dataesr/scientific-paragraphs-categorization huggingface dataset:
The spacecraft trajectory and attitude during the occultation are obtained with the help of SPICE kernels and ICY Toolkit  (Acton 1996). Important geometrical information is given in Table  1. The distance from the spacecraft to Titan, the integration duration, and the spacecraft velocity and attitude determine the vertical sampling of the atmosphere. Integration time is 1 s for all solar occultations analyzed here. The distance from the spacecraft to the center of Titan and from the spacecraft to the tangent altitude point range from 10 3 to 10 5 km (the tangent altitude is the shortest distance from the surface of Titan to the line of sight from the spacecraft to the Sun). As a consequence, the vertical sampling varies between approximately 1 km to about 5 km. In addition to the general steps in the UVIS data analysis described in the Cassini/UVIS User's Guide (LASP 2014) available through the NASA Planetary Data System (PDS), some particular procedures are necessary to analyze UVIS EUV solar occultations.
Data Corrections The most important corrections to the solar port data of the EUV channel are the background subtraction and, for observations with problematic pointing, the wavelength registration. These corrections were performed separately for each of the two spatial lines on the detector containing the solar image, after the onboard binning and before adding the signal in the lines. There are many sources of background. The Radio Thermal Generator background (henceforth BKG1) can be neglected. The present analysis accounts for contributions of photons coming from sources other than the Sun (BKG2), and from light dispersed by the grating (BKG3. 1) and by internal reflections (BKG3. 2). The contribution of BKG2 was estimated from observations made when all solar light is completely extinguished by atmospheric absorption (altitudes 300 km), giving for all occultations a negligible contribution at a rate of a few 10 -2 counts sec -1 pixel -1.
UVIS OCCULTATIONS ANALYZED We analyzed solar occultations through Titan's atmosphere measured with the UVIS/EUV channel that took place during flybys T10 through to T78. The data are available on the PDS database. Geographical and other ancillary information about the solar occultations analyzed in this work is presented in Table  1. When a range of values is given, the values are sorted by increasing time of observation. This final list merits some comments. In some cases an ingress occultation and an egress occultation were measured during the same flyby. This is the case of T10, T62 and T78. The ingress leg of T10 is unusable, the spacecraft was inside the atmosphere while the occultation took place and the light curves are not appropriate for the analysis. The egress leg of T10 will therefore be simply referred to as T10.
Number Density Variability In the context of the variability observed in Titan's thermosphere (see e. g. Magee et al. 2009; Snowden et al. 2013) , it is interesting to analyze the behavior of the number densities measured. The solar occultation data confirm the variability observed in the upper atmosphere by other instruments, and are consistent with the decrease in densities over time observed in the INMS data. Even for profiles derived from one flyby but different occultations (e. g. T78), the profiles are clearly different. Aiming at a quantitative analysis of variability, we concentrated on the number densities measured at 1250 km for N 2 and at 900 km and 1170 km for CH 4. Table  2  shows statistics for the number densities corresponding to the altitudes in the profiles closest to the altitudes mentioned above.
The high altitude value in the profile of methane from T62 egress , and the profile of nitrogen from the same flyby were not considered for the analysis of variability. The values in Table  2  indicate that the relative dispersion measured for nitrogen is more important than that measured for methane, and that the relative dispersion of methane sampled at low altitude is smaller than that sampled at high altitude. It has to be taken into account, however, that the different locations and times corresponding to the different observations are blended in this statistics. Figure  8  shows the number densities for the selected altitudes, plotted as a function of time. In both the CH 4 and the N 2 data sets there is an overall tendency of decreasing abundance with time. The steepest decrease as a function of time is that of the values sampled at 900 km in the CH 4 profiles.
It is worth noticing, however, that different locations are blended in this plot. A downward general trend of the N 2 densities during the Cassini mission has been observed by  Westlake et al. (2014). In they analysis of INMS data from the TA-T95 flybys the highest densities observed were measured during the TA and T5 encounters and the lowest densities observed late in the mission. Snowden et al. (2013) , in their analysis of INMS data from the T5-T71 flybys, observed that the median temperature in the upper atmosphere decreased after flyby T32, which took place in June 2007. This correlates with the decrease in N 2 densities in the present data set after T26, which took place in March 2007. Nevertheless, considering the limited sampling in the present work, the overlapping of uncertainties at high altitudes, and the oscillations in the density profiles, the trends described at the different altitudes should be interpreted with caution.
