dataesr/scientific-paragraphs-categorization huggingface dataset:
The alpha diversity Shannon and Simpson indices were also calculated. The Good's coverage was calculated according to the equation: C = 1-(n/N) where n is the number of OTU and N is the total number of sequences  (Good, 1953). Sequences from selected dominant OTUs (>1% of total sequences) were aligned using Muscle  (Edgar, 2004)  with related sequences retrieved from NCBI databases, and a phylogenetic tree was built with MEGA7  (Kumar et al. , 2016)  using the Maximum Likelihood method  (Tamura and Nei, 1993). Tree topology confidence was determined by bootstrap analysis on 1,000 replicates  (Felsenstein, 1985). The archaeal and bacterial 16S rRNA gene reference sequences of OTUs have been deposited in the Genbank database under the accession numbers KY773181-KY773204 and KY771104-KY771161, respectively.
Statistical Analyses Treatment effects (i. e. , sulfate source, type of substrate) on parameters to be analyzed (i. e. , H 2 S production, microbial diversity) were evaluated using a one-way analysis of variance (ANOVA) with a Bonferroni post-hoc test using SPSS version 17. 0 (SPSS Statistics, Inc. , Chicago, IL, USA). P < 0. 05 were considered as statistically significant. Spearman rank correlations were used to investigate the relations among parameters (i. e. , performances of H 2 S production and the proportion of individual taxon or the indices of community diversity). The data obtained at end point time of experiment (day 14) were analyzed by Principal Component Analysis (PCA) using XLSTAT (Addinsoft, XLSTAT Version 2014. 5. 03).
Data We used the ADF-S for our analysis. ADF-S was covered by four far-infrared (FIR) AKARI bands, centered at 65, 90, 140, and 160 µm, with a continuous filter coverage, which allows for very precise estimation of the dust luminosity and temperature, eliminating uncertainties caused by gaps in the filter coverage. Observations were made by the Far-Infrared Surveyor (FIS:  Kawada et al. 2007) , and the field was centered at RA = 4 h 44 m 00 s , DEC = -53 • 20 00. 0 J2000  (Shirahata et al. 2009b ). More than 2 000 sources were detected in the area of ∼ 12. 3 deg 2. Based on a sample of sources detected at 90 µm WIDE-S band and brighter than 0. 0301 Jy (which corresponds to ∼ 10σ detection level), we created a multi-wavelength catalog  (Małek et al. 2010) , which contains 545 sources with optical counterparts found in public databases (NED, SIMBAD, IRSA).
The median value of angular distance of the source from a counterpart is 9. 7 arcsec. This sample was previously used for a more general analysis of properties of active, star forming FIR sources  (Małek et al. 2010 (Małek et al. , 2013 (Małek et al. , 2014)). In the present paper, new measurements, mainly from GALEX, Spitzer/MIPS sample  (Rieke et al. 2004 , taken from public database and for a part of ADF-S sources, measured directly from images by ourselves), WISE  (Wright et al. 2010) , and ATCA-ADFS survey  (White et al. 2012) , as well as new spectroscopic data not included in our previous studies  (Sedgwick et al. 2011; Jones et al. 2009) , were added to create the extended version of our multi-wavelength catalog. We used 545 galaxies in total. In our sample, 98 galaxies have measurements in UV (GALEX), 100 sources have 15, 24 and/or 70 µm Spitzer measurements, and 280 sources have WISE data (W1, W2, and/or W3; we did not use W4 data as the errors of the photometric measurements were too great to make them usable for the SED fitting).
Detailed information with the name of the survey, the band name, and effective wavelength, as well as number of sources correlated with the ADF-S database, can be found in  Małek et al. 2014 , Table  1. To improve our analysis, we have also used Herschel/SPIRE photometric measurements  (Griffin et al. 2010)  taken from the HerMES survey  (Oliver et al. 2012 ) second data release located in the HeDaM Herschel Database in Marseille 1. The search for Herschel/SPIRE counterparts was performed within a radius of 10", but most of the identified sources have counterparts closer than 5" (mean angular distance equal to 2. 48 ± 1. 91"; our result is in agreement with the typical astrometric accuracy of SPIRE maps as given by  Swinyard, 2010, and Bendo, 2013, for example). Herschel/SPIRE measurements allow us to compute dust temperature and dust luminosity for our sample of galaxies with a very good precision.
