dataesr/scientific-paragraphs-categorization huggingface dataset:
Topo IIAs encoded by Bacteria and eukaryotes form two monophyletic groups nested within Topo IIA encoded by Caudoviricetes and Nucleocytoviricota, respectively. Importantly, Nucleocytoviricota remained well separated from eukaryotes after removing both Bacteria and Caudoviricetes from the data set, indicating that the separation of Nucleocytoviricota and eukaryotes is probably not due to long-branch attraction artifact. The topologies of our trees suggest that the eukaryotic Topo IIA was probably acquired from an ancestral member of the Nucleocytoviricota of the class Megaviricetes, before the emergence of the last eukaryotic common ancestor (LECA). This result further highlights a key role of these viruses in eukaryogenesis and suggests that early proto-eukaryotes used a Topo IIB instead of a Topo IIA for solving their DNA topological problems.
Data collection For Bacteria, we downloaded the full proteomes of a set of 112 bacterial strains spanning 10 representative groups (Aquificae, Dictyoglomi, Elusimicrobia, FCB group Plactomycetales, Verrucomicrobiales, Chlamydiae, Nitrospirae, PVC group Fibrobacterota, Chlorobiota, and Bacteroidota, Proteobacteria, Spirochaetes, Terrabacteria group, and Thermotogae). We used BLASTP v2. 9. 0+  (Ramsay et al. 2000; Camacho et al. 2009 ) recursively to collect the homologs of Escherichia coli K12 GyrB and GyrA proteins (WP_000072067. 1, NP_416734. 1) in those 112 proteomes. Finally, we concatenated each related pair of GyrB and GyrA hits. We also added the sequence of E. coli Topo IV (Supplementary Table  S1 ) that branched at the base of DNA gyrase in previous analyses. For Caudoviricetes (tailed phages), we downloaded all the 1,131,926 Caudoviricetes proteins and next used BLASTP to search for the homologs of the three subunits of the T4 phage topoisomerase II (E-value lower than 1e-10).
2019 ) (Supplementary Table  S1 ). To improve this data set, we added one sequence from Acanthocystis turfacea Chlorella virus and three sequences from Pithoviruses (Pithovirus LCPAC104, Pithovirus LCPAC201 and PithovirusLCPAC202). Finally, in order to improve our sampling in the Asfuvirales and Pandoravirales orders, we used our TopoIIA HMM profile against the Giant Virus Database  (Aylward et al. 2021). We obtained seven hits in Pandoravirales and twenty in Asfuvirales that were not yet in our data set (three stars in Supplementary Table  S1 ). A preliminary phylogenetic analysis led to an unusual placement for some TopoIIA proteins from metagenomic assemblies. This could represent true phylogenetic positions which could be explained by horizontal gene transfers or artifactual positions.
It turned out to be more challenging to assemble the data set of eukaryotic Topo IIA sequences because we found many fragments of Topo IIA in eukaryotic proteomes. Thus, we produced position-specific scoring matrices (PSSMs) for GyrA and GyrB proteins using alignments from the PFAM database (files provided as Supplementary material) and searched for coding sequences matching both profiles. We defined a list of fifty-two eukaryotic organisms, representative of the known eukaryotic diversity. When possible, we downloaded the corresponding proteomes and used PSSM as PSI-BLAST queries to obtain Topo IIA homologs. For those organisms where no proteome was available, we looked for transcriptomic data and performed de novo assembly using Trimmomatic v0. 36  (Bolger, Lohse, and Usadel 2014)  for the read pre-processing step, SortMeRNA v2.
1b  (Kopylova, Noé, and Touzet 2012)  to filter out rRNA sequences, and Trinity v2. 2. 0  (Grabherr et al. 2011)  for the assembly (two stars in Supplementary Table  S1 ). We then used the GyrA and GyrB PSSMs as queries for a TBLASTN search against the assemblies and kept hits matching both profiles. One star in Supplementary Table  S1  means that the accession number corresponds to the eukaprot db. id. (Richter et al. 2020).
Confidence branch supports were assessed using the transfer bootstrap expectation (1,000 replicates except for the tree including all sequences, where 100 replicates were used)  (Lemoine et al. 2018 ). We used iToL v4. 4. 2  (Letunic and Bork 2016)  to generate the figures. All trees and alignments are available 10. 5281/zenodo. 7081315.
