dataesr/scientific-paragraphs-categorization huggingface dataset:
This is an advantage over methods that rely on metagenomic assemblies (such as VIRify) because the analysis of reads allows the detection of low-abundance phages that are difficult to assemble into contigs  [85, 86]. However, the advantage of using protein profile HMMs is that they gather viral reference data in a more efficient and compact way, in comparison with databases of complete genomes generally required by kmer-based methods. This is particularly relevant in the case of Phanta, which was designed to perform taxonomic profiling at the species level. Therefore, the combination of VIRify with a larger collection of ViPhOGs covering the entire viral taxonomy would be easier to implement as a general-purpose viral taxonomic profiling, than methods relying on the use of collections of complete reference genomes.
Although VIRify has been benchmarked and validated with metagenomic data in mind, it is also possible to use the pipeline to detect RNA viruses in metatranscriptome assemblies (e. g. SARS-CoV-2, see  [87] ). Some additional considerations in this regard include 1) quality control, 2) assembly, 3) post-processing, and 4) classification. Some brief recommendations on how to prepare metatranscriptome assemblies and run them through VIRify can be found in the GitHub manual. Overall, our results demonstrated the utility of VIRify for analysing viral communities in metagenomic datasets. In contrast with other resources currently available, VIRify offers an enhanced capability to predict contigs from eukaryotic viruses and the ability to taxonomically classify viral contigs using a set of carefully curated HMMs and their bespoke bitscore thresholds.
Runtime and resources The pipeline runtime can vary significantly depending on the hardware and data size. For optimal performance, we recommend running VIRify on high-performance computing (HPC) systems or the cloud, especially for larger datasets. On a typical laptop with 8 cores, the pipeline runs reasonably fast for small datasets, such as the two mock community data sets, taking approximately 16 minutes for the Kleiner co-assembly and 30 minutes for the Neto co-assembly. However, for larger datasets like the 243 TARA Ocean assemblies, the pipeline requires 2 days and 13 hours on an HPC system with SLURM and the default configuration profile for cluster execution. This runtime estimate includes the execution time for each process, excluding database downloads. Keep in mind that the actual runtime can be influenced by factors such as fluctuation and pending jobs due to high demand on the HPC.
3% (B) Visualization of predicted (top row) and annotated ORFs for one exemplar contig from TARA Oceans assembly CEUI01. Grey bars indicate hits against an HMM of the corresponding database, while informative ViPhOG hits with taxonomic information are shown in green. The top ViPhOG track shows hits filtered by bit score (or e-value if no bit score could be assigned for a model, see Methods) and the bottom ViPhOG track shows e-value-filtered hits. (C) While the model-specific ViPhOG bit score threshold can lead to the loss of potentially informative annotations for taxonomy assignment, it can also reduce the number of false positive model hits and thus increase the overall accuracy of VIRify. https://doi. org/10. 1371/journal. pcbi. 1011422. g007.
EPOS Seismology risk models and the ability to host national models if desired, EFEHR services provide access to many underlying data relevant for hazard and risk estimation and ensure the reproducibility of the derived models. The coordinated development of products and services of EMSC, ORFEUS and EFEHR was significantly sponsored by a number of EU projects of the FP6, FP7, and Horizon 2020 programs, which also greatly helped the build-up of a European community of contributors. The success of these community-driven initiatives and the experience gained in their development and operation contributed significantly to the inception of EPOS during the first decade of the third millennium. While many European seismological institutions are today at the same time members of EMSC and ORFEUS, and a growing number of institutions are joining EFEHR, the areas of interest and responsibility of each community are sufficiently different so that a relatively clear separation of the content of the three initiatives can be maintained.
ORFEUS: Access to waveform data and related products These goals are achieved through the development and maintenance of data services targeted to a broad community of seismological data users, ranging from earth scientists to earthquake engineering practitioners. Two Service Management Committees (SMCs) are consolidated within ORFEUS, devoted to managing, operating and developing (with the support of one or more Infrastructure Development Groups): (i) the European Integrated waveform Data Archive (EIDA; https://www. orfeus-eu. org/data/eida/); and (ii) the European Strong-Motion databases (SM; https://www. orfeus-eu. org/data/strong/). A new Service Management Committee is being formed to represent the community of European mobile instrument pools. Products and services for computational seismologists are also considered for integration in the ORFEUS domain.
