dataesr/scientific-paragraphs-categorization huggingface dataset:
Currently the prose should therefore be taken as the denitive way of encoding the phenomena under discussion: that is, even if a corpus validates against the schema, it might still not be encoded according to the recommendations. The Parla-CLARIN schema uses the following TEI modules: • the obligatory tei, header, core, and textstructure modules dening the elements used in any TEI-encoded text; • the corpus module to encode the root <teiCorpus> element and the details of various metadata of the corpus; • the spoken module for encoding speech corpora, so that speeches are encoded as utterance elements; • the figures module, which, among other things, denes the elements for encoding tables, as these can also appear in parliamentary proceedings; • the namesdates module, which denes a wealth of elements and attributes to describe people and organizations; • the transcr module, which is used for transcription of primary sources, such as manuscripts, and is useful for encoding historical parliamentary corpora where the facsimile is of interest; • the linking module, which denes useful attributes for linking elements of the corpus; • the analysis and iso-fs modules, the former for encoding linguistic analyses of the transcriptions and the latter for dening formal pieces of data, such as decomposing morphosyntactic descriptions into their features; • the gaiji module for encoding special characters that are especially likely to appear in historical parliamentary proceedings.
Presentation of Parla-CLARIN Like the TEI Guidelines, the Parla-CLARIN recommendations are available on GitHub, as a project  7  of the CLARIN ERIC collection. The project contains a folder for the schema (i. e. , the Parla-CLARIN ODD document and XML schemas derived from it), a folder for the programs that convert the ODD into the XML schemas and to the HTML of the prose and schema denitions, and a folder for examples, which contains an articial but fully worked out example of a Parla-CLARIN document and subfolders with various example resources, where each should contain: 1. a sample of a corpus in its source encoding; Furthermore, the project contains a document folder with the HTML of the recommendations, which can be read online via the github. io pages. 8 Finally, the project has a wiki, which gives the technical details on how to validate a corpus against the Parla-CLARIN XML schema, how to add example documents to the project, and how to change the ODD in case it turns out to be insucient for the modeling needs of a particular corpus.
Akoma Ntoso Akoma Ntoso  12  was explicitly developed as an XML format for encoding legislative and judiciary documents, including parliamentary proceedings, is an OASIS standard, and has already been used to encode various legal documents in a number of countries. Akoma Ntoso denes an XML schema (called AKN) for modeling legal documents, uses FRBR (Functional Requirements for Bibliographic Records) concepts, and has a built-in relationship to ontologies. While these are all good reasons for AKN to be the interchange format for parliamentary corpora, there are, we feel, nevertheless a number of reasons why TEI-based recommendations are preferable. First, corpus compilers and users are typically unfamiliar with AKN but-as shown in table  1 relatively familiar with TEI. It should also be noted that for most corpus compilers, parliamentary corpora will be only one type of corpus they will be compiling, so it is somewhat unrealistic for them to learn AKN and develop conversion scripts from it for just one type of corpus; on the other hand, TEI can be used for practically any type of corpus.
Nevertheless, AKN is an important schema for modeling parliamentary proceedings, especially as the primary encoding standard used by various legislative bodies, so some of AKN's solutions were used in developing the Parla-CLARIN proposal, in particular the typology of divisions of a document. Also developed was a partial, but non-trivial, conversion from AKN to Parla-CLARIN, which covers several AKN example documents. As mentioned in section 2. 3, the example documents and conversion script can be found in the Examples folder of the Parla-CLARIN Git repository. The akn2tei. xsl script attempts to preserve the IDs of the source AKN document, converts the AKN addressee, role, and questions and answers to Parla-CLARIN, and maps FRBR data (which distinguishes a "work" from its "expression" and its expression from its "manifestation") to the appropriate TEI elements and attributes.
