dataesr/scientific-paragraphs-categorization huggingface dataset:
2020). Now, nomenclatural acts valid under the PhyloCode can be published in regular journals. Among amphibian taxa, much remains to be done because only Amphibia  (Laurin et al. 2020a) , Lissamphibia  (Laurin et al. 2020b) , Caudata (D. B. Wake 2020)  and Gymnophiona (M. H. Wake 2020) have been converted so far. Building on our recent phylogenetic analysis of the "RANOIDEA" Ford and Cannatella, 2004 (~ SCOPTANURA in  Dubois et al. , 2021) , we take the opportunity to convert three taxon names on which our recent work focuses  (Lemierre et al. 2021). We follow the nomenclature proposed by  Dubois et al. (2021)  in their recent work regarding the names that we convert. Bonaparte, 1850 [Lemierre & Laurin] , converted clade name (RegNum registration number: 558).
2000) ;  Catalão, Brazil (Oliveira and Imbernon 1998). Consequently, many exploration programs worldwide have been launched in the last decades for carbonatite and associated deposits to develop and diversify the supply source for critical metals. The occurrences of carbonatites outcrops in largely remote areas, makes the adoption of remote sensing data to map, delineate, and discover these complexes a time-and cost-effective approach, especially in vast and arid regions. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data have been successfully used for mapping and investigating carbonatite complexes in many areas by using a variety of processing techniques. One of the relevant studies has used the ASTER Thermal Infrared (TIR) band rationing (B13/B14) and decorrelation stretch (bands: 13, 12, and 10 displayed in RGB, respectively) to highlight the carbonatite outcrops of the Khanneshin volcano in Afghanistan; and matched filtering for mapping the distribution of calcitic and ankeritic carbonatites  (Mars and Rowan 2011).
Another study by  Rajendran and Nasir (2013a)  has used the spectral absorption properties to distinguish carbonatite in greyscale and RGB images by white pixels in the TIR region and dark pixels in the Visible and Near Infrared-Short Wave Infrared (VNIR-SWIR) region owing to the molecular emission and absorption characters of carbonate minerals. These authors have also used the ASTER VNIR-SWIR data through Principal Component Analysis (PCA) technique to highlight carbonatite outcrops in Batain Nappe of Oman. However, the presence of lithological facies with similar spectral characteristics in the same area has probably complicated their task based only on one method such as grey image visualization, band ratio, or color composite. Indeed, the ASTER spectral features of carbonates such as absorption in band 8 could be confused with the absorption of ferromagnesian minerals (e.
2 wt. % REE and 0. 3 wt. % Nb 2 O 5  (ONHYM 2016a, b). Despite these potential mineral resources, the geology of the Oulad Dlim massif remains poorly understood because of accessibility issues. The 1:1,000,000 Geological Map of Morocco  (Bronner et al. 1985)  is the only available complete geological map of the massif with few higher resolution geological maps (1:50,000; https://cartesgeoscientifiques. mem. gov. ma/catalogue). Therefore, a new geological mapping approaches based on the interpretation of satellite imagery can contribute in improving our understanding of this area's geology. The present study highlights the potential of processing data recorded by ASTER sensor to identify and map carbonatite complexes and related mineral deposits. In this context, the enhancement of ASTER imagery by the combination of several image processing techniques [band rationing, PCA, minimum noise fraction (MNF), and supervised classification (SC)] is used here to highlight the extension of carbonatite bodies and associated iron oxide-apatite ores.
Data acquisition and pre-processing We used two multispectral ASTER level 1 T scenes (AST_L1T) covering the Gleibat Lafhouda region (Table  1 ). The data are downloaded from the Land Processes Distributed Active Archive Center (LP DAAC;https://LPDAAC. usgs. gov). The AST_L1T radiance data are produced from AST_L1B, which have been geometrically corrected, and projected into Universal Transverse Mercator (UTM)_zone 28 North  (Duda et al. 2015). ASTER is a multispectral sensor launched in 1999 onboard the Earth Observing System (EOS) Terra platform. The usefulness of ASTER data has been proved for mineral exploration and geological mapping by several studies (e. g. ,  Mars and Rowan 2011; Rajendran and Nasir 2013b; Ninomiya and Fu 2016; Yazdi et al. 2018; Abdelkareem and El-Baz 2018; Shi et al.
