dataesr/scientific-paragraphs-categorization huggingface dataset:
Overhead In order to measure the effective impact caused by the library on the monitored code, a simple test was used. It consists of a small code that is being run twice, one with and one without monitoring, both runs being timed. The code simply performs a reduce, transferring an arbitrary amount of data through MPI COMM WORLD. Different number of MPI processes are used 48 (2 nodes), 96 (4 nodes) and 192 (8 nodes). This test is launched 180 times to clear statistical fluctuations. The results are shown in Fig. 3. The error bar is the 95% confidence interval computed with the student T test using unpaired measures and unequal variance. We plot only the data for small message size because the overhead can been seen only in these cases. Results show that most of the time the overhead is not statistically significant.
Rank Reordering on Conjugate Gradient The conjugate gradient algorithm is an iterative algorithm that computes the solution of a system of linear systems whose matrix is symmetric and positivedefinite. Such algorithm is perfectly suited for the reordering use-case as the communication pattern of each iteration is the same. Hence, we can monitor the first iteration, build the communication matrix, compute a new mapping and apply a rank reordering as explained in Sec. 5. In this paper, we have taken the conjugate gradient code from the NAS parallel benchmark 3. 3 3  called CG. We have designed two functions one to start the monitoring and one to compute the reordering. The CG code uses only the MPI COMM WORLD communicator. In order to apply the reordering we have changed this to a global variable which is assigned to MPI COMM WORLD at the beginning of the program and to the new computed communicator after the reordering phase has been done.
Last, we have presented a dynamic rank reordering algorithm and show that, as long as the communication cost is large enough, the reordering cost is amortized leading to almost 2-time performance improvement. This library is based on a monitoring module available only in Open MPI (version 4. 0 or later). The advantage of such a library is that it hides the low-level MPI tool variables and command. Hence, if a monitoring module would be developed in another MPI implementation (such as MPICH), our proposed library could easily be ported to such implementation enabling a better portability.
Infiltration, RNA extraction, and retro-transcriptase quantitative PCR (RT-qPCR) Xpm or Xci suspensions of c. 5 9 10 8 CFU ml À1 (in 10-mM MgCl 2 ) were infiltrated into the abaxial surface of 4-wk-old cassava leaves or fully expanded sweet orange leaves, respectively. Infiltrated tissue was collected at 50 hpi and ground in liquid nitrogen in a TissueLyser II (Qiagen). Total cassava RNA was extracted using the Invitrap Spin plant RNA Mini Kit (Stratec, Birkenfeld, Germany) per the manufacturer's instructions. Sweet orange RNA was extracted with the TRIzol reagent (Thermo Fisher Scientific) according to the manufacturer's instructions. Total RNAs were treated with TURBO TM DNase (Thermo Fisher Scientific), and cDNA synthesis was performed with the SuperScript TM III Reverse Transcriptase (Thermo Fisher Scientific) and an Oligo(dT)12-18 Primer (Thermo Fisher Scientific).
This finding prompted us to search for candidate cassava genes targeted by Xc TALEs, using the Talvez program which predicts EBEs in a host genome based on the TALE code (P erez-Quintero et al. , 2013; Table  S6 ). Strikingly, TALE23 is predicted to target the CBB susceptibility gene MeSWEET10a known to be induced by Xpm TAL20 upon binding to a 20-nt EBE, which is overlapping with that predicted for TALE23 (Fig. 4d ). To assess the role of MeSWEET10a in CBN, CRISPRi Xc strains were transformed with the pME6010-dTALE-SW10A or the EV and leaf-infiltrated into CM6438-14 cassava plants. Water-soaked symptoms were restored upon the expression of dTALE-SW10A and correlated with MeSWEET10a upregulation in the leaves at 48 hpi (Fig. 4b, c ). This is the first description of the molecular mechanisms underlying the pathogenicity of the nonvascular.
, 2008). Regarding this strain, it is noteworthy that dTALE-induced expression of OsSWEET14, which is a major BLB S gene, was sufficient to overcome most but not all of the virulence defects caused by tale silencing. This result is in agreement with previous data showing that PXO99 A relies on the induction of other S genes for full virulence. These could include the transcription factor OsTFX1, which is targeted by the TALE PthXo6  (Sugio et al. , 2007). Similar conclusions were drawn upon the systematic deletion of all PXO99 A tale genes, whereby the deletion of pthXo1, which induces OsSWEET11, had the strongest impact on virulence  (Ji et al. , 2016). Silencing of the Xci IAPAR 306 strain TALome prevented canker symptoms and dramatically decreased the expression of CsLOB1. As expected, CsLOB1 induction was higher upon infection of sweet orange leaves with the silenced strain IAPAR 306-RBS than with the poly-tale mutant, where all tales including pthA4 are knocked out.
