dataesr/scientific-paragraphs-categorization huggingface dataset:
Strain Marseille-P2489 T was susceptible to amoxicillin (<0. 16 μg/mL), minocycline (<0. 16 μg/mL), penicillin G (0. 005 μg/ mL), imipenem (0. 004 μg/mL) and vancomycin (0. 293 μg/mL). The major fatty acid is 12-methyl-tridecanoic acid. The genome of strain Marseille-P2489 T is 4 863 528 bp long with 39. 45% G + C content. The 16S rRNA and genome sequences are available in the EMBL-EBI database under accession numbers LT223701 and FNLH00000000 respectively. The type strain Marseille-P2489 T (= CSUR P2489 = DSM 103460) was isolated from the stool of a healthy Nigerien girl. Its habitat is the human digestive tract. Description of Bacillus phocaeensis sp. nov. Bacillus phocaeensis (pho. cae. en 0 sis, L. masc. adj. phocaeensis, from Phocea, to refer to the city of Marseille, where the strain was isolated).
phocaeensis is able to ferment only D-glucose, D-fructose, salicin, D-cellobiose, D-maltose, D-lactose and inulin (Supplementary Table  S4 ). Strain SIT16 T was susceptible to amoxicillin (<0. 16 μg/mL), minocycline (<0. 16 μg/mL), penicillin G (0. 005 μg/mL), imipenem (0. 083 μg/mL) and vancomycin (0. 19 μg/mL). The major fatty acid is 13-methyl-tetradecanoic acid. The genome of strain SIT16 T is 4 561 140 bp long with 38. 3% G + C content. The 16S rRNA and genome sequences are available in the EMBL-EBI database under accession numbers LN881595 and FBXX00000000 respectively. The type strain SIT16 T (= CSUR P2184 = CCUG 69739) was isolated from the stool of a Senegalese boy with kwashiorkor. Its habitat is the human digestive tract.
11 4042 96. 31 3387 97. 10 4473 97. 73 4,63 96. 30 Total RNA genes 81 1. 89 155 3. 69 101 2. 90 104 2. 27 178 3. 70 Proteins with function prediction 3023 71. 81 2882 71. 30 2354 69. 50 3005 67. 18 3253 70. 26 Proteins assigned to COGs 2722 64. 66 2528 62. 54 2090 61. 71 2827 63. 20 2836 61. 25 Proteins with peptide signals 410 9. 74 416 10. 29 381 11. 25 503 11. 25 491 10. 60 No. of protein associated to ORFan 207 4. 92 164 4. 06 175 5. 17 160 3. 58 201 4. 34 Genes with transmembrane helices 912 21. 66 952 23. 55 790 23. 32 1139 25. 46 1151 24. 86 Genes associated with PKS or NRPS 12 0. 29 30 0. 74 9 0. 27 30 0. 67 14 0. 30 No. of antibiotic resistance genes 0 0 2 0. 05 0 0 0 0 6 0. 13 No. of genes associated with Pfam-A domains 3832 89 373 88 3088 88 4126 90 4248 88 COGs, Clusters of Orthologous Groups database; NRPS, nonribosomal peptide synthase; PKS, polyketide synthase.
29 209 4. 51 E Amino acid transport and metabolism 329 7. 81 301 7. 45 203 5. 99 300 6. 71 299 6. 46 F Nucleotide transport and metabolism 94 2. 23 79 1. 95 82 2. 42 104 2. 33 83 1. 79 H Coenzyme transport and metabolism 161 3. 82 131 3. 24 147 4. 34 161 3. 6 185 4 I Lipid transport and metabolism 147 3. 49 174 4. 3 101 2. 98 199 4. 45 145 3. 13 P Inorganic ion transport and metabolism 180 4. 28 150 3. 71 132 3. 9 191 4. 27 199 4. 3 Q Secondary metabolites biosynthesis, 84 2. 00 81 2 40 1. 18 98 2. 19 75 1. 62 transport and catabolism R General function prediction only 258 6. 13 236 5. 84 179 5. 28 285 6. 37 272 5. 87 S Function unknown 195 4. 63 184 4. 55 175 5. 17 223 4. 99 210 4. 54 - Not in COGs 1488 35. 34 1514 37. 46 1297 38. 29 1646 36. 8 1794 38. 75 COGs, Clusters of Orthologous Groups database.
