dataesr/scientific-paragraphs-categorization huggingface dataset:
e. , that some instance exist. Because of this focus, the object manipulated in these works is the metamodel itself. Like depicted in Figure  1 , we aim at being able to mechanize semantics and type systems of the language, hence properties of instances of the metamodel. So the metamodel has to be transformed into a type, such that terms (or instances) of that type can be manipulated. Some previous works have studied such transformations:  (Djeddai et al. , 2012)  have defined a bidirectional transformation between Ecore and Isabelle's inductive type. To obtain a bijection, they restrict to single-level single inheritance: each abstract class A is mapped to an inductive type t; and each concrete class C is transformed to a constructor c of the inductive type a mapped from the super class A of C.
A RUNNING EXAMPLE To illustrate the discussion in subsequent sections, we use the metamodel for λ terms of Figure  2. A File is composed of Definitions, each containing a Term. A term is either an Abstraction, an Application or a Variable. In order to avoid issues related to naming and scopes, the abstract syntax assumes variables 1 Unless a predefined super class implicitly generalizes any class, for instance, like Ecore's EObject class. In this case, all the reference types are generalized to EObject. have already been resolved, hence Variable has a non-containment reference to Binder, which is either an abstraction or a definition. Classes are generic such that terms can be annotated, e. g. , with types. We expect that our transformation generates the following Coq script (or equivalent), i.
THE TRANSFORMATION Ecore is an object-oriented language for metamodels. A metamodel consists in some classes, organized into hierarchically-nested packages, and spread over one or several Ecore files. A specialization/generalization relationship provides inheritance and subtyping. Any class can specialize one or several general classes. Some classes can be abstract, meaning that they cannot be instantiated. Each class contains structural features (or fields) which are further refined as either attributes (store plain-Java objects only) or references (store Ecore objects only). References can be containment or non-containment references. A model, or instance of a metamodel, is therefore a tree of objects (following the containment references) with additional non-containment references. Derived features have their value computed on-thefly; transient features are omitted from XMI serialization; volatile features are not stored in the in-memory instance.
It would be tempting to map packages to modules. However, consider for instance an abstract class A in package p1, specialized by concrete class C of package p2. Class C maps to constructor C that belongs to type A, which in turn is mapped from class A. If packages were mapped to modules, type A should be in module P1 and constructor C should be in module P2. This is impossible since constructors belong to types, not to modules. To avoid this issue, step 1 removes packages and gathers all the dependencies within a single package. Figure  4  shows an excerpt of the metamodel of Figure  2  after step 1. The metamodel is almost unchanged. Still, classes from the Ecore metamodel are pulled into the package, starting with EObject because it is used as the raw type of type in Term. Because of boundName in Binder, EString is pulled too.
DISCUSSION Except for the limitations listed in Section 6, Ecore is fully supported. For this reason, the transformation cannot be bijective. Figure  8  shows a trivial example of two different metamodels that result in identical Coq scripts. Indeed, at step 6 , all the structural features are pulled from classes to constructors, without tracking the class they originate from. We motivate this choice by two arguments. First, any instance of one of these metamodels is also an instance of the other one. Indeed, in both cases, models contain only instances of B, which contain one member x that is an integer. Second, our transformation is intended at allowing the language designer providing formal specifications, proving properties of these specifications, and setting up an infrastructure for proof-carrying code.
As long as code and proofs written in the formal world need not be extracted back to Java and EMF, having a bijective transformation superfluously restricts the set of eligible metamodels. Steps 1 , 5 , 8 , 10 and 11 are bijective. No fundamental issue prevents step 4 from making this step bijective: more accurate types can easily be generated for collections, such that exact multiplