dataesr/scientific-paragraphs-categorization huggingface dataset:
5 For that, four oceanographic vessels and different autonomous platforms measured properties near the air-sea interface and acquired thousands of upper-ocean (400-2000 m) profiles. However, each device had its own observing capability, varying from deep measurements acquired during vessel stations to shipboard underway near-surface observations and measurements from autonomous and uncrewed systems (such as Saildrones). These observations were undertaken with a specific sampling strategy guided by near-real time satellite images and adapted every half day based on the process that was investigated. These 10 processes were characterized by different spatio-temporal scales: from mesoscale eddies, with diameters exceeding 100 km, to submesoscale filaments of 1 km width. This article describes the data sets gathered from the different devices and how the data were calibrated and validated, in order to ensure an overall consistency, the platforms' datasets are cross-validated using a hierarchy of instruments defined by their own specificity and calibration procedures.
g. , in lab and in reference to standard or reference material). As introduced in for example  Wong et al. (2003) , by comparing with all nearby profile data and considering distance in space and time as a measure for impact, the offset, and drift behaviors of specific float measurements can be reconstructed. The goal is to perform a quality assessment of a dataset, which in turn is composed of individual datasets from different observations platforms and sensors. For this purpose, we introduce here an assessment scheme of the individual datasets based on their traceability to reference data (traceability level). In the most optimal case, the reference material (RM) is a defacto standard  (Otosaka et al. , 2020) , such as standard seawater for salinity, oxygen titration for dissolved oxygen, or triple point cells for temperature.
As an example, for salinity the RM is Standard Seawater (SSW), giving a hierarchy as follows: SSW is assigned traceability level 0 and is used to reference a salinometer  (Bacon et al. , 2007)  (traceability level 1). The salinometer readings for bottle samples are used as a statistical basis for the ship's CTD salinity correction (traceability level 2). The corrected ship CTD salinity is then further used to correct the TSG (traceability level 3). Bottle samples were also collected for the TSG and used via the salinometer as a statistical basis for the ship's CTD salinity correction (traceability level 2). The TSG is used to correct the MVP data (traceability level 4 or level 3, depending on the TSG calibration). Similar hierarchies can be built for all sensors. Part of the Quality Assurance of the combined dataset is determining accuracy and precision, and also considering in this process the expected stability of the sensors given by the manufacturer.
Calibration strategy The EUREC 4 A-OA experiment relied on numerous devices to measure physical and chemical properties of the water column from the three European ships and the various autonomous platforms deployed from the ships. We also include here the five US Saildrones funded under the NOAA and NASA ATOMIC project  (Quinn et al. , 2021; Gentemann et al. , 2020). Their deployments were conducted by scientific staff originating from two institutions: GEOMAR (Kiel, Germany) and IFREMER (Brest, France). They have specific practices, sometimes leading to different procedures of deployment, data acquisition and calibration, while still complying to international standards  (Sloyan et al. , 2019). The various calibration practices are either linked to similar devices from different manufacturers, or to various procedures in laboratories before and after the cruise.
For the purpose of degassing, the bottles were heated in a water bath to 5-10°C above laboratory temperature and then brought back to laboratory temperature. The released gas was extracted. Only then were the samples analyzed. More information on the CTDs and salinometers can be found in the cruise reports  (Karstensen et al. , 2020; Branellec et al. , 2020). The salinity data from bottle samples of the R/Vs Maria S. Merian and L'Atalante is considered level 2 traceability. The processing of CTD conductivity was done by first applying basic processing steps from the SBE processing routines (Seasoft V2) and including loop edit (0. 2 m sec). The prepared raw data was then calibrated using the bottle sample analysis. Slightly different approaches were taken for the R/Vs Maria S. Merian and L'Atalante.
The R/V Meteor did not have a salinometer on board. Samples were taken for later analysis on shore, but the analysis could not be done. Some CTD profiles from the R/Vs Maria S. Merian and Meteor were performed close in space and time and covered the full water column. They are used here for the purpose of the R/V Meteor CTD salinity sensor calibration and https://doi. org/10. 5194/essd-2022-402 Preprint. Discussion started: 9 December 2022 c Author(s) 2022. CC BY 4. 0 License. validation. Thus, the R/V Meteor salinity data is considered level 3 traceability. For the R/V Maria S. Merian, the processing was as follows: after allocating a downcast profile segment to the upcast bottle sample stop via a vertical gradient criterion, the conductivity difference between bottle sample analysis and CTD sensor recording was calculated.
Dissolved Oxygen Two SBE43 dissolved oxygen sensors were used for a range of measurements from 0 to 120% of the surface saturation. The accuracy from the manufacturer is 2% of the saturation. The sensor showing the more stable measurements was kept for data reduction. Pre-and post-cruise lab calibrations were carried out on the sensors in laboratories in the same way as the temperature and conductivity sensors. As for conductivity, water samples were collected in bottles for calibration of the sensor measurements. The dissolved oxygen concentrations in the water samples were estimated using Winkler titration  (Winkler, 1888). The chemistry reports for the different R/Vs describe the operating modes for the R/V L'Atalante  (Branellec et al. , 2020)  and R/V Maria S. Merian  (Karstensen et al.
Intercalibration of CTD data -the effect of oceanic variability For all three ships, the acquisition of temperature, salinity, and dissolved oxygen data are performed with sensors that have similar accuracy and resolution. The calibration and validation of these quantities, performed by either IFREMER or GEOMAR, are in agreement with international recommendations from GO-SHIP. There are two main differences between the methodologies of deployment: for IFREMER, the first measurements started at a depth of 5 meters, while for GEOMAR they started at around 1. 5 meters. For IFREMER, the upward movement of the CTD package was stopped for 30 seconds before closing the Niskin bottles, while for GEOMAR they were closed underway. To assess any discrepancies, a calibration of the raw measurements from the R/V L'Atalante CTD were performed with the GEOMAR procedures.
Again, there are two notable differences in terms of calibration: First, the positioning of the CTD station was different between the methods. Second, the GEOMAR toolbox calibrates all the profiles together, while it was chosen to use the IFREMER toolbox to perform piecewise calibration on 5 to 6 profiles at a time. Excluding the interpolated surface layer, these different approaches showed no major differences in terms of temperature and salinity. For dissolved oxygen, the different calibration procedures can lead to differences of up 5µmol/kg. In general, at each isopycnal level, the differences between two profiles with small temporal and spatial separations can be linked to two sources: different calibration procedure and the internal ocean variability. As the IFREMER and GEOMAR CTDs calibration procedures provide similar if not equal results, the remaining differences between the various datasets must be due primarily to ocean variability.
However, the creation of an assembled dataset gathering all profiles requires a comparison of these arrays. Figure  5  displays the vertically averaged differ-295 ences for each parameter, removing the first 50 m to avoid taking into account the surface oceanic variability. The left column shows these differences for profiles performed by the same R/V as a function of both time and distance, also represented by the blue and red curves on the right panels. These curves exhibit the oceanic variability plus the post-calibration uncertainty; for near-by CTD pairs, they tend towards this last value. The central column of Figure  5  represents the difference calculated with one CTD profiles from each R/V, synthesized by the green curves on the right panels. This curve is the result of both oceanic 300 variability and uncertainty linked to the differences of deployment and calibration between each R/V and laboratory.
Underway CTD (uCTD) An Ocean Science underway CTD system was used on the R/Vs L'Atalante and Maria S. Merian. The uCTD consists of a small winch system mounted on the bulwark of the ship and a CTD probe measuring temperature, conductivity, and pressure  (Rudnick and Klinke, 2007). The probes sample at 16 Hz and data is recorded internally and read out onboard via a Bluetooth connection. This probe is designed to record data during descent, and the deployment procedure minimizes the influence of surface waves. The uCTD can be used in "free-cast" and "tow-yo" (or free fall) modes, depending on whether a winding line is either spooled or not onto the tail. In the first case, the probe descent is decoupled from the winch spool friction, keeping a rather steady descent rate of about 4 dbar/s. In the second mode, the probe fall rate is determined by the idle friction of the spool and the probe friction, and descent may vary between 3.