RDF 25 The Resource Description Framework (RDF 14 ) is a W3C specication and a standard model for computer-processable data interchange on the web. It is also the base format for modeling information in the context of Linked Open Data (LOD), an inuential model for linking data on the web. While most LOD datasets do not focus on language data, there does exist the Linguistic Linked Open Data Cloud (LLOD  15  ) initiative, which is explicitly aimed at language resources and is active, for example, in the scope of the COST Action NexusLinguarum, "European network for Web-centred linguistic data science. "  16 RDF/LOD has also been used for modeling parliamentary debates, in particular the Debates of the European Parliament as Open Data (Aggelen et al. 2017). Again, the question is, why not use RDF to encode parliamentary corpora, rather than developing a TEI-based solution? Partially it is the community addressed by Parla-CLARIN: while LOD is targeted at computer scientists and assumes a machine-processable and -linked World Wide Web, TEI addresses mostly researchers from the digital humanities and models internally complete resources, while XML is also more popular than RDF in the NLP community.
In practical terms, RDF data are machine-processable but hardly human-readable, and highly connected to external data sources; TEI documents, in contrast, are relatively self-explanatory, especially after some exposure to the TEI Guidelines, can be edited in any XML editor, and are mostly self-contained. Furthermore, while LLOD is indeed focused on language data, it has so far been used mostly to encode lexical resources, and its treatment of corpora has so far been concerned only with encoding linguistic annotations (Declerck et al. 2020). Detailed encodings of particular types of language resources are thus still lacking, and the same can be said for RDF attempts at encoding parliamentary debates, which model only rather shallow aspects of such data. Our position is that RDF could be a useful downstream encoding for exploiting such corpora, and it would be a worthwhile exercise to develop a TEI-to-RDF conversion.
Conclusions In this paper we have given an overview and presented the motivation and justication for developing a proposal for a standard interchange encoding scheme for corpora of parliamentary proceedings meant for scholarly investigations. This scheme is currently a straightforward As we wanted to have corpora that are not only interchangeable but interoperable as well, we created a bespoke ParlaMint XML schema directly in RelaxNG -the schema is compatible with Parla-CLARIN as it validates a subset of documents that would be validated against Parla-CLARIN. We produced common scripts that can convert any of the four corpora to plain text, to CoNLL-U format as used by the Universal Dependencies project, and to vertical format as used by the CWB  19  and Sketch Engine 20 (Kilgarri et al.
2014) concordancers, as well as to extract complete speech metadata into TSV les. In order for Parla-CLARIN to achieve its goal of becoming a widely recognized encoding format for corpora of parliamentary proceedings, signicant work remains to be done. On the basis of the lessons learned in creating ParlaMint, we plan to revise the prose recommendations and to write a more prescriptive TEI ODD that will allow, as much as possible, only elements, attributes, and content models that are in line with the recommendations. Furthermore, we plan to change the examples given in the schema specication from the default ones in the TEI Guidelines to ones taken or adapted from the collected parliamentary corpora. Second, as we have already done for ParlaMint, we plan to add to the GitHub Parla-CLARIN project more down-conversion scripts with which we would increase the usability of the Parla-CLARIN corpora.
Concerns regarding AHP As mentioned by  Vargas (1990)  "the Analytic Hierarchy Process (AHP) is a theory of measurement for dealing with quantifiable and/or intangible criteria that has found rich applications in decision theory, conflict resolution and in models of the brain. It is based on the principle that, to make decisions, experience and knowledge of people is at least as valuable as the data they use". Decision applications of the AHP are carried out in two phases: hierarchic design and evaluation. The design of decision hierarchies requires experience and knowledge of the problem area. Two decision makers would normally structure two different hierarchies of the same decision. Thus, a decision's hierarchy is not unique. On the other hand, even when two people design the same decision's hierarchy, their preferences may yield different courses of action.
Dashboard access is protected with an access code; sharing the access code allows collaborative item collection. WOA is deployed as a browser extension. It uses web augmentation strategies  (Díaz, 2012)  to transparently attach itself to any website, and to enrich it with functionality to support information objects extraction. Web Augmentation can be implemented using different strategies (like DOM manipulation at a proxy, bookmarklets, and extensions at the client). WOA performs Document Object Model (DOM) manipulation through the API of web-extensions on the client side.
