dataesr/scientific-paragraphs-categorization huggingface dataset:
IV. AN ILLUSTRATIVE EXAMPLE In order to illustrate the appearance and the origin of these multiple solutions, we consider the hydrogen molecule in the 6-31G basis set which corresponds to a two-electron system with four spatial orbitals (one occupied and three virtuals). This example was already considered in our previous work  38  but here we provide further insights on the origin of the appearances of these discontinuities. The downfolded and upfolded G 0 W 0 schemes have been implemented in the electronic structure package QuAcK  103  which is freely available at https://github. com/pfloos/QuAcK. These calculations are based on restricted HF eigenvalues and orbitals. We denote as |1 1 the N-electron ground-state Slater determinant where the orbital 1 is occupied by one spin-up and one spin-down electron.
We crossed VGAT Cre/+ ; Mafa flox4A/+ with Mafa flox4A/flox4A mice and recorded the ventilation of VGAT Cre ; Mafa flox4A/flox4A (Mafa VGAT4A ) mutant neonates. Fifty five percent (6/11) of Mafa VGAT4A mutant pups died before P2 compared to only 15% (2/13) death observed among control pups. Moreover, plethysmographic recordings indicated that Mafa VGAT4A mutants showed an apneic time fraction double that of control littermates (Fig. 3e-g ) accounted by a selective increase in the incidence of breath holding apneas (Fig. 3h ). The reasons why Mafa VGAT4A mutants show reduced morbidity compared to Mafa n4A/n4A mutant is presently unknown. These data show that restricting the 4A mutation to inhibitory neurons was sufficient to recapitulate the severe increase in the incidence of breath holding apneic events.
The plethysmographic chamber (20 mL) was connected to a reference chamber of equal volume and the inter-chamber pressure difference was measured using a differential pressure transducer (Validyne DP-103-14) connected to a demodulator (Validyne CD15). The plethysmographic signals recorded in the absence of limb or body movements were sampled at 1 kHz, stored on a computer and analyzed using the Elphy2 software (developed by G Sadoc at CNRS). The durations of inspirations (Ti) and expirations (Te) were measured to calculate breath frequency F R (F R = 1/ Ti + Te; breath/min); tidal volume, V T (microL); and ventilation V E (V E = F R xV T / 1000 μL/g/min). Calibrations were performed by injecting 2. 5 µL of air in the chamber with a Hamilton syringe. The CO 2 chemo-reflex was tested by measuring ventilation changes induced by a two minute exposure to 8% CO 2 enriched air.
3a ). Note that the analysis of plethysmographic recordings during vocalizations (Supplementary Fig. 3a ), must prominently take into account lung compression, thus the relationship between pressure, flow rate and resistance of upper airways 91 (Boyle law) in addition to the vaporization of water during inspiration (Ideal gas law) itself prominent during resting breathing. Similarly during breath holding apneic breathing clicks were time-locked both to inspiratory onswitch, and the termination of breath holding apneas (Fig. 1f  and Supplementary Fig. 3b ). Whether clicks associated to inspiratory on-switch also denote an endexpiratory obstructive context remains to be investigated. Audio recordings were obtained with an UltraSoundGate condenser microphone capsule CM16 (sensitive to frequencies from 20 Hz to 180 kHz) and Avisoft Recorder software (sampling rate, 250 kHz; format, 16 bit) from Avisoft Bioacoustics.
Repeated tests demonstrated that this procedure ensured that the latencies between the plethysmographic and the audio signals were <2 ms in a 10-min recording. Elphy configuration and program files are available at http://yzerlaut. github. io/Elphy/. A total of 1070 clicks were counted in joint audio-plethysmographic recordings (5 min duration) from WT animals (n = 6) and found preferentially associated to vocal breathing (81. 5 ± 4. 6 %) and breath holding apneic breathing (15. 0 ± 3. 7%) while very scarce during eupneic and central apneic breathing (2. 2 ± 0. 7% and 1. 1 ± 0. 5% respectively, Supplementary Fig. 3e ). Examination of the occurrence of clicks in relation to respiratory contexts was performed on 5 s samples during vocalizing events (n = 70 samples from 4 wild type pups), eupnea (n = 40 samples from 3 wild type pups) and breath holding events (n = 15 samples from 5 Mafa n4A/ n4A mutant pups).