However, as more data become available on deep-pelagic communities there are opportunities for new global biogeographic analyses to support these policy processes. Based on present knowledge and available biotic and abiotic datasets on deep-pelagic ecosystems, we here propose a biogeographical classification schema for the mesopelagic zone, with the explicit proviso that the sparsity and spatiotemporally biased nature of mesopelagic data are why expert maps are still required in under-sampled areas of the ocean. We present this as a 'current state of knowledge' framework against which future data/analyses can be used to: 1) refine boundary locations and dynamics as spatiotemporal information accumulates; 2) investigate these dynamics to better understand the mechanisms underlying pelagic boundaries; and 3) provide a guide to the regional scales over which the deep-pelagic ocean varies in terms of biodiversity and function, thereby informing global conservation efforts.
g. , light environment, permanent thermocline, diel vertical migration). The number of clusters was limited to 10 to avoid "over-splitting" the data at greater depths where there is lower variability in oceanographic parameters. The algorithm iteratively designated an arbitrary mean for each cluster and then assigned each 0. 5°gridcell from the CARS dataset to the cluster with the closest mean. A new cluster mean was calculated based on all the gridcells assigned to a given cluster. The process was repeated until the number of pixels migrating between iterations was small. The final clusters were mapped and displayed on a whiteboard for discussion by workshop participants. Existing water mass classifications (e. g. Talley et al. , 2011) , based largely on global-scale hydrographic programs such as the World Ocean Circulation Experiment Hydrographic Program, were referenced when interpreting the cluster results.
, 2010). Fasham and Foxton (1979) , in an analysis of pelagic decapod crustacean distribution in the eastern North Atlantic, did not detect this faunal boundary in their datasets. Hulley and Krefft (1985)  also questioned this subdivision based on results of the 1979-Sargasso Sea Expedition of the R/V Anton Dohrn, finding differences in species abundances rather than faunal composition. There is evidence of east/west regional differences within the Central North Atlantic, with some species restricted to one side or the other (e. g. , Maurolicus weitzmani in the western North Atlantic, Argyropelecus olfersi in the eastern). The Azores Front, a permanent southerly return branch of the Gulf Stream, has been reported as a biogeographic boundary separating Eastern and Western Atlantic Water  (Gould, 1985; Domanski, 1986) , though the effect is primarily on abundance and rank order versus presence/absence of species.
Discussion In this paper we have integrated new and previous efforts to develop a global biogeographical classification of the mesopelagial, designed to mesh with the epipelagic and deep-benthic classifications developed as parts of the GOODS biogeographic classification  (UNESCO, 2009; Spalding et al. , 2012; Watling et al. , 2013). In considering a biogeographic division of the global mesopelagial, given the data gaps we have listed, one may ask, "Why now, and why is this important?" The reasons are many, and relate to an increasing awareness of the important role of mesopelagic animals in the structure and function of the global ocean. Mesopelagic fishes dominate the world's total fish biomass and constitute a major component of the global carbon cycle. Gjøsaeter and Kawaguchi,1980  estimated their biomass at 1000 million tons, but acoustic surveys now suggest that mesopelagic fish biomass may be an order of magnitude higher  (Kaartvedt et al.
g. , lanternfishes and deep-sea smelts;  Sassa et al. , 2004). Thus, these diffuse and often asymmetrical biogeographical boundaries apply primarily to 'typical' assemblages, rarely to individual species. It is also clear, as more data on depth distributions of a range of taxa become available, that the depth ranges encompassed by epi-, meso-, and bathy-pelagic zone definitions are not borders, and species patterns vary with depth and taxa. Our understanding of how trends may change within the mesopelagial will no doubt evolve as more information is gathered on the deeper bathyal fauna. Developing genetic approaches also offer considerable promise for determining geographical relationships, and discovery of cryptic species (e. g. ,  Kulagin et al. , 2014).
These authors chose a ten-class acoustic model (36 provinces) as corresponding most closely to existing mesopelagic biogeography. In large areas of the Pacific and Indian Oceans the 36province model has many of the same features as the present scheme, but lack of data in the Atlantic Ocean, North Pacific and Northern Indian Ocean, along with their schema having no taxonomic component, limit its comparability with a global mesopelagic biogeography. Their acoustic schema, like our 33-ecoregion schema, revealed a biogeographic structure with more complexity than simple latitudinal banding patterns. Given the disparate methodologies used, the biogeographic patterns revealed by the two studies were similar in many regards, emphasizing the importance of surface ocean processes on deep-pelagic community structure.