Unlike the previous airborne versions of FLASH-A with transverse optical setup, the StratoClim FLASH-A rendition has a coaxial optics similar to that of the FLASH-B balloon-borne instrument  (Yushkov et al. , 1998). The water vapour mixing ratio is detected by sensing the fluorescence light yielded by photodissociation of water molecules after their exposure to Lyman-α radiation. A near Lyman-α line (123. 6 nm) is produced by a krypton lamp, whereas the hydroxyl fluorescence at the 300-325 nm wavelength range is detected by a photomultiplier operating in photon-counting mode. The accuracy of water vapour measurements in the 1-100 ppmv range is estimated at 8 %, whereas the precision of 1 Hz data in the stratosphere is 0. 2 ppmv with a detection limit of 0. 1 ppmv for 5 s integration time. FLASH-A was calibrated against a reference MBW-373L frost-point hygrometer before and after the aircraft deployment as well as during the campaign using FISH calibration facility.
Ensemble trajectory modelling and convective cloud top data For investigating the link between the variations in water vapour observed locally by the Geophysica aircraft and the deep convection upwind detected using satellite IR imagery, we use the TRACZILLA Lagrangian model (Pisso and  Legras, 2008) , a modified version of FLEXPART  (Stohl et al. , 2005). The simulation was designed to release an ensemble of 1000 back trajectories every second along the aircraft flight path, travelling back in time for 30 d. The calculation of back trajectories was performed using the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis horizontal winds and diabatic heating rates provided at hourly frequency and 31 km horizontal resolution. For detection of convective cloud encounters (convective hits) along the diffusive back trajectories, we use cloud top information from geostationary satellites (MSG1 and Himawari-8).
Further insights into the AMA gaseous/particular composition and dynamics will be provided by an upcoming airborne campaign within the Asian summer monsoon Chemical and Climate Impact Project (ACCLIP; https://www2. acom. ucar. edu/acclip, last access: 28 February 2022), which will sample the western Pacific mode of the monsoon and eastward eddy shedding using NASA WB-57 and NCAR GV aircraft. The stratospheric impact of overshooting convection in the North American monsoon is a primary target of the Dynamics and Chemistry of the Summer Stratosphere (https://dcotss. org/, last access: 28 February 2022) project, involving ER-2 high-altitude aircraft. Data availability. The airborne data will be available from the HALO database at https://halo-db. pa. op. dlr. de/mission/101 (last access: 30 July 2021) (DLR, 2021).
In the meantime they may be provided by the respective principal investigator upon request. TRACZILLA data are available upon request. MLS data are publicly available at http://disc. sci. gsfc. nasa. gov/Aura/data-holdings/MLS (last access: 28 February 2022;  Lambert et al. , 2015) , GNSS-RO data at https://www. romsaf. org/product_archive. php (last access: 28 February 2022;  EUMETSAT, 2022) , CALIOP data at https://doi. org/10. 5067/CALIOP/CALIPSO/LID_L1-STANDARD-V4-10 (NASA/LARC/SD/ASDC, 2016), and CATS data at https://doi. org/10. 5067/ISS/CATS/L1B_N-M7. 2-V3-00 (NASA/LARC/SD/ASDC, 2019). Video supplement. The animation showing the hourly evolution of back trajectories released at the B7 point of StratoClim Geophysica flight F7 is available at: https://doi. org/10. 5281/zenodo. 5168703 (Khaykin et al.
cm -3 , M being the molecular weight of the dye and N A the Avogadro constant (6. 022 × 10 23 mol -1 ). When necessary, full width at half maximum values of the ICT absorption bands were determined by deconvolution of the absorption spectra using the Python SciPy library scipy. optimize. curve_fit package. Fluorescence quantum yields were measured as the mean of values obtained against two to three standards. Measurements were repeated four to five times for FONs suspensions. Average values are shown in Table  1. Standards were chosen according to the excitation and emission range of the samples: Fluorescein (Φ f FL = 0. 9 in 0. 1M NaOH), Rhodamine 6G (Φ f R6G = 0. 94 in EtOH), Cresyl Violet (Φ f CV = 0. 54 in MeOH), 4-Dicyanomethylene (Φ f DCM = 0. 44 in EtOH), Nile Red (Φ f NR = 0. 79 in DMSO).
