dataesr/scientific-paragraphs-categorization huggingface dataset:
Ferrybox. From temperature and salinity to carbonate system A Ferrybox system operated for the first time in the Mediterranean, on the route connecting the ports of Piraeus (Athens) and Heraklion (Fig. 1 ), for one year between 2003 and 2004 within the framework of the EU-15 funded project Ferry-Box  (Nittis et al. , 2006). This fully automated, flow-through system included sensors for underway measurement of temperature, salinity, fluorescence and turbidity. High frequency measurements took place every night, and the data were delivered in Near Real Time (NRT). The system was reactivated in 2012 and operates since then (with a gap from late 2014 to mid 2017), with an upgrade of the components, that now include O 2 , CO 2 and pH sensors. The FB has been proven a helpful tool in the study of water circulation (e.
Personnel. From separate specialists to multitask collaborators 25 Specialized personnel is the major component for a smooth, continuous functioning of any multiplatformmultidisciplinary observatory. Since its beginning, POSEIDON invested in the necessary human resources, namely a dedicated group of scientists and engineers that operate, maintain and upgrade the system on a full-time basis. Over the last years as the number and complexity of platforms significantly grow and as the inflow of data increased, the knowledge level of personnel became more demanding. Balancing these demands with personnel 30 shortage, due to budgetary constraints, led not only technicians but also scientists to have multifunctional duties that "…may involve aspects of a bosun, chemical safety officer, satellite communications specialist, network administrator and electronics technicians" (NRC, 2011).
Biogeochemical Modelling Forecasting tools are centrally placed in the POSEIDON system, with a number of state-of-the-art weather, wind waves, ocean circulation and marine ecosystem numerical models, initialization and data assimilation schemes providing 5-days ahead information on daily basis regarding the atmospheric  (Papadopoulos et. al. , 2002) , sea state  (Korres et. , 2011)  and hydrodynamic conditions  (Korres et al. , 2010)  in the Aegean/Ionian Seas 20 and in the Mediterranean. Currently, the POSEIDON modelling group is providing the wave forecasting products of the Copernicus Marine Environment Monitoring Service (CMEMS) for the Mediterranean Sea in the framework of MED-MFC. The POSEIDON ecosystem simulation tool is one of the first developed in the Mediterranean, producing daily forecasts for a range of ecosystem parameters for the whole basin.
, 2013; Tsiaras et al. , 2017)  or for the assimilation algorithms of sea colour data in BGC models  (Kalaroni et al. , 2016). Ocean Sci. Discuss. , https://doi. org/10. 5194/os-2018-3 Manuscript under review for journal Ocean Sci. Discussion started: 6 February 2018 c Author(s) 2018. CC BY 4. 0 License.
Connection with European and international observatories 25 A regional observatory can reach a higher potential when it belongs to a wide network of observatories  (Ruhl et al. , 2011). Ocean observation at global scale is implemented through the international program GOOS (Global Ocean Observing System) executed by the Intergovernmental Oceanographic Commission (IOC) under the auspices of UNESCO (www. ioc-goos. org/), aiming to inform scientists, policymakers and society  (Karl, 2010). GOOS is a global network of ships, buoys (fixed and drifting), subsurface floats, tide gauges and satellites that 30 collect real time data on the physical state as well as the biogeochemical profile of the world's oceans for three component (including coastal buoy and Ferrybox) in the framework of JERICO-NEXT project in an attempt to characterize the timing, intensity, and fate of organic matter and the coupling of offshore with coastal processes.