In Figure  10  we compare the profiles of methane and nitrogen derived from the UVIS/EUV-stellar occultation during T21, with those we derived from the UVIS/EUV-solar occultation during T26, which took place 88 Earth days later, and further south. Table  3  presents temporal and geographical information for the data in Figure  10. The UVIS/FUV-stellar methane profile from T21 falls below the UVIS/EUV-solar profile measured for T26, the FUV-stellar nitrogen profile from T21 is above the EUV-solar profile measured for T26. -25 - The optimal measurement conditions for INMS and UVIS are different so it is uncommon to have both type of measurements in the same flyby. However, INMS performed measurements of N 2 and CH 4 during flybys T26 and T58. The profiles from the inbound and outbound legs of these flybys are compared with the UVIS solar occultation results in Figure  10.
SUMMARY AND CONCLUSIONS We analyzed 8 UVIS/EUV-solar occultations by Titan's atmosphere, taking place between flybys T10 and T78, for which data are available in the PDS archive. We developed methods to correct the data from background contamination, and wavelength shifts due to pointing instabilities. In some cases, the wavelength re-calibration implemented permitted the analysis of observations that, without the corrections, would be useless for retrieving the atmospheric composition. From the solar occultations we retrieved the density profiles of CH 4 at altitudes of 850-1300 km, and density profiles of N 2 at altitudes of 1100-1600 km. The profiles include oscillations that might be indicative of atmospheric waves  (Koskinen et al. 2011; Snowden et al. 2013)  or, in case of small scale fluctuations, artifacts from the inversion procedure.
5 g; NaHCO 3 , 0. 5 g, glucose, 2 g and 100 g/L of NaCl. The pH was adjusted to 7. 5 with 10 M NaOH before autoclaving. Strain Vm-5 T (GenBank accession number HG931931) exhibited a 16S rRNA sequence identity of 97. 3% with Virgibacillus olivae strain E 30 8 T (NR043572), its phylogenetically closest bacterial species with standing in nomenclature (Fig. 1 ). Colonies were obtained on our homemade culture medium after 24 hours of incubation in aerobic conditions at 37°C. The colonies of strain Vm-5 T were circular, greyish, shiny and smooth, with a diameter of 2 to 5 mm. Cells stained Gram positive (Fig. 2 ). They were motile by polar flagella, were terminal spore forming and most commonly occurred as single cells or in pairs. Colonies were not haemolytic on bloodenriched agar. Strain Vm-5 T was mesophilic and grew at temperatures ranging from 15 to 45°C, at an optimum temperature of 37°C.
NMNI V. senegalensis strain SK-1 T (LK0211111) Halobacillus halophilus strain NBRC102448 T (AB681790) Gracilibacillus halotolerans strain NN T (AF036922) Antimicrobial susceptibility testing demonstrated that strain Vm-5 T was susceptible to penicillin, ampicillin, amoxicillin, ceftriaxone, imipenem, doxycycline, rifampicin, vancomycin, nitrofurantoin, erythromycin, ciprofloxacin and gentamicin but was resistant to trimethoprim/sulfamethoxazole and metronidazole. MALDI-TOF analysis MALDI-TOF protein analysis was used to analyse strain Vm-5 T. Briefly, a pipette tip was used to pick one isolated bacterial colony from a culture agar plate and spread it as a thin film on a MALDI-TOF target plate (Bruker Daltonics, Leipzig, Germany). Twelve distinct deposits were done for strain Vm-5 T from 12 isolated colonies.
proomii strain 10403186, V. pantothenticus strain DSM 26 T , V. halodenitrificans DSM 10037 T , Oceanobacillus massiliensis DSM 24644 T and O. jeddahmassiliense strain DSM 28586 T. The identification method included m/z from 3000 to 15 000 Da. For every spectrum, a maximum of 100 peaks were compared with spectra in database. The resulting score enabled the identification (or not) of tested species: a score of 2 with a validly published species enabled identification at the species level. No significant MALDI-TOF score was obtained (< 0. 9) for strain Vm-5 T against the Bruker database, suggesting that our isolate was not a member of a known species. We added the spectrum from strain Vm-5 T to our database (Fig. 4 ). Finally, the gel view showed the spectral differences with other members of the genus Virgibacillus (Figs.