EIDA  [Strollo et al. , 2021]  is the distributed infrastructure in ORFEUS that provides access to raw seismic waveform data archives and associated station metadata collected and curated by European seismic networks. Established in 2013, EIDA presently provides seamless access to 12 data archives -the EIDA nodes -by means of standard services (FDSN and EIDA-specific services), exposing data on behalf of hundreds of network operators and research organizations. EIDA currently comprises ~ 14,000 seismic stations and approximately 600 TB of seismic data  [Strollo et al. , 2021; their Figure 2]. The seismic networks integrated in EIDA include weak-motion, strong-motion, pressure, rotation and other sensor types. EIDA typically serves 5000+ unique users / year. The EIDA system is designed to scale up to add new services, data types, and nodes.
Leveraging on EC funding opportunities, EIDA is currently active in developing suitable data management approaches for new emerging technologies (e. g. , Distributed Acoustic Sensing systems DAS, dense nodal and MEMS-based instrumentation) and challenges related to big and novel datasets. The European strong-motion systems  [Lanzano et al. , 2021]   tary services on two different time scales: the RRSM provides automatic information within the first few hours or days after the earthquake occurrence; after manual processing, the ESM becomes the authoritative source of information. The RRSM is a downstream product of EIDA and uses only data integrated in EIDA (including onscale velocity data), while the ESM also includes offline data from other data sources. The ESM includes advanced interactive software tools, e.
g. , allowing users to process strong-motion data or to select ground-motion waveform sets for engineering studies. The ESM is presently the reference database for harmonised seismic hazard and risk studies in Europe. Overall, ORFEUS services currently provide access to the waveforms acquired by ~ 16,000 stations, including dense temporary experiments, with strong emphasis on open, high-quality data (Figure  3 ). Contributing to OR-FEUS data archives means benefitting from long-term archival, state-of-the-art quality control, improved access, increased usage, and community participation. Access to data and products is ensured through state-of-the-art information and communication technologies, with strong emphasis on web services that considerably enhance user access to data gathered and/or distributed by the various ORFEUS institutions (see https://orfeus-eu.
org/data/ eida/webservices/ and https://esm-db. eu/#/data_and_services/web_services). Web services also facilitate the automation of downstream products. Particular attention is paid to adopting clear policies and licenses, and acknowledging the crucial role played by data providers, who are part of the ORFEUS community. Note that ORFEUS strongly encourages the use of international network codes, seismic network digital object identifiers  [Evans et al. , 2015] , and full network citations (generated using the web interface of the FDSN, "networksgenerate citations for network data") in journal papers using data provided by seismic networks [details are given in  Cauzzi et al. , 2021]. All ORFEUS services are developed in coordination with EPOS and are largely integrated in the EPOS Data Access Portal (https://www.
ics-c. epos-eu. org/). Documentation on ORFEUS data and services is provided on the ORFEUS website and is complemented by a large archive of ORFEUS community workshops and webinars (typically attended by more than 100 participants on average, and with maximum attendance exceeding 200 people for virtual events) organized in the last few years (https://orfeus-eu. org/other/workshops/). ORFEUS data and services are assessed and improved with the help of technical and scientific feedback from a User Advisory Group (UAG), which comprises European Earth scientists with expertise on a broad range of seismology domains. ORFEUS actively participates in EC-funded projects (see Acknowledgments) and collaborates with global and international organizations with similar scope, as mentioned in the Introduction.