HCMR has therefore invested to grow up its capabilities (e. g. new winch allowing casts much deeper than 1000 m -Fig. 8 ). 35  Ocean Sci. Discuss. , https://doi. org/10. 5194/os-2018-3 Manuscript under review for journal Ocean Sci. Discussion started: 6 February 2018 c Author(s) 2018. CC BY 4. 0 License. During the R/V visits in the area of the fixed biochemical platforms the order of sampling is always CTD-Niskin bottle casts followed by net tows. The vast majority of casts and net tows (>80% after 2010) were made between 09h00 and 14h00 (local time). The order of sampling, the sampling procedure and storing protocols follow the international recommendations described by  Lorenzoni and Benway (2013)  and remain consistent since 2010, with recording of cruise metadata (Cruise Summary Reports available at www.
seadatanet. org). Adaptations 5 of certain protocols have been made in certain cases, considering the open ocean oligotrophic conditions of the area. For example, zooplankton sampling was initially made with a single 200 µm mesh size net but soon it was changed into parallel two mesh-size nets (45 µm mesh size and 200 µm mesh size) tows. This was done due to the small size organisms found in the area, since combined data from several nets allows for a better estimation of the mesozooplankton biomass  (Frangoulis et al. , 2016). In all cases, when a new method was introduced, a 10 minimum one-year period of sampling-analysis using both old and new methods was applied, before moving exclusively to the new method (e. g. Chl-a by fluorescence and by HPLC where measured in parallel during 3 consecutive years).
Derived biochemical-ecosystem parameters and model state variables Any necessary unit conversion of physical and chemical oceanographic data for model validation, is 15 generally straightforward. However, many biological parameters expressed in biomass units are usually derived from the initial data with some conversion factor assumed. These conversions introduce biases that have to be carefully considered by biologists and modellers  (Flynn, 2005; Frangoulis et al. , 2010; Tsiaras et al. , 2017). In the case of the Cretan Sea biochemical-ecosystem model, the choice of appropriate conversion factors from literature, that can be considered, is made by the data providers (biologists) in communication with modellers and is revised 20 regularly. Besides units' conversion, a provider-modeller communication is mandatory as the numerous measured biological parameters often have no direct correspondence with the state variables of the operational biogeochemical model.
Fig. 9  summarizes the correspondence between measured parameters and ERSEM model variables used by the POSEIDON team for the Cretan Sea. Most plankton groups measured (except bacteria and 25 diatoms) do not have a direct correspondence with a model variable. To make such links several plankton groups have to be grouped together, whereas others have to be split into subgroups based on their size and/or trophic functioning (e. g. Tsiaras et al. , 2017). Planktonologists and the modellers of the observatory agreed that there is no rule of thumb, and model-field data correspondences should be adjusted according to the season and region.
6 Metadata and data handling 30 The data collected from the different platforms undergo Quality Control procedures according to EuroGOOS and OceanSITES working group standards and methodologies. The POSEIDON database is set to include BGC and BGC-associated parameters, either remotely sensed (pH, pCO 2 , Chl-a, O 2 , meteorological, T, S), or obtained from in-situ sampling (Chl-a, O 2 , nutrients, plankton stock). The POSEIDON Data Centre, as the regional data collection unit of the CMEMS, provides the compatibility of the recorded data with the existing large  European 35 data infrastructures (EMODnet, CMEMS and SeaDataNet). Data can be visualized through the POSEIDON website (fixed platforms, Ferrybox) and the MonGOOS data portal (http://www. mongoos. eu/data-center, all platforms Ocean Sci.
Discuss. , https://doi. org/10. 5194/os-2018-3 Manuscript under review for journal Ocean Sci. Discussion started: 6 February 2018 c Author(s) 2018. CC BY 4. 0 License. except sediment traps, ADCP), while the data are freely available to the public, the stakeholders and the scientific community, acknowledging the EC INSPIRE directive, in order to enable easy access to data and their reuse.
Finally, providing an operational status to the regular in situ sampling program is expected, following the experience gained and the standardisation of the procedures. Ocean Sci. Discuss. , https://doi. org/10. 5194/os-2018-3 Manuscript under review for journal Ocean Sci. Discussion started: 6 February 2018 c Author(s) 2018. CC BY 4. 0 License. This strategy will give scientists the opportunity to study primary production, secondary (zooplankton) production, higher trophic level web structure, as well as feedback effects, such as the capacity to store CO 2 , and the ecosystem's feedback on physics (light attenuation). In addition, the long-term time series data and the expanded NRT data delivery, proxy estimations, hazard mapping, and higher resolution predictions will benefit numerous society users (local authorities, technical institutions, tourism industry, educational organizations, 5 fisheries industry, environmental organizations, policy-makers etc).