In this regard, Logikós differs from AskSheet in that it considers the data collector a stakeholder, deciding what items on the web are suitable candidates. In addition, Logikós simplifies data collection with templates at the expense of being useful only in websites with a stable structure. Asksheet does not provide any specific support for the later phases of the decision-making process (besides that offered by the spreadsheet formulae); the tool's focus is data collection. In this regard, Logikós improves upon Asksheet in that it facilitates decision-making using AHP with information collected from the web. The data collection facilities offered by Logikós (templates, the template editor, the item collector, and the dashboard) can be seen as tools for web scraping. Web scrapping tools and libraries have been available for a long time, many of them aimed at software developers.
Funding: The design and development of the methods and tools reported in this article were funded by  Universidad National de La Plata  ( La Plata , Argentina). The experiments and reporting activities were jointly funded by  Universidad Nacional de La Plata  ( Argentina), Toulouse 1 University Capitole (Toulouse, France ), and the  European Union  [ RUC-APS  project, grant  691249 , funding scheme  H2020-MSCA-RISE-2015 ]. Conflicts of interest/Competing interests: There are no relevant financial or non-financial competing interests to report.
INTRODUCTION Nowadays, environmental constraints are increasing at a fast rate, leading to the appearance of new materials in the building world, in particular thermal insulators. However, their use stays limited due to non-availability of databases in reference to their intrinsic properties. Moreover, we lack hindsight regarding their sustainability (humidity sensitivity, fluctuation of micro-structure, fungal growth). The purpose of this paper is to present a method which enables to identify on site thermal properties of insulating materials, in order to maintain an active monitoring of their properties overtime. In literature, some characterization methods exist : The most simple techniques which enable to determine an isotropic conductivity k [W. m -1 K -1 ] in equilibrium is the hot plate method  [1].
(  3 )): (c I C I + C P ) Ṫ = (k I K I + A)T + U (4) The size of these matrices are [N , N ], where N = 61, 591 taking into consideration the degree of precision for the representation of the geometry. A numerical simulation was executed, using a second-order solver working at a variable time-step, to evaluate the temperature field of the formerly discussed insulator. With the same set of thermal characteristics (k I = 0. 041 [W. m -1. K -1 ] and c I = 1. 15 × 10 5 [J. m -3. K -1 ]). Our simulation has been validated with the modeling software COMSOL Multiphysics®. Figure  3  shows the evolution of the temperature at the 2 measuring points A and B of the probe over time, as well as the results obtained by the Blackwell analytical model. One can thus note the important difference between these two models.
The real time target will achieve 24/7 data acquisition and real time processing. The other components will be in charge of data storage, online and offline data visualizations, experiment setting and processing without modifying software core. This scalable architecture could be used as well for JHR experimental devices with high availability as for testbed. This architecture could be run on a standalone station for a measuring bench or deployed on cluster with redundant data acquisition system for high availability. CAREDAS's design is modular and use proven widely used open source solutions of IIoT world (Industrial Internet of Things). All parts are independent from each other and can be replaced with another technology with the same functionalities. This ensures sustainability and control of software sources.
The real-time DAQ is modular according to the user's needs with various inputs/outputs such as analog inputs, digital inputs, temperature sensor. A DAQ management software, which can be used by a non-IT specialist, combines the functions of parameters setting, supervision and visualization of measurements. Real-time processing is defined in this software with a scientific programming language such as Scilab. This architecture is modular and scalable according to the needs. It offers high availability on demand at all levels.
II. CAREDAS ARCHITECTURE CAREDAS architecture (Fig. 2 ) was designed to ensure high availability for 20 independent acquisition systems and adaptable according to the needs of the plant. It ensures the archiving of a large volume of data during experiment. The acquisition chain has a sustainability of at least 50 years. At the bottom of the chain, there are real-time DAQ allowing continuous acquisition of up to 300 sensors while performing 200 real-time processing for 50ms cycle time. No data loss is provided by redundant DAQ. DAQ software is independent of the hardware on which it runs. Linux operating system with real-time functionality is used. The user can, through a configuration tool, configure his experience, add or remove measurement channels, hardware without software programming.