This model includes young stellar population tracks from the Geneva database, and the Frascati database for older populations (for a more detailed discussion we refer the reader to  Maraston 2005, and Maraston et al. 2009). In general,  Maraston (2005)  models provide reliable information on the NIR-bright stellar population of galaxies, which is very important for our analysis, since our sources have been detected in the NIR bands. To calculate the initial mass function (IMFs), CIGALE has two built-in algorithms based on  Salpeter (1955)  and  Kroupa (2001)  models.
For three galaxies, the reduced χ 2 was too high to use them for the further analysis, and for the remaining objects, the fitted dust temperature was either lower than 10K (and at the same time, the uncertainties were equal to 0) or the estimated errors were much higher than 50% of the dust temperature value. We excluded them from the final analysis. We stress that none of the LIRGs and ULIRGs identified by CIGALE were identified as normal galaxies by CMCIRSED, but rather CMCIRSED was unable to perform a reliable fit to their SEDs. This discrepancy between the results given by both codes is well explained as the lack of Herschel/SPIRE data for some galaxies, since far-infrared data are crucial for a code based on the FIR data only. CIGALE has the advantage over CMCIRSED in the cases where the IR measurements between 8 and 1000 µm are scarce.
Stellar mass ADF-S galaxies are relatively massive with the median value of M star equal to 10 9. 38 ± 10 0. 38  [M ]. The mean M star computed for ULIRGs, LIRGs, and galaxies with dust ) < 11 [L ] is equal to 11. 51 ± 0. 37, 10. 35 ± 0. 31, and 10. 03 ± 0. 50 [M ], respectively. Stellar masses computed by CIGALE for the ADF-S sample consistent with stellar masses calculated for LIRGs and located redshifts, selected from infrared surveys and published by: We have also compared our results with more distant galaxies, reported by: -Giovannoli et al. (  2011  In both cases (local, and more distant Universe), the stellar masses for the LIRGs and ULIRGs we found in the ADF-S data are consistent with the literature. Both our results and results reported in the literature suggest that LIRGs and ULIRGs are more massive than normal galaxies, and that their stellar masses increase with infrared luminosity.
IR power-law slope Figure  11  shows the distribution of α parameter  (Dale & Helou 2002)  for the ADF-S LIRGs and ULIRGs. It demonstrates that our sample consists mostly of galaxies active in star formation. Only five ULIRGs have α > 2. One of them is the most distant galaxy from our sample, a quasar, with known spectroscopic z=1. 23, with α = 3. 15 ± 0. 47. Unfortunately, for this galaxy we have no Herschel/SPIRE data which implies that the temperature of dust may be not well evaluated. Nevertheless, more than 80% of ULIRGs, and 95% of LIRGs are characterized by a low value of α. Taking into account a high Fig. 13 : Stellar mass versus SFR for ULIRGs (filled red ellipses), for LIRGs (filled blue ellipses), and for normal galaxies (filled gray ellipses). The black solid line represents log(M star ) : log(SFR) relation given by  Noeske et al.
Figs. 11, 15, and 21, for example. Properties of the same object, calculated with a new redshift z=0. 43, give us a typical LIRG (log(L dust ) = 11. 12 ± 0. 09[L ]) with physical parameters characteristic for the LIRG sample. As the previous redshift (1. 23) is given by the NED and other public databases, we decided to present the results based on the reference, but we point out that the results obtained with the lower redshift by Keeney et al. (2013)  appear much more reasonable. In the sample, 22 galaxies (32%) were classified as LIRGs (including five galaxies with known spectroscopic redshift). This means that LIRGs and ULIRGs in total compose 56% of the bright ADF-S sample at redshift >0. 05. The control sample contains 30 normal galaxies (12 of them have spectroscopic redshift). We note that in our sample of LIRGs and ULIRGs, only one LIRG (ID ADFS =46) and one ULIRG (ID ADFS =212) have only eight photometric measurements.