7) b. Integration of disciplines, platforms and analysis methods, by bridging various measurement scales and methodologies as well as through a step-by-step integration of an increasing number of different biochemical platforms (see Sect. 4), parameters and analysis methods (see Sect. 5) c. Maintain a quality controlled biochemical-ecosystem database, with reduced data delivery time and 20 expanded accessibility (see Sect. 6) d. Support ecosystem model validation for improved ecosystem forecasting and management e. Provide a technology test bed for new biogeochemical sensors f. Maintain collaboration through strong networking with similar observatories for common strategy, complementary tasks, protocol standardisation, and transfer of knowledge (see Sect. 4) 25.
Acknowledgements We would like to thank  M. Kouratoras  for the infographics and all HCMR technical and scientific personnel that has contributed to discrete biochemical samples collection, analysis, and data processing at the POSEIDON E1-M3A location. Part of the work has been funded by  JERICO-NEXT  project. This project has received funding 20 from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  654410 '.
e experiments were conducted applying a back pressure of 110 MPa and also without back pressure. e microstructures across the thickness of the fins were characterized by scanning electron microscopy (SEM) and electron back-scattering diffraction (EBSD) operated in a JEOL JSM-6500F field-emission gun-scanning electron microscope. Data acquisition and analyses were carried out by the Aztec HKL and the ATOM software  [18] , respectively. For the detection of grain boundaries, disorientation angles between neighboring pixels were required to be greater than 5 °. In order to obtain and compare mechanical properties of the fins produced at different gap widths, tensile tests were performed at room temperature. e tensile direction was set parallel to the longitudinal direction of the fin, and the strain rate was 0.
Simulation Procedures. e commercial DEFORM-2D/3D V11. 0 FE code was used for the FE simulations to obtain insight into the stress and strain distributions within the workpiece during the PFM process. All parts of deforming tools were defined as rigid bodies, whereas the workpiece was represented by 10000 tetragonal deformable elements. Adaptive meshing was used to accommodate large strains during the material flow within the lateral channel. e material behavior was taken isotropic using the von Mises model with the hardening law σ � 180ε 0. 23 vM (MPa) (σ is the von Mises equivalent stress, and ε vM is von Mises strain). e parameters of the hardening law were obtained by approximating the stress-strain curve of Al1050 from  [19]. Friction was modeled by the Siebel friction law τ � 0. 2σ.
Mechanical Properties and the Effect of the Fin ickness Ratio. e tensile test results of the initial and PFMprocessed samples corresponding to different fin thickness ratios, ranging from 0. 325 to 0. 75, are presented in Figure  7(a). e geometry of tested samples is displayed in Figure  7 (b) with h being the thickness of the sample. As can be seen, a significant increase in strength, about more than 2. 5 times, was achieved in all produced fins. Good elongations-which were far higher than those in other SPD counterparts-were also attained. A comparison of ductility obtained at a similar strength range for Al1050 from several SPD processes is presented in Table  1. e data were collected from different studies. As can be seen, in a comparable range of UTS strength, PFM provides higher uniform and total elongations than other SPD processes.
The 2019 Nucleic Acids Research (NAR) Database Issue contains 168 papers spanning molecular biology. Among them, 64 are new and another 92 are updates describing resources that appeared in the Issue previously. The remaining 12 are updates on databases most recently published elsewhere. This Issue contains two Breakthrough articles, on the Virtual Metabolic Human (VMH) database which links human and gut microbiota metabolism with diet and disease, and Vibrism DB, a database of mouse brain anatomy and gene (co-)expression with sophisticated visualization and session sharing. Major returning nucleic acid databases include RNAcentral, miRBase and LncRNA2Target. Protein sequence databases include UniProtKB, InterPro and Pfam, while wwPDB and RCSB cover protein structure. STRING and KEGG update in the section on metabolism and pathways.
