dataesr/scientific-paragraphs-categorization huggingface dataset:
We provide this tool for the users of two-hybrid technology, since there is no freely available such software suite. A commercial suite does exist (DNADynamo). However, it does not support multiple sequences, neither assembly of sequencing products using forward and reverse sequencing. While Contig Assembly Program 3 (CAP3), a DNA assembly program, can be used for this purpose since it supports these features  (Huang & Madan, 1999) , it is however not dedicated to Y2H and thus lacks features such as identification of clones or trimming of vector sequences. 2HybridTools also improves on these two programs by introducing a model sequence against which clones are aligned, thus producing a summary of specific mutations resulting for example from a RY2H screen, as well as open reading frame detection and automated Blast identification of clones.
Sequencing quality trimming The very start of sequencing files can contain a number of unidentified bases (N) due to poor sequencing quality in the first 15-40 bases at the 5 end of the fragments. Therefore only the nucleotide sequence following the first N will be used by the program as a default value. Likewise, bases following the second N at the 3 end will not be used neither. However, if required, the user can modify this default setting (Fig. S1 ), which brings up a JOptionPane object.
Protein translation By default, the universal genetic code is selected. This can however be overridden for use with bacterial two-hybrid, in which case GUG and UUG start codons are documented  (Kozak, 1983). ORF and strand are user-defined except in the case of automatic ORF analysis in which these parameters are set up automatically. We made use of the BioJava translation method with the following exception: in the case of a codon containing an N, if the two other bases unambiguously point towards a specific amino acid, e. g. , GTN for Valine, then it will be translated as such. Otherwise, the result will be designated as X but will, however, not be treated as a mutation.
Sequence model alignment and mutation report For RY2H, a DNA or protein model sequence can be loaded prior to analysis, which will result in all translated sequences being aligned in turn to the model protein sequence. The model can either be loaded from a local FASTA file, or downloaded directly from NCBI by inputting the protein accession number. This is achieved by posting a URL containing the parsed NCBI accession number, eliciting a response in plain FASTA text format. Selecting a model following translation will not cause sequences to be translated or overlapped again. We perform a Smith-Waterman alignment (by calling a SmithWaterman object from BioJava) with low substitution penalties and high insertion, deletion and gap penalties using the BLOcks SUbstitution Matrix clustered at the 62% level (BLOSUM62) substitution matrix  (Henikoff & Henikoff, 1992).
Comparison to other software As mentioned above, other solutions that encompass sequence assembly already exist, and can thus be readily used for Y2H analysis. A summary of the functionalities of 2HybridTools compared to other similar programs is shown on Table  1. CAP3  (Huang & Madan, 1999) , a recognized all-purpose sequence re-assembly program and one of the most widely used tool, can be used for the purpose of clone re-construction as it implements sequencing quality cut-off, clone identification using the latter. But it cannot assemble sequence(s) containing vector sequences. CAP3 was not written specifically for the purpose of Y2H/RY2H analysis. Conversely, 2HybridTools features vector-trimming and multiple sequence Blast, which greatly facilitates clone identification. Moreover, CAP3 does not implement protein translation, which renders protein Blast impossible and thus would incorrectly align a DNA sequence containing a deletion induced by induced or spontaneous mutagenesis to a reference sequence.
DNADynamo, a commercial software suite, also supports several of the above mentioned functions but does not support multiple sequences. Furthermore, 2HybridTools provides a unique, RY2H-dedicated mutation report function, which allows pinpointing mutations that could define a surface of interaction that plays an important role in protein-protein interactions. Overall, implementation of the automated Blast, vector trimming and translation features provided in 2HybridTools allow easier clone identification compare to CAP3, and provides a unique, RY2H-dedicated mutation report function, which is absent in DNADynamo. This feature thus allows an in-depth Y2H/RY2H analysis, as detailed below.