4. The preparation was then transferred to the recording chamber (2 ml) on a net and superfused (2 ml/min) with oxygenated aCSF at 27 °C. Phrenic nerve roots were recorded using glass suction electrodes (150 µm tip diameter). The micropipettes filled with aCSF were connected through silver wires to a high-gain AC amplifier (7P511; Grass, West Warwick, RI), bandpass filtered (3 Hz to 3 kHz), recorded and integrated (time constant, 100 ms) on a computer via a digitizing interface (CED micro 1401) and analyzed using spike2 software (CED, Cambridge, UK). Viral Tracing experiments and histology. Briefly, mouse pups between ages P2-P4 were anaesthetized by hypothermia and two microliters of a viral solution containing equal volumes of Rb-ΔG-mCherry (titer ~1e + 8) and a helper virus, HSV-hCMV-YTB (titer ~3e + 8) was pressure injected unilaterally into the geniohyoid muscle via a glass micro-pipette.
gag-pol, using lipofectamine 2000 (Invitrogen). Retroviral particles were harvested 48-72 h after transfection. Statistical analysis. All data are reported as mean ± sem. Normal distributions of data points were tested using D'Agostino & Pearson or Shapiro-Wilk tests. One-and Two-way ANOVA was used to compare groups of data, unpaired and paired Student's t-test were used to compare two Gaussian distributions of continuous variables, non-parametric tests (Mann-Whitney or Wilcoxon) were used otherwise. Chi square (χ 2 ) test was used for discrete variables. All graphs and statistical analyses were generated using GraphPad Prism software. * p < 0. 05, * * p < 0. 01, * * * p < 0. 001.
Acknowledgements We deeply thank  Noura Mebirouk ,  Christophe Alberti ,  Frederic Bertrand ,  Francoise Ruelle ,  Jessy Leloup ,  Magalie Larcher ,  Valerie Lavallée ,  Krystel Saroul  and  Sandra Autran  for transgenic animals production and maintenance. C. P. is Equipe labellisée  Ligue Contre le Cancer. This work was supported by  ANR-15-CE16-0013-02  and  ANR-19-CE16-0029-02  grants to G. F.
2  and Table  1 ), both of which remained significant even after applying Bonferroni and false discovery rate (FDR) adjustments  (47). Results were nearly identical after applying a correction based on the intronic category (SI Appendix, Table  S2 ), and similar, although with slightly lower statistical significance, when correcting by the synonymous values (SI Appendix, Table  S3 ). Results for the high-confidence LoF subsets (which excluded mutations with annotation warnings as well as those in genes at the upper end of the mutation rate distribution) were nearly identical to those for the main LoF dataset (SI Appendix, Fig. S5 ), suggesting this result is not driven by annotation errors or the inclusion of pseudogenes. Similar differences between species were also observed for one-to-one orthologs and genes intolerant to variation (i.
Beyond the quantitative analyses of deleterious burden and patterns of deleterious variation in the Iberian and the Eurasian lynx, this work provides a genome-wide database of over 4 million derived mutations, of which several thousand are potentially deleterious and likely deserve further research. Incidentally, some deleterious traits believed to have a genetic basis, such as idiopathic epilepsy, membranous glomerulonephritis, and cryptorchidism, are currently relatively common in the Iberian lynx  (84, 86) , even in the captive population, despite its high level of admixture  (34). Further investigation of these traits through genome-wide association studies and candidate gene approaches may ultimately lead to the identification of variants of major effect, whose selection could be eventually integrated into the ongoing genetic management.
Materials and Methods Sampling and Genomic Datasets. Our sample included 31 Iberian lynx individuals from the last two remnant populations of AND (n = 19) and DON (n = 12), in southern Spain, before they were reconnected through translocations and reintroductions, and 29 Eurasian lynx from KIR (n = 13), NOR (n = 8), and POL (n = 8). For details on the demography of these populations, please refer to SI Appendix. Additionally, we included one individual bobcat (Lynx rufus), from the Jerez Zoo (Spain). A summary of the sample is provided in SI Appendix, Table  S7. We arranged samples in four datasets for depth-filtering purposes. Our main analyses were carried out on 48 samples (12 each from AND and KIR, and eight each from DON, NOR, and POL) resequenced at a depth of ∼5. 75× (range: 5× to 7×) using Illumina HiSeq2000 v3 and v4.
See SI Appendix for further details on each dataset. DNA Extraction, Library Preparation, and Sequencing. DNA was extracted from good-quality tissue or blood samples. Paired-end libraries were prepared, and then sequenced in a fraction of a sequencing lane of HiSeq2000 flowcell v3 (Illumina Inc. ), as detailed in SI Appendix. Read Processing and Mapping. Read processing and mapping were mostly performed as described elsewhere  (40) , and are further detailed in SI Appendix. Trimmed reads were mapped to the Iberian lynx reference genome using BWA-MEM (96) with default parameters. Variant Calling, Polarization, and Filtering. GATK v3. 7 HaplotypeCaller (97) was used to generate variation data for the pool of 60 Iberian and Eurasian lynx samples. Repetitive, low-complexity, and low-mappability regions, which together account for 46.