Microbial genomes are covered by IMG/M and resources for human and model organism genomics include Ensembl, UCSC Genome Browser, GENCODE and Flybase. Genomic variation and disease are well-covered by GWAS Catalog, PopHumanScan, OMIM and COSMIC, CADD being another major newcomer. Major new proteomics resources reporting here include iProX and jPOSTdb. The entire database issue is freely available online on the NAR website (https://academic. oup. com/nar).
The Nucleic Acids Research (NAR) Database Issue reaches its 26th annual issue in 2019. As ever, the 168 papers within cover the full range of biological research. Among them, entirely new databases account for 64 (Table  1 ) while 92 cover resources that have previously appeared in the Issue and now return with updates. The remaining 12 papers are updated on databases last published elsewhere (Table 2). The usual categorization is again used: after reports from the major resource collections at the U. S. National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EBI) and the BIG Data Center at the Beijing Institute of Genomics, Chinese Academy of Sciences there are these groupings: (i) nucleic acid sequence and structure, transcriptional regulation; (ii) protein sequence and structure; (iii) metabolic and signaling pathways, enzymes and networks; (iv) genomics of viruses, bacteria, protozoa and fungi; (v) genomics of human and model organisms plus comparative genomics; (vi) human genomic variation, diseases and drugs; (vii) plants and  (viii)  other topics, such as proteomics databases.
Many interdisciplinary databases defy easy categorization, encouraging readers to browse the whole issue. The NAR online Molecular Biology Database Collection, classifies databases more finely using 15 categories and 41 subcategories, and can be found at http://www. oxfordjournals. org/nar/database/c. Among the major global centers, the NCBI (1) reports on new and expanded literature resources, including PubMed Labs (2) a new interface to PubMed, and new sequence database search options. The EBI paper (3) reports on the new databases Single Cell Expression Atlas and PDBe-Knowledgebase. The latter encompasses FunPDBe, an initiative to better harness structural bioinformatics methods and international collaborators to annotate the protein structural data in PDBe. An interesting facility reported by the BIG Data Center paper (4) is their BIG Search which not only scans across the Center's many resources but accesses indexes from non-Center partner databases on topics as diverse as lncRNAs, plant transcription factors and autophagy-related proteins.
Major returning resources in the 'Nucleic acid databases section include miRBase (5) which focuses on criteria to assess the reliability of microRNA entries and functional annotation from linked target predictions, external manual curation and text mining. For long non-coding RNAs and their targets, LNCipedia (6) contributes an update, also with a major focus on text mining and manual curation. The popular LncRNA2Target database  (7)  reports a new release with major increases in lncRNAs, targets and lncRNAtarget associations. Two papers address piRNAs (the returning piRBase; 8) or their targets (the newcomer piRTar-Base; 9). The RNAcentral  (10)  hub now retrieves ncRNA data from a total of 28 databases. Important progress since the last paper is reported in mapping genome locations, quality control using the Rfam database  (11)  and functional annotation.
Elsewhere two new databases--Plasmid Atlas  (12)  and PLSDB (13)--allow easy analyses and searches against the ever-increasing number of bacterial plasmid sequences. In resources for transcription factors (TFs), An-imalTFDB  (14)  now covers 97 animal genomes and includes a variety of new data such as links from TF-SNP pairs to GWAS data, TF gene expression data and proteinprotein interaction networks involving TFs. An interesting new database MethMotif  (15)  integrates TF binding sites with data on DNA methylation, demonstrating the cell type specificity of many TFs in terms of both binding site sequences and methylation profiles. In the section on protein sequence and structure databases, UniProtKB (16) reports continued exponential growth of much data, growth made manageable by a focus on Reference Proteomes.
There is an interesting discussion of the importance of primary manual curation of the Swiss-Prot portion of the database, especially in cases that computational methods would struggle with, and mention of new methods that might contribute to better propagation of that information to the unreviewed UniProtKB/TrEMBL section. Some of these methods use domain assignments from InterPro  (17) , also contributing an update here describing, among other improvements, annotation with 'flavors' of intrinsic disorder and better treatment of discontinuous domains. A contributor to InterPro and major resource in its own right Pfam also has an update paper  (18). It reports refinement of many existing entries and the generation of over 800 new protein families using the ECOD structural database  (19). This exercise helped refine the description of some Domains of Unknown Function, while the paper also explains how useful annotations for these can flow back from InterPro work to integrate and rationalize content across its multiple contributing databases.