2020; Khan et al. 2020; Beirami and Tangestani 2020). ASTER sensor has relatively ameliorated spatial, spectral, and temporal resolutions compared to most other multispectral sensors such as Landsat. It measures reflected radiation in nine bands between 0. 52 to 2. 43 µm (VNIR-SWIR) with 15 to 30 m resolution  (Fujisada 1995; Abrams 2000). Additionally, ASTER has five bands in the thermal infrared wavelength region between 8. 125-11. 65 µm with 90 m resolution (Table  2 ). This makes ASTER sensor more suitable for discrimination and mapping of carbonatites and related deposits. The ASTER TIR data were used with band rationing, without any atmospheric correction to avoid the influence of correction algorithms on the originated spectral data (e. g. ,  Ninomiya et al. 2005). On the other hand, the VNIR and SWIR bands were co-registered in one file of nine bands and resampled to 15 m spatial resolution.
Then, they were atmospherically corrected using the FLAASH (Fast Line of sight Atmospherics Analysis to Hypercubes) module (e. g. , Cooley et al. 2002) for converting radiance data to surface reflectance and eliminating the effects caused by water vapor and cloud cover. Finally, several algorithms of image enhancements were applied on the VNIR and SWIR data such as PCA, MNF, and band rationing. The workflow chart summarizing the methodology adopted in this paper is shown in Figure  2.
2017). In order to assess the performance of the used band ratios, we established a database of previously known carbonatites and IOA mineralization occurrences  (Montero et al. 2016; Benaouda et al. 2020). Then the digital numbers of each band ratio and the corresponding sample from the database were plotted in the Receiver Operating Characteristic (ROC) curves  (Nykänen et al. 2015). The curve was performed by plotting sensitivity (also known as true positive rate) against 1specificity (false positive rate) at varying thresholds. The Area Under Curve (AUC) was used as an indicator to quantify the performance of the various band ratios used.
Field validation and X-ray analysis The fieldwork was carried out in the Gleibat Lafhouda area to evaluate the resulted maps and to investigate the occurrence and distribution of carbonatite rocks and associated IOA mineralization. In-situ geochemical analyses of about 80 samples were performed. For this purpose, the Handheld Xray florescence (XRF) Niton XL5 analyzer was used as it represents a powerful tool for rapid collection of large compositional data sets which are important for geostatistical purposes  (Young et al. 2016). This technique gives generally comparable results with laboratory analysis for most elements with the advantage of providing fast and real-time geochemical information. Two international reference standards (CG-2, OPY-1) were analyzed to assess the precision of the acquired data, and they have shown good agreement with the proposed values from GeoReM database (http://georem.
Supervised classification The obtained results were used as training classes to perform a supervised classification using the Maximum Likelihood (ML) algorithm. The ML classifier is one of the most used methods for satellite image classifications (e. g. , Xiuping Jia and Richards 1994; Ahmad and Quegan 2012). It is based on a discriminant function that assigns each pixel to the appropriate class with the highest likelihood. The accuracy of the ML classification was assessed using a confusion matrix, which is based on the comparison of the reference data and the corresponding results.
3 ). Since the eigenvectors present a reverse trend compared to the spectral profiles of target minerals, the expected carbonatite areas appear in this component as dark pixels (Fig. 6a ). Thus, the PC4 was chosen among the other component to enhance the outcropped carbonatite areas. The selected spectral subset of ASTER data used as input in the MNF method is the same as that used for PCA (i. e. , bands 1, 2, 5 and 8). The resulted transformation vectors are shown in Table  4. The MNF4 shows a highly positive contribution of bands 5 (0. 803) with opposite (negative) contributions of bands 1, 2, and 8 (-0. 400, -0. 283, and -0. 338 respectively). This trend is relatively identical to the most prospective minerals of carbonatite (e. g. , calcite, dolomite, apatite, and phlogopite), and as expected the target areas are displayed in this component as bright pixels (Fig.
The field data were used to validate several anomalous zones given by the different methods and validate the performed classification. The classified zones by the ML-algorithm as carbonatite and IOA ore are concordant with the common anomalies detected by method combinations  (Figs. 10, 11). Indeed, the classified carbonatite pixels (Fig. 14 ) show more surface extension and complete those observed in class 3 of the integrated map (Fig. 10 ). Similarly, the classified pixels as IOA ores (Fig. 14 ) fit with class 2 of the integrated map (Fig. 11 ) and display the IOA outcrops extension. The ML algorithm based-classification has an overall accuracy of 98% which shows the good distribution of the mapped facies. The kappa coefficient calculated using the confusion matrix method is 0. 86, which is considered as an excellent agreement category of the Kappa coefficient (e.