DISCUSSION 2HybridTools improves on other non-dedicated software used for Y2H analysis software by combining features uniquely supported by some in an all-in-one fashion. To our knowledge, our software is the first to implement dedicated RY2H analysis. The alignment to a reference sequence as well as the identification of mutation positions, nature and frequencies provides a valuable tool for RY2H. Ensuring that positive sequences, which resulted in abolishing the bait/prey interaction, were in frame also allows dismissing false positives. The ability to align sequencing products from both ends when dealing with sequences longer than 500-800 bp in an automated fashion, for multiple sequences, also provides a net gain of analysis time for Y2H and RY2H end-users, as does the automated identification of multiple clones.
CONCLUSIONS A possible future development for this tool would be the automated mapping of mutations using 3D modeling software such as Rasmol and automatically generated Rasmol scripts, which would directly map mutations on a given crystal structure. In fine, our software can be used to expand current protein-protein interaction databases. Finally, as recent developments to Y2H/RY2H have been made to exploit next-generation sequencing (NGS) to sequence positive clones  (Suter et al. , 2015) , a further development to this software would entail the use of NGS sequencing results.
Availability 2HybridTools is a portable Java application which requires BioJava  (Holland et al. , 2008)  ≥ 1. 5, which is distributed with 2HybridTools and installed in the application's system classpath, i. e. , the lib directory or in the lib/ext directory of the Java runtime environment (JRE) virtual machine folder. Alternatively, BioJava is available at https://biojava. org/. 2HybridTools requires Java ≥ 1. 5. The application is entirely open source. Binaries and example files for Y2H as well as RY2H can be obtained freely at GitHub under https://github. com/pc297/2HybridTools.
The work described in this article is within the scope of METROWAMET first work package. This work package deals with the development of the essential metrological infrastructure and protocols required to assess the performance of domestic water meters under a dynamic test regime in future instead of the current stationary one. Depending on the variability in consumer behaviour one or more pre-normative reference load profiles will be derived which will serve as input for the assessment of water meters under the novel test regime. Information about the representativeness of these profiles regarding region, season etc. will be provided. One additional result will be recommendations for the time-resolved monitoring of consumption profiles. Test rigs operated with dynamic load changes based on different principles will be realised and a comprehensive inter-comparison of the rigs and rigorous uncertainty assessment of the systems carried out.
In the scope of JRP METROWAMET, LNE-CETIAT will take part, in summer 2020, in an international comparison of National Metrology Institutes and Designated Institutes, all developing dynamic flow calibrations facilities, to validate the methods developed, and submit new Calibration and Measurements Capabilities (CMCs) to the Bureau International des Poids et Mesures (BIPM) Key-Comparisons Data Base (KCDB). The transfert standards will be provided by LNE-CETIAT and will be based on an Emerson MicroMotion Elite CMF025 Coriolis mass flow meter. Consequently, the dynamic gravimetric test rig will be used to assess water meters and more generally liquid flow meters, using methodology such as provided in  [5, 6]. This will allow providing more representative calibrations to customers with complementary and useful information such as time response and accuracy against defined flow profiles and transients.
Archive Analysis Modeling the topics of a research field is a challenge in NLP (see e. g. ,  Hall et al. , 2008; Paul and Girju, 2009). Here, our objectives were two-fold: (i) to compute the most frequent terms used in the domain, (ii) to study their variation over time. Like the study of citations, our initial input is the textual content of the papers available in a digital format or that had been scanned. Over these 50 years, the archives contain a grand total of 269,539,220 words, mostly in English. Because our aim is to study the terms of the NLP domain, it was necessary to avoid noise from phrases that are used in other senses in the English language. We therefore adopted a contrastive approach, using the same strategy implemented in TermoStat  (Drouin, 2004). For this purpose, as a first step, we processed a vast number of English texts that were not research papers in order to compute a statistical language profile.
To accomplish this, we applied a deep syntactic parser called TagParser 1 to produce the noun phrases in each text. For each sentence, we kept only the noun phrases with a regular noun as a head, thus excluding the situations where a pronoun, date, or number is the head. We retained the various combinations of sequence of adjectives, prepositions and nouns excluding initial determiners using unigrams, bigrams and trigrams sequences and stored the resulting statistical language model. This process was applied on a corpus containing the British National Corpus (aka BNC) 2 , the Open American National Corpus (aka OANC 3 )  (Ide et al. , 2010) , the Suzanne corpus release-5 4 , the English EuroParl archives  (Koehn, 2005)  (years 1999 until 2009) 5 , plus a small collection of newspapers in the domain of sports, politics and economy, comprising a total of 200 M words.