EMSC: Access to earthquake and other seismological information products The European Mediterranean Seismological Centre (EMSC, https://www. emsc-csem. org/), founded 1982 in Strasbourg (France), is a not for profit organization that federates seismological observatories in the European-Mediterranean region that promotes scientific collaborations and data exchanges and provides rapid earthquake information on earthquakes and their effects. It is governed by its currently 81 member institutes from 56 countries and has a structure comprising a central infrastructure and five nodal members, institutions who provide specific support to EMSC or its operations. LDG (France) is a nodal member as a host of the EMSC and its central infrastructure since 1994, IGN (Spain) for operating a back-up website, INGV (Italy) for offering the AHEAD [European Archive of Historical EArthquake Data;  Albini et al.
, 2013; Locati et al. , 2014; Rovida et al. , 2015]  service on historical European seismicity (INGV Milan) and for expertise in earthquake location (INGV Rome), and GFZ Potsdam (Germany) for providing rapid earthquake locations. Since 1998 EMSC also produced a comprehensive reviewed earthquake bulletin for the European-Mediterranean region from all the data it received  [Godey et al. , 2006]. In order to avoid duplicate efforts with the ISC, and also due to shortage of resources, the decision to discontinue the EMSC bulletin was taken in 2015. That bulletin covers the period 1998-2012, contains 550'000 events and 10 million seismic phases. Specific European earthquake catalog requirements are today re-discussed in particular with regard to the needs of the earthquake hazard community. The EMSC data and products service infrastructure is based on a comprehensive IT architecture comprising data collection, processing, archival and dissemination that has continuously evolved over the last decades (Figure  4 ).
Parametric seismic data are collected from seismological observatories around the globe and collated at EMSC, while eyewitness observations (felt reports and geo-located pictures) are crowdsourced through the LastQuake [  Bossu et al. , 2018]  mobile app and websites. Seismic information is then disseminated through social media, websites and apps as well as dedicated mechanisms [web services, http message bus HMB;  Heinloo, 2016]  for the scientific community. The "Seismic Portal" (www. seismicportal. eu), initially developed within the EU FP6 NERIES project, provides a common entry point for EMSC services and the link to EPOS data portal.
Florian Haslinger et al. Rapid earthquake information products are based on the collation of parametric data from about 100 institutes and more than 7,000 stations worldwide, leading to about 50,000 to 70,000 earthquake locations per year published by EMSC. There are 3 types of EMSC locations (i. e. earthquake source parameters time, location, magnitude): Reported locations are locations -generally of small magnitude earthquakes -reported by a single network and falling geographically within the reporting network. An authoritative location is a reliable and accurate location (generally from the institute responsible for the region) as described by  Bossu and Mazet-Roux [2012]  that is published by EMSC as received, although the earthquake is reported by several other agencies. Finally, when none of the several locations available for the same earthquake fit the authoritative criteria, a location is recomputed by EMSC based on part or all the received phase arrival information, depending on station coverage at short epicentral distances [see  Bossu and Mazet-Roux, 2012].
These only represent 10 to 15% of all the disseminated locations. Alongside earthquake locations, focal mechanisms and moment tensors are also collected and made available. Earthquake effects are mainly derived from crowdsourced data (felt reports, geo-located pictures) by LastQuake, a citizen seismology initiative comprising websites, a smartphone app and an eponym Twitter quakebot  [Bossu et al. , 2020]. Felt reports (750,000 collected over the last 12 month period) are exploited to generate rapid automatic macroseismic maps and intensity vs distance curves. They contribute to ARISTOTLE, a rapid multihazard impact evaluation service for the European Civil Protection Unit  [Michelini et al. , 2020] , and a methodology is being finalized to ingest them in ShakeMap  [Quitoriano and Wald, 2020; Quitoriano et al.
, 2021]. A real-time exchange mechanism for felt reports is being tested and will allow any institute to exploit them. AHEAD is conceived as a pan-European, common, and open platform to support the research on historical earthquake data, by tracing back, retrieving, preserving, inventorying, and eventually granting access to the sources of earthquake data (such as papers, reports, macroseismic intensity data, and catalogues), by suggesting relationships among earthquake data of different provenance, to foster new insights and promote cross-border cooperation. AHEAD is the successful result of previous attempts (sponsored by EU framework programmes 1, 3 and 6) to establish a coordination framework and common data archive among European organizations collecting information about earthquakes that occurred in the pre-instrumental era, thus mostly described by means of macroseismic intensity data.