FONs fluorescence was excited with a tunable pulsed Mai-Tai 2P laser (Spectraphysics) set to 890 nm and detected in the 600-750 nm (for Q 1 and Q 2 FONs) or 630-800 nm (for Q 3 and Q 4 FONs) spectral band on another PMT. For each of the four FON types, the PMT gain was adjusted on the FONs@PAH condition so as to acquire images on the best optimised dynamic scale. It was then kept untouched for all of the following images to allow for comparison. Z-stack recordings were acquired. Maximal projection of the stacks and scaling of the resulting images was performed using Fiji/ImageJ for data representation. All images of a given condition are displayed using the same grayscale. All images are displayed with the same contrast.
Acknowledgments: We thank  Judith Bruns  for her contribution to the synthesis of the dyes. Transmission electron microscopy and optical microscopy was performed at the  Bordeaux Imaging Centre (BIC) , a service unit of the  CNRS, INSERM and Bordeaux University , member of the national infrastructure  France BioImaging  and supported by the  French National Research Agency  ( ANR-10-INBS-04 ). The help of  Sabrina Lacomme  and  Jérémie Teillon  is acknowledged for technical assistance in electron and optical microscopy, respectively. Cell culture was performed in the cell biology facility of the  Interdisciplinary Institute for Neuroscience , a service unit of the  CNRS and Bordeaux University , funded by unit resources and the  LabEx BRAIN initiative. The help of  Rémi Sterling  is acknowledged.
Funding: This research was funded by the  Horizon 2020  research and innovation programme H2020/2014-2020/under the  Marie Skłodovska-Curie  grant agreement number  841379  and the  European Union 's  Seventh Framework Programme FP7 /2007-2013/under the  Marie Skłodovska-Curie  grant number  607721. M. B-D. also acknowledges funding from the  Conseil Régional d'Aquitaine for a Chaire d'Accueil  and financial support from the  French National Research Agency  ( ANR-15-CE16-0004 ) and the  IdEx Bordeaux  ( ANR-10-IDEX-03-02  via the LAPHIA cluster of Excellence). The APC was funded by the  Horizon 2020  research and innovation programme H2020/2014-2020/under the  Marie Skłodovska-Curie  grant agreement number  841379. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
[51, 52] This Ni(OH) 2 deposition reaction might be further inhibited as the layer of hydroxide blocks electrode charge transfer, explaining why the reduction current 2 rapidly drops. To decipher the mechanism of Ni electrochemical deposition and the contribution of the competing reactions contained in the electrochemical signature, the operando optical images recorded during the LSV are extensively analyzed. These images assembled in a movie is provided in supporting information, SI, along with the Python program routines used to automatically analyze it. The positions of all the NPs in the optical images are localized and the evolution of their optical intensity is recorded during the whole experiment and at the single NP level. This procedure is named hereafter collecting single "optical transients" that act as real time reporters of the NP's activity.
Nanoscale reactivity Color optical images were acquired during the LSV at a 20 Hz frequency and were synchronized with the potential ramp. The very first image is considered as the background and is subtracted from all other subsequent images. Each color image is split along its three color-channels and the red one is selected for data treatment as it presents the best signal to noise ratio. The last frame of the optical monitoring, recorded at -1. 5 V, is shown in Figure  2a.
However, sizing the NPs by SEM requires acquiring high magnification images limiting the SEM field of view (FOV), or the SEM image size, and therefore greatly complicates the correlative approach. We then resorted to a template matching algorithm to localize and assess the size of all the NPs produced on the electrode. Briefly, a database of higher resolution SEM images is constructed by acquiring intermediate (IM) and high-magnification (HM) SEM images within the droplet footprint to fully cover its surface area. Then, the template matching algorithm was employed to overlay all HM and IM SEM images on the LM image (Figure  3a ) and to prioritize them. In this way, a single NP selected on the LM image can be identified both in the IM image (Figure  3b ) and in the most appropriate HM image (Figure  3c ) from the images database.
Acknowledgements This work was partially financially supported by the  ANR   JCJC program  ( PIRaNa  project,  ANR-20-CE42-0001 ) and through the  CNRS and Université Paris Cité. The authors acknowledge the  ITODYS SEM facility , the  Ile-de-France region and IDEX  for financial support of the  AFM-Beam-Rex  platform. Received: ((will be filled in by the editorial staff)) Revised: ((will be filled in by the editorial staff)) Published online: ((will be filled in by the editorial staff)).