Acknowledgements. We thank the anonymous referee for useful comments and suggestions. This work is based on observations with AKARI, a  JAXA  project with the participation of  ESA. Research was conducted in the scope of the  HECOLS International Associated Laboratory. This research has made use of the SIMBAD database, operated at  CDS, Strasbourg, France , the  NASA/IPAC  Extragalactic Database (NED), which is operated by the  Jet Propulsion Laboratory , and the  California Institute of Technology , under contract with the  National Aeronautics and Space Administration. This research has made use of the  NASA/ IPAC Infrared Science Archive , which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration.
This research has made use of data from  HerMES  project (http://hermes. sussex. ac. uk/). HerMES is a  Herschel Key Programme utilising Guaranteed Time  from the  SPIRE  instrument team, ESAC scientists and a mission scientist. The HerMES data was accessed through the Herschel Database in Marseille (HeDaM -http://hedam. lam. fr)operated by CeSAM and hosted by the  Laboratoire d'Astrophysique de Marseille. This work have been supported by the  Polish National Science Centre  (grants  UMO-2012/07/B/ST9/04425  and  UMO-2013/09/D/ST9/04030 ), and the  European Associated Laboratory Astrophysics Poland-France HECOLS. MM acknowledges support from  NASA  grants  NNX08AU59G  and  NNX09AM45G  for analysis of GALEX data in the AKARI Deep Fields. TTT has been supported by the  Grantin-Aid for the Scientific Research Fund  ( 24111707 ), and by the  Strategic Young Researches Overseas Visits Program for Accelerating Brain Circulation  commissioned by the  Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan.
Figs. 11 11 Figs. 11, 15, and 21, for example. Properties of the same object, calculated with a new redshift z=0. 43, give us a typical LIRG (log(L dust ) = 11. 12 ± 0. 09[L ]) with physical parameters characteristic for the LIRG sample. As the previous redshift (1. 23) is given by the NED and other public databases, we decided to present the results based on the reference, but we point out that the results obtained with the lower redshift by Keeney et al. (2013)  appear much more reasonable. In the sample, 22 galaxies (32%) were classified as LIRGs (including five galaxies with known spectroscopic redshift). This means that LIRGs and ULIRGs in total compose 56% of the bright ADF-S sample at redshift >0. 05. The control sample contains 30 normal galaxies (12 of them have spectroscopic redshift).
The resulting score enabled the identification (or not) of the tested species: a score of 2 with a validly published species enabled identification at the species level, a score of 1. 7 but <2 enabled identification at the genus level and a score of <1. 7 did not enable any identification. No significant MALDI-TOF MS score was obtained for strain SIT2 against the Bruker database, suggesting that our isolate was not a member of a known species. Consequently, we added the spectrum from strain SIT2 to our database, and the organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to members of the genus Dermatophilus  [2]. The phylogenetic subtree highlighted the phylogenetic position of this bacteria relative to other species. Sequences were recovered by a nucleotide BLAST (Basic Local Alignment.
NMNI Search Tool) against the National Center for Biotechnology Information (NCBI) 16S rRNA Targeted Loci Project database. The bacterium was identified by sequence analysis of the 16S rRNA. Its phylogenetic relationships with closely related species were determined by MEGA v6. The evolutionary history was inferred by using the maximum likelihood method based on the JTT matrix-based model. Strain SIT2 exhibited a 98% 16S rRNA sequence identity with Mobilicoccus pelagius (NZ-BAFF00000000. 1), the phylogenetically closest bacterial species with standing in nomenclature (Fig. 1 ). Genomic DNA of Mobilicoccus massiliensis was sequenced via MiSeq Technology (Illumina, San Diego, CA, USA) with the two applications: paired end and mate pair. The reads of both applications were trimmed, and the optimal assembly was obtained through SPAdes (St Petersburg genome assembler) software with 245 contigs of coverage in eight scaffolds, which generated a genome size of 3.
was analysed with the Antibiotic Resistance Gene-ANNOTation (ARG-ANNOT) database and BLASTp in Gen-Bank  [11]. The functional annotation of protein sequences was performed using BLASTp against the GenBank and Clusters of Orthologous Groups (COGs) databases  [11]. The exhaustive bacteriocin database available in our laboratories (Bacteriocins of the Unité des Maladies Infectieuses et Tropicales Emergentes (URMITE) database; http://drissifatima. wix. com/bacteriocins) was performed by collecting all currently available sequences from the databases and from NCBI. Protein sequences from this database allowed putative bacteriocins from human gut microbiota to be identified using BLASTp methodology  [11]. The genome of Mobilicoccus massiliensis SIT2 has been deposited in GenBank with accession number CDGT01000000 and 16S rRNA accession number LK985391.