2016) (Figure We see that some terms remained popular, such as "HMM," "Speech recognition," "Language Model," "Noun Phrase" or "Parser," which stayed in the top 20 terms over 20 years from 1996 to 2015 (Figure  2 ). We also studied several terms that became more popular over time, such as "Annotation" and "Wordnet," which gained a lot of popularity in 1998 when the first LREC was organized, "Gaussian Mixture Models (GMM)" and "Support Vector Machines (SVM)," "Wikipedia," and, recently, "Dataset," "Deep Neural Networks (DNN)" blooming in the top 40 terms in 2013 and "Tweet" blooming in the top 20 in 2011 (Figure  3 ). Among terms losing popularity, we may find "Codebook," "Covariance," and "Linear Prediction Coding (LPC)," which disappeared from the top 50 terms in 2005 (Figure  4 ). We also studied the changes in the use of some related terms, such as "bigram" and "trigram" that were clearly replaced by "Ngram" (Figure  5 ).
Machine Learning for Time Series Prediction We also explored the feasibility of predicting the research topics for the coming years based on the past  (Francopoulo et al. , 2016a). We used for this the Weka 9  machine learning software package  (Witten et al. , 2011). We applied each of the 21 algorithms contained in Weka to the time series of terms up to 2014 ordered according to their frequency and retained the one which provided the best results with the corresponding set of optimal parameters (especially the past history time length), after a-posteriori verification on the observed 2015 data. We then applied this software to the full set of the NLP4NLP corpus, year by year. Table  2  gives the ranking of the most frequent terms in 2013 and 2014 with their frequency, the topic predicted by the selected Weka algorithm for 2015 on the basis of the past rankings and the ranking actually observed in 2015.
Use of Language Resources The LRE Map We have similarly conducted an analysis of the mentions of Language Resources (LR) in the papers of the corpus. Language Resources are bricks that are being used by researchers to conduct their research investigations and develop their system  (Francopoulo et al. , 2016b). We consider here Language Resources in the broad sense embracing data (e. g. , corpus, lexicons, dictionaries, terminological databases, etc. ), tools (e. g. , morpho-syntactic taggers, prosodic analyzers, annotation tools, etc. ), system evaluation resources (e. g. , metrics, software, training, dry run or test corpus, evaluation package, etc. ), and meta-resources (e. g. , best practices, guidelines, norms, standards, etc. ). We considered the Language Resources that are mentioned in the LRE Map  (Calzolari et al.
, 2012). This database was produced in the FlaReNet European project and is constituted by the authors of papers at various conferences of the domain who are invited when submitting their paper to fill in a questionnaire which provides the main characteristics of the Language Resources produced or used in the research investigations that they report in their paper. The LRE Map that we used contains information harvested in 10 conferences from 2010 to 2012, for a total of 4,396 resources. After cleaning those entries (correcting the name of the resources, eliminating the duplicates, regrouping the various versions of resources from the same family, etc. ), we ended up with 1,301 different resources that we searched in the NLP4NLP corpus.
Data We should remind that we consider here the 67,937 documents coming from various conferences and journals which constitute a large part of the existing published articles in the field, apart from the workshop proceedings and the published books. Some documents are identical as they were published in joint conferences, but we must take them into account individually in order to study the flow of reuse across conferences and journals. The corpus follows the organization of the ACL Anthology with two parts in parallel. For each document, on one side, the metadata is recorded with the author names and the title under the form of a BibTex file. On the other side, the PDF document is recorded on disk in its original form. Each document is labeled with a unique identifier, for instance paper identified as number 1 at the LREC 2000 conference is named "lrec2000_1" and is reified as two files: "lrec2000_1.