0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. CAZC was supported by a doctoral fellowship awarded by the IRD and received funding from the Biological Sciences Faculty from Universidad de los Andes. JMJ was supported by a National Science Foundation Postdoctoral Fellowship in Biology (DBI -1306196). The Laboratoire des Interactions Plantes-Microbes-Environnement is part of the TULIP French Laboratory of Excellence project (ANR-10-LABX-41) and of the TULIP graduate school (ANR-18-EURE-0019). All authors, except for CM, ET, CL and AB, benefited from the COST Action CA16107 EuroXanth. Table  S1  Microorganisms used in this study. Table  S2  Scale for scoring black rot symptoms and calculating disease index in Brassica oleracea var.
Data availability Publicly available datasets were analyzed in this study: Genomes from PXO99 A (GCF_000019585. 2), MAI1 (GCF_003031365. 1), and IAPAR 306 (GCF_000007165. 1) were retrieved from NCBI. The promoter sequences obtained in this study are shown in Table  S4 , while RVD sequences for Xanthomonas cassavae TALEs are summarized in Table  S5.
Genome assembly We used matching assembly tools to generate genome assemblies of reads obtained from the different sequencing methods. We assembled ONT reads of Xoo PXO35, FXO38 and Huang604 and Xoc BAI35 and MAI23 each with Flye (v2. 8. 3) (43) using parameters "--plasmids -meta --minoverlap 5000". For the initial assembly, we filtered reads using Filtlong (v0. 2. 0, https://github. com/rrwick/Filtlong) with parameter "--target_bases 500000000" to obtain a subset of high-quality reads. Mapping of the complete set of ONT reads to the respective assemblies was performed with minimap2 (v2. 17-r941)  (44). Assemblies were initially polished using these long-read-mappings and one round of Racon (v1. 4. 13) (45) followed by medaka (v1. 2. 6, https://github. com/nanoporetech/medaka). For all strains, we additionally ran Flye without the "--minoverlap" parameter and proceeded with the assembly with the best contiguity.
Busco genome completeness To assess the completeness of the assemblies with regard to the genes they contain, we used BUSCO 5. 1. 3 (54) , which uses universal single-copy orthologs to quantify completeness. We restricted the calculation to the orthologs of the "xanthomonadales_odb10" dataset, which contains 1,152 BUSCO markers. We used BUSCO in genome mode with the parameter "-m genome" and report the proportion of complete BUSCOs of each assembly. Alignment using progressiveMauve To visualise similarities and differences between the different PXO35 assemblies on a genomic level, we created a genomic alignment of all PXO35 assemblies with progressiveMauve 2. 4. 0  (47). To compare the newly sequenced and assembled strains of the Xoo and the Xoc pathovar, we generate corresponding ge-nomic alignments using progessiveMauve to investigate similarities and rearrangements between the genomes.
Testing multiplexing capacity by sub-sampling We investigate, which coverage is sufficient to decode the TALome of Xoo PXO35 and, hence, how many Xanthomonas strains could be multiplexed on a single ONT flow cell, by sub-sampling from the ONT reads. For this purpose we randomly sample 75%, 50%, 25%, 12. 5%, 6. 25% and 3. 12% of the original ONT reads with seqtk sample https://github. com/lh3/seqtk. For each of the generated subsamples, we generate an assembly with Flye, which we further polish with Racon and medaka as described above for the complete set of ONT reads. Subsequently, we apply the computational correction of TALE genes proposed in this manuscript including custom substitution polishing and finally use AnnoTALE for TALE annotation. ONT-based assemblies of Xoo and Xoc genomes are available from github at https://github.
Comparison of assemblies by general statistics. For the purpose of comparing the different basic sequencing methods, we first assembled the genome of Xoo PXO35 in a non-hybrid manner from either only Illumina, only PacBio, or only ONT reads. For the assembly from Illumina reads only, we used the MaSuRCA method which is a hybrid approach that allows variable read lengths and significant sequencing errors  (48). For the assembly based solely on short Illumina reads, we obtain a very large number of contigs (314) with a relative low N50 weighted median contig length of 26,708 bp. To assess the assembly with regard to the genes they contain, we used BUSCO  (54) , which relies on single-copy orthologs to quantify completeness. Applying the 1,152 BUSCO markers of the "xanthomonadales_odb10" dataset, the Illumina assembly still had a decent Busco score indicating that despite the low contiguity, many genes are still fully covered by a contig (cf.
TALEs and TALE classes present in strains Having established a pipeline for assembling fully contiguous Xanthomonas genomes from ONT reads combined with a computational correction of TALE genes, we applied this pipeline to two further Xoo strains, namely FXO38 and Huang604, and to two African Xoc strains, BAI35 and MAI23. For these remaining strains with ONT data generated in this study, each assembly leads to a single, circular chromosome with a length in the expected range of approx. 5 Mbp (Table  5 ). Busco completeness is in the same range as observed for Xoo PXO35 previously. Here, we observe the lowest Busco completeness for Xoc BAI35 (93. 2%) and the highest Busco completeness for Xoc MAI23 (96. 0%). The number of TALEs annotated for these genomes using AnnoTALE after computational correction of TALE genes varies between 16 (Xoo Huang604) and 20 (Xoo PXO35, Xoc BAI35 and MAI23), with up to one additional pseudo gene, and one to two iTALEs per strain.
FUNDING This work was supported by grants from the  Deutsche Forschungsgemeinschaft  (http://www. dfg. de)( BO 1496/8-2  to JB,  GR 4587/1-2  to JG and  FZT 118/2  to SK and MM). Work in RK's laboratory was supported by a grant from the  French Agence Nationale de la Recherche  ( ANR-2010-BLAN-1723 ). MM and SK were supported by the  Ministry for Economics, Sciences and Digital Society of Thuringia (TMWWDG) , under the framework of the Lan-.
These authors reported the discovery of nine dust rings and derived the distances, with the most distant one lying at 3635 ± 36 pc, potentially already beyond the detection range of the RF09 method. Observations with IXPE  (Negro et al. 2023 ) confirm the most distant dust ring found by Swift at 3. 75 ± 0. 0375 kpc and report an even more distant dust curtain at 14. 41 ± 0. 865 kpc. Recently,  Vasilopoulos et al. (2023)  reported a detailed analysis of Swift XRT data and also found evidence for dust out to 15 kpc (see  Williams et al. 2023  for further analysis), and XMM-Newton analysis of a total of 20 dust rings presented by  Tiengo et al. (2023)  detects an even further dust curtain at ≈18. 6 kpc. The Galactic disk exhibits a warp (e. g. , Hou & Han 2014, and references therein). The map derived by  Hou & Han (2014, their Figure 16)  shows that at the Galactic longitude of GRB 221009A (l = 52°.
However, scatter still remains, with especially the H band being fainter than the models and the K band being brighter. The precise light-curve fit leads these normalizations to have small errors, causing large χ 2 values that are not formally acceptable even for fits that generally model the SEDs well. The source of this scatter is less easy to understand than for the light-curve data points themselves; e. g. , in the case of the H and K bands, most data points are from the final analyses presented in refereed papers (e. g. , O'Connor et al. 2023), and the few GCN points have larger errors and do not disagree with the fit curves. Furthermore, these data span a long time period, e. g. , from 0. 23 to 25. 4 days for H and 4. 4 to 25. 4 days for K. This would imply that all data from multiple sources are systematically offset in the same manner.
Properties of the GRB Afterglow from Bayesian Inference We analyzed our data in the framework of the standard afterglow model, where the observed emission is dominated by the synchrotron radiation from shock-accelerated electrons at the forward external shock due to the deceleration of a relativistic jet by the ambient medium (assumed here to be uniform). We explored the allowed parameter space of this model with a Bayesian approach using the constraints provided by two distinct data sets. Both data sets include X-ray data from the Swift/XRT instrument (at 1 and 10 keV), following the procedure outlined in Section 2. 1 and downsampling the data to avoid our Bayesian inference runs being entirely dominated by X-ray observations. These data were combined with HXMT-LE data at 5 keV. We then combine the Swift XRT and HXMT X-ray data with two different optical data sets.