We believe that, taken together, these variables can provide a representative picture of the nwb language ecology as depicted by the sources that we con-14 We included these as fixed effects on the premise that decisions on what should be fixed and what should be random effects are erratic (see Bolker 2018 and references therein). However, there are several other options to incorporate control for spatial autocorrelation, including the use of the spatial conditional autoregressive term in the package brms of the statistical program R and including latitude and longitude as smoothed interaction terms in generalized additive models  (Wood 2017). Language Dynamics and Change 12 (2022) 155-223 sulted (see Section 5. 1 for discussion). While these variables are neither exact nor exhaustive, they appear to shed light on aspects of the interaction between gender systems and the local sociogeographic environment, which we want to test further with the support of quantitative methodologies and based on the full data set of 179 nwb languages.
3). For instance, languages with no syntactic agreement and where animacy-based marking occurs on a single target only minimally differ from languages with no gender agreement. Similarly, languages with both syntactic and animacy-based agreement, where the latter is potentially available for all agreement domains, are in effect not so different from languages with only animacy-based gender. In view of this, we think that if any binary distinction is to be made in our typology, it should be between languages that only have syntactic agreement and all other languages (i. e. , languages with any amount of animacy-based agreement or no gender marking at all). We do use the four-way typology for plotting in Sections 2. 3 and 4 as we find it more fine-grained and insightful. 16 The data on the sociogeographic variables were collected from the following sources: -Ancestor in rainforest and current location in rainforest.
e. , touching borders) with Ubangi-and/or Central Sudanic-speaking communities. Data on where these communities are located were taken from Ethnologue (Lewis et al. 2016). -Number of L1 speakers. These data are taken from Ethnologue  (Lewis et al. 2016). 19 Given that we excluded Shiwa (see footnote 7) and two other languages due to missing data on population size (see footnote 19), the final data set contains 176 languages. The relationship between the type of gender system and demographic and geographic factors was assessed using several different models. As we deal with a mixture of data types (binary, continuous, counts), we primarily constructed generalized linear mixed effects models (glmm s) using the package brms  (Bürkner 2017 ) in R (R Core Team 2017). This package allows the user to fit Bayesian multilevel models in R using the probabilistic programming language stan  (Carpenter et al.
2018). 20 It contains six groups: Ababuan (22 languages in our sample), Bantu A-B10-B20-B30 (70), Central-Western Bantu (130), East Bantu (12), Lebonya (6), and Mbam-Bube (15). 21 Our sample does not include all Central-Western and all East Bantu languages, as many of these are spoken in different Guthrie zones. We included only languages from the nwb area, from Guthrie zones A, B, C, D, and H (see Section 2. 3). For more information regarding the use of Glottolog as the main grouping variable and for the phylogenetic trees used for additional analyses, see Supplementary Information 2, Section 3. We constructed various generalized linear mixed effects models (glmm s) using the package brms  (Bürkner 2017). For reasons of space, only the most relevant aspects of the analyses are discussed here.
Acknowledgments This paper is the result of a research collaboration begun in May 2016, during the first Quantitative Methods Spring School, organized by the  Department of Linguistic and Cultural Evolution  at the  Max Planck Institute for the Science of Human History (Jena). We are very thankful to the spring school's directors,  Russell Gray  and  Fiona Jordan , and to all participants for support and inspiration. Ongoing analyses and preliminary results of this research have been presented at various conferences, workshops, and other academic venues. We are particularly thankful to the audiences of the workshop on " Language shift and substratum interference in (pre)history" (Jena 2017 ), the sle conferences of 2017 (Zürich) and 2018 (Tallinn), and the  African Linguistics research seminar of the Humboldt University (Berlin ,  2017 ).
Language Dynamics and   Change 12 (2022) 155-223   Bantu borderland, vol. 1. London:  Oxford University Press & International African Institute (iai ). Guthrie, Malcom. 1967-1971. Comparative Bantu: An introduction to the comparative linguistics and prehistory of the Bantu languages. Farnborough: Gregg International Publishers. Guzmán Naranjo ,  Matías & Laura Becker. 2021. Statistical bias control in typology. Linguistic Typology. doi:  10. 1515/lingty-2021-0002. Hadfield, Jarrod. 2010. mcmc methods for multi-response generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software  33. 1-22. Hammarström, Harald ,  Robert Forkel & Martin Haspelmath  (eds. ). 2018. Glottolog 3. 3. Jena:  Max Planck Institute for the Science of Human History. doi:10. 5281/zenodo. 1321024.
