dataesr/scientific-paragraphs-categorization huggingface dataset:
presented work has received funding from the European Union Seventh Framework Programme (FP7/ 2007-2013) under grant agreement No. 606692 [HELCATS]. This study was supported by the Austrian Science Fund (FWF): [P26174-N27]. L. P. acknowledges support from the Natural Sciences and Engineering Research Council (NSERC) of Canada. V. K. acknowledges the support of the Czech Science Foundation grant 17-06818Y. This research has made use of SunPy, an open-source and free community-developed solar data analysis package written in Python [The Sunpy Community.
STEREO: http://aten. igpp. ucla. edu/forms/stereo/level2_plasma_and_magnetic_field. html MESSENGER: http://ppi. pds. nasa. gov/search/?sc=Messenger&t=Mercury&i=MAG VEX: data obtained from magnetometer PI T. L. Zhang Tielong. Zhang@oeaw. ac. at Animation of Figure 2: doi. org/10. 6084/m9. figshare. 4602253 https://www. youtube. com/watch?v=Jr4XRzGCaaQ&.
Experimental set-up COMPASS is a fixed-target experiment situated at the high-intensity M2 beam line of the CERN SPS. A detailed description of the experiment can be found in Ref. [24]. The µ + beam had a nominal momentum of 160 GeV/c with a spread of 5% and a longitudinal polarisation of P ≈ -0. 8 known with the precision of 5%. The data were taken at a mean intensity of 3. 5 × 10 8 µ/spill, for a spill length of about 10 s every 40 s. A measurement of the trajectory and the momentum of each incoming muon is performed upstream of the target. The momentum of the beam muon is measured with a relative precision better than 1%. The beam traverses a solid-state ammonia (NH 3 ) target that contains transversely polarised protons. The target is situated within a large aperture magnet with a dipole holding field of 0.
Systematic studies In order to estimate the systematic uncertainties of this measurement the following contributions were examined: i) false asymmetries, ii) a possible bias of the applied estimator of the asymmetries, iii) the sensitivity to the background parameterisation, iv) the stability of asymmetries over data taking time, v) the compatibility between the three mean asymmetries obtained by averaging the one-dimensional distributions in Q 2 , x Bj and p 2 T , vi) the uncertainty in the calculation of dilution factor, beam and target polarisations. i) False asymmetries are extracted by analysing subsamples of data with the same spin orientation of target protons. In such a case, non-zero values of azimuthal asymmetries would indicate an experimental bias. In particular, false asymmetries provide a test of validity of the reasonable assumption, see Eq.
(  25 ), i. e. whether during data taking the acceptance has changed in a way that influences the extraction of asymmetries. False asymmetries are determined in two ways: by using the data from the upstream and downstream cells, as well as by the artificial division of the central cell into two 30 cm subcells. This test is performed without separation into signal and background asymmetries, and independently for the ranges |E miss | < 3 GeV and -3 GeV < E miss < 20 GeV. The resulting false asymmetries are found to be consistent with zero within statistical uncertainties. Nevertheless, an upper limit on the false asymmetries is estimated to be 0. 01  [26]  at the level of raw asymmetries defined in Eq. (  23 ). This estimate represents a conservative limit for breaking the reasonable assumption given by Eq.
The estimation yields typically a systematic uncertainty of 30% of the statistical one. iv) The data stability over time is examined by comparing asymmetries extracted from two consecutive subsets of data taking. A division into a larger number of subsets is not possible due to limited statistics. All asymmetries extracted from the two subsets of data are found to be compatible within statistical uncertainties. v) The extraction of asymmetries may be unstable due to limited statistics. The effect is examined by comparing the asymmetries extracted from the entire data sample with those obtained from averaging the results obtained in bins of kinematic variables Q 2 , x Bj or p 2 T , which are used for the extraction of final results, see Fig. 8  (right). The comparison indicates a bias that is estimated to be up to 20% of the statistical uncertainty.
l Supported by the  DFG Research Training Group Programme 1102 "Physics at Hadron Accelerators " m Supported by the  German Bundesministerium für Bildung und Forschung  n Supported by  EU   FP7  ( HadronPhysics3 , Grant Agreement number  283286 ) o Supported by  Czech Republic MEYS  Grant  LG13031  p Supported by  SAIL (CSR), Govt. of India q Supported by  CERN-RFBR  Grant  12-02-91500  r Supported by the  Portuguese FCT -Fundacão para a Ciência e Tecnologia, COMPETE  and QREN, Grants  CERN/FP 109323/2009 ,  116376/2010 ,  123600/2011  and  CERN/FIS-NUC/0017/2015  s Supported by the  MEXT  and the  JSPS  under the Grants No. 18002006 , No. 20540299  and No. 18540281 ;  Daiko Foundation  and Yamada Foundation t Supported by the  Israel Academy of Sciences  and Humanities u Supported by the  Polish NCN  Grant  2015/18/M/ST2/00550.
Programmatic development has proceeded in the past few years at the Zebrafish International Resource Center (ZIRC) housed at the University of Oregon in Eugene, Oregon  (Varga and Westerfield, 2011). Currently the ZIRC holds the largest biomedical collection in the US with around 60,000 samples from zebrafish representing some 9000 lines and 26,000 characterized single alleles. To exclude redundancies, a curator-approved name must be established with the Zebrafish Model Organism Database called ZFIN (www. zfin. org). A similar, but smaller repository is being developed for live-bearing fishes held at the Xiphophorus Genetic Stock Center (XGSC) housed at Texas State University in San Marcos, Texas (http://www. xiphophorus. txstate. edu/). A major national-level advance for aquatic germplasm resources came in 1990 when national legislation was passed that provided the US Department of Agriculture (USDA) with a mandate to conserve animal genetic resources  (Blackburn, 2011).
The current inventory is maintained in a database that can be viewed at: www. ars-grin. gov:8080/j2ee/nagppub/jsp/nagp/drilldown2. jsp. At present the core collection at NAGP has an inventory of 32,500 samples from around 3,000 individual animals representing major groupings of freshwater and marine fishes, and marine invertebrates. Aquatic species comprise 4. 4% of the entire NAGP collection based on number of samples, but comprise 15% of the entire collection based on number of individuals. This program, database, its collection, and core capabilities are a tremendous resource for aquatic germplasm conservation in the United States, and has been developing relationships with other countries such as Brazil and Canada. Samples from other collections, such as those mentioned above from the LSU Agricultural Center, USFWS, XGSC, and ZIRC are routinely transferred into the collection at NAGP.
Large collections such as those from the Nez Perce tribe, University of Idaho and Washington State University (some 50,000 samples) of chi-nook salmon and rainbow trout (also mentioned above,  Cloud et al. , 2011)  have been transferred to NAGP because resources became unavailable for archival storage at the facilities that performed the original collections. These samples are being catalogued into the database for inclusion in the core collection (H. Blackburn, personal communication). The NAGP can provide a useful model for aquatic species in general for the development of an integrated repository system that incorporates a single or a few well-equipped, experienced central facilities that carry out most of the cryopreservation work using samples or broodstock sent to the facility  (Caffey and Tiersch, 2011).
Action Purpose Development of the technical capabilities, and establishment of standardized and streamlined procedures. High-throughput processing and reliable quality control of samples. Development of equipment, devices and facilities. Automated handling of small sample volumes. Establishment of quality control protocols and standardization or harmonization of protocols, labelling, terminology and reporting of results. Establish databases, development of best practices manuals or other guidelines. Development of central facilities that have strong operational capabilities. Develop cooperation with other organizations and facilities. These relationships can include sharing of samples, capabilities and expertise. Establishment of training programs. Education of personnel from different user laboratories for procedural efficiency.
