dataesr/scientific-paragraphs-categorization huggingface dataset:
coli. Bioengineers could use this information to more reliably modify strains by limiting designs to post-translationally compatible proteins or by co-transforming parts with their requisite posttranslational modification machinery. Furthermore, the synthetic biology community could make such information more accessible for learning design rules by incorporating this information into parts repositories such as SynBioHub. 46 This information would enable these repositories to function as dependency management systems for synthetic organisms, analogous to the Advanced Package Tool (APT) for Ubuntu packages.
Community adoption as a common toolkit Realizing the full potential of BpForms and BcForms as formats for the primary structures of macromolecules will require acceptance by the omics, systems biology, and synthetic biology communities. We have begun to solicit users by submitting the BpForms and BcForms grammars to the FAIRsharing registry of standards and the EDAM ontology of formats, contributing the alphabets of residues and the ontology of crosslinks to BioPortal, proposing a protocol for using BpForms with SBOL, and helping the PRO consortium use BpForms to represent proteoforms. To further encourage community adoption, we plan to encourage the developers of central repositories of DNA, RNA, and protein modifications such as MethSMRT,  5  the PDB, and RMBase 6 to export their data in BpForms format.
The toolkit is backward compatible with the IUPAC/IUBMB format to maximize compatibility with existing bioinformatics tools and knowledge. The toolkit can also be integrated with frameworks for network research such as BioPAX, CellML, SBML, and SBOL. We anticipate that BpForms and BcForms will be valuable tools for omics, systems biology, and synthetic biology. First, the tools can help researchers precisely communicate information about macromolecules. For example, the tools can help experimentalists communicate observations of proteoforms and help bioinformaticians exchange information among databases of polymers and complexes. Similarly, the tools can make models and genetic designs more understandable by capturing the semantic meaning of the species represented by models and capturing the structures of the parts of synthetic organisms.
For example, BpForms could describe proteins produced by expanded genetic codes. The tools can also help quality control information about macromolecules. For example, the tools could help researchers find errors in reconstructed proteoforms such as inconsistencies between the modified and translated sequences, merge duplicate entries in databases of proteoforms, and identify gaps and element imbalances in models. In addition, BpForms and BcForms can help researchers integrate structural, epigenomic, transcriptomic, and proteomic information about macromolecules. For example, the tools can help researchers integrate observations of individual protein modifications into descriptions of entire proteoforms. The tools can also help researchers integrate databases of modified proteins into a model of post-translational processing, combine the model with models of other processes to create WC models, and refine the model by identifying missing combinations of protein states.
BpForms and BcForms are available open-source under the MIT license. Optionally, a license for ChemAxon Marvin is needed to calculate protonation and tautomerization states and generate molecular visualizations. Free licenses are available for academic researchers. BpForms and BcForms are platform independent. The installation of BpForms and BcForms requires Python 3. 6 or higher, Open Babel, and, optionally, ChemAxon Marvin. A Docker image with these dependencies is available at http://dockerhub. com/u/karrlab. BpForms and BcForms abstract the primary structures of polymers and complexes as combinations of residues, crosslinks, and nicks. For example, BcForms abstracts a disulfide-linked homodimer (A, green box) of a selenocysteine-modified tripeptide (B, blue boxes) as two copies of the tripeptide and a single crosslink (C, green text) and BpForms abstracts the peptide as a sequence of three residues, including selenocysteine (U) (D, blue text).
The models provided here are the latest iteration using the distribution data available at the end of 2018. It is hoped that publishing these models will aid experts to engage the more extensive research and professional community in the drive to expand and validate the VectorNet database, and will also contribute to the veterinary and public health planning for Europe and its neighbouring countries. Readers are encouraged to contact the authors or visit the VectorNet website [1] for further details of the project, and to view distribution maps of arthropod disease vectors of midges, ticks, mosquitos, and sandflies. For each model, abundance maps with a resolution of 1 km were generated using both Boosted regression trees and Random Forest spatial modelling techniques available through the VECMAP [3] system.
Model training data The reported distributions of each vector species held in the VectorNet archive on May 2018 were used as the basis for species present training data for the analysis. They were formally released to the authors on request to ECDC (reference number 18-1421). The raw input data was provided by light trap surveillance of adult Culicoides set up mostly in ruminant farms across continental Europe and surrounding regions (72N-33. 5S, -11. 2W -62E), concentrated in Western countries, supplemented by transect samples in eastern and northern Europe. Data from central EU are relatively sparse (see maps Appendix 1). These data were obtained either from National surveillance systems or from surveys carried out by the VectorNet project. Species were identified using a morphological identification key  [17]  from field collections or, in some case, retrospectively from stored collections from National surveillance systems.