He will define his real-time processing in a structured scientific programming language without programming DAQ. A DAQ supervision and a realtime visualization of measurements allow to check settings as close as possible to the hardware. At the top of the chain, data and system settings archiving ensure high availability of storage and access to data. The database selected is InfluxDB  [2] , a Time series database (TSDB) which is able to absorb and store a large amount of data. For example, a DAQ with the maximum number of channels and 50ms of cycle time represents an amount of 14 GB/day. The real-time acquisition chain is made up of two networks: the supervision network and the acquisition network. The supervision network and the acquisition network are common to all DAQ and are based on separate Ethernet networks.
This division isolates and secures DAQ. The acquisition network must ensure no data loss and its isolation allows to not be disturbed by traffic that the connected systems are not receiver. Communication between all these functions is ensured by messaging using the open source MQTT (Message Queuing Telemetry Transport) protocol  [3]  that is widely used and proven. Offline data visualization is achieved with Grafana to compose dashboards that query directly InfluxDB databases. Only three software in C++ language are homemade to ensure sustainability: real time data acquisition, writing data into InfluxDB, tools for experiment setting and supervision. All software run on station or cluster nodes on the Linux operating system (Red Hat distribution).
Measurements are grouped to optimize message transmission. A data serialization, Google Protocol buffers [4], is using to make a MQTT message (Fig. 3 ). It was developed by Google and available under an Open Source License. Protocol buffers is a language for describing a data structure that allows a program to produce or read a message. MQTT CAREDAS architecture (Fig. 4 ) is composed of a cluster of three brokers and two load balancer. The cluster ensures high availability of MQTT messaging. In case of a node is lost in the cluster or a network failure, other nodes take over. The selected open source MQTT broker is EMQ X from EMQ  [5]. IV. DATA ARCHIVING InfluxDB is the database to store DAQ measurements. Data storage is based on a cluster architecture that is a collection of nodes or servers (Fig.
5 ). A cluster enables high availability and load balancing across multiple nodes. Like MQTT cluster, a load balancer distributes requests from clients to InfluxDB nodes following nodes load. Data are automatically replicated on all cluster nodes. Online data visualization displays data directly from DAQ in subscribing to MQTT messages (Fig. 6 ). It is reachable in the configuration tool. The user can tune DAQ parameters and displays the result with the same tools near the DAQ. A Grafana plugin allows to display diagrams on dashboard with objects animated by data value like SCADA for industrial process survey (Fig. 8 ). Objects appearance can be change on data threshold like color change in a rule. Grafana run as service on a Linux server. A high availability is getting by running many Grafana services on different nodes.
VI. DATA ACQUISITION SYSTEM Real time data acquisition software is modular and technology independent (Fig. 9 ). It can compose of many chassis with different technologies following the user needs. Proven industrial system technologies have been selected to ensure sustainability on 10 years. Technologies implemented are PXIe bus, CompactRIO and CompactDaq from National Instruments, EtherCAT protocol and various measurement units over Ethernet. The operating system is Linux with PREEMPT_RT real time functionality. CAREDAS data acquisition software can also run on a Raspberry PI. To ensure the high availability and no data loss many mechanisms are implemented. First, data are stored locally on a disk. MQTT client of the DAQ stores messages in memory while few minutes during a network loss. Messages stored in memory will be transmitted if the link is restored before this period.
If this deadline is exceeded then data stored on disk will be transmitted. DAQ can also be redundant with three systems. DAQ provides data timestamp in UTC (Universal Time Coordinated) with a 1ms, 1µs or 1ns precision. Electronic board synchronization is realized by distributed hardware clocks. These clocks are generated from system clock that is synchronized by TSN protocol  [7]. Thus, all DAQ are synchronized at 1µs. DAQ software is homemade in C++ language. It is modular, technology, operating system and hardware independent. This architecture allows adding new hardware or replace a library without impact on all DAQ software. Real time processing are describing in configuration tool, thus user do not need to modify DAQ software. An open source mathematical expression parser ExprTk [7] performs real time processing.
