dataesr/scientific-paragraphs-categorization huggingface dataset:
0. 3  85  , to produce a single haploid genome assembly for each sample. The I. elegans draft assemblies were then polished with short read data from one resequencing sample (TE-2564-SwD172_S37, Table  S1 ), using the POLCA tool in MaSuRCA v 4. 0. 4  86. For every draft and final assembly of I. elegans, we computed quality metrics as mentioned above and assessed the completeness of conserved insect genes using BUSCO v 5. 0. 0 87 and the "insecta_odb10" database (Fig. S1 ). For I. senegalensis, we report quality metrics of the final assemblies (Fig. S2 ).
Structural variants We used two complimentary approaches to identify SVs overlapping the genomic region uncovered by both k-based and SNP-based GWAS. First, we mapped the raw data from each long-read sample to the assemblies of alternative morphs (e. g. Ao data mapped to Io and oo assemblies), and called SVs using Sniffles v 1. 0. 10 106 (Extended Data Fig. 1 ). These SV calls may represent fixed differences between morphs, within-morph polymorphisms, or products of assembly error. We therefore used SamPlot v 1. 3. 0 107 and our short-read samples (n = 19 per morph) to validate morph-specific SV calls (Extended Data Fig. 1 ). Samplot identifies and plots reads with discordant alignments, which can result from specific types of SVs. For example, if Sniffles called a 10 kb deletion in the Ao and Io long-read samples relative to the oo assembly, we then constructed a Samplot for this region using short-read data, and expected to find support for such deletion in I and A samples, but not in O samples.
Linkage disequilibrium and transposable elements To estimate linkage disequilibrium (LD), we used the same variant calling file as for the SNP based GWAS, which included only variant sites and was filtered by mapping quality, genotyping quality, minimum allele frequency, and read depth, as described above (Extended Data Fig. 1 ). The file was downsampled to one variant every 100th using vcftools v 0. 1. 17 105 , prior to LD estimation. We estimated LD using PLINK v 1. 9 97 , and recorded R 2 values > 0. 05 for pairs up to 15 mb apart or with 10,000 or fewer variants between them. We estimated LD for the unlocalized scaffold 2 of chromosome 13, which contains the morph loci and is about ~15 mb in the A assembly. For comparison, we also estimated LD across the first 15 mb of the fully assembled chromosomes (1-12 and X), the main scaffold of chromosome 13, and the unlocalized scaffolds 1, 3 and 4 of chromosome 13.
Gene content and expression in the morph locus We assembled transcripts in the A morph genome (Extended Data Fig. 1 ) to identify potential gene models unique to the A or A and I morphs and which would therefore be absent from the I. elegans reference annotation (based on the O haplotype). First, all raw RNAseq data from I. elegans samples were mapped to the A assembly using HISAT2 v 2. 2. 1 109 and reads with mapping quality < 60 were filtered using Samtools v 1. 19 101. Transcripts were then assembled in StringTie v 2. 1. 4 110 under default options, and merged into a single gtf file. Transcript abundances were quantified using this global set of transcripts as targets, and a transcript count matrix was produced using the prepDE. py3 script provided with StringTie. Mapped RNAseq data from I.
Nucleotide sequences of all transcripts mapped to the 1. 5 mb morph locus in the A assembly were selected. Coding sequences in these transcripts were predicted using Transdecoder v 5. 5. 0 (https://github. com/Trans Decoder/TransDecoder). Predicted CDS and peptide sequences were read from the assemblies using the genome-based coding region annotation produced with Transdecoder and gffread v 0. 12. 7 116. We investigated whether any inferred peptides or transcripts were unique to A or A and I by comparing these sequences to the DToL reference transcriptome and proteome (based on the O haplotype). We then searched for homologous and annotated proteins in other taxa in the Swissprot database using Blast v 2. 9. 0 100. We found three gene models which are protein-coding and present in both A and O females (see main results, Fig.
Acknowledgements We thank  H. Dort ,  R. A. Steward ,  J. Haushofer ,  P. de Sessions , and the  Monteiro Lab  for suggestions and helpful discussions. We are also grateful to  M. P. Celorio-Mancera  and  H. M. Low  for invaluable technical support. Prof. A. Monteiro  hosted B. W. at the  National University of Singapore  during part of the duration of this study. Computation and data handling were enabled by resources provided by the  Swedish National Infrastructure for Computing (SNIC)  through the  Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) , under projects  2022/6-230  and  2022/5-419  awarded to EIS. Specimens of I. senegalensis were collected in Singapore, under a Research Permit ( NP/RP22-015b ) from the  National Parks Board, Singapore. This work was supported by an  International Postdoc Grant  from the  Swedish Research Council  (VR; grant no.
2019-06444 ) to BW. Funding was provided by the  Swedish Research Council  (VR; grant no. 2017-04386 ) to CWW and KT. SN was funded by a scholarship grant for Master's students from  Sven  and  Lily Lawski's Foundation. EIS was funded by grants from  Stina Werners Foundation  (grant no. 2018-017 ),  Erik Philip Sörensens Stiftelse  (grant no. 2019-033 ) and the  Swedish Research Council  (VR; grant no. 2016-03356 ).
Code availability Scripts used in this study can be found at GitHub via URL: https://github. com/bwillink/Morph-locus Extended Data Fig. 3. The A and I reads mapped to inversion break points on the O assembly (see Extended Data Fig. 2 ) map to multiple locations on the A assembly. a Reads from the first inversion breakpoint. b Reads from the second inversion breakpoint. Each row represents a sample and each circle an individual read. The x-axis corresponds to coordinates on the A assembly.
2  Lef t: Phase-folded transit photometry of SPECULOOS-3 b in (from top to bottom) the g ′ , r ′ , i ′ , I + z, z ′ , and Ks filters. The photometry is binned per 2 minutes and the light curves are shifted along the y-axis for clarity. The g ′ , r ′ , i ′ , and z ′ light curves are dominated by the extremely precise GTC/HiPERCAM light curves of only one transit, while the Ks light curve is the stack of two transits observed by UKIRT/WFCAM in the Ks filter. Right : Measured transit depths in the different filters (dots with error bars), compared to the transit depth measured in the global analysis assuming a common transit depth (dashed lines = 1σ error bar). All measurements agree at better than 1σ with the common transit depth measurement. the transit photometry, including the a priori knowledge of its stellar properties, with an adaptive Markov chain Monte Carlo (MCMC) code (see Methods).
SPECULOOS-3 b is the smallest planet amenable to emission spectroscopy with MIRI/LRS. Data from https://exoplanetarchive. ipac. caltech. edu/ (16th of October 2023). SPECULOOS-3 with SNO and MuSCAT-3 failed to detect any outer transiting planets (see Methods). This indicates that both systems had different formation/evolution histories. As outlined by recent works, resonant systems like TRAPPIST-1 are rare because they are prone to disruption by dynamical instabilities  [25] [26] [27]. SPECULOOS-3 b could thus be the outcome of such a disruption. Outer planets may still exist, but on much longer and/or mutually inclined orbits. Nevertheless, we cannot exclude the possibility that outer well-aligned planets do exist, but that they are more similar in size to Mars than to Earth, and are just too small to be detected with current observations (see methods).
2 ′′ -1. 6 ′′. We used the red channel with 600/7500 grating and 1. 5 ′′ -wide slide to obtain 6000-9500 Å spectra at an average resolution of λ/∆λ = 1900. Two exposures of 1200 s each were obtained with the slit aligned with the parallactic angle at an average airmass of 1. 02. We also observed the G2 V HD 205113 at a similar airmass for telluric absorption correction, and the spectrophotometric calibrator star BD +28 4211  [57, 58]  for flux calibration. Dome-illuminated flat-field and arc emission lamps were obtained at the start of the night for pixel response and wavelength calibration. All data were reduced using the kastredux package 2  , which included cosmic ray correction, flat fielding, source extraction, wavelength calibration (to 0. 48 Å = 21 km/s precision), telluric correction, and flux calibration.
TESS photometry: rotation period and variability We downloaded the TESS two-minute-cadence PDCSAP Sector 41 and 55 light curve using lightkurve  [79]. The light curve shows some large flare features, including a ∼70% flare in Sector 55, and distinct variability (Figure  8 ). Inspecting the pixel-level light curves clearly shows that the flaring behavior is located on the target, while TESS data using the SHERLOCK package  [83]  (see section 'Search for a second planet' below). In summary, the analysis of the TESS photometry of SPECULOOS-3 reveals its flaring nature, leads to a marginal detection of the transit of its planet, and does not result in a unambiguous determination of its rotation period.
Follow-up MuSCAT2 photometry A transit of SPECULOOS-3b was observed on Aug 12 2023 with the MuSCAT2 multi-imager instrument  [84]  at the Telescopio Carlos Sánchez (TCS) located at the Teide Observatory (Spain). MuSCAT2 observes simultaneously in 4 bands (g ′ , r ′ , i ′ and z ′ ). Data reduction was performed using a custom Python pipeline developed specifically for MuSCAT2  [85]. Unfortunately, the night was cloudy and the resulting photometry was too noisy to be of any scientific use.