Midge abundance varies throughout the year, and several metrics may be used to represent abundance. The one used here for every species is the mean annual maximum number per trap per day. Data was used only from locations that were sampled with at least one collection per month throughout the season of the peak of abundance. If data from more than a single year was available, the annual average was used. For each species zero values from the abundance datasets were included in the input data, but were not supplemented by zero values for which only presence/absence data were available. These values represent a standardised measure of abundance at the annual resolution, and so represent one aspect of absolute abundance. They are not, however comparable with traditional absolute abundance measures as they are not associated with a specific date.
Quality Control As indicated above, only raw data with sufficient samples per site to ensure reliability were used as model inputs. The model outputs were evaluated using the standard, and very extensive, accuracy metrics (e. g. R-squared, AIC, Kappa, Confusion matrices) provided by the VECMAP [3] software. Providing the accuracy metrics indicated sufficient statistical reliability, the outputs were ensembled as described above. AUCs for the training sets for all the models exceed 0. 85.
Sampling strategy The abundance data used to train the maps were collected by longitudinal UV-light trap collections, a method commonly used to survey adult Culicoides populations at a wide scale. The reliability of UV-light trap collections to assess the ' aggressive density' on animals (which is the abundance parameter related to the risk of transmission) is still under debate and may be species dependent  [24] [25] [26] [27] [28]. However, it is worth highlighting that abundances assessed by UV-light traps have been used for more than a decade to manage animal movements under EU regulations, and that this system has demonstrated its utility.
Volcanological observatories have common needs and often common practical issues for multi-disciplinary data monitoring applications. Real-time access to integrated data, technical metadata, modeling and estimation of uncertainties are fundamental for an efficient interpretation. But in fact, the heterogeneity of instruments or acquisition systems and the inherent problems to produce rapid models using real-time data lead to difficulties that may hinder crisis management. In an attempt to globally address these questions, the French volcanological and seismological observatories have developed a specific operational software system over the past 19 years. Based on GNU/Linux open source tools and a Web interface, the WebObs system mainly offers: (1) a modular database for equipment network management; (2) a dozen of evolving dedicated periodic tasks for each monitoring technique like seismology, deformations and geochemistry that use standard data formats with automated execution of periodic tasks that produce high-quality graphs on preset moving time intervals, data exports, optional event notifications including e-mail alerting, instruments status controls based on their data validity; (3) web-form interfaces for manual data input/editing and export; (4) a user request form to adjust the tasks parameters for a single execution and to produce customized graphs and data exports.
This system hence constitutes a web-based tool that performs integrated, centralized and automated real-time volcano monitoring. It has therefore become a strong support for data analysis and exchange between researchers, engineers, and technicians during periods of unrest as well as periods of long-term quiescence. WebObs is also widely open for development of interdisciplinary modeling and enhanced data processing. This allows scientists to test new methods with real-time data flux and to instantaneously share their results in the community.
Some are focused on single scientific method while others are concentrated on access to data through a global database. Noteworthy among these are the pioneer software PC-BOB for time series data management  (Murray, 1990) , µGRAPH utility for data analysis  (Beauducel, 1998) , FFM software for eruption forecasting  (Cornelius and Voight, 1995) , VALVE system for multidisciplinary database  (Cervelli et al. , 2002 (Cervelli et al. , , 2011)) , SWARM tool for real-time seismic data streams  (Cervelli et al. , 2004) , dMODELS software package for supervised deformation modeling  (Battaglia et al. , 2013) , and the WOVODat platform for worldwide volcanic unrests datasets  (Newhall et al. , 2017). In the French volcanological and seismological observatories which are responsible for La Soufrière de Guadeloupe, La Montagne Pelée, Piton de la Fournaise and recently the new Mayotte submarine volcano, we have developed since late 2000 an operational system named WebObs (WO) that attempts to address these common questions in the context of a generic pluri-instrumental volcanological and seismological observatory  (Beauducel and Anténor-Habazac, 2002; Beauducel et al.
Strategy and Pragmatic Solutions In order to reach these objectives, elegant overall solutions obviously exist but they rely on extensive technical means and long-term investment particularly in the case of: (1) building a single, huge, multidisciplinary new database for all the data; (2) upgrading all sensors, telemetry and acquisition systems to make them homogeneous in standard data formats; (3) making automatic the manual measurements, when technically possible; and finally (4) using a large computer to process any user's requests without delay. Thus, in the project we have discarded from the beginning the perspective of structurally reforming existing overall solutions and opted for the development of a more pragmatic and less costly solution. The strategy that we have proposed has been efficient on the short-term in order to: • keep existing acquisition systems and data archives as they are, • connect and make accessible all data in their native formats, even though we promote standard formats and protocols since WO has implemented many, • process the data through dedicated scheduled tasks to anticipate the most common real-time requests, • facilitate manual data edition and access through simple text databases.