ACKNOWLEDGMENTS We wish to thank the ACL colleagues,  Ken Church ,  Sanjeev Khudanpur ,  Amjbad Abu Jbara ,  Dragomir Radev , and  Simone Teufel , who helped them in the starting phase,  Isabel Trancoso , who gave her ISCA Archive analysis on the use of assessment and corpora,  Wolfgang Hess , who produced and provided a 14 GBytes ISCA Archive,  Emmanuelle Foxonet  who provided a list of authors given names with genre,  Florian Boudin , who made available the TALN Anthology,  Helen van der Stelt  and  Jolanda Voogd  (Springer) who provided the  LRE data and Douglas O'Shaughnessy ,  Denise Hurley ,  Rebecca Wollman  and  Casey Schwartz  ( IEEE ) who provided the  IEEE ICASSP  and TASLP data,  Nancy Ide  and  Christopher Cieri  who largely improved the readability of parts of this paper. They also thank  Khalid Choukri ,  Alexandre Sicard , and  Nicoletta Calzolari , who provided information about the past LREC conferences,  Victoria Arranz ,  Ioanna Giannopoulou ,  Johann Gorlier ,  Jérémy Leixa ,  Valérie Mapelli , and  Hélène Mazo , who helped in recovering the metadata for LREC 1998, and all the editors, organizers, reviewers and authors over those 50 years without whom this analysis could not have been conducted!.
005 13117 Date when the term appeared 1966 1965 1965 1980 1967 1970 1967 1967 1965 1965 Rank Term Variants of all sorts 1 Dataset data-set, data-sets, datasets 2 Metric metrics 3 Subset sub set, sub sets, sub-set, sub-sets, subsets 4 Neural ANN, ANNs, Artificial Neural Network, Artificial network Neural Networks, NN, NNs, Neural Network, Neural Networks, NeuralNet, NeuralNets, neural net, neural nets, neural networks 5 Classifier classifiers 6 SR ASR, ASRs, Automatic Speech Recognition, SRs, Speech Recognition, automatic speech recognition, speech recognition 7 Optimization optimisation, optimisations, optimizations 8 Annotation annotations 9 POS POSs, Part Of Speech, Part of Speech, Part-Of-Speech, Part-of-Speech, Parts Of Speech, Parts of Speech, Pos, part of speech, part-of-speech, parts of speech, parts- of-speech 10 LM LMs, Language Model, Language Models, language model, language models.
LaurenceUrdang (1966), The Systems Designs and Devices Used to Process The Random House Dictionary of the English Language. Computer and the Humanities. Interestingly, the author writes: "Each unit of information-regardless of length-was called a dataset, a name which we coined at the time. (For various reasons, this word does not happen to be an entry in The Random House Dictionary of the English Language, our new book, which I shall refer to as the RHD). " a statement which witnesses her authorship of the term.
60°, that makes illumination homogeneous in the field of view without the need to use a conventional condenser. To immobilize the glassbottom Petri dish containing the microchip, we designed a 3D-printed adaptor for the xy-stage. A temperature sensor is also connected to the Arduino board for the continuous recording of this parameter during the experiment. Figure  S2  shows a representative evolution of the temperature over time inside the chamber. Temperature varies according to the photoperiod in the 21. 5 ± 1. 5 °C range. The flowchart of the recording routine is shown in Fig. 5c. To ease the experiments, we developed a graphical user interface (Matlab) for the control of the LED intensity, the image timelapse parameters, and the recording of the pictures taken with the camera. Currently, the microscope is built with a 10 × plan-corrected objective with a low numerical aperture and without any   5  a Schematic representation of the in-house microscope built for long-term studies.