(i) GRANDMA data points in the optical and NIR (presented in Sections 2. 2 and 2. 3) are simply completed in the u band by early Swift UVOT points. We denote this set as "GRANDMA. " (ii) We enrich the "GRANDMA" data with the same observations collected in the literature as already used in the introduction of Section 3. This full data set has the advantage of including J, H, K, and F560W in our analysis, increasing the existing optical data, and extending the observations up to nearly 60 days. We denote this set as "Extended. " Both sets are corrected for extinction using the SF11 assumption for the foreground extinction; see Section 3. 2. We made the choice not to take into account any radio data, as only a subset was publicly available at the time of the publication of the article (e. g. , data from  Laskar et al.
We have analyzed both the GRANDMA and Extended data sets with NMMA. For this work, we follow  Kunert et al. (2023)  and first employ the top-hat jet structure (with on-axis assumption and a free case) with the semianalytic code afterglowpy  (van Eerten et al. 2010; Ryan et al. 2020). 83 In this model, the dynamics of the relativistic ejecta propagating through the interstellar medium are treated under the thin-shell approximation, and the angular structure is introduced by dissecting the blast wave into angular elements, each of which is evolved independently, including lateral expansion. Magnetic field amplification, electron acceleration, and the synchrotron emission from the forward shock are treated according to the analytical prescriptions of  Sari et al. (1998). The observed radiation is computed by performing equal-time arrival surface integration.
5 ± 1°. 0)  (Wang et al. 2018 ). The afterglowpy model, which is used by NMMA despite already being a refined implementation of the external shock afterglow model  (Ryan et al. 2020) , suffers from some limitations. The dynamics of the jet deceleration is assumed to be in the self-similar regime at all times, which can lead to flux overestimates at very early times when the jet is still in the coasting phase. We also note that synchrotron self-Compton (SSC) scattering is not accounted for; this could be important in the case of GRB 221009A, where some very high energy photons observed may hint toward strong SSC emission. To further validate the previous analysis, we also model the afterglow data of GRB 221009A using the afterglow model from C. Pellouin & F. Daigne (2023, in preparation), which not only includes synchrotron radiation but also computes the SSC radiation, taking into account both the Thomson and Klein-Nishina regimes with a treatment following  Nakar et al.
(2009). This model also accounts for the jet lateral structure at any viewing angle and includes the treatment of the coasting phase of the jet propagation, which can induce differences at early times. A detailed description of this afterglow model will be provided in C. Pellouin & F. Daigne (2023, in preparation). However, an analysis with the best-fit parameters shows that it both the GRANDMA and extended data. Those values are listed in Table  4 , and the results are presented in Figure  9. Our analysis with this independent model confirms the relatively poor quality of the best fit. However, when fitting the extended data set, another solution emerges in the MCMC posteriors with this model; this fit has a lower χ 2 but still leads to a best fit of poor quality. Contrary to NMMA using afterglowpy, the model does not include the lateral expansion of the jet at late times, which leads to an alternative scenario with an early jet break with a shallow post-jet break decay slope.
Bayesian inference presented in Section 3. 4. 2. Shown is a marginalized posterior distribution of the free parameters best fitting the extended data with an on-axis observation of a top-hat jet radiating via synchrotron only, as presented in Section 3. 4. 2. In blue, we show marginalized distributions for the model that features a low core q and p ∼ 2, not found with NMMA. In orange, we show marginalized distributions for the model with a high core q , similar to what is found with NMMA. The median values and 90% confidence intervals can be found in Table  4. the very narrow core q models. We leave to a future study the investigation of more advanced models regarding, for instance, the jet structure of the external medium density.
Discussion and Conclusion In this work, the properties of the GRB 221009A afterglow are studied using a multiwavelength data set presenting data from optical observations from ground-based telescopes or the GRANDMA/KNC network and the LE X-ray telescope on board the Insight-HXMT satellite. The X-ray observations were made 9. 8 hr to 3 days after the trigger time, while the ultraviolet, optical, and NIR sky was covered from the prompt emission (shallow limits from all-sky cameras) and then (with narrow-field instruments) from 2. 2 hr after the trigger time to about 20 days. The GRANDMA network involved more than 30 telescopes, including both professional and amateur telescopes, and collected more than 200 images for this GRB. This is one of the few GRB afterglows that has been observed extensively by amateur astronomers.