Technical Specifications WO can run on a single computer server under the GNU/Linux operating system on IA-32 (i386) or x86-64 architectures. It is an installable package of bash scripts and using a combination of several languages: Perl and Javascript for the web interface, Matlab standalone binaries (no license needed), Python and some C binaries for the data processings, but any other Linuxcompatible language are compatible welcome. In account of the obvious heterogeneity of acquisition systems, data formats and the specificity of data archiving in every observatory, we decided that for automatic systems WO should not recreate a database of existing monitoring data but will be able to read the raw data in their native format, on-thefly, adapting itself to existing archives or data streams.
g. , gravimetry, electrical resistivity, spontaneous potential, magneto-telluric). Due to very low sampling rate, these data account for a negligible size of storage but they still are of primary importance and must be equally considered in the monitoring system. WO proposes few web-form interfaces to input/edit and export this kind of data, and each are associated to a dedicated process to also produce automatic graphs, in the same way as high sampling rate automatic methods. Although there are some internal databases in sqlite3 format for the system management itself, most of the system uses text files for configuration parameters and symbolic links under a basic folders architecture, easy to edit or share with other systems. WO provides a web portal using a HTTP server for the graphical user interface and web services, and provides user authentication associated with an extended resources access management.
WO can be used as an internal web portal, and/or connected to the internet for external access, restricted or even public. But the main goal is to be able to run standalone, even under offline internet conditions. This aim leads to voluntarily limit the use of any external internet services. The web pages use a customizable menu with sub-menus using HTML and CSS facilities. The welcome page contains fixed areas with customizable content: a title banner, an information area, a news area, an extract of agenda events. Additional free text-content web pages can be created and accessed through the main menu. All text zones can use the MarkDown syntax. One of the main tools of WO is a modular databank to manage information on site measurements, stations, sensors, any equipment or observations. The proposed network architecture can be adapted to various objects with a very broad concept of what is metadata: interactive maps, log history, customizable features, photos, documents.
For the data processing, we have adopted a near real-time solution which consists of producing static images (PNG and EPS formats), automatically updated by periodic tasks under control of a dedicated jobs scheduler. Pre-set moving time windows are defined for each method, from hours to decades, so all the standard graphs are instantaneously accessible for users, without additional server solicitation. User manual requests of any other time interval are available at any time but will have lower priority than periodic tasks. For historical reasons, the most advanced data processing modules have been written in the Matlab language, a choice justified by the native matrix computing capabilities perfectly suited to signal processing, numerical modeling, inverse problem and high-quality graphical outputs.
• a "form" is a manually editable small database, adapted to non-automatic data acquisitions. A form has a table data display with search parameters, editable form inputs with value checking, data export, and can be linked to a proc to produce automatic graphs. Views and procs are associated with a "domain, " a higher level object to group several grids into general categories, mainly for retrieval and display purposes. Default domains are Seismology, Deformation, Geochemistry, Geophysics, Imagery, Phenomenology, and Acquisition. This list is fully customizable, for example: domains can be a list of different volcanoes. Examples are given in Tables  S1, S2. A global search tool allows to find any event contents in all grids and nodes.
An other output of procs is the status of a node: the last valid data timestamp is compared to a time delay to set if the node is active or not, while the amount of valid data on a certain period is compared to the theoretical acquisition period to compute a sampling rate performance. These indicators are displayed in the main proc's table to give an overview of a network health status. Some specific procs may produce per-event outputs, e. g. , for earthquake events, in that case all former outputs will be stored and accessible by date. Any user may submit a proc request after filling a web-form of dates interval, graphical options and some selected proc's parameters. This request will run exactly the same proc code and data as used for periodic task, but the outputs (graphical and data exports) will be written in a separated folder and an email will notify the user of the end of the job.
System Administration, Install and Upgrade WO is distributed with a single binary package, a detailed README file, and a user manual. A bash script creates the disk structure, detects missing dependencies and installs the system with default jobs, examples of views and procs. The same setup script is used to upgrade code, documentation and configuration to a new version. The results presented in this paper correspond to version v2. 1. 4, dated November 2019. System administration can be achieved using shell commands after logging in on the server, while some important tools can be handled through the web interface: grids and nodes management, tasks scheduler (see Figure  S8 ), user administration, configuration files editor, wiki pages. Each proc can activate a debug mode to increase log verbosity.