Genome Sequencing Information Genome project history The V. massiliensis genome was sequenced as part of a culturomics study aiming at isolating all bacterial species colonizing the human gut  [1]  and because of its potential classification as a new species within the Virgibacillus genus. The genome from V. massiliensis strain Vm-5 T is the fourth genome of a Virgibacillus species and the first genome of V. massiliensis sp. nov. This genome consists of seven contigs and was deposited in Gen-Bank under accession numbers CCDP010000001 to CCDP010000007CCDP010000001CCDP010000002CCDP01 0000003CCDP010000004CCDP010000005CCDP010000006 CCDP010000007. Table  3  shows the project information. Growth conditions and genomic DNA preparation Virgibacillus massiliensis sp. nov. , strain Vm-5 T (CSUR P971 = DSM 28587), was grown on a homemade culture medium at 37°C in aerobic atmosphere.
The library profile was visualized on a High Sensitivity Bioanalyzer LabChip (Agilent Technologies). The libraries were normalized at 2 nM and pooled. After a denaturation step and dilution at 10 pM, the pool of libraries was loaded onto the reagent cartridge and then onto the instrument along with the flow cell. Automated cluster generation and sequencing run were performed in a single 42-hour run in a 2 × 251 bp. Total information of 4. 7 Gb was obtained from a 488K/mm 2 cluster density, with a cluster passing quality control filters of 97. 2% (9 590 000 clusters). Within this run, the index representation for V. massiliensis strain Vm-5 T was determined to be 11. 16%. Illumina reads where trimmed using Trimmomatic  [43] , then assembled through Spades software  [44, 45]. Contigs obtained were combined together by SSpace  [46]  and Opera software  [47]  helped by GapFiller  [48]  to reduce the set.
Genome properties The genome of V. massiliensis strain Vm-5 T contains 4 353 177 bp with a G + C content of 36. 87% (Fig. 6 , Table  4 ). One hundred twenty-five RNAs were detected, including five rRNAs (one 16S rRNA, one 23S rRNA, three 5S rRNA), 42 tRNAs and 78 miscellaneous RNAs. Overall, 4394 genes were identified, representing a coding capacity of 3 754 518 bp (coding percentage, 86. 25%). Among these genes, 322 (7. 33%) were identified as putative proteins and 1107 (25. 19%) were annotated as hypothetical proteins. Moreover, 4291 genes matched a least one sequence in the Clusters of Orthologous Groups (COGs) database  [58, 59]  with BLASTP default parameters. The properties and the statistics of the genome are summarized in Table  4. The distribution of genes into COGs functional categories is presented in Table  5.
Genome Comparison At the time of analysis, only four whole genome sequences of Virgibacillus were available at the National Center for Biotechnology Information. Therefore, whole genome comparison was done between V. massiliensis, V. alimentarius (GenBank accession number NZ_JFBD00000000), V. halodenitrificans (NZ_ALEF01 000000) and V. senegalensis (NZ_CCXU01000000) (Table  7 ). Among Virgibacillus genomes, that of V. massiliensis (4. 35 Mb) is the largest, followed by V. halodenitrificans (3. 92 Mb), V. senegalensis (3. 92) and V. alimentarius (3. 05 Mb). To estimate the mean level of nucleotide sequence similarity at the genome level between V. massiliensis and the other four Virgibacillus genomes, we calculated the average genomic identity of orthologous gene sequences (AGIOS) values using an in-lab pipeline named Marseille Average Genomic Identity (MAGi).
Briefly, this pipeline combines Proteinortho 4 software (with the following parameters: e-value 1e-05 , 30% of identity, 50% coverage and algebraic connectivity of 50%) for detecting orthologous proteins between genomes compared pairwise, then retrieves the corresponding gene nucleotide sequences and determines the mean percentage of nucleotide sequence identity among orthologous open reading frames using the Needleman-Wunsch global alignment algorithm  [5]. Similarity values at the genome level were also calculated using genome-to-genome distance (GGDC) calculator software  [60]. The number of orthologous genes is indicated in Table  7. The AGIOS and GGDC values obtained using the MAGi.
