality of the main evaluation criteria (e. g. , mental illness, Parkinson disease); they were pregnant or breastfeeding; or they were not considered by the investigator or designee to correctly use the OdySight modules after the training session. To ensure a wide range of visual acuity, each participant's eye was assigned to one of the three cohorts according to the level of near visual acuity, measured at a distance of 40 cm from the Sloan ETDRS letter chart (40-cm ETDRS): cohort 1, with near visual acuity of between ? 1. 0 and ? 0. 7 logMAR; cohort 2, with near visual acuity of between ? 0. 6 and ? 0. 3 logMAR; or cohort 3, with near visual acuity of between ? 0.
Conduct of the study During screening, inclusion criteria were checked, optical coherence tomography (OCT) was performed, and the participant's BCVA was determined so that each eye was assigned to the corresponding cohort. The three medical modules were then presented to the participant. Because it is known that a learning phenomenon can occur, participants were asked to perform practice tests following instructions given by the examiner. At the end of this training session, the examiner estimated whether or not the participant was sufficiently capable of using the app. Eyes from participants who fulfilled all of the criteria were included, and a participant could be included for one or both of his/her eyes. During the evaluation, participants performed tests to assess visual acuity, contrast sensitivity, and detection of scotoma and metamorphopsia with both standard tools and digitized tests from OdySight.
Participants did not receive dilation treatment and, if relevant, were prompted to remove their contact lenses at least 1 h before any exam. All tests were performed at a distance of 40 cm, with the head of the participant leaning against an ophthalmological chin piece and the smartphone or chart fixed on a desk at an adequate height. Before each evaluation, distance was checked with a tape measure and luminosity was checked with a lux meter. All tests were monocular, the eye tested was equipped with the adequate correction, and the eye not being tested was covered with an occluder. The order of the tests (standard exams first vs. OdySight modules first) as well as the duration of resting breaks varied for each participant based on the discretion and assessment of the examiner. All statistical outputs were generated using SASÒ version 9.
Visual Acuity Visual acuity was assessed with two standard methods: with the ETDRS chart at a test distance of 4 m (4-m ETDRS)-and at 1 m if needed with ? 0. 75 D added for correction-and with the Sloan ETDRS chart at 40 cm (40-cm ETDRS). All tests were performed in a dedicated testing room with adequate illumination (B 161. 5 lx). Visual acuity was determined by asking the participant to read each letter starting from the first line until the smallest letter readable on the chart. During the same visit, visual acuity was also evaluated with the visual acuity module of OdySight. Results of the visual acuity tests were recorded in terms of number of letters read.
Contrast Sensitivity Contrast sensitivity was assessed with the Pelli-Robson chart at 1 m, in a dedicated testing room with adequate illumination (B 161. 5 lx). Participants removed their own glasses and instead wore a trial frame equipped with the adapted correction for distant vision increased by ? 0. 75 D. The contrast sensitivity level was determined by asking the participant to indicate each letter, starting from the first letter until the last readable letter. The examiner recorded each letter identified correctly by the participant, and the last triplet of letters was validated if the participant was able to read at least two of them. Results were recorded in LogCS. During the same visit, contrast sensitivity was also evaluated with the contrast sensitivity module of OdySight. Results of contrast sensitivity were record in logCS.
Amsler Grid The presence of metamorphopsia and/or scotoma was assessed using an empty Amsler grid printed on a white sheet of paper (10 9 10-cm grid) and a felt tip pen. The participant was asked to draw lines (or wavy lines) where distortion was seen, or to fill an area where any type of spot was seen (e. g. , black spot, white spot, area where the grid disappears) while fixing the black dot. During the same visit, the presence of metamorphopsia and/or scotoma was also evaluated using the digital Amsler Grid module on OdySight. After the participants performed each test, the clinical team evaluated the presence or absence of metamorphopsia and/or scotoma for each type of grid. Results were recorded as the presence or absence of metamorphopsia and/or scotoma.
Contrast Sensitivity There is no strict consensus in the literature for an unacceptable limit. The limit reported in the literature varies from ± 0. 14 (2. 8 letters) to ± 0. 48 logCS (9. 6 letters). The average of these limits is ± 0. 23 logCS and the median is ± 0. 18 logCS  [13, 14]. In current practice, some ophthalmologists may consider that there is a significant difference between two measurements if the difference is greater than ± 0. 15 logCS (three letters). Amsler Grid For evaluation of the two versions (standard and OdySight module) of the Amsler grid, the presence or absence of metamorphopsia and/or scotoma was noted for each type of grid. A McNemar test was used to assess comparability between the results.
Ophthalmic History Among the evaluated eyes, 15. 8% had no eye condition, 50. 8% of eyes had AMD, 8. 3% had retinitis pigmentosa, 8. 3% had a Stargardt disease, and 4. 2% had glaucoma (Table  2 ). The OCT examination detected abnormalities in at least one eye for approximately 90. 8% (n = 69/78) of participants: approximately 40% of eyes had macular atrophy, 35% had drusen, 14% had either hypo-or hyperpigmentation of retinal pigment epithelium, and 10% had choroidal neo-vascularization. OCT was not performed on four eyes (Table  3 ). All 78 of the included participants underwent OdySight training for the three medical modules, and all were considered to be able to correctly use the application. The B&A analysis showed a mean difference in units of 0. 53 letters (95% CI -0. 42, 1. 48) and a 95% LoA of between -9.