The measurements with the deepest limiting magnitudes reach m 24. 6 lim = mag in the g¢ band with a professional telescope (CFHT) and m 21. 5 lim = mag in the V band with an amateur telescope, demonstrating the potential for citizen contributions to timedomain astrophysical science. We also collected prompt observations of the GRB in the optical (between T 0 and T 0 +500 s) by cameras managed by the Desert Fireball Network, but no optical flash was detected in the V band (down to a limiting magnitude of 3. 8 mag). We furthermore collect public data from the XRT telescope on board the Swift satellite, with the first observation having been taken about 1 hr after the GRB trigger time. Two specially tuned photometric pipelines, STDPipe and MUPHOTEN, are used to analyze the GRB afterglow data.
The observations are calibrated using stars from the PS1 catalog, with slightly different results being obtained for Johnson-Cousins filters between the two pipelines. For this reason, only a subset of data with good quality and consistent results has been selected for analysis. In this paper, we tackle the challenge of determining the significant extinction correction, as the GRB lies behind the Galactic plane. To correct for this, we employ two different techniques. First, we use the SF11 maps, which may overestimate the extinction. Second, we use the RF09 maps, which utilize NIR color excess determinations based on 2MASS observations. This method results in a significantly lower extinction value (but is only valid out to 2-3 kpc) compared to the SF11 value. Taking into account the existence of dust at larger distances determined by X-ray measurements of dust rings  (Negro et al.
(2023) and O'Connor et al. (2023). Object GRB 221009A is an absolutely unique event, representing not just the nearest extremely energetic GRB but potentially also the most energetic GRB ever detected. These two factors combined make it by far the brightest GRB ever seen, at the very least a once-in-a-lifetime event and probably even a millennial one. To have such an event occur when we have a fleet of satellites in space able to detect gamma rays and the ground-and space-based capabilities to determine the distance and follow up the afterglow evolution in detail, even by amateur astronomers, is fortuitous indeed. It is unlikely that a chance like this will come again in the coming decades or even centuries, making this an event to be remembered through the ages. Note. Swift data have been converted from the Vega system to the AB system.
The GRANDMA consortium thanks the amateur participants of the  Kilonova-Catcher program  and observers from GRANDMA. GRANDMA thanks the paper writing team managed by D. A. K. The  Kilonova-Catcher program  is supported by the  IdEx Université de Paris Cité   ANR-18-IDEX-0001. The GRANDMA collaboration thanks  G. Parent ,  E. Maris ,  F. Bayard ,  O. Aguerre , and  M. Richmond  for their observations. This project has received financial support from the  CNRS  through the  MITI interdisciplinary programs. We thank  Mathias Schultheis  for fruitful discussions regarding extinction selection. D. A. K. acknowledges the support by the  State of Hessen  within the  Research Cluster ELEMENTS (Project ID   500/10. 006 ). S. A. acknowledges the financial support of the  Programme National Hautes Energies  (PNHE) and Crédits Scientifiques Incitatifs dUCA 2023.
M. W. C. acknowledges support from  National Science Foundation  grant Nos. PHY-2010970  and  OAC-2117997. C. A. and M. W. C. were supported by the  Preparing for Astrophysics with LSST Program , funded by the  Heising Simons Foundation  through grant  2021-2975  and administered by  Las Cumbres Observatory. J. -G. D. is supported by a research grant from the  Ile-de-France Region  within the framework of the  Domaine d'Intérêt Majeur-Astrophysique et Conditions d'Apparition de la Vie (DIM-ACAV). This work has made use of the Infinity Cluster hosted by  Institut d'Astrophysique de Paris. C. P. acknowledges funding support from the  Initiative Physique des Infinis (IPI) , a research training program of the Idex SUPER at  Sorbonne Université. The Egyptian team acknowledges support from the  Science, Technology & Innovation Funding Authority (STDF)  under grant No.
45779. S. K. is supported by the  European Structural and Investment Fund  and the  Czech Ministry of Education, Youth and Sports  (project  CoGraDS-CZ. 02. 1. 01/0. 0/0. 0/15_003/0000437 ). J. M. is supported by the  NSFC 11673062 and Oversea Talent Program of Yunnan Province. The Insight-HXMT team acknowledges support from the  National Key R&D Program of China  ( 2021YFA0718500 ) and the  National Natural Science Foundation of China  under grant Nos. U1838201  and  U1838202. J. Mao is supported by the  National Natural Science Foundation of China 11673062 and Yunnan Revitalization Talent Support Program  ( YunLin Scholar Award ).