No direct or lab calibration was done with the glider CTD sensors; instead, data calibration was performed through comparison with nearby (time, space) CTD stations. To ease comparison we group all three UEA Seaglider, the IFM gliders, and 470 the Kraken (Figure  14  above and middle line panels). The number of close-by pairs of CTD and glider profiles is quite low for the Kraken. Nevertheless, the mean differences for pairs of profiles found closer than 30 km are less than 30 km are below 2 10 -2 °C, and 1 10 -2 psu. The IFM gliders tend to constant positive bias in temperature and salinity compared to the near-by CTD stations, with a low standard deviation despite having a higher number of pairs of profiles. Within the first 15 km the uncertainty is on the order of 8 10 -2 °C, and 3 10 -2 psu.
Data availability The underlying primary CTD and TSG datasets, used in this study for comparison with other devices, are available for each R/V on the AERIS website (https://observations. ipsl. fr/aeris/eurec4a/#/). Additionally, for the R/V L'Atalante, the CTD measurements can be retrieved on the Seanoe website (https://doi. org/10. 17882/79096) (Speich et al. , 2021). Calibrated TSG measurements for the R/Vs Maria S. Merian and Meteor are available on the Pangea website under the cruise names of MSM89 (https://doi. pangaea. de/10. 1594/PANGAEA. 951515) and M161 (https://doi. pangaea. de/10. 1594/PANGAEA. 951515) respectively  (Karstensen et al. , 2020; Mohr et al. , 2020). After the secondary data quality control process was applied, the various data sets were interpolated to the same vertical pressure grid with a 0.
5 dbar resolution. This was done for temperature, salinity, and dissolved oxygen data and, when available, horizontal ocean currents. For each device, a NetCDF file is available for download on the Seanoe website, organized by type of device and ship, with its own DOI. The naming of the variables and parameters follows the convention of the NetCDF Climate and Forecast (CF) Metadata Conventions  Eaton et al. (2003). The secondary quality control uCTD and MVP profiles can be found on the Seanoe website (https://doi. org/10. 17882/91352 and https://doi. org/10. 17882/91485 respectively). Additionally, the concatenated sections described in the previous section, composed of CTD, secondary quality control uCTD and MVP profiles, and S-ADCP measurements from the R/Vs L'Atalante and Maria S. Merian can be accessed on the Seanoe website (https://doi.
org/10. 17882/92071). Measurements from the autonomous devices, Saildrones, underwater gliders and drifters can also be retrieved from the AERIS website (https://observations. ipsl. fr/aeris/eurec4a/#/). Furthermore, the UEA gliders measurements are available on the British Oceanographic Data Center website (doi:10. 5285/c596cdd7-c709-461a-e053-6c86abc0c127). Data from the Argo floats are available on the Coriolis website (https://dataselection. coriolis. eu. org/). Table  1  summarizes the different links and DOIs to access these various datasets. The oceanic instruments deployed during the EUREC 4 A-OA experiment provide a large set of observations characterized by different oceanic structures, including mesoscale eddies intensified at the surface or at depth, finer scale filaments, and salinity barrier layers.
Acknowledgements. This research has been supported by the people and government of Barbados; by the  European Research Council (ERC)  advanced grant  EUREC4A  (grant agreement no. 694768 ) under the European Union's  Horizon 2020 research and innovation program  ( H2020 ), with additional support from  CNES  (the  French National Center for Space Studies)  through the  TOSCA SMOS-Ocean, TOEddies , and EUREC4A-OA proposals, the  French national program LEFE INSU, IFREMER , the  French research fleet , the French research infrastructures AERIS and ODATIS, IPSL, the  EUREC4A-OA JPI Ocean and Climate program , the  Chaire Chanel program  of the  Geosciences Department at ENS, Météo-France , by the  Max Planck Society  and its supporting members and by the  German Research Foundation (DFG)  and the  German Federal Ministry of Education and Research  (grant nos.