Acknowledgements This research was made possible in part by The  Lenfest Ocean Program , who provided support for the workshop through a grant to Duke University: " Pelagic Conservation in the Open Ocean: Building the Science Case " and in part by a grant from  The Gulf of Mexico Research Initiative DEEPEND: GoMRI  No. SA15-21 ). Data used in summarizing the Gulf of Mexico are publicly available through the  Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC)  at https://data. gulfresearchinitiative. org (doi:  10. 7266/N7VX0DK2 ). The secretariats of GOBI and INDEEP helped organize the workshop. Daniel Dunn  was supported in part by the  NF-UBC Nereus Programme. Malcolm Clark  was supported in part by the  NIWA "Vulnerable Deep-Sea Communities" Project  (Contract  CO1X0906 ).
The former is defined by the Investopedia dictionary as a hypothetical nickname for the smaller companies that would have been formed if Microsoft had been broken up for violation of antitrust rules in 2000. These companies have never been formed, and the event itself is not topical any more, but the term is still listed in professional databases (e. g. , Investopedia and the financial dictionary at The Free Dictionary: http://financial-dictionary. thefreedictionary. com) and may potentially appear in economic press. According to the Investopedia dictionary, mini Madoff is used to denote financial con men who are accused of or have committed crimes similar to those of Bernard Madoff. The attribute mini implies that the runners of financial pyramid schemes are not as notorious as Bernard Madoff.
The following examples illustrate the types of texts used in training LSP translators that feature the application of various foregrounding techniques aimed at bringing some information into focus. The explosion of mind-boggling technological "tools" mushrooming from the global envelopment of the Internet into cellular telecommunications, powerful financial and investment software, wireless computing connectivity, and high-volume electronic data management. All were developed by techno-wizards with laudable intentions, but were promptly adapted by what came to be known as the "black hat" community of high-tech fraudsters, saboteurs, and terrorists. (Goldman, 2010, p. 5)  The excerpt from the text Fraud in the Markets: Why It Happens and How to Fight It by Peter Goldman is a good medium for practicing the translation of interdisciplinary popular LSP texts featuring the use of a variety of foregrounding techniques.
Online Health Communities as Platforms for Co-creation With their increasing interactivity, social media technologies provide an ideal platform to foster co-creation between the different stakeholders in health care  [14, 43]. Here, social media technologies refer to Web-based technologies that enable individuals around the globe to connect with each other to share and exchange information via virtual platforms, often also referred to as online communities or networks  [44]. Technologies for these Web-based communities include, among others, online message boards (forums), chat rooms, as well as an ever-expanding landscape of social networks such as Twitter, Facebook, YouTube, or Instagram  [45]. There is an extensive body of literature investigating the role of OHCs in the context of peer-to-peer support  [5, 46, 47] , with findings suggesting there is indeed an ongoing exchange taking place in OHCs, leading to the development of rich databases of experiential knowledge that individuals can draw on  [21].
Study Design As this study is explorative in nature, our aim was not to explain or proof but rather to provide a rich description of the phenomenon under investigation. We thus adopted a descriptive qualitative research design, following the consolidated criteria for reporting qualitative research guidelines (see Multimedia Appendix 1)  [58]. According to Braun and Clarke, descriptive qualitative work aims to "'give a voice' to a topic or a group of people, particularly those we know little about"  [59]. In line with this aim, the focus of our study was to give a voice to the community managers of existing online communities for people with disabilities to explore their views and experiences related to knowledge co-creation in their respective communities. Data were collected through semi-structured interviews with community managers.
Data Collection Data collection was carried out from October 2015 to June 2016. A total of nine semi-structured interviews (three email, five video-calling, and one face-to-face) were conducted with community managers of the remaining eight online communities (five spinal cord injury specific and three pan-disability). In one of the included OHCs, two moderators agreed to participate in the interview. All interviews were conducted by one author (JA), a female PhD student in health communication, trained in qualitative research methods with a particular research interest in patient participation. Informed consent was obtained from all participants. The semistructured interview guide was developed by the two authors and was not guided by a preexisting framework to allow for a certain degree of flexibility, enabling us to identify and follow up on participants' individual experiences.
Acknowledgments Funding for this study was provided by  Swiss Paraplegic Research. The authors would like to thank  Nicola Diviani  for his valuable comments on earlier versions of this manuscript and  Carly Toepke  for her comments and proofreading of the final manuscript. The authors would also like to thank all of the study participants for their time and their precious insights. Moreover, the authors would like to thank the reviewers and editor for their valuable comments and suggestions, which helped to significantly improve the quality of this paper.