Seismic Chart and Bulletin For the seismic continuous and high frequency data flux, WO proposes an innovative combination of a digital stripchart paper for multiple data streams, a manual and semiautomatic detection and classification of events, and a bulletin with dynamic graphs of event types: hourly/daily/moving histogram, cumulated number of events, cumulated seismic moment and Gutenberg-Richter diagram. The system accepts SEED and Earthworm data protocols, some basic filtering (median/trend removal, low/high/band pass or bandstop Butterworth/Bessel/Chebyshev N-order filters) and the catalog can be linked to external earthquake databases (local QuakeML or any web-service FDSN compatible) and a raw data access in miniSEED format. The objective of these tools is to construct and update a human-controlled earthquake bulletin, offering the possibility to visually detect and/or check automatic triggered events, and classifying the type from a customized list.
Extensometry Extensometers are useful to monitor active cracks and fractures. The superproc makes time series of linear distance, air temperature and wind strength for each station, a summary graph of all distances grouped in geographic zones and a map showing extensive or compressive oriented arrows of displacements  (Tamburello et al. , 2019). A specific form is available to manage manual data input in a dedicated database (see section 3. 3. 3).
Hot Springs This superproc operates physical and chemical parameters from hot springs water sampling on-site measurements and laboratory analysis: air and water temperature, sampling condition, pH, conductivity, cation and anion concentrations, some isotopes. The superproc is able to plot time series of single element or element ratio time (like chlorine/sulfur or carbon/sulfur) and ternary plots (magnesium/calcium/sodium and chlorine/sulfate/carbonate). A specific form is available to manage manual data input in a dedicated database (see Figure  12  and section 3. 3. 2).
Thus, a wide range of specialists in various fields and from different national institutions participated in the day-today monitoring. Moreover, WO facilitated the share of tasks, like the analysis and localization of seismic signals among different institutes and universities, as it is able to collect data and products from different databases and merge them into one single database (e. g. , SeisComP3 catalog of earthquake events). WO has been pivotal in the complex daily and structured, collegial efficient scientific response to the ongoing Mayotte crisis, especially to create synergies among the scientific response team and to report to authorities in charge of civil protection decisions.
ACKNOWLEDGMENTS FB warmly thank many colleagues that have extensively used, supported or simply encouraged this project from the early thoughts in 2000 until the implementation at more than 15 observatories today:  Jean-Louis Cheminée ,  Claude Jaupart ,  Stéphane Acounis ,  Gilbert Hammouya ,  Jean-Christophe Komorowski  (also for having improved the English of the manuscript),  Yves Caristan ,  Alberto Tarchini ,  Thierry Kitou ,  Xavier Lalanne ,  François Truong ,  Albert Tarantola ,  Pierre Briole ,  Jacques Varet ,  Frédéric Randriamora ,  Benoît Coste ,  Roderick Stewart ,  Valérie Clouard ,  Nathalie Feuillet ,  Cyril Aubaud ,  Philippe Kowalski ,  Florent Brenguier ,  Valérie Ferrazzini ,  Stephen Roselia ,  Laura Henriette ,  Frédérick Massin ,  Marie-Paule Bouin ,  Jean-Bernard de Chabalier ,  I.
DATA AVAILABILITY STATEMENT The open-source codes, documentation, developers forum and free access to installation packages can be found at the IPGP/WebObs repository: https://github. com/IPGP/webobs. Global elevation models are a merge of SRTM Non-Void Filled: https://doi. org/10. 5066/F7K072R7 and ETOPO1: http://doi. org/ 10. 7289/V5C8276M. Sample data are available at Volobsis IPGP data portal: http://volobsis. ipgp. fr, IGN RGP: http://rgp. ign. fr, and Geoscope: http://geoscope. ipgp. fr.
FUNDING The WebObs project has been supported mainly by IPGP and CNRS/INSU (SNOV, Observation National Service for Volcanology) funding for the French volcanological and seismological observatories. Additional fundings came from the French Ministry of Ecology (now MTES), the Spirales project from DSI-IRD, the French ANR Domerapi (ANR-12-BS06-0012), the IRD emergency budget, and finally EUROVOLC project that received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 731070. The French volcanological and seismological observatories have benefited from recurrent funding for network and infrastructural development from the.
Inference of ancestral MSV sequences An alignment containing the 59 MSV-A isolates for which symptoms were quantified (hereafter referred to as 'phenotyped' isolates), together with an additional 630 MSV-A sequences and 182 sequences belonging to MSV strains B through K (all of which can be obtained from GenBank), was constructed using MUSCLE with default settings  (Edgar, 2004)  and edited by eye using the suite of editing tools available in IMPALE  (Khoosal and Martin, 2015). This 871 MSV full genome sequences alignment was screened for recombination using RDP4. 46  (Martin et al. , 2015)  in a two-stage process. In an initial screen, default settings were used and all evidence of recombination within MSV strains other than MSV-A was removed from the alignment by identifying recombinationally-derived sequence fragments and removing these by replacing the associated nucleotide characters in the alignment file with the standard 'gap' character, '-".