Follow-up T150 photometry We conducted a full-transit observation of SPECULOOS-3 b on 20 September 2023 using the T150 at the Sierra Nevada Observatory in Granada (Spain). The T150 is a 150-cm Ritchey-Chrétien telescope equipped with a thermoelectrically cooled 2K×2K Andor iKon-L BEX2DD CCD camera with a field of view of 7. 9 ′ × 7. 9 ′ and pixel scale of 0. 232". We used the Johnson-Cousin I filter with an exposure time of 60 s. The photometric data were extracted using the AstroImageJ package  [92]. program  [95]. The resulting differential light curves showed significant correlated noise that we attribute to the FWHM variations, the drift of the stars on the detector, and the poor sampling of the PSF. After a systematic test of all potential comparison stars and of a large set of extraction apertures, the most precise differential light curve was obtained with an aperture of 5 pixels.
Search for a second planet Under the arguments presented in ref. [130] , we monitored intensively SPECULOOS-3 with SNO-Artemis and MuSCAT-3 (data described above) in the hope to detect additional transiting planets on longer orbital periods. Our visual inspection of all the gathered light curves did not reveal any convincing additional transit-like structure. After detrending, removal of flares and of transits of SPECULOOS-3 b, we performed a global analysis of all our ground-based light curves with the TLS algorithm  [131]  that failed to detect any significant power excess indicative of a second transiting planet. Using the flattened TESS light curve described before, we used our SHERLOCK package  [83]  to (i) recover the candidate at 0. 72 d and (ii) search for extra transiting planets in the system.
SHERLOCK is especially set up for searching low-S/N transit-like features that might be attributable to planets. In particular, it uses a multi-detrend approach and the TLS algorithm  [131]  to optimize the transit search by converging to the signals with the highest S/N and SDE (signal-detection-eficiency)  [132]. During this search process, we found at first a strong signal corresponding to the 0. 72 d candidate, which allowed us to confirm the detectability of this planet in TESS data. Aside from this signal, we found a few other weaker signals in terms of S/N and SDE, in particular, one at 9. 65 d, another at 3. 24 d and finally one at 2. 22 d. Our ground-based effort allowed us to refute all of them, and we attribute them to noise. We then performed injection and retrieval experiments on this dataset that allowed us to establish detection limits.
To this end, we used our MATRIX package  [83, 133] , which generates a sample of synthetic planets by combining a range of orbital periods, planetary radii, and orbital phases that were injected in the TESS flattened light curve. In particular, we generated 2700 scenarios processed in the search for transits using a process that mimics the SHERLOCK procedure. From the results, displayed in Fig. 10 , we conclude that TESS data allows us to detect Earth-size planets with orbital periods shorter than 1 d. However, these small planets' detectability rapidly decreases for longer orbital periods, and if they exist and transit, their detection would be very challenging. For example, assuming the existence of TRAPPIST-1-like planets in this system, they would have detection probabilities <30%. On the other hand, transiting super-Earth planets with sizes larger than 1.
on behalf of the Gemini partnership: the  National Science Foundation (United States) ,  National Research Council (Canada) ,  Agencia Nacional de Investigación y Desarrollo (Chile) ,  Ministerio de Ciencia, Tecnología e Innovación (Argentina) ,  Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brazil) , and  Korea Astronomy and Space Science Institute (Republic of Korea). FJP, PJA, AS, RV, and JA acknowledge financial support from the grant  CEX2021-001131-S  funded by  MCIN/AEI/ 10. 13039/501100011033. This work benefits from observations made at the  Sierra Nevada Observatory , operated by the  Instituto de Astrofísica de Andalucía (IAA-CSIC). This research was carried out in part at the  Jet Propulsion Laboratory, California Institute of Technology , under a contract with the  National Aeronautics and Space Administration  ( 80NM0018D0004 ).
This work is partly supported by  MEXT/JSPS KAKENHI  Grant Numbers  JP15H02063 ,  JP18H05439 ,  JP18H05442 ,  JP21K13955 ,  JP21K20376 ,  JP22000005 , and  JST CREST  Grant Number  JPMJCR1761. This paper is based on observations made with the MuSCAT3 instrument, developed by the  Astrobiology Center  and under financial supports by  JSPS KAKENHI  ( JP18H05439 ) and  JST PRESTO  ( JPMJPR1775 ), at  Faulkes Telescope North  on Maui, HI, operated by the  Las Cumbres Observatory. Observations made with the  Wide-Field Camera (WFCam)  on the UKIRT telescope were granted through Director's Discretionary Time. UKIRT is owned by the  University of Hawaii (UH)  and operated by the  UH Institute for Astronomy. This research has made use of the  NASA  Exoplanet Archive, which is operated by the  California Institute of Technology , under contract with the  National Aeronautics and Space Administration  under the  Exoplanet Exploration Program.