001, 0. 01, and 0. 1) and dominance (h). Since h ≈ 0 can lead to huge amounts of hidden burden for very large populations and, therefore, to very large contributions of purging to the evolution of the overall derived count, we considered the more conservative h = 0. 05 value and, for the sake of symmetry, h = 0. 25 and 0. 45. Data Availability. Raw sequence data of all newly reported samples are available in the European Nucleotide Archive under the accession code PRJEB44874  (99). The putatively deleterious mutations database is available in our institutional repository, DIGITAL. CSIC: https://digital. csic. es/handle/10261/ 224885  (100). All scripts used in the analyses are available at https://github. com/Arynio/genome-annotation  (101).
ACKNOWLEDGMENTS. This work was supported by the  Direcci on General de Investigaci on Cient ıfica y T ecnica of the Spanish Ministerio de Ciencia e Innovaci on  (Projects  CGL2013-47755-P  and  CGL2017-84641-P  to J. A. G. , and Project  PGC2018-095810-B-I00  to A. G. -D. ). Iberian lynx samples were kindly provided by the  Centro de An alisis y Diagn ostico de la Fauna Silvestre , the  Iberian Lynx Ex Situ Conservation Programme , and the  Life+IBERLINCE  project (Project  LIFE10NAT/ES/570 ). Eurasian lynx samples and additional support were provided by the  Polish National Science Center  (Project  2014/15/B/NZ8/ 00212  to K. S. ), the  European Union 's  Seventh Framework Programme  ( Marie Curie Actions)  under the project " Biodiversity of East-European and Siberian large mammals on the level of genetic variation of populations -BIOGEAST " (Contract  PIRSES-GA-2009-247652 ), and the  Russian Science Foundation  (Project  18-14-00093  to A.
A4 Mie calculations The theoretical extinction-to-backscatter ratio for the plume has been calculated using the Python-based miepython Mie code, available at: https://miepython. readthedocs. io/en/latest/. The extinction and backscatter coefficients have been estimated at 750 and 532 nm, respectively, to simulate OMPS and CALIOP observations. Typical sulphate aerosols refractive indices have been considered, with the assumption of very weakly absorbing particles (based on the results of  (Kloss et al. , 2022) ). Log-normal size distributions with varying standard deviation are simulated, to study how this ratio changes with radius.
Code and data availability. MLS and OMPS-LP data are available from EarthData centre at: https://disc. gsfc. nasa. gov/. CALIOP data v3. 41 are available at: https://doi. org/10. 5067/CALIOP/CALIPSO/CAL_LID_L1-VALSTAGE1-V3-41. ALADIN data are available from ESA at https://earth. esa. int/eogateway/missions/aeolus/data. IMS data will be available on a public deposit. ERA5 data are available at https: //www. ecmwf. int/en/forecasts/datasets/reanalysis-datasets/era5. The python scripts and notebooks used in this study will be available at https://github. com/bernard-legras/ASTuS and the intermediate datasets will be available from Zenodo. In the mean time, send requirements to the corresponding author Video supplement. https://mycore. core-cloud. net/index. php/s/CQdtD1VLY2xYuKe.
Acknowledgments We thank two anonymous reviewers for their constructive comments. F. Li is supported by the  National Natural Science Foundation of China  ( 42030110 ;  41874010 ). J. Yan is supported by the  National Natural Science Foundation of China  ( U1831132 ). M. Ye is supported by the  National Natural Science Foundation of China  ( 41804025 ). J. -P. Barriot is funded by a  DAR  grant in planetology from the  French Space Agency (CNES). Q. Y. Deng  thanks  Z. Y. Luo  for her sincere accompany.
Data Availability Statement Data-The spherical harmonic gravity models of the Moon are available at (https://pds-geosciences. wustl. edu/grail/ grail-l-lgrs-5-rdr-v1/grail_1001/shadr/). The derived science data of GRAIL is from  Kahan (2013). LRO topography data we used here can be found at (https://pds-geosciences. wustl. edu/lro/lro-l-lola-3-rdr-v1/lrolol_1xxx/ data/lola_gdr/cylindrical/jp2). The crustal thickness model of the Moon  (Wieczorek, 2012)  we used is archived at Zenodo (https://doi. org/10. 5281/zenodo. 997347). Software-The authors are grateful to Mark Wieczorek for providing the open source software SHTools  (Wieczorek et al. , 2018) , which can be found at Zenodo (https://doi. org/10. 5281/zenodo. 5255218). Several figures were created with the Generic Mapping Tools (GMT) software  (Wessel & Smith, 1991).