For protein structure both the wwPDB consortium  (20)  and the RCSB (21) report updates, the former pointing out the deposition and validation challenges brought by cryo-EM and serial femtosecond crystallography, the latter listing the impressive variety of external resources integrated into the webpages and describing the incorporation of a new method for description of biological assemblies. Protein post-translational modifications are well-covered by the returning PhosphoSitePlus ® database (  22 ), now 15 years old and with exciting new integration of disease-related mutations and protein isoform data, and the iEKPD resource  (23)  for phosphorylation-related protein domains. They are joined by the new database qPhos  (24)  covering the dynamics of protein phosphorylation. Among other interesting new arrivals are the Ancestral Genomes database  (25) , providing reconstructed proteomes for 78 extinct ancestors of current species and two new resources for transmembrane proteins: EncoMPASS (26) focusing on structural similarities and symmetries, and MemProtMD  (27)  which provides the results of embedding the structures in a lipid bilayer and subsequent coarse-grained dynamics simulations.
A major new arrival in the metabolic and signaling section is the Issue's first Breakthrough Article. It is increasingly apparent that the gut microbiota and human diet interact in complex ways with human host metabolism to influence health and disease. The Virtual Metabolic Human (VMH) database (  28 ) is an impressively ambitious resource that seeks to capture that complexity through linking together modules containing genes, reactions and chemical compounds within the human cell (both as a whole and in compartments) and gut microbes (more than 600 species). Further resources cover nutrition, both in terms of typical diets and in mapping dietary components onto VMH metabolites. As well as inter-connectedness between these modules, VMH links out to more than 50 other databases. The authors envisage that simulations employing VMH with different diets and different microbial abundances can be used to generate testable hypotheses, for example, regarding correlations between microbiota composition and disease states.
Elsewhere, two returning manually curated databases focus on protein complexes. CORUM (29) covers mammalian D4 Nucleic Acids Research, 2019, Vol. 47, Database issue complexes and new features include a network-style visualization of subunit interactions and, most interestingly, a recognition and accounting of the impact alternative splicing can have on protein complex function. Complex Portal  (30)  presents a new interface incorporating visualizations of data from other databases on metabolism, protein structure and gene expression. The very popular database of protein-protein functional associations STRING reports  (31)  an update to version 11. 0. Not only has the number of species covered doubled since the previous version, but the database now allows genome-scale expression dataset uploads and annotation of the resulting networks according to gene-set enrichment analysis.
The well-used HumanNet  (32) , comprising a network of human gene associations with data weighted in a Bayesian framework, reports an update. Already employed data such as protein-protein interactions increased significantly in volume and were supplemented by two novel sources of data, pathway annotations and coessentiality data. New candidates for involvement in disease can be identified by network-based expansion from a set of known guide genes. Finally, the KEGG database, particularly valued for its pathway reconstructions, reports important new developments in the shape of the KEGG NET-WORK and KEGG VARIANT components  (33). These human-specific elements allow the integration of variants such as cancer-related mutations of signaling proteins into networks (derived from KEGG's original pathways) in order to visualize the effects of perturbation on disease-related pathways.
A network variation map summarizes the impacts of a set of perturbants--which may also include viral proteins, environmental factors and drugs--on a given pathway. The microbial genomics section contains updates from twin Joint Genome Institute databases. The IMG/M database of genomes, metagenomes and metatranscriptomes reports growth of around 60% in just 2 years  (34). Its interface is improved in a variety of ways, including a powerful new search capability, BLAST searches against specific and bespoke databases, and powerful statistical comparisons of gene function between groups. IMG/M links to genomic metadata in the longstanding GOLD database, also reporting an update here  (35). The IMG/VR viral genomics resource has tripled in size in the same period and now includes improved viral host prediction and geographic mapping for uncultivated viral genomes  (36).