Blasi ,  Carlos A. Botero ,  Claire Bowern ,  Carol R. Ember ,  Dan Leehr ,  Bobbi S. Low ,  Joe McCarter ,  William Divale & Michael C. Gavin. 2016. D-place: A global database of cultural, linguistic and environmental diversity. PLoS one 11(7). e0158391. Klieman, Kairn A. 2003. The  Pygmies Were Our Compass: Bantu and Batwa in the History of West Central Africa ,  Early Times  to c. 1900 c. e. Portsmouth, NH: Heinemann.
Bürkner 2017]andMCMCglmm [Hadfield 2010]) allow for a wider range of models, including a mixture of categorical and continuous fixed effects, as well as random effects that control for genealogical relations by using the full structure of a phylogenetic tree (set). Additional reasons for opting for a Bayesian framework are discussed by McElreath (2020). Other recent typolog- ical studies that opt for a Bayesian approach are Erben Johansson et al. (2020), Urban & Moran (2021), and Guzmán Naranjo & Becker (2021). and Coupe (2018) and is gaining ground (Sinnemäki & Di Garbo 2018; Schmidtke-Bode & Levshina 2018; Schmidtke-Bode 2019; among others). Our immediate reason for choos- ing Bayesian glmm s over frequentist statistics was that Bayesian packages in R 18 World Language Mapping System, version 17, Global Mapping International, 2015, http:// worldgeodatasets.
Methods Covert-attention experiment. Participants. Sixteen young naïve adults (10 women, mean age = 27. 8 ± 2. 3 years) took part in the experiment. Eye movements were monitored on five of them in a separate control session. Written informed consent was obtained from all participants. The local ethics committee (Comitato Etico Pediatrico Regionale-Azienda Ospedaliero-Universitaria Meyer-Firenze FI) approved the experimental paradigm, which complied with the Declaration of Helsinki. Experimental setup. Participants were tested individually in a dark room. Stimuli were presented through an ACER computer (Windows 7) using the Psychophysics Toolbox extensions for Matlab  46. The experiment was displayed on a 120-Hz gamma-corrected CRT Silicon Graphics monitor (1024 × 768 pixel), subtending 38.
250 non-neutral trials have 50% cue validity (125 valid trials and 125 invalid) and the other 250 trials have 80% cue validity (200 valid trials and 50 invalid). Data for each participant were collected in two sessions, one for each cue validity, performed in random order across participants. In each session, participants performed one block of neutral trials and two blocks of non-neutral trials, one for the experimental and one for the control condition, presented in random order. Each participant performed 1448 trials in total. A subset of participants performed an additional separate session with one block of neutral trials and one block of non-neutral trials with 80% cue validity while their eye movements were recorded. This session allowed us to control that the results obtained in the main covert-attention task were not due to uncontrolled saccades toward the salient cue, which could potentially reduce the perceptual threshold by reducing the distance of the gabor from the fovea.
Data processing. Percent correct data were fitted (MLE) with a cumulative Gaussian error function. For each participant, condition (experimental and control), cue validity (50% and 80%), and trial type (neutral, valid, and invalid) thresholds were calculated as the target contrasts yielding 80% correct responses. Thresholds for neutral trials of each condition were used as baseline for non-neutral trials. That is, they were subtracted from those obtained in valid and invalid trials, and the result divided by them to provide a measure of the percentage increase or decrease of contrast thresholds in non-neutral trials. In the control session, we considered a saccade execution any shift of gaze position further than 2 degrees from the fixation point. Experimental setup. Each participant was tested individually in a dark room.
Stimuli were presented through a MacPro computer (OS 10. 6. 8), using the Psychophysics Toolbox  46  and the Eyelink Toolbox extensions  48  for Matlab. The experiment was displayed on a 120-Hz CRS Display++ LCD monitor (1920 × 1080 pixel), subtending 70 × 40 degrees at a viewing distance of 57 cm. Participants' viewing was binocular, but only the right eye was recorded by an Eyelink 1000 video-based eye tracker (1 kHz). The observers' head was stabilized with a chin-and forehead rest.