Acknowledgements We gratefully acknowledge the  Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex ) and the authors from the originating laboratories responsible for obtaining the specimens and the submitting laboratories from which genetic sequence data were generated and shared via the GISAID initiative included in Supplementary Table 1, as well as the  Unidad de Investigación Médica de Yucatán of the Instituto Mexicano del Seguro Social , which collected most of the BW. 1 and BA. 5. 6 samples used in this study. We appreciate the computer assistance provided by  Jerome Verleyen , and  Juan Manuel Hurtado. The project  LANCAD-UNAM-DGTIC-396  of the  Dirección General de Cómputo y Tecnologías de la Información (DGTIC-UNAM ) provided supercomputing resources in MIZTLI.
Venus Images Taken with Ground-Based Telescopes To study the CD events, we inspected the amateur observations of Venus hosted in the database of ALPO-Japan http://alpo-j. sakura. ne. jp/indexE. htm (accessed on 5 February 2021)  [18]. We selected and examined 458 NIR and 552 UV observations of the eastern elongation 2019/2020. The NIR observations were obtained with filters in the range 685-1050 nm and the UV observations with filters in the ∼320-410 nm range. Table  1  provides details about these NIR and UV observations as well as the Venus phase angle and the nominal best resolution. The resolution of the amateur images ranged from 187 to 663 km depending on the apparent angular size of Venus and the best resolution allowed by the diameter of the telescope  [19]. One of us (EK), on 11 March 2020 (with Venus having a solar elongation of 45.
The images from amateur observations were obtained thanks to the technique of lucky imaging, where thousands of images are captured in a few minutes with fast planetary cameras and then stacked to obtain a single one more nitid and with better resolution (by up to a factor of four in poor seeing conditions)  [20, 21]. Software such as Autostakkert (http:// www. autostakkert. com, accessed on 10 February 2021) or Registax (http://astronomie. be/ registax, accessed on 10 February 2021)  [22]  were used following this strategy: (a) selection of the highest quality images, (b) alignment, (c) stacking, and (d) processing of the final image to get a sharper version  [23]. To obtain these observations, sensitive CMOS cameras (e. g. , ZWO290 mm) were equipped on ∼0. 2-0. 5 m aperture telescopes. In the case of NIR images, Venus's clouds exhibit lower contrast than in UV images, and a different image processing is required  [6].
The first step in the analysis was to properly define the navigation of each image, i. e. , the correct orientation (north-south), fitting of the limb, and the phase of the planet to a synthetic outline (calculated by software's ephemeris). For this, and further processing of the images, we used the free software WinJupos (http://www. grischa-hahn. homepage. tonline. de, accessed on 10 February 2021)  [24]. We also used this software to measure the motions of clouds patterns (latitude-longitude position, size, and wind speed). The phase and the ephemeris of the planet are automatically calculated by the software. Two rotation periods are implemented in WinJupos for the determination of the planet longitudes: System 1 (S1) accounting for the surface rotation with a period of ∼243 days, and System 2 (S2) with a period of 4.
Five events of the CD during March (11 March 2020, 16 March 2020, 21 March 2020, 26 March 2020, and 31 March 2020) were studied in combination with Akatsuki images, which covered orbits 142-144 of the mission  [32] [33] [34] [35]. During March 2020, the phase angle of Venus as observed from Akatsuki varied between 30 • and 160 • , while the spatial resolution of UVI and LIR images at lower latitudes ranged 12-90 and 40-360 km/pixel, respectively. The UVI images were photometrically corrected, i. e. , correcting for the limbdarkening effect  [36]. Both UVI and LIR images were processed and projected as described by Gonçalves et al. [37]. A devoted software written in IDL was used to process and perform measurements in the Akatsuki images  [38].
Acknowledgments: We are grateful for support from all the members of the  Akatsuki mission. We are also grateful to many amateur observers that observed Venus intensively during the investigated period providing data for this research. Special thanks to the observer  Raimondo Sedrani  for using some of his observations. E. K. would like to offer his special thanks to  Grischa Hahn developer of WinJupos  software for providing help and advice for the proper use. Moreover, E. K. would like to acknowledge the continuous support of his wife Dimitra.