Conclusions A c c e p t e d M a n u s c r i p t In this study, we demonstrate the significant information that can be retrieved from satellite remote sensing ASTER data for mineral exploration and geological mapping. The ASTER processed data coupled with field observations, portable XRF analyses, and petrographic characterization were examined to show their ability for identifying and mapping of carbonatite outcrops and related iron oxide-apatite mineralization. The combination of band ratios from TIR region (B13/14) and SWIR bands (B6+B9/B7) alongside with PCA, and MNF has proven to be reliable and probative to increase the accuracy of carbonatite mapping. Based on spectral properties of most indicative minerals of carbonatites (e. g. , carbonates, apatite, phlogopite, iron oxides) a spectral subset (bands: 1, 2, 5, and 8) was determined to perform the PCA and MNF transformations.
Overall, the obtained results have several implications for the use of multispectral satellite imagery in general and ASTER data in particular, for carbonatite and IOA deposit exploration programs. Indeed, through this study, we highlight the benefit of the remote sensing-based approach as a powerful time-and cost-effective tool especially in zones where the conventional geological mapping is difficult and requires large investments. Further work for extending this approach on other alkaline complexes and related mineral deposits types may be of great interest especially, in arid regions. A c c e p t e d M a n u s c r i p t.
Acknowledgment This work was initiated in the frame of  FP7-PEOPLE-IRSES project  " MEDYNA "  2014-2017  (" Maghreb-EU  research staff exchange on geoDYnamics, geohazards, and applied geology in Northwest Africa", Work Package #3: " Deep structures and mantle processes "), and was supported and funded by the  UM6P  project. The authors would like to thank the Military services and local authorities for their assistance during the entire period of field missions. The authors wish also to thank  Bassou Zayi  ( UM6P-Geology & Sustainable Mining & UM6P-OCP Geo-Analytical Lab ) and  Christophe Nevado  and  Doriane Delmas  ( Géosciences Montpellier ) for their help in sample and thin section preparations. We thank two anonymous reviewers for their constructive and helpful comments.
Considering a scenario where the aqueous alteration comes from the melting of cometary-like ices, could the pH be initially acidic before rock-water interaction drives A59, page 6 of 16 A. Bouquet et al. :  Endogenous radiolysis in chondritic bodies it toward alkaline values? We calculated the pH of an aqueous solution resulting from melting an ice with the volatile composition of comet 67P/C-G, as assessed by the ROSINA instrument  (Rubin et al. 2019). We considered species that can participate in acid-base chemistry, using the SpecE8 app of the Geochemist Workbench 2021 software with the thermo. com. V8. R6+ database. No mineral or redox reactions were included and the temperature is assumed to be 25 • C. The species that could be taken into account include H 2 O, CO 2 , HCOOH, CH 3 COOH, NH 3 , HCN, H 2 S, SO 2 , HF, HCl, and HBr; the species that were not included for lack of thermodynamic data all have abundances below 0.
127 0. 0706 Elect. conductivity = Hardness = carbonate = non-carbonate = Carbonate alkalinity= Water type = ( * ) 29709. 71 uS/cm (or umho/cm) CS 2 H 2 CS ( * ) 0. 00 mg/kg sol'n as CaCO3 CH 3 SH ( * ) 0. 00 mg/kg sol'n as CaCO3 HF 0. 00 mg/kg sol'n as CaCO3 HCl 11319. 97 mg/kg sol'n as CaCO3 NH4-HCO3 0. 0057 0. 0027 0. 038 0. 011 0. 014 0. 0032 0. 0015 0. 0211 0. 0061 0. 0078 Bulk volume Fluid volume Mineral volume Inert volume = = = = 1. 06e+03 cm3 Notes. Species flagged with an asterisk ( * ) are absent from the thermo-1. 06e+03 cm3 dynamic database (thermo. com. V8. R6+), and are therefore not included 0. 00 cm3 in the calculations. 0. 00 cm3 Porosity = 100. % Permeability = 98. 7 cm2 redox couples Eh (volts) pe A59, page 9 of 16.