This is probably due to the fact that in addition to the limited spectral data reported in the literature, no entry for 2-azabutadiene is available in the widely used CDMS database  29, 30  or in the JPL catalog. 31 n this respect, here, we report a refined analysis of the rotational spectrum of 2-azabutadiene based on new rotational transitions recorded between 225 and 330 GHz. The experimental work has been supported by high-level quantum-chemical calculations, which guided us through the spectral interpretation and provided a good reference set of spectroscopic parameters. This manuscript is organized as follows. In the next two sections, quantum-chemical computations and experimental details are discussed. Then, the results on 2-azabutadiene are presented in the fourth section, while a comparison with other dienes is discussed in the last section.
Interatomic Interaction Potential for α-quartz We perform the simulations using the molecular dynamics package LAMMPS  (Plimpton, 1995) , using the Vashishta potential. The 1997-version of the potential  (Broughton et al. , 1997)  is optimized toward the material properties of crystalline α-quartz and it is a modified version of the  Nakano et al. (1994)  three-body potential, which was modified from the original version of the potential  (Vashishta et al. , 1990). Tables  S1  and S2  in Supporting Information S1 display the parameters used in the simulations. To ensure that the simulated material has properties similar to α-quartz within the pressure and temperature range of our simulations, we have calculated the elastic parameters, density, and the compressibility parameters of the lattice along different crystalline directions (see Figures S2-S4 in Supporting Information S1) and found that it is in agreement with experimental measurements (e.
Acknowledgments We thank  Fabian Barras  and  Jessica McBeck  for useful and constructive suggestions on an early version of the manuscript. This work was funded by the  Research Council of Norway  (project History Dependent Friction 287084 to AMS) and the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (Grant  101019628 BREAK  to FR).
S1B ). Purified MVs were then visualized by transmission electron microscopy (TEM) to determine their size distribution and to rule out bacterial contamination of the purified sample (Fig. S1D  and E ). The size of the MVs was measured using ImageJ software, and a normal size distribution with mean sizes of 103 and 100 nm, respectively, was observed under the two conditions, with and without bismuth treatment (Fig. 1C ). However, the global size distributions of MVs from the two populations were slightly different: untreated samples exhibited a slightly wider size distribution and were more heterogeneous, with diameters ranging from 20 nm to 240 nm (Fig. 1C ). In contrast, MVs purified from bismuthtreated samples displayed a slightly more homogeneous size distribution, ranging from 40 nm to 210 nm.
(C) Size distribution of MVs purified from control and bismuth-treated H. pylori cells. MV diameter was measured with the ImageJ software using TEM images of a total of 600 MVs for each condition, and the Gaussian equation was fitted to the histogram data to obtain a frequency distribution plot. The nonparametric Kolmogorov-Smirnov test shows statistically significant differences between the two distributions (P = 0. 006). (D) Volcano plot representing the differential abundance of proteins purified from MVs from bismuth-treated H. pylori cells and from control bacteria. The x axis shows the bismuth/control fold change value in logarithmic scale. The y axis shows the 2log 10 of the adjusted P value showing statistical significance. The horizontal dashed line corresponds to a P of 0. 01 used as the threshold cutoff.
The resulting pellet was finally vacuum dried and processed for ICP-OES analysis. Purified MVs were stored at 220°C. The quality of the preparation and the absence of contaminating bacteria were validated by TEM (Fig. S1D  and E ). The MV purification yields (particles/mL culture) were measured by NanoSight tracking analysis and were similar for the two conditions, i. e. , with and without bismuth. DLS of purified MVs. Dynamic light scattering (DLS) analysis was performed on purified MVs using a DynaPro plate reader (Wyatt, Santa Barbara, CA). Data were recorded at 20°C with 20 acquisitions, each lasting 10 s. Three sets of data were acquired for each sample with two independent biological replicates. Particle size determination was done using Dynamics V7 software (Wyatt). The intensity-weighed distribution of vesicles was plotted against diameter size.