Acknowledgements We are grateful to  L. Hadjadj  ( Unité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) ,  UM63 CNRS 7278 IRD 198 INSERM U1905 ,  IHU Méditerranée Infection, Facultés de Médecine et de Pharmacie, Aix-Marseille Université, Marseille, France ) for technical assistance. Supported in part by the  Centre National de la Recherche Scientifique (CNRS)  and  Infectiopôle Sud Fondation.
6811423 Carbohydrate transport and metabolism E 275 8. 179655 Amino acid transport and metabolism F 60 1. 7846519 Nucleotide transport and metabolism H 114 3. 3908389 Coenzyme transport and metabolism I 106 3. 1528852 Lipid transport and metabolism P 159 4. 729328 Inorganic ion transport and metabolism Q 68 2. 0226057 Secondary metabolites biosynthesis, transport and catabolism R 302 8. 982749 General function prediction only S 155 4. 610351 Function unknown - 1263 37. 566925 Not in COGs COGs, Clusters of Orthologous Groups database. a Total is based on total number of protein-coding genes in annotated genome.
Overview Dothideomycetes phylogeny Consensus phylogram (50 % majority rule) of 80 552 trees resulting from a Bayesian analysis of the LSU sequence alignment (153 taxa including outgroup; 779 aligned positions; 402 unique site patterns) using MrBayes v. 3. 2. 6  (Ronquist et al. 2012). Bayesian posterior probabilities (PP) >0. 74 are shown at the nodes and thickened lines represent nodes with PP = 1. 00. The scale bar represents the expected changes per site. Families and orders are indicated with coloured blocks to the right of the tree. GenBank accession or Fungal Planet numbers are indicated behind the species names. The tree was rooted to Candida broadrunensis (GenBank KY106372. 1) and the taxonomic novelties described in this study for which LSU sequence data were available are indicated in bold face.
The alignment and tree were deposited in TreeBASE (Submission ID S21807). Consensus phylogram (50 % majority rule) of 140 328 trees resulting from a Bayesian analysis of the LSU sequence alignment (70 taxa including outgroup; 816 aligned positions; 288 unique site patterns) using MrBayes v. 3. 2. 6  (Ronquist et al. 2012). Bayesian posterior probabilities (PP) >0. 74 are shown at the nodes and thickened lines represent nodes with PP = 1. 00. The scale bar represents the expected changes per site. Families and orders are indicated with coloured blocks to the right of the tree. GenBank accession or Fungal Planet numbers are indicated behind the species names. The tree was rooted to Orbilia vinosa (GenBank DQ470952. 1) and the taxonomic novelties described in this study for which LSU sequence data were available are indicated in bold face.
Asexual morph not observed. Culture characteristics -Colonies covering Petri dishes after 2 wk at 25 °C. On PDA, colonies with cream to yellowish floccose aerial mycelium, reverse yellowish with centre pale brown. On MEA, colonies are similar to PDA with reverse yellowish to amber. On WA, colonies with sparse growth and whitish mycelium, reverse uncoloured. Typus. Brazil, Rio Grande do Norte state, Mossoró municipality, Universidade do Estado do Rio Grande do Norte (S5°22'43. 85" W37°30'12. 25"), as endophyte from Lippia gracilis (Verbenaceae), Mar. 2015, M. G. Viana (holotype URM 90067, culture ex-type URM 7547, ITS, LSU and BenA sequences GenBank KY855413, KY855414 and KY855412, MycoBank MB820711). Notes -According to morphological features and phylogenetic inferences,  Wang et al. (2016a, b)  demonstrated that Achaetomium is a monophyletic lineage in the family Chaetomiaceae.