Oxyurid nematodes (Syphacia spp. ) from bank (Myodes glareolus) and field/common (Microtus spp. ) voles, from disparate geographical sites in the British Isles, were examined morphologically and genetically. The genetic signatures of 118 new isolates are provided, based primarily on the rDNA internal transcribed spacers (ITS1-5. 8S-ITS2) region and for representative isolates also on the small subunit 18S rDNA region and cytochrome c oxidase subunit 1 (cox-1) gene locus. Genetic data on worms recovered from Microtus spp. from the European mainland and from other rodent genera from the Palaearctic, North America and West Africa are also included. We test historical hypotheses indicating that S. nigeriana is a generalist species, infecting a range of different rodent genera. Our results establish that S.
5% agarose gel. PCR products were purified using AMPureXP beads according to the manufacturer's instructions and the final DNA concentration was estimated by Nanodrop before dilution with nuclease-free water to the required concentration for sequencing. Sequencing primers, identical to the amplification primers, were diluted to the required concentration with nuclease-free water and supplied to Source Bioscience or Eurofins, along with PCR products, for Sanger sequencing. Chromatograms were inspected visually for ambiguities and sequences trimmed to the 3 ′ end of the primers. Sequence alignments were prepared using ClustalW within the MEGA X package  (Kumar et al. , 2018)  followed by visual inspection. Phylogenetic analysis was performed in MEGA X using maximum likelihood (ML) with a partial deletion threshold set at 95% in MEGA (v10).
Intraspecies (each separate parasite species based on phylogenetic analysis) and interspecies (all sequences) minimum spanning network (MSN) plots were produced in PopART  (Leigh and Bryant, 2015)  with an epsilon of zero  (Bandelt et al. , 1999). Intraspecies MSNs were linked together based on the interspecies MSN, but indel and single nucleotide polymorphism (SNP) numbers were added in manually given that sites with indels are ignored in MSN model calculations. In addition to the novel sequences generated in this project, we exploited genetic records of rDNA and cox-1 from Syphacia in GenBank. Some of these were from our own earlier work  (Stewart et al. , 2018) , and those for S. agraria and isolates from Microtus spp. from Russia were from the work of  Gorelysheva et al. (2021). Since the focus of the current study was on Syphacia spp.
in Microtus spp. , we used only representative sequences from Apodemus and Mus spp. but more information on how other isolates from these hosts fit into the phylogenetic trees can be found in  Stewart et al. (2018). Because of the large number of identical sequences deposited by  Gorelysheva et al. (2021)  for isolates from Russian voles, we selected for the current analyses only representative sequences for the clades referred to in  Gorelysheva et al. (2021) , in order to show how our novel sequences related to those from Russian rodents. Voucher sequences, including all sequences generated by this study and included in the current paper, have been deposited in GenBank (Table  1 ). Voucher numbers for accession to worms from M. rutilus held at the Museum Southwestern Biology, University of New Mexico, are as follows: Isolate from Russia, MSB:Para:25548; isolate from Alaska, USA, MSB:Para 25557; isolates from the Yukon, USA, MSB:Para:24824 and 24848.
Molecular genetic comparison of worms In total, we provide 118 new sequences [64 for rDNA (ITS-1-5. 8S-ITS-2), 28 for cox-1 and 26 for 18S rDNA (SSU)], which we have combined with 52 sequences from GenBank [29 for rDNA (ITS-1-5. 8S-ITS-2) and 23 for cox-1]. rDNA (ITS-1-5. 8S-ITS-2) region The ML phylogenetic tree for rDNA (ITS-1-5. 8S-ITS-2), illustrated in Fig. 2A , shows that Syphacia isolates from rodents trapped throughout the British Isles had mostly identical genetic sequences, irrespective of whether the worms were isolated from field, bank or common voles (the latter only from Guernsey). A large proportion of the isolates from voles from the British Isles were identical, and these included isolates from the island of N. Uist in the Outer Hebrides, the most northerly location, to those from Devon in the south west of the British Isles, the island of Anglesey in Gwynedd, Wales in the west and Sussex in the southeast (Node a in Fig.
, 2020) , although to date the sequences are not available in GenBank. Our isolates from Russia and North America had been carefully examined by one of us (JMK) and designated as S. petrusewiczi rauschi and deposited as such in the Museum Southwestern Biology, University of New Mexico. It is interesting that this S. petrusewiczi rauschi clade was quite distant to that of our worms from European voles with a deep split in the phylogenetic tree of each of the three genes in our study. This is exactly consistent with the cladistic tree published by  Hugot (1988)  in which S. petrusewiczi and S. petrusewiczi rauschi were illustrated as sister species on a branch deeply separated from that on which S. nigeriana and S. obvelata were placed. It is also consistent with  Gorelysheva et al. (2020)  and  Okamoto et al.