Data Availability Statement: This study was based on ground-based images of Venus provided by worldwide amateur observers and Akatsuki observational data provided by ISAS. Ground-based observations are publicly available in the Venus section of ALPO-Japan at http://alpo-j. sakura. ne. jp/Latest/Venus. htm (accessed on 10 Februray 2021). All original Akatsuki/UVI and LIR data are available via Data ARchives and Transmission System (DARTS), provided by the Center for Sciencesatellite Operation and Data Archive (C-SODA) at ISAS/JAXA, and NASA PDS Atmospheres Node. The analyzed data are the L2b and L3bx products, and these data are provided in the UVI datasets (accessed on 10 Februray 2020) https://data. darts. isas. jaxa. jp/pub/pds3/vco-v-uvi-3-cdr-v1. 0/ (accessed on 15 February 2021) and at https://data.
darts. isas. jaxa. jp/pub/pds3/extras/vco_uvi_ l3_v1. 0/ (accessed on 15 February 2021), and LIR datasets at https://data. darts. isas. jaxa. jp/pub/ pds3/vco-v-lir-3-cdr-v1. 0/ and https://data. darts. isas. jaxa. jp/pub/pds3/extras/vco_lir_l3_v1. 0/ (accessed on 15 February 2021).
METHODOLOGY The development of the CT starts with the characterisation of the system and the boundaries of the domain. Classification of the components, qualitative formalisation of parthood and connection relations between components (mereotopology), and relations between functions and capabilities of each component have been studied and reverse engineered. Each component has been classified as seen in Figure  1. The Festo sorting station operates as follows: 1. When the workpiece enters the sensing unit, the system sends the data to the knowledge graph (KG). The KG associates a workpiece ID and the spatial region s_in to the timestamp received. 2. The sensing unit measures the colour of the workpiece and once measured, sends the order to the gate actuator to let the workpiece go. 3. When the gate actuator opens, the system sends the results of the sensing process to the KG, together with the related timestamp.
The KG associates the workpiece ID, the spatial region s_out, and the colour to the timestamp received. 4. If the workpiece is red, the first actuator is activated sorting the part to the first collection point, whereas if it is metal the second actuator is activated sorting the part to the second collection point. No actuator is activated if the workpiece is black. A physical obstacle conveys the black workpiece through the conveyor system to the third collection point. In this case, data points for spatial regions n1 and n2 are associated with the relative workpiece ID. 5. When every workpiece is detected by the retro-reflective sensor, the system sends the data point to the KG. The KG associates the timestamp and spatial region w with the relative workpiece ID.
Ontology model development The ontology is exported from the Protégé tool in the. owl file format. The ontology file created will then be imported into the data management tool together with all the other ontologies used (BFO, CCO, and IOF-Core). The ontology of the Festo sorting station has been created with the Protégé tool (https://protegewiki. stanford. edu/wiki/Main_Page). The data is collected and managed within the same data management tool, GraphDB (https://graphdb. ontotext. com/). SPARQL (https://www. w3. org/TR/sparql11-overview) queries have been used to add information about the structure and functions of the system and its components, the related processes as well as the reasoning for the malfunctions. The following section describes how these queries transform the real-time monitoring data into state descriptions of the workpiece.
Separate SPARQL queries have been used to infer the occurrences and their process types from the state descriptions as required. For example, if the analysis is conducted for a particular workpiece, all the occurrences in which the workpiece participated as a patient may be inferred from the related state descriptions using suitable SPARQL. The rules given from (4) to (7) are Horn rules and SPARQL Construct queries have been used to encode them. The ternary predicate malfunctionedFor is reified as a separate class (not modelled under any upper-level ontology) linking the instances of component, process, and the workpiece.
CT development Figure  3  shows the architecture of the CT and how it works. Data points from the Festo sorting system have been sent to GraphDB, which is the tool selected for data management. GraphDB is a free tool that allows the creation of knowledge graphs (KG). The KG represents the network of all the entities that constitute the system (objects, events, data, etc. ) and illustrates the relationships between them. It is the graph database that stores the data points received from the physical system and where it is possible to query the competency questions created before. It is a key element of the CT. The system sends data points to the KG in 5 points: i) the diffuse sensor, called s_in (entering the sensing unit); the gate actuator, called s_out (leaving the sensing unit); the first actuator, called n1 (pushed to the first collection section); the second actuator, called n2 (pushed to the second collection section); and the retroreflective sensor, called w (workpiece stored in the slope).