Code availability. The code PROSE used to reduce the SPECULOOS, TRAPPIST, and MuSCAT3 data is available at https://github. com/lgrcia/prose. The code TRAFIT used to analyse the light curves is a Fortran 2003 code that can be obtained from the first author on reasonable request. The HiPERCAM pipeline is available at https: //cygnus. astro. warwick. ac. uk/phsaap/hipercam/docs/html/. The SHERLOCK package used to search for planets in the TESS data is publicly available at https://github. com/ franpoz/SHERLOCK. The detection limits in the TESS data were computed using the MATRIX package, publicly available at https://github. com/PlanetHunters/tkmatrix. Data availability. All the data (Kast, SpeX, and CARMENES spectra, SPECU-LOOS, Saint-EX, TRAPPIST, T150, MuSCAT3, GTC/HiPERCAM, UKIRT/WF-CAM light curves) used in this work are available from the first author on reasonable request.
used the 2. 0-m Faulkes Telescope North at Haleakala Observatory located in Hawaii to observe SPECULOOS-3. The telescope is equipped with the MuSCAT3 multi-band imager [86]. The campaign was started on the single night of Sept 3 2023, and then from Sept 15 2023 to Sept 26 2023. Its main goal was to search for additional transiting planets in the system. During this campaign, we observed two full transits of SPECULOOS-3 b on UT September 17 and 19 2023 in the Sloan-g ′ , -r ′ , -i ′ and z s filters. All datasets were calibrated using the standard LCOGT BANZAI pipeline [87] , and photometric measurements were extracted in an uncontaminated target aperture using the PROSE pipeline [88]. Follow-up TRAPPIST-North photometryTRAPPIST-North (TRAnsiting Planets and PlanetesImals Small Telescope) is a 60-cm robotic telescope located at Oukaimeden Observatory in Morocco [89] [90] [91].
Data from the Rhine River As part of their porosity measurement campaign in the Rhine River,  Frings et al. (2011)  carried out 46 laboratory measurements with sediment obtained from sub-surface layers of the channel bed and river bank, consisting mainly of quartz. The sediment was put inside a cylindrical container and the water displacement method was used to determine porosity of the individual samples that featured a size range of 0. 02 mm -200 mm. To set up the porosity predictors for this data set, we assumed that the sediment form was generally similar to the ones we used for calibration in Sect. 3. This can be justified as the samples for the CT scans were taken from the sediment used in the laboratory measurements, even though the calibration only made use of gravel-sized grains. Consequently, we applied the same interaction functions as in Sect.
Data from the Bès and Galabre River To investigate the generalizability of the packing models and their parameterizations to other rivers, we made use of a second extensive data set obtained by  Tabesh et al. (2022)  from the banks of two rivers in the Rhône-Alpes in France, named Bès and Galabre. They are significantly smaller than the Rhine, and feature a different composition of the sediment, both in terms of lithology and shape. Samples were collected at four different sites with varying sediment characteristics, and their porosity was analyzed later in the laboratory via the water displacement method. The resulting 52 data points again featured size distributions in the range of 0. 02 mm -200 mm. In contrast to the Rhine data set above, no information about the porosity values of uniform packings of the different size classes was provided, and also no details about form characteristics of the sediment were given.
Acknowledgements. The authors want to thank  Axel Winterscheid  and  Wenjia Xu  for fruitful discussions that helped to shape the research. CR gratefully acknowledges the support through the  German Research Foundation (DFG)  grant  FR 3509/4-2 , awarded to RF. UR is grateful for the support through the  DFG  project  433735254. The authors gratefully acknowledge the HPC resources provided by the  Erlangen National High Performance Computing Center   (NHR@FAU)  of the  Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). NHR funding is provided by federal and  Bavarian  state authorities. NHR@FAU hardware is partially funded by the  DFG -440719683. Furthermore, the authors gratefully acknowledge the  Gauss Centre for Supercomputing  e. V. (www. gauss-centre. eu) for funding this project by providing computing time on the GCS Supercomputer SuperMUC-NG at  Leibniz Supercomputing Centre  (www.
Code and data availability. The simulation software, including the numerical method and the setups, is publicly available via WALBERLA's main repository (https://walberla. net). The sediment geometries used in the simulative studies are available on Zenodo (Rettinger et al. ,   2022c). Additionally, a Python implementation of the packing models including examples can be found on Zenodo  (Rettinger and Frings, 2022)  alongside the results of the binary and multi-sized packings obtained by the simulations presented here.