Based on our phylogenetic analyses using concatenated ITS, BenA and LSU sequences, A. lippiae is closely related to A. luteum. Based on a megablast search in GenBank, the ITS sequence of A. lippiae has 98 % (525/535) similarity to A. luteum  (CBS 618. 68 ; GenBank KX976571. 1), 96 % (519/541) similarity to A. macrosporum  (CBS 152. 97 ; GenBank KX976573. 1), and 95 % (519/541) similarity to A. strumarium  (CBS 333. 67 ; GenBank NR_144811. 1), amongst others. On its LSU sequence, A. lippiae is 99 % (792 /797) similar to A. strumarium  (CBS 333. 67 ; GenBank AY681170. 1), amongst others. The BenA sequence has 95 % (400/423) similarity to A. luteum  (CBS 618. 68 ; GenBank KX976912. 1), 89 % (377/423) similarity to A. macrosporum  (CBS 152. 97 ; GenBank KX976914. 1) and 86 % (420/487) similarity to A.
strumarium  (CBS 333. 67; GenBank AY681238. 1). Morphologically, A. lippiae is different from A. strumarium in size of the ascomata ((120-)160-300 µm diam vs 122-159(-256) µm diam in A. lippiae), number of ascomatal hairs (3 µm vs absent in A. lippiae), size of asci (48-78 × 7-11 µm vs 35-60 × 8-9. 5 μm in A. lippiae) and ascospores ((10-)11-13(-13. 5) × 6-7. 5 µm vs 10-16 × 5. 5-6. 5(-8) μm in A. lippiae), and presence of chlamydospores (absent vs present in A. lippiae)  (Cannon 1986). Achaetomium lippiae also differ from A. luteum in ascomata size  (116. 2-182. 6 × 99. 6-157. 7 μm) , asci (37-40. 7 μm) and ascospores (8. 8-10. 3 × 3. 7-6. 6 μm)  (Rai et al. 1964) ; and from A. macrosporum in ascomata size  (140-290 × 110-210 μm) , asci (55-80 × 12-19 μm) and ascospores (16. 5-21. 5 × 10-13.
5 μm)  (Cannon 1986 ). A 50 % majority rule consensus maximum likelihood tree calculated from calmodulin sequences showing the relationships of taxa within Aspergillus sect. Usti. The partitioning scheme and substitution models for analysis were selected using Partition-Finder v. 1. 1. 1 (Lanfear et al. 2012 ). The HKY+I model was used for introns, TrN model for the 1st, F81 for the 2nd and HKY+I for the 3rd codon positions. The tree was constructed with IQ-TREE v. 1. 4. 0  (Nguyen et al. 2015). The dataset contained 45 taxa and a total of 805 characters of which 419 were variable and 360 parsimony-informative. Bootstrap support values at branches were obtained by generating 1 000 bootstrap replicates. Only bootstrap support values ≥ 70 % are shown; ex-type strains are indicated by a superscript T.
Colonies on OA after 3 wk of incubation at 15 °C 44 -45 mm diam, flat, floccose at the centre, greyish brown (6D3) at the centre and brownish orange (5C4) at the edge; exudates absent; diffusible pigment absent; sporulation sparse; reverse greyish brown (6D3) at the centre and pale grey (1D1) at the edge. Minimum temperature of growth, 5 °C; optimum temperature of growth, 15 °C; maximum temperature of growth, 25 °C. Typus. antarCtiCa, South Shetland archipelago, King George Island, near to Carlini's Argentinean scientific base, from a diesel-contaminated soil sample, 11 Jan. 2011, A. M. Stchigel (holotype CBS H-23211, cultures ex-type CBS 143035 = FMR 16056; ITS and LSU sequences GenBank MG385664 and MG385663, MycoBank MB822232). Notes -Cadophora antarctica, recovered from a soil sample contaminated with diesel in King George Island (Antarctica), displays the typical features of a psychrotrophic organism: it has an optimal temperature of growth at 15 °C and is not able to grow above 25 °C.