Acknowledgments The authors thank  Dr E. Kopeika ,  Dr M. Flajšhans ,  Dr B. Dzyuba ,  Dr S. Rakers ,  Dr A. Ciereszko  and  Dr R. Geisler  for their help in tracking the history of the European cryobanks. This work was partially funded by  COST Office (Food and Agriculture COST Action   FA1205 : AQUAGAMETE) and projects  KLING 31-03-05-FEP-73 ,  CRIOBIV 31-03-05-FEP-59 ,  REPLING 31-03-05-FEP-69  financed by  Portuguese PROMAR program ; grants  AGL2011-27787 ,  AGL2014-53167-C3-3-R  and  AGL2015-68330-C2-1R  financed by  MINECO-FEDER, Spain ;  NKFIH  grant  K109847  and  9878-3/2016/FEKUT  of the  Ministry of Human Resources of Hungary ;  French program  " Investissements d'Avenir "  ANR-11-INBS-0003  ( CRB-Anim 2013-2019 ), and  Creche  ( Ofimer 136/08/C ) and  CRB Anim  ( ANR-11-INBS-0003 );  National Institutes of Health of U.
S. ( 5R24OD010441 );  New Zealand Ministry of Business, Innovation and Employment (CAWX1315) ; Brazilian funding agencies  FAPEMIG  ( PPM 00038-13 ) and  CNPq  ( 474001/2013-0 ); and  FCT postdoctoral fellowship  ( SFRH/BPD/48520/2008 ) funded by  Portuguese National Funds (MEC). Development of functioning storage repositories. Provide rules for use and disposal of samples with appropriate security and backup for basic services. Implementation of archival-quality labelling and creation of robust databases. Handling biological information and maintaining inventory and identification of sample locations. Integration of sperm repository databases Exchange information with existing databases for biological and genetic information of strains or lines.
Acknowledgements. We wish to thank  Dr. Roger Chammas  for helpful suggestions and  Dr. Jürg Tschopp  for providing CTL granule preparations. TC, NJV and MY were recipients of PhD fellowships from  Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, Brazil). This work was supported by grants from the  Conselho Nacional de Desenvolvimento Científico e Tecnológico  ( CNPq-31194-/2015-8 ) to MDB,  Investigator Award  from  Science Foundation Ireland  to  SJM, Agencia de Promoción Científica y Tecnológica  ( PICT 2012 ;  2014 ) to GAR and  FAPESP  ( 2014/16352-6 ) to GPAM.
New in silico and in vitro options to assess T cell activation 2. 4. 1 In silico methods to predict immunogenicity The available in silico methods aim to predict the interactions of specific peptides with HLA molecules. The principles of the methods include peptide alignments, scoring matrices, structural analysis and learning algorithms. The advantages of in silico methods are that they are easy to use, not expensive and available via web resources e. g. the Immune Epitope Database (www. immuneepitope. org). In silico methods are commonly used in early steps of drug development for preliminary immunogenicity assessment and T cell epitope mapping. The available methods have shown very good allele-dependent predictions of peptide binders. Moreover, they have been able to predict CD4+ T cell epitopes  (Wang et al, 2008).
, 1993; Burel et al. , 2017). It has been hypothesized that this may be linked to the T cell precursors available in the T cell repertoire of an individual blood donor. However, the exposure conditions play a crucial role as well, as it is generally agreed among the scientific community that if the dose of a strong or extreme sensitizer is high enough nearly all donors will be sensitized  (Friedman et al. , 1983). While exposure to a weak or moderate sensitizer will only sensitize a select number of donors with a larger range of responses. To deal with the wide T cell response spectrum, it was proposed that the inter-donor variability could be mapped in a database by testing the T cell response magnitude for a large amount (>50) of blood donors reflecting the most represented HLA haplotypes of the human population.
4 The importance of T cell-based assays for the development of integrated testing approaches It is commonly agreed that the assessment of skin sensitization potential without animal testing requires a combination of alternative methods in integrated approaches  (Jowsey et al. , 2006; Reisinger et al. , 2013; Ezendam et al. , 2016; Jaworska, 2016). The AOP plays an important role in the development of integrated approaches, because it provides a scientific framework to cover the mechanistic steps and KEs of the skin sensitization process. Several DAs have been submitted to the OECD, each integrating data from non-animal test methods that address one or more AOP KEs  (OECD, 2016). The Cosmetics Europe Skin Tolerance Task Force and the National Toxicology Program Interagency Center for Evaluation of Alternative Toxicological Methods (NICEATM) have evaluated several of these DAs using a comprehensive database with non-animal test method, LLNA and human skin sensitization data  (Hoffmann et al.