VII. DATA ACQUISITION SETTING The configuration tool (Fig. 10 ) allows user to define intuitively all necessary information for DAQ. It surveys the DAQ operation and visualizes online data in real time directly from DAQ MQTT messages. The user can tune DAQ parameters near the DAQ with a laptop. He can define an unlimited number of configuration stored in InfluxDB database. Every parameter backup generates a new configuration version. The tool is able to generate the CAREDAS configuration for all the acquisition chain when adding a new DAQ (MQTT topics, create database, DAQ system configuration). The configuration tool is a homemade software in C++ language usable on any operating system. Multiple tabs allow to simply define chassis, electronic boards and channels. Hardware channels are defined in channel tab and associates the hardware channel to the measurement name in database.
VIII. CAREDAS AS SINGLE STATION All the CAREDAS architecture is able to run on single station like personal computer (PC) without software modification (Fig. 12 ). On this PC run EMQ X MQTT broker, InfluxDB database, offline data visualization with Grafana and CAREDAS configuration tool. CAREDAS data acquisition software can also run on this station when the hardware is not open like a black box. CAREDAS is then adapted to a standalone measuring bench.
IX. CONCLUSIONS A proof of concept has been realized by the end of 2019. Data flow of 20 DAQ experimental devices were simulated 24/7 for two months without data loss (Fig. 13 ). Experimental devices had 800 channels each for a cycle time of 50ms. Two real DAQ with CompactRIO and PXIe DAQ are used and Raspberry PI 3 simulates the 18 others. This represents 16000 measurement channels every 50ms ether a flow of 320000 measurements by second and 28 billion measurements by day. MQTT cluster is made of three DELL R630 dual processor server with 64 GB of RAM to store messages in case of client network failure. InfluxDB cluster is composed of two data nodes and three meta nodes with SSD disk for databases. Computers are DELL R630 dual processor server with 16 GB of RAM.
GC p < 0. 0001; DFC p = 0. 0035; FC p = 0. 0107. Box limits = 25th to 75th percentiles; line = median; whiskers = min to max. Source data are provided as a Source Data file. modification (Supplementary Fig. 7 ). As TFIP11 and coilin colocalize and interact, we compared our TFIP11 iCLIP data with a published coilin iCLIP dataset  27. Strikingly, TFIP11 and coilin bind a large number of common targets. Indeed, 63-68% targets associated with coilin were also bound by TFIP11 (Fig. 4f, g ), suggesting a tight functional interaction between these two proteins. Such an overlapping binding profile was not observed for other nuclear RNA binding proteins such as TIA, TIAL1  28  and HNRNPC  29  (Fig. 4h ). As knockdown of proteins that are essential for CB integrity can result in lower expression of all U snRNAs  30  , we assessed whether TFIP11 modulated U snRNA or sca/snoRNA levels by performing a small non-coding RNAseq (sncRNA-seq) analysis.
15 by one-way ANOVA, n = 15,973 tags mapping to 51 genes) (e). Bands indicate medians, boxes indicate first and third quartiles and whiskers indicate 1. 5× the interquartile range. f, g Venn diagrams of snRNAs (f) and snoRNAs (g) bound by TFIP11 and coilin. Where transcripts can arise from multiple genomic copies, each copy is treated separately. h UpsetR plot of snoRNAs bound to splicing factors (TIA1, TIAL1, HNRNPC), to coilin and to TFIP11 (two independent iCLIP libraries: TFIP11-A and TFIP11-B), to visualize the number of commonly bound snoRNAs. Columns represent the number of snoRNAs in the categories schematized beneath. Colored squares above each column represent enrichment p-value computed by SuperExactTest. Categories are not independent: e. g. , the snoRNAs in the TFIP11-A category are also present in all other categories that include TFIP11-A.