Cadophora antarctica differs from all previously known species of the genus  (Gramaje et al. 2011 , Travadon et al. 2014) , displaying holoblastic conidiogenesis, forming conidiophores morphologically similar to cladosporiumlike taxa. Based on a megablast search of NCBIs GenBank nucleotide database, the closest hit using the ITS sequence is with the ex-type strain of Cadophora luteo-olivacea (CBS 141. 41, GenBank AY249066; Identities = 493/513 (97 %), Gaps 2/513 (0 %)); and using the LSU sequence it is with the same strain of Cadophora luteo-olivacea (GenBank AY249081; Identities = 533/541  (98 %) , no gaps). Our ITS phylogenetic tree corroborated the placement of our isolate as a new species of the genus Cadophora, phylogenetically closely related to Cadophora luteo-olivacea. Yarrowia parophonii Gouliamova, R.
For full physiological test results see MycoBank MB819716. Typus. Bulgaria, from the gut of Parophonus hirsutulus (Carabidae), 9 Aug. 2009, D. Gouliamova (holotype D189, ex-type cultures NBIMCC 8889 = CBS 12427 preserved in metabolically inactive state, D1/ D2 domains of LSU rDNA and ITS (ITS1+2) sequences in GenBank JQ026370. 2, JQ026371. 2, MycoBank MB819716). Additional materials examined. Bulgaria, from the gut of Parophonus hirsutulus (Carabidae), 9 Aug. 2009, D. Gouliamova, 83Y (NBIMCC 8888 = CBS 12462), 25L (NBIMCC 8900 = CBS 12468), 30L (NBIMCC 8902 = CBS 12466), BH1 (NBIMCC 9804 = CBS 12471), KL1 (NBIMCC 8903 = CBS 12465) and 29L (NBIMCC 8901 = CBS 12441), LSU sequences GenBank KC810944, KY457253-KY457257; ITS sequences GenBank KC810951, KY457248-KY457252, respectively. Notes -The phylogenetic analysis of the combined ITS and LSU rDNA sequence alignment showed that the ex-type strain clusters with C.
5  (-5. 5 ) µm. Culture characteristics -Colonies on OA reaching 79 mm diam after 7 d at 25 ± 1 °C, flattened, white (M. 4A1); reverse white (M. 4A1). Colonies on MEA reaching 86 mm diam after 7 d at 25 ± 1 °C, floccose, brownish grey (M. 4D2) to dark grey (M. 4F1); reverse dark grey (M. 4F1). NaOH spot test negative. Crystals absent. Optimal temperature of sporulation and growth, 25 °C; minimum temperature of growth, 15 °C; maximum temperature of growth, 30 °C. Typus. Spain, Huelva, Almonte, road HF6245 from Los Cabezudos village to Los Bodegones village, from herbivorous dung, Mar. 2016, coll. C. González-García and G. Sisó, isol. N. Valenzuela-Lopez (holotype CBS H-23198, cultures ex-type FMR 15231 = CBS 143031, ITS, LSU, tef-1α and rpb2 sequences GenBank LT800501, LT800500, LT800503 and LT800502, MycoBank MB820451).
Notes -Coniella heterospora is characterised by the production of coppery-coloured conidia that are variable in shape. Based on a megablast search of NCBIs GenBank nucleotide database, the closest hit using the LSU sequence is C. fragariae CBS 183. 52 (GenBank KJ710442; Identities = 835/838 (99 %), no gaps). Closest hits using the ITS sequence are C. fragariae CBS 198. 82 (GenBank KJ710465; Identities = 600/601 (99 %), no gaps) and C. solicola CPC 17308 (GenBank KX833598; Identities = 589/591  (99 %) , no gaps). The closest hits using the rpb2 sequence are C. solicola CBS 114007 (GenBank KX833504; Identities = 756/767 (99 %), no gaps) and C. fragariae CBS 454. 68 (GenBank KX833477; Identities = 751/767  (98 %) , no gaps). The closest hits using the tef-1α sequence are C. solicola CPC 17308 (GenBank KX833702; Identities = 311/335 (93 %), gaps 4/335 (1 %)) and C.