[69] The motion of unbleached lipids in the membrane allows a recovery of fluorescence in the bleached ROI with kinetics that can be monitored and fitted with appropriate models. Lateral diffusion coefficients in the literature for pure PBut-b-PEO or pure POPC giant vesicles, were reported to be respectively D = 0. 22 and 9. 8 µm 2 s -1. [61] sing giant hybrid unilamellar vesicles presenting homogenous distribution of the lipid and polymer content at the microscale, it was shown that lipid lateral diffusion coefficient could be modulated by the lipid/polymer composition. We thus hypothesized that an asymmetric POPC/PButb-PEO membrane would give intermediate diffusion values closer to those observed in biological membranes which are around 1 µm 2 s -1. [70] We used confocal microscopy imaging (Figure  5a ) and the FRAP analyzer software to measure the diffusion coefficients of a DOPE-rhod probe inserted into the POPC outer monolayer of the aGHUV for different temperatures and different membrane types.
Samples (≈20 µL) were injected in a homemade chamber that was sealed to prevent evaporation. The laser outputs were controlled via the Acousto-Optical tunable filter and the two collection windows using the Acousto-Optical beam splitter and photomultipliers as follows: NBD was excited with an argon laser at 488 nm and DOPE-rhod was excited at 561 nm. The helium-neon laser at 633 nm (10 %) was used in transmission mode. Fluorescence Recovery after Photobleaching: FRAP was performed using the FRAP-Wizard of the LAS-AF microscope software which allowed to control and tune the scanning conditions: prebleach, photobleach, and postbleach phases. DOPE-rhod was excited and bleached with the 561 nm laser line and the emission was collected in the 600-700 nm range. ROIs were defined over the vesicles with a diameter of 3 µm.
The FRAP analyzer software was used for quantitative analysis of the FRAP data. After normalization (double normalization), the data were fitted with the circular spot model in 2D diffusion. It is important to note that the preparation method used to generate aGHUV, described below, allows the sedimentation of the vesicles in the bottom of the cover slip and perfect immobilization, obviously necessary for FRAP experiments. Preparation of Asymmetric Giant Hybrid Unilamellar Vesicles: Asymmetric giant hybrid unilamellar PBut 2. 5 -b-PEO 1. 3 -lipid vesicles (aGHUV) were prepared by a previously reported emulsion-centrifugation method. [58] Briefly, 5 µL of a sucrose solution (0. 3 m sucrose, 0. 01 m HEPES, 0. 15 m NaCl, pH 7. 4) was poured into 3 mg mL -1 PBut 2. 5 -b-PEO 1. 3 in 500 µL toluene.
Acknowledgements This work was funded by the  French Ministry of Research and Education  (fellow A. P. ) and the  Agence Nationale de la Recherche  ( ANR program  NO- SynthCell   N8 ANR-14-CE16-0015 ). Prof. Manuel Prieto  and  Dr. Fabio Fernandes  ( CQFM, IST Lisbon ) are gratefully acknowledged for valuable comments regarding quenching experiments.
Data and methods Targeted eddy surveys are logistically challenging. Eddy locations can be identified using real-time satellite SLA data. To further differentiate a positive SLA (indicative of anticyclonic-rotating eddies) into either an ACE or an ACME the SST anomaly across the eddy was additionally inspected, because ACMEs (ACEs) in the eastern tropical North Atlantic show a cold (warm) SST anomaly  (Schütte et al. , 2016a, b). For further evidence, Argo profile data were inspected to detect anomalously low temperature/salinity signatures also indicative of low oxygen ACMEs in the region  (Karstensen et al. , 2015; Schütte et al. , 2016b). In late December 2013 a candidate eddy was identified through this mechanism and in late January 2014 a pre-survey was initiated, making use of autonomous gliders.
Glider surveys Data from glider IFM12 and glider IFM13 were used in this study (Fig. 1 ). Glider IFM12 surveyed temperature, salinity, and oxygen to a depth of 500 m as well as chlorophyll a fluorescence and turbidity to 200 m depth. Glider IFM13 surveyed temperature, salinity, and oxygen to a depth of 700 m as well as chlorophyll a fluorescence and turbidity to 200 m depth. Glider IFM13 was also equipped with a nitrate sensor that sampled to 700 m depth. For one full eddy survey of glider IFM12 (Fig. 1 ) we combined data from 3 to 5 February and from 7 to 10 February 2014 because, due to technical problems, data were not recorded in between these periods. Glider IFM13 surveyed one full eddy section from 3 to 7 April 2014. All glider data were internally recorded as a time series along the flight path, while for the analysis the data were linearly interpolated onto a regular pressure grid of 1 dbar resolution.