g. supporting the safety assessment of novel substances and challenging weak and non-sensitizing substances with equivocal test data from other assays, are conceivable. A recent publication by  Vukmanović and Sadrieh (2017)  described additional mechanisms for the induction of skin sensitization, which are independent from the current AOP involving the presentation of hapten-carrier peptides to T cells. The existence of these suggested mechanisms (incl. pharmacological interactions with immune receptors, ALTEX Online first published October 2, 2017 doi:10. 14573/altex. 1709011 10 HLA groove blockade, peptide exchange and cryptic epitope presentation) could explain the imperfect concordance between in vitro assay data based on the hapten/carrier concept and animal/human reference data. The authors pointed out the importance of developing and applying T cell-based assays, as they are the only downstream test methods able to detect immunogenic potential resulting from all possible mechanisms of skin sensitization, including those not yet covered by the current AOP.
In Tier 2, more complex T cell-based assays could provide more detailed mechanistic information on the antigen-specific T cell response at multiple concentrations using cells from responding donors in Tier 1. The assays could evaluate different parameters including the T cell receptor repertoire, HLA type, presented peptide by DCs and T cell subset activation. By testing substances with different properties in multiple human donors, a database could be established that covers a wide range of substances. The immune response data in combination with exposure information and considerations of genetic and environmental factors could be used to assess the allergenicity of a given substance.
By testing substances with different properties and potencies, a database could be established that covers a large applicability domain (e. g. cosmetic ingredients). This tier will provide information on the in vitro concentration at which a substance will induce an immune response, the type of response and strength of the response via comparison with benchmark substances. Such information could be used to define a safe exposure level. This implies that an agreed way to translate results from the in vitro assays (e. g. effective concentration or response frequency) to a metric value that can be used to define a safe human dose would be available. To learn how the information from T cell-based assays could support safety assessment it was recommended to perform case studies on reference sensitizers.
The first entity Place owns two properties that correspond to its name and its upper place. The second entity Instrument owns three properties: its name, its place and its type i. e. sensor or actuator. These two entities will be stored into a database and instances of such entities will be introduced from SAN models. Another entity TimeSpan is added into the target model with two properties started and stopped which types are timestamps. This entity represents a span of time that will be used as the data structure of request messages that aims at retrieving data of instrument instances. However, this entity TimeSpan will not be stored into a database. In addition, the fixed part of target models is composed of several abstract components which are provided by Java libraries. The first two components concern data acquisition by the SCADA application from instrument instances: the first one called TimeStamper sets the time-stamp of object data, the second one called HibernateCreator inserts object data into a database.
The last six components concern data retrieving by the users from the SCADA application: Two components called JsonDeserializer and JsonSerializer in charge of, respectively, decoding or coding messages in JSON format are introduced into target models. A component called FeatureGrabber able to extract data features is introduced into target models in order to extract started and stopped values from TimeSpan objects. Three components provided by a REIFIER component library for Hibernate are also introduced into target models. The first one called HibernateCriteriaProvider prepares SQL statements from a given entity. The second one called Hi-bernateTimeSpanFilter inserts SQL restrictions from the grabbed started and stopped features from TimeSpan objects. The third one called HibernateListRetriever executes SQL statements and provides data lists.
e. its type, name and place; • an entity that complies the instrument aspect i. e. with properties that correspond to the instrument aspect features which instances are stored into a dedicated table of a database; • a compound component composed of the instrument component that provides instrument data, the TimeStamper component, the HibernateCreator component; • a service that wraps the previous compound component; • a service that receives a message that corresponds to a TimeSpan object data and that provides the list of instances from the dedicated database table of the instrument entity for the requested span of time. Finally, process transformation consists either of introducing the process component at the end of the compound component transformed from the instance if this process is triggered on an event, or of introducing a resource that wraps the same compound component within a Java thread if this process is triggered at fixed-rate.