The white illumination is provided by a white LED controlled with an Arduino micro-controller. The LED is turned on intermittently for a short amount of time to allow the picture recording by the CMOS camera. The camera is controlled by a Matlab script and the Micro-Manager software. The microscopic setup is encased in a box equipped with a LED tile on the ceiling, used to set the experimental photoperiod (night: 8 h, day: 16 h). The chamber temperature is recorded all along the experiment using a thermocouple sensing module. b Picture of the experimental setup during an experiment. c Flowchart of the movie recording and automatic frame tagging routine. The LED tile is used to impose the photoperiodic illumination of the sample. Within each day/ night cycle, τ represents the time increment between two pictures, and is usually equal to 10 min.
t acq corresponds to exposure time of the camera and hence the time during which the Arduino-controlled LED is turned on to allow imaging. To automatically tag the pictures with their relevant photoperiodic step (day or night), a picture of the sample is recorded prior to each acquisition with the Arduino-controlled LED turned off, to measure the light intensity in the chamber. After averaging, the intensity of each picture is compared to a reference value to discriminate if the picture of the microchip has beed acquired by night or by day, and the information is stored in a metadata file for further analysis. d Time-lapse microscopic recording of the growth of P. patens in the microdevice achieved with the custom-built setup, from day 6 after immobilization. Scalebar = 100 µm tube lens. The optical setup has a field of view sufficient to observe 1 to 3 developing plants.
As Arduino boards can be easily controlled by open-source softwares such as Python, the total cost can further be reduced if needed, at the expense of a modification of the control code and the GUI. This set up allows imaging of P. patens development at high resolution and over long time periods. Following this procedure, we were able to observe different development stages of moss in controlled conditions with a minimum disturbance and maximum of survival rate. In our hand, we describe the first steps of cell wall regeneration and the first asymmetric division providing evidences that our immobilized system is suitable for time-lapse imaging of dynamic processes. We validated our system by modifying culture conditions and monitor their impact on cell elongation or gametophores formation. This procedure ensures the systematic analysis of numerous cells, during a long period of time, providing a task force for further screenings and/or statistical analysis.
Programming, Image and data analysis Image analysis was performed with the ImageJ/Fiji software  [48]. Spores and protoplasts size distributions have been measured from brightfield pictures that were thresholded, binarized, and characterized using the particle measurement tool of Fiji/ImageJ. Kymographs were built from protonema growth time-lapse recording using the Kymograph Builder tool built in the Fiji/Image J software. This work has received support of "Institut Pierre-Gilles de Gennes" (Laboratoire d'excellence: ANR-10-LABX-31 PSL, "Investissements d'avenir": ANR-10-IDEX-0001-02 PSL and Equipement d'excellence: ANR-10-EQPX-34 PSL).
We develop an open-source Python software integrating flexibility needs from Variable Renewable Energies (VREs) in the development of regional energy mixes. It provides a flexible and extensible tool to researchers/engineers, and for education/outreach. It aims at evaluating and optimizing energy deployment strategies with high shares of VRE; assessing the impact of new technologies and of climate variability; conducting sensitivity studies. Specifically, to limit the algorithm's complexity, we avoid solving a full-mix cost-minimization problem by taking the mean and variance of the renewable production-demand ratio as proxies to balance services. Second, observations of VRE technologies being typically too short or nonexistent, the hourly demand and production are estimated from climate time-series and fitted to available observations.
[Wiese et al. , 2014]  reviews existing energy models and proposes a novel open-source software for public participation in the development of strategies adapted to the German and European electricity system. Their study shows the need for tools that are both accessible  (open-source, open-data, documented, etc. )  and with a level of complexity amenable to sensitivity studies, as opposed to operational electricity-system models used by system operators. We share with the aforementioned studies the overarching goal of assessing the techno-economic feasibility of existing energy transition strategies and exploring dif-ferent energy transition solutions integrating high shares of VRE. This work differs, however, both by the methodology that is developed and by the design of the associated e4clim software.
In Section 4 we illustrate the capabilities of e4clim with an optimization of geographical distribution of wind and PV generation in Italy for historical climate conditions, with a comparison with the actual PV-wind mix. We also show how e4clim can be used to assess the impact of climate variability on the optimal mixes and the sensitivity of the results to the climate data. Conclusions are drawn in Section 5. Furthermore, an extensive supplementary material is provided. There, Appendix A details the energy and climate datasets, the production and demand models. The meanvariance optimization problem, its mathematical formulation and the algorithm are presented in Appendix B. The robustness of the numerical results is tested against observations in Appendix C. Finally, the e4clim source-code is available at https: //gitlab.