III. RESULTS Figure  2  shows a backward x-ray scattering spectrum recorded from a diamond sample (10 lm thickness) at ambient conditions with and without using an inserted four-bounce Si-111 monochromator in the x-ray beamline. The energy calibration was carried out using the Ka and Kb x-ray emission lines from chromium samples. The presented spectra are normalized to the Compton peak maximum to account for shot-to-shot variations in x-ray flux, sample thicknesses, and materials. To reduce the detector noise, all pixels whose values were below a threshold corresponding to the single-photon event were discarded, before averaging over the whole data set. Due to the low transmission of the monochromator and therefore the low x-ray flux, $18 000 shots were accumulated for the scattering spectrum, compared to the average of $90 shots for obtaining a representative spectrum without monochromating the x-rays.
In both cases, the carbon K-edge resulting from scattering from core electrons is clearly visible as a peak in the spectrum at $5715 eV. The downshift of $285 eV from the elastic peak (corresponding to the 1 s binding energy) places the carbon K-edge at the low energy tail of the inelastic Compton scattering feature. Reducing the x-ray energy bandwidth further improves the data quality, enhancing the visibility of the L-edge features at $6 eV below the elastic peak and substructures at the K-edge, which can be used for an x-ray Raman spectroscopy investigation. We measured the total energy resolution by elastic scattering from a metallic glass sample (mixture of Co/Si/B/Fe/Ni, 18 lm thick foil). The higher atomic number results in an enhanced intensity of elastic scattering, which allows for a decoupled analysis of the elastic scattering signal and neglecting the inelastic spectral features.
ACKNOWLEDGMENTS We acknowledge the  European XFEL in Schenefeld, Germany , for provision of x-ray free-electron laser beamtime at the  Scientific Instrument HED (High Energy Density Science)  and would like to thank the staff for their assistance. We thank  G. Geloni  for the current information about the self-seeding performance of the European XFEL. K. V. , N. J. H. , O. S. H. , A. K. S. , and D. K. were supported by the  Helmholtz Association  under No. VH-NG-1141  and O. S. H. was supported by the  Helmholtz Association  under Grant No. ERC-RA-0041. K. F. and M. S. were supported by the  Helmholtz Association  under Grant No. VH-NG-1338. K. R. acknowledges funding by the  Center for Advanced Systems Understanding (CASUS)  which is financed by the  German Federal Ministry of Education and Research (BMBF)  and by the  Saxon Ministry for Science, Culture and Tourism (SMWK)  with tax funds on the basis of the budget approved by the  Saxon State Parliament.
The ancillary GALEX, CFHT, Calar Alto 2. 2m telescope, Spitzer, and Herschel photometric data are described in  Fossati et al. (2018). In addition, for the comparison with our models we use VIVA Hi and 20 cm continuum data  (Chung et al. 2009 ) and 6 cm radio continuum data from  Vollmer et al. (2013). Fossati et al. (2018)  reconstructed the quenching histories of NGC 4330 in various regions along the major axis by means of stellar population fitting. They performed a joint fitting of spectra and photometry using Monte Carlo techniques to optimally explore the parameter space. The emission of the galactic disk was divided into 13 apertures along the major axis of NGC 4330, as shown in Fig. 3. Aperture photometry was obtained by summing the calibrated flux values in each pixel contributing to a given aperture minus the background value in the same aperture.
For this purpose  Fossati et al. (2018)  adopted the multizone models for the chemical and spectrophotometric unperturbed disc evolution originally presented in  Boissier & Prantzos (2000)  and later updated by  Muñoz-Mateos et al. (2011). The model was projected to fit the high inclination of the disc of NGC 4330 and the SFH were derived in each of the apertures. Fossati et al. (2018)  further modified the unperturbed SFHs by introducing an exponential decline of the SFR to parametrize the quenching event. Parametric models to the spectro-photometric data were produced using MULTINEST  (Feroz & Hobson 2008; Feroz et al. 2009 Feroz et al. , 2013)). A grid of stellar spectra was constructed using the quenched SFHs coupled to  Bruzual & Charlot (2003)  high-resolution models. Nebular emission lines were added to the stellar template.