Protocols and materials Participants performed a battery of three tests consisting of six 20 m sprints (SP), horizontal upper limb ballistic push-offs (HBP) with different masses to displaced and crank ergometer all-out sprints (CES). Before each test, players performed a specific warm-up. The six sprints were performed on a wooden floor and the warm-up consisted of 5 minutes of wheelchair displacement in circles in the gymnasium, followed by some short accelerations. The best of the six sprints was keeping to data processing. Wheelchairs were equipped with three dimensions (x, y, and z-axis) Inertial Measurement Units (IMU) on each rear wheel (WheelPerf System, AtoutNovation, France, 128 Hz). The IMUs were placed with the z-axis perpendicular to the plane of the wheel  [21, 22]. The size of the rear wheels, the mass of the participants, and the mass of their wheelchairs were recorded.
𝒑𝑽(𝒙) =𝒑𝟏𝒙 𝟒 +𝒑𝟐𝒙 𝟑 +𝒑𝟑𝒙 𝟐 +𝒑𝟒𝒙+𝒑𝟓 (5) The coefficients for the polynomial (p1, p2…, p5) were returned to be the best fit (in a leastsquares sense) for the velocity data (𝑽 𝑻 ). The coefficients and the polynomial were computed with the MATLAB functions 'polyfit" and "polyval". 𝑭 𝒓𝒓 was estimated using a deceleration test  [25]  on the 20 m sprint field and computed with equation 6. In this equation 𝒈 was the gravitational constant, 𝝁 𝒓 was the rolling resistance coefficient compute as the deceleration value divided by 𝒈. 𝒌 𝒇 was the coefficient of influence of speed on friction  [26]. 𝑭 𝒓𝒓 =𝒎 𝒕 𝒈(𝝁 𝒓 +𝒌 𝒇 𝒑𝑽 𝟐 ) (6) The aerodynamic drag force was obtained withequation 7 where 𝑪 𝒅 𝑨 was the drag coefficient in the function of the frontal area of the system  [27]  and 𝝆 was the air density (1.
Cycling test The torque obtained from the arm ergometer software (Lode Ergometry Manager 10 th version) was used to compute the tangential force produced on the left (𝑳𝑭) and right (𝑹𝑭) cranks by dividing the torque (𝑳𝑴 and 𝑹𝑴) with the length of the right crank (𝑪𝑹) and the left crank (𝑪𝑳) respectively (Equation  8 ). For the cycling test, the force-velocity profile was created by taking the average of the force and velocity during a complete turn of the cranks for each cycling sprint at different resistance levels. 𝑳𝑭 = 𝑳𝑴 𝑪𝑳 𝑎𝑛𝑑 𝑹𝑭 = 𝑹𝑴 𝑪𝑹 (8) Left (𝑳𝑷𝒐𝒘) and right (𝑹𝑷𝒐𝒘) power were calculated as the product of the force torque with the rotational velocity of the cranks (𝑽𝑹) (Equation  9 ).
+ |𝑳|𝒅𝒕 𝒕𝟐 𝒕𝟏  (10)  Where R and L was the assessed variable on the right and left sides, respectively, and where t1 and t2 represented the start and the end of the period during which the ISI was calculated. For the SP test, we used velocity data to calculate the ISI because this measure is considered more representative of the participant's action than other metrics. We calculated the ISI at three-time points during the sprint: at the start of the sprint (corresponding to the first three cycles of propulsion), in the middle of the sprint (corresponding to the cycles of propulsion between the start and the end), and at the end of the sprint (corresponding to the last five cycles of propulsion). For the HBP test, we calculated the ISI using force data from the right and left force plates. Specifically, the ISI was computed from the force applied to the plates between the start of the sled displacement and the end of the push-off, when the hands left the force plates.
Statistics Analyze Correlations between each variable measured were computed via Pearson correlations in SPSS, assuming strong relationships for r=0. 7-1. 0, moderate when r=0. 40-0. 69 and weak relationship when r<0. 1-0. 39  [29]. Significant differences were assumed when p<0. 05. The instantaneous symmetry index was compared between the three devices and between the three levels of resistance with a two factors ANOVA with Bonferroni's post-Hoc. Analysis was conducted using R (Posit Team, 2023), RStudio (Integrated Development Environment for R. Posit Software, PBC, Boston, MA. URL http://www. posit. co/) with "corrplot" package (https://github. com/taiyun/corrplot), "car" package (https://r-forge. r-project. org/projects/car/) and "multcomp" package (http://multcomp. R-forge. Rproject. org).