AHEAD covers the years from 1000 to 1899 and the continental European region in space. Macroseismic data come from the collection of published research activities that investigate and interpret historical documents in seismological terms (Figure  5 ). AHEAD is governed by the Board of AHEAD Members that is composed of 12 organizations operating under a Memorandum of Understanding and INGV acts as the executive body taking care of the data archive. Data archived in AHEAD is of fundamental importance for the compilation of long-term, continent-wise, and homogeneous earthquake catalogues  [Stucchi et al. 2012; Rovida and Antonucci, 2021] , an essential component for seismic hazard assessment  [Woessner et al. , 2015]. The data and products offered by EMSC, including those from AHEAD, are accessible in various ways: through web services, where applicable following international standards, in particular those developed within FDSN and by the Open Geospatial Consortium OGC (www.
opengeospatial. org), some dedicated services (e. g. the Flinn-Engdahl region lookup, the event ID mapping service and the AHEAD macroseismic data service), and also by means of interactive GUI-based websites. All web services are compliant with the EPOS guidelines on data interoperability, therefore are fully integrated in the EPOS ICS-C data access portal. A major effort has been initiated, thanks to dedicated financial support, to improve EMSC services, covering data collection and dissemination, websites, standardization and harmonization, with first effective results expected by the end of 2022. These developments are an opportunity to improve FAIRness of EMSC products and services by adding relevant identifiers and enhancing the visibility of data contributors without affecting user experience and remaining coordinated at global level for formats and standards.
, 2021]. The geologic fault information is organized into crustal faults and subduction systems, which are both meant to provide the necessary elements to estimate seismicity rates in a variety of tectonic contexts, including onshore and offshore active plate margins and the plate interiors. The EDSF platform is designed to distribute other regional datasets, provided that appropriate agreements with various data distributors are established. Presently, all datasets are identified by a DOI and distributed under a CC-BY or CC-BY-SA license. The data and products offered by EDSF are accessible through web services that follow OGC standards (WFS and WMS), and the metadata follows the EPOS-DCAT-AP standard which has allowed the EDSF13 data to be accessible through the EPOS ICS-C platform. The European Ground-Shaking Intensity Models (GSIMs) service (https://egsim.
gfz-potsdam. de/home) is a web application programming interface (API), implemented recently along the lines of popular seismological web services (e. g. , FDSN): the user can query the toolkit via configurable URLs in order to retrieve model predictions of ground motions from either observed or hypothetical earthquake scenarios. These can be used to develop model-to-model comparisons of the expected shaking, but also to provide fields of expected ground motions and their uncertainties at user-defined locations. Web services are designed to facilitate the exploration of ground motion models and their comparison against observational strong motions from European data sets. The European seismic hazard platform (http://hazard. efehr. org) provides access to specialized hazard datasets, input models, results, documentation and information.
, 2021] ; vi) documentation and scientific support on all of the datasets and models; vii) web services for automated access to the data and models. All products are released under a CC-BY license, and are associated with DOIs and clear instructions related to how to use and cite the work. Two main categories of web services are currently available for the various seismic risk data and models released by EFEHR: 1) web services to access the data available in the interactive map viewers that follow the OGC and Open Source Geospatial Foundation (OSGeo) standards; 2) web services to access the data, models and files stored in various GitLab repositories that can be found at https://gitlab. seismo. ethz. ch/ efehr, making use of the GitLab API. As with the other services of EFEHR described above, the exposure maps have been made available through the EPOS ICS-C platform.
Multidisciplinary activities are also increasingly being carried out within the EPOS Seismology subdomains. For example, the ORFEUS Annual Observatory Meeting and Workshop 2021 was devoted to "New Data Types and Communities", and aimed at discussing the challenges posed by integration of special datasets (e. g. large-N deployments, seismic data acquired by Distributed Acoustic Sensing systems, portable instrumentation including Ocean Bottom Seismometers, processed GNSS time-series, rotational data, gravimetry data and infrasound data) into existing seismological archives and workflows, i. e. , a task that also requires coordination with other communities in EPOS. Another multidisciplinary example is the cross-domain service utilisation in ongoing initiatives such as the candidate TCS Tsunami in EPOS  [Babeyko et al.