5. 3. 8 against the Helicobacter pylori G27 UniProt reference proteome database (1,501 entries) concatenated with the usual known MS contaminants and reversed sequences of all entries. Andromeda searches were performed with trypsin chosen as a specific enzyme with a maximum number of 4 missed cleavages. Possible modifications included carbamidomethylation (Cys, fixed), oxidation (Met, variable), and N-terminal acetylation (variable). The mass tolerance in MS was set to 20 ppm for the first search and then 6 ppm for the main search and 10 ppm for the tandem MS (MS/MS). The maximum peptide charge was set to 7, and five amino acids were required as the minimum peptide length. The maximum peptide mass was increase to 8,000 Da. The "match between runs" feature was applied between replicates with a maximal retention time window of 0.
7 min. One peptide unique to the protein group was required for the protein identification. A false discovery rate (FDR) cutoff of 1% was applied at the peptide and protein levels. The MaxLFQ, i. e. , Maxquant's label-free quantification, algorithm was used to calculate protein intensity profiles across samples. The iBAQ feature was selected for further quantitative analysis (see Data Set S1 in the supplemental material). The MS proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository under the data set identifier PXD028509. Statistical analysis of proteomics data. For the differential analyses, proteins identified in the reverse and contaminant databases and proteins "only identified by site" were first discarded from the list of identified proteins.
Then, proteins exhibiting fewer than two quantified values in at least one condition were discarded from the list. After log 2 transformation of the protein intensity values, these values were normalized by median centering within conditions (wrapper. normalizeD function of the R package DAPAR  [59] ). The remaining proteins without any intensity value in one of the two conditions have been considered proteins quantitatively present in a condition and absent in another. They have therefore been set aside and considered differentially abundant proteins. Next, missing values were imputed using the impute. mle function of the R package imp4p  (60). Proteins with a fold change of less than 2 have been considered not significantly differentially abundant. Statistical testing of the remaining proteins (with a fold change greater than 2) was conducted using a limma t test from the R package limma.
An adaptive Benjamini-Hochberg procedure was applied to the resulting P values using the function adjust. p of R package cp4p  (61). The proteins associated with an adjusted P value inferior to an FDR threshold of 1% have been considered significantly differentially abundant proteins. The proteins of interest are therefore those which emerge from this statistical analysis supplemented by those which are considered to be absent from one condition and present in another (Data Set S1). Functional analysis of the proteins of interest identified by proteomics. The identified proteins of H. pylori strain G27 were mapped to proteins of other strains (strain ATCC 700392, 26695, or P12) if they shared at least 90% of the same amino acid sequences, in order to infer additional annotations (GO terms and KEGG pathways) (Data Sets S1 and S2).
From these annotations, an overrepresentation analysis was performed using hypergeometric tests to assess the overrepresentation hypothesis for each GO term/KEGG pathway using R software. All the proteins identified by MS were used as background for the hypergeometric tests. A significantly low enrichment P value means that the proportion of proteins related to a GO-term/KEGG pathway is significantly superior in the considered list than in this background. The protein-protein interaction network of the proteins found to be significantly more abundant in "bismuth" samples than in "control" samples was determined from STRING v11 (62) and visualized using Cytoscape v3. 8. 0  (63)  with the plugins (Cytoscape) stringApp and Omics Visualizer  (64). The widths of the edges correspond to the combined score from STRING, reflecting the confidence placed in each interaction.
The bismuth content was measured by ICP-OES with an Agilent 720 series with axially viewed plasma and with a Bi calibration curve of 10 to 1,000 ppb at the Institut Lavoisier de Versailles. The content of Bi was determined using a standard curve prepared by calibrating the machine with certified ICP-grade Bi standards. The amount of bismuth was determined by measuring the emission wavelength at three wavelengths (222. 828, 223. 061, and 306. 771 nm). The measurement of each strain under each condition was performed in at least three biological duplicates. Data were measured in two technical replicates for each sample. The results are presented as the percentage of the ratio of bismuth mass versus total sample mass used for the analysis. TEM analysis of purified membrane vesicles. Purified MVs (10 mL) were allowed to adhere to alcian blue-treated (1%) (Sigma-Aldrich) 300-mesh Formvar-Cu-coated grids (Electron Microscopy Science) for 15 min.