As there remained some spurious difference between down and up profiles we averaged upcast and downcast profiles to further minimize the slow sensor response problem in high gradient regions, particularly at the mixed layer base. The optical (Wetlabs ECO-PUC) chlorophyll a fluorescence and turbidity data were not calibrated against bottle samples; only the factory calibration is applied. We subtracted a dark (black tape on sensor) offset value and the data are given here in relative units. The nitrate (NO - 3 ) measurements on glider IFM13 were collected using a Satlantic Deep SUNA sensor. The SUNA emits light pulses and measures spectra in the ultraviolet range of the electromagnetic spectrum. It derives the NO - 3 concentration from the concentration-dependent absorption over a 1 cm long path through the sampled seawater.
During the descents of the glider the sensor was programmed to collect bursts of five measurements every 20 s or about every 4 m in the upper 200 m and every 100 s or about every 20 m below 200 m. The sensor had been factory calibrated 8 months prior to the deployment. The spectral measurements of the SUNA were post-processed using Satlantic's SUNACom software, which implements a temperature and salinity dependent correction to the absorption  (Sakamoto et al. , 2009). The SUNA sensors' light source is subject to aging which results in an offset NO - 3 concentration  (Johnson et al. , 2013). To determine the resulting offset, NO - 3 concentrations measured on bottle samples by the standard wet-chemical method were compared against the SUNA-based concentrations. The glider recorded profiles close to the CVOO mooring observatory (see  Fiedler et al.
5 µmol kg -1. All temperature and salinity data are reported in reference to  TEOS-10 (IOC et al. , 2010)  and as such we report absolute salinity (S A ) and conservative temperature ( ). Calculations of relevant properties (e. g. buoyancy frequency, oxygen saturation) were done using the TEOS-10 MATLAB toolbox  (McDougall and Barker, 2011). We came across one problem related to the TEOS-10 thermodynamic framework when applied to isolated eddies. Because the eddies transfer properties nearly unaltered over large distances the application of a regional (observing location) correction for the determination of the S A  (McDougall et al. , 2012)  seems questionable. In the case of the surveyed eddy the impact was tested by applying the ion composition correction from 17 • W (eddy origin) and compared with the correction at the observational position, more than 700 km to the west, and a salinity difference of a little less than 0.
Ship survey Data from two ship surveys have been used, surveying about 6 weeks after the first glider survey (and 3 weeks before the last glider survey) on the same eddy (Fig. 1 ): R/V Islandia cruise ISL_00314 performed sampling between 5 and 7 March 2014 and R/V Meteor cruise M105 sampled on 18 and 19 March 2014. From M105 we make use of the CTD data and the water current data recorded with a vessel mounted 75 kHz Teledyne RDI acoustic Doppler current profiler (ADCP). The data were recorded in 8 m depth cells and standard processing routines were applied to remove the ship speed and correct the transducer alignment in the ship's hull. The final data were averaged in 15 min intervals. Only data recorded during steaming (defined as a ship speed larger than 6 kn) are used for evaluating the current structure of the eddy.
Acknowledgements. We thank the authorities of  Cape Verde  for the permission to work in their territorial waters. We acknowledge the support of the captains and crews of  R/V Islandia  (glider survey support) and  R/V Meteor. We thank  Tim Fischer  for processing the M105 ADCP data as well as  Marcus Dengler  and  Antony Bosse  for fruitful discussions. The critical comments from two reviewers and the comments as well as support from the guest editor are very much appreciated. Financial support for this study was provided by a grant from  Cluster of Excellence "The Future Ocean " to  J. Karstensen ,  A. Körtzinger ,  C. R. Löscher , and  H. Hauss. Glider data analysis was supported by the  DFG Collaborative Research Centre 754  (http://www. sfb754. de). B. Fiedler was funded by  German Ministry for Education and Research (BMBF)  project  SOPRAN  (grant no.
03F0662A ). F. Schütte and P. Testor were supported by the AWA trilateral project supported by  BMBF  (grant no. 01DG12073E ). Analysis was supported by the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement no. 633211  (AtlantOS). Edited by:  D. Gilbert Reviewed  by: two anonymous referees.