This clientside application is unique as the code generation complies to the rules explained in section 5 and offers the three services of the fixed transformation that help to navigate through out sensor and actuator networks uniformly. SCADA Application. The generated JEE application is a basic SCADA application. In fact, data acquisition is ensured as the generated JEE application is able to store sensor and actuator data into a database by the means of the transformed instance compound component and the transformed service that wraps the previous component. Moreover, it is able to provide these data by chunks of time intervals by the means of the other transformed service. Such a service enables supervisory control as SCADA applications users then can visualize data and, if needed, then launch some operations by the means of processes whose trigger is a user one.
Such controls can be automatized by processes either triggered on instance communication or at fixed-rate. The code generation powered by the REIFIER tool also provides trendy SCADA application features such as service-oriented application, generic client-side application interfaces as figure  5 , relational database persistence as well as NOSQL management for big data processing. Nevertheless, it doesn't allow to manage SQL and NOSQL databases alongside. However, the generated JEE application is not a complete SCADA application in the sense that it lacks of auxiliary functionalities. Users, roles and grants are not taken into account. Indeed, this approach is devoted to one sort of users: administrators of sensor and actuator networks. That should be required in order to adapt SAN views according to user roles.
SCADA Engineering. The code generation carries out most of the SCADA application components. It carries out application architecture and logic as well. This makes then possible to focus more on model design than application development. Development merely consists either in communication modules with sensors or actuators or in control operations for specific application behaviour. For example, listing 2 illustrates the Java implementation of a HTTP-based sensor communication component that retrieves data from a luminosity sensors. It's a pull communication component. In fact, this sensor component implementation rely on a underlying data type, here hidden, called LuxSensorMeasurement. It consists of an in-Listing 2: The atomic component LuxSensor. @Parameter ( name= " u r i " , t y p e = " u r i " ) p r i v a t e URI u r i ; @Parameter ( name= " t y p e " , t y p e = " t y p e " ) p r i v a t e S t r i n g t y p e ; @Parameter ( name= " data " , t y p e = " s t r i n g " ) p r i v a t e S t r i n g data ; public void doProcess ( H t t p S e r v l e t R e q u e s t request , HttpServletResponse response ) throws S e r v l e t E x c e p t i o n { I n t e g e r l u x = t h i s.
This atomic component complies the Component interface and can be embedded into a composite component. In fact, the SCADA application code geneartion of ICAM smart lighting demonstrator provides a composite component called LuminosityAComponent that corresponds to the model instance luminosity-a of the place c115a and that embeds the atomic component LuxSensor. Listing 3 illustrates how such atomic components are compound into a composite component. Other types of communication can be handled: the pull and pooling communications. Pull commu-nication component merely consists in retrieving data from sensors and in populating an instance of the data structure associated to the sensor. Pooling communication consists, on the one hand, in a push-like communication component and, on the other hand, in a resource that initializes the connection with the sensor.
The idea is to divide the responsibility in dividing the expert skills by requiring from them only their specific knowledge. Thus, one large model is difficult to visualize, maintain, and analyze taking into account evolution. Different views onto the feature model or the combination of two or more features models, one for each domain, may solve some of the existing problems. Testing. The step of verification and validation of distributed systems is another considerable challenge  (Yang et al. , 2014). In  (Süß et al. , 2008)  approach to the problem of testing a SCADA thanks to Modelica, an object-oriented mathematical modelling lan-guage for component-oriented modelling of complex physical systems. It is an open standard and implementation, and provides a rendering of its input language in Ecore, the metalanguage of the Eclipse Modeling Framework (EMF).
3 Radioactive Decay Data Library. Other sources of nuclear data include 900 or so radionuclides converted from the Evaluated Nuclear Structure Data File (ENSDF), 500 from two UK libraries (UKPADD6. 12 and UKHEDD2. 6), the IAEA Actinide Decay Data Library, with the remainder converted from the NUBASE evaluation of nuclear properties. Mean decay energies for a number of radionuclides determined from total absorption gammaray spectroscopy (TAGS) have also been included, as well as more recent European results from TAGS measurements performed at the University of Jyväskylä by groups from the University of Valencia, Spain and SUBATECH, the University of Nantes, France. The current status of the DDEP collaboration and the JEFF Radioactive Decay Data Library will be presented.