Strain Vm-5 T was susceptible to penicillin, ampicillin, amoxicillin, ceftriaxone, imipenem doxycycline, rifampicin, vancomycin, nitrofurantoin, erythromycin, ciprofloxacin and gentamicin but was resistant to trimethoprim/sulfamethoxazole and metronidazole. The percentage of G + C content of the genome is 36. 87%. The 16S rRNA and genome sequences are deposited in Gen-Bank under accession numbers HG931931 and CCDP010000001 to CCDP010000007, respectively. The habi tat of the microorganism is the human digestive tract. The type strain Vm-5 T (= CSUR P971 = DSM 28587) was isolated from the stool specimen of a healthy Amazonian boy.
39 Carbohydrate transport and metabolism E 371 8. 65 Amino acid transport and metabolism F 122 2. 84 Nucleotide transport and metabolism H 134 3. 12 Coenzyme transport and metabolism I 153 3. 57 Lipid transport and metabolism P 234 5. 45 Inorganic ion transport and metabolism Q 47 1. 1 Secondary metabolites biosynthesis, transport and catabolism R 510 11. 89 General function prediction only S 662 15. 43 Function unknown COGs, Clusters of Orthologous Groups database. a Total is based on total number of protein-coding genes in annotated genome.
This review article is intended to capture a broad crosssection of observation impact studies for regional applications, including studies using global, basin-scale and shelf-scale models and high-resolution observational databases. Applications include results from traditional Observing System Experiments (OSEs; e. g. Oke & Schiller, 2007) , traditional Observing System Simulation Experiments (OSSEs; e. g. Milles, 1990) , OSSEs with adaptive sampling  (Bishop et al. 2001) , the Representer Matrix spectrum (RMspec) using stochastic modelling (Le  Hénaff, 2009)  and observation footprints  (Oke & Sakov, 2012). Contributions from the GODAE community to observing system design and evaluation have been previously documented  (Oke et al. 2009 ). This review article provides an update on this community's contribution to regional observing system evaluation, under the auspices of GODAE Ocean-View, and is complemented by a companion paper describing global studies  (Oke et al.
18 psu; and the addition of the third altimeter (3ALT -2ALT) changes of temperature and salinity of up to 0. 8°C and 0. 14 psu. The difference between reanalysed SLA and observed SLA (including assimilated and unassimilated data) in each OSE is compared in Table  1 , showing the RMSD and correlation between reanalysed SLA and along-track SLA from Jason-1, Jason-2 and Envisat. Also shown in Table  1 , is the percentage improvement in the RMSD relative to the OSE that assimilates no altimeter data. These results show that assimilation of data from three altimeters Figure  1. Profiles of the 90th percentile of the RMSD for temp erature (left) and salinity (right) between OSEs performed using the Bluelink system using data from one and zero altimeters (1ALT 0ALT; blue), two and one altimeters (2ALT 1 ALT; green), three and two altimeters (3ALT 2ALT; red).
0 3. 1 3. 1 3. 3 Saral AltiKa (SA) 3. 4 3. 5 3. 6 3. 8 Cryosat 2 (C2) 3. 8 3. 9 3. 9 4. 1 J2+SA+C2 3. 5 3. 5 3. 6 3. 8 nolds SST analyses and correlation with AVISO SLA gridded data is calculated for each run. The results are presented in Table  3 , which also shows the mean RMSD for all T/S Argo data. A All does not attain the smallest RMSD and the highest SLA correlation, for reasons described above. However, considering the overall performance, the A All produced the best results. Assimilation in the A All OSE consistently reduces the RMSD of SST, T and S and increases the SLA correlation by more than 80%. It can be noted that the version of the REMO system used in this study is relatively immature, having only been recently developed. This is reflected in the results presented in Figure  3  and Table  3 , showing relatively poor performance compared to other systems (e.
Marine mammal T/S OSEs in the Southern Ocean Results from a series of near-real-time (NRT) OSEs using the FOAM system are described in the published literature  (Lea, 2012; Lea et al. 2013; Oke et al. 2015). Results presented here are from a series of more traditional OSEs, with a focus on the Southern Ocean and the region around the Kerguelen Plateau using the FOAM system  (Lea et al. 2013; Blockley et al. 2013). Briefly, this version of Global FOAM uses the NEMO ORCA025L75 ocean model coupled to the CICE sea-ice model. Data assimilation is performed using the NEMOVAR 3D-Var system with profile observations from EN3  (Ingleby & Huddleston, 2007)  as well as altimeter, SST and sea-ice data  (Blockley et al. 2013). Temperature and salinity profiles are obtained from instrumented marine mammals in NRT.