EPOS Seismology mology supports the consolidation of the ICS data portal as the main access point and showcase of all data services integrated in EPOS, and recommends its future developments be centered on scientific user feedback. It is important to acknowledge that web portals and graphic user interfaces are meant to be mainly used for data discovery and / or occasional download of datasets of small-to-moderate size. Frequent users, as well as users that need access to large or massive datasets, typically do not rely on web interfaces and rather access data directly through automated queries to web services [e. g. ,  Quinteros et al. , 2021]. With this background, supporting the consolidation and improvement of data services provided by the various communities contributing to EPOS is a crucial issue to be addressed by EPOS.
coordinated by ORFEUS are the Rapid Raw Strong Motion [RRSM; https://orfeus-eu. org/rrsm/; Cauzzi et al. , 2016], the Engineering Strong Motion [ESM; https:// orfeus-eu. org/esm/; Luzi et al. , 2016] databases, and the associated web interfaces and web services. The RRSM and ESM platforms are unique examples of data access in the domain of strong-motion seismology. The RRSM is a totally automatic system for rapid dissemination of earthquake data, while the ESM provides quality-checked, manually processed waveforms and reviewed earthquake information. The RRSM and ESM operate as complemen-Florian Haslinger et al.
g. the Sendai Framework). The currently active services of EFEHR that are fully integrated within EPOS, and which can be accessed via http://www. efehr. org, include: the European Databases of Seismogenic Faults (coordinated by INGV Italy), a web service designed to facilitate the exploration of ground motion models and their comparison against observational strong motions from European data sets (coordinated by GFZ Potsdam), a European seismic hazard platform (coordinated by ETH Zurich) and a European seismic risk platform (coordinated by EUCENTRE, Pavia). The services related to the European Databases of Seismogenic Faults (EDSF), are made available through the www. seismofaults. eu/ platform, which provides access to the European database released in 2013 as part of the European SHARE project [EDSF13; Basili et al.
S6. At Day 7 post-wounding, CWs were carefully debrided to remove dead and sloughing tissue. Briefly, mice were anaesthetized with isoflurane by inhalation, placed on a heated mat and administered Buprenorphine (0. 05 mg/kg sc). The existing Tegaderm dressing was carefully removed, ensuring the wound was not pulled in the process. Debridement was performed using 4. 25 inch dissection scissors and curved tweezers (Sigma-Aldrich) Vehicle (PBS) or BMS-470539 (MC1R-Ag) were delivered topically by pipette into the wound cavity immediately after debridement (100 l in a 30% Pluronic F-127 gel; Sigma Aldrich). Wound areas were calculated using ImageJ software.
Microscopy Tissue sections were imaged on an Axioscan Z1 slide scanner (Zeiss, Cambridge, UK) using the 20x air objective. Immunofluorescence images were taken using a Leica DM2500 microscope, Leica DFC7000 camera and LAS software (Leica Microsystems, GmbH, Milten Keynes, UK), using the 20 x air objective. Numbers of leukocytes per field of view (FOV) were calculated using thresholded 32-bit images and the "analyze particles" function in FIJI software. Blood and lymphatic vessels were quantified by thresholding on fluorescent area in FIJI software.
Collagen alignment Collagen fibre orientation was desired to be able to identify the level to which wounds recovered their natural structural components during the wound healing process. To undertake this, we developed a MATLAB code which first isolated collagen fibrils from nonfibrous tissue using a colour-based segmentation algorithm. First, the user selected image is converted from an RGB image to a two-dimensional matrix of type 𝑚 × 𝑛 × 3. Where 𝑚 and 𝑛 represent the row and column indices respectively. Our code (which we name FIBRAL) converts the image colour space from RGB to L*a*b to more accurately predict small colour differences, key for PSR staining in which small variation detection is required  (25). Both the full a-channel and positive range of the b-channel were isolated and superimposed.