The mammals, mostly elephant seals, sample to depths of up to 2000 m in high latitude regions where there are very few other in situ observations. Two OSE integrations are performed using the UK Met Office's Global FOAM v12 system: SealTSwhere all mammal temperature and salinity profiles assimilated; and NoSealsno mammal data assimilated. Both experiments assimilated all of these observations, except the marine mammal profiles are withheld in the NoSeals OSE. The SealTS OSE assimilated 20,593 mammal profiles between 1 December 2010 and 31 December 2011, of which 13,579 were in the Southern Ocean. Table  4  and Figure  4  show observation minus model background (OmB) statistics for 2011. These statistics provide a measure of the forecast skill of the system, representing comparisons with observations immediately before assimilation.
2013 ). One option is to assimilate only the T data from the mammal database. To test this, a third OSE is performed to assimilate seal temperature profiles only. The SealT OSE is identical to SealTS, except all mammal salinity data is excluded from the assimilation. SealT statistics show improvements compared with the SealTS OSE (Table  4 ). In the Southern Ocean, temperature profile RMSD improvements increase from 4. 3 to 5. 5% using the all-profiles method (Table  4 ). A larger positive impact is found in the Kerguelen region, with an increase from 1. 8 to 5. 8% using the all-profiles method and sign reversal to show a modest benefit using the Argo-only method (-3. 4 to 0. 6%, Table  4 ). The SealT OSE has no impact on the global ocean salinity statistics but causes an improvement of around 2.
Glider OSSEs in the Ligurian Sea A series of OSSEs was performed for the Ligurian Sea (Western Mediterranean) to evaluate the impact of the assimilation of glider data on forecast ocean temperature. The impact of a cooperative-coordinated glider fleet flying in a triangular formation maintaining a 25 km distance between the platforms is compared to a cooperative-unaware fleet where the individual platforms can freely move in the domain. Both configurations were optimised to minimise the temperature error between the surface and 100 m depth in a 1. 8-km resolution regional simulation of the Ligurian Sea based on the ROMS  (Shchepetkin & McWilliams, 2005). Observations were simulated from a nature run provided by a reference ROMS simulation and assimilated in a slightly modified configuration of the model (a socalled fraternal twin-experiment) using an ensemble Kalman filter [EnKF;  Evensen (2003) ].
This paper also includes a demonstration of the benefits of adaptive sampling, where a carefully 'flown' fleet of gliders, or a high-resolution array of CTD measurements, can constrain the mesoscale variability in a high-resolution model. It is clear from this community paper, that forecast systems developed under GODAE and GODAE Ocean-View are maturing to the point where they can benefit from a range of different observation types in addition to the conventional data types that are associated with the GOOS. Different systems have been developed at global, regional and coastal scales. For each of these scales, different observing systems are used. That is, additional observations are assimilated in regional systems compared to global systems; and in coastal systems compared to regional systems.
The results presented in this paper demonstrate the positive impact of those regional datasets on ocean forecasts. Conclusions from this review include the following:. data from HF radars, gliders, instrumented mammals and airborne profiles contain independent information to the conventional observation platformsproviding additional constraints on systems that better resolve the mesoscale;. regional observation platforms may have limited impact globally, but very significant impacts locally reducing local errors by as much as 50%. It is recommended that global forecast systems assimilate regional data sets in addition to the those normally associated with the GOOS;. carefully designed regional in situ observation arrays (e. g. optimized glider fleets, or high-resolution XBT surveys) can add significant constraint to high-resolution modelswith up to 40% improvement;.
OSEval studies are sensitive to details of the underpinning systemsand can be used to identify strengths and weaknesses of data assimilation systems. It is recommended that the GOV OSEval-TT coordinate community OSSEs, as well as OSEs to further assess the GOOS as well as contributing to the assessment and improvement of the underpinning data assimilation systems;. the suite of tools available to routinely assess observing systems for operational and quasi-operational ocean forecast has expanded (e. g. RMspec; spectral analysis; adjoint sensitivities); and. the GOV OSEval-TT is well-placed to assess and improve the quality of OSEval experiments conducted by various groups. As well as show-casing a range of conventional and emerging techniques for assessing the impact of observations on the ocean models assimilating them, this paper demonstrates the value of regional observation platforms, such as HF radar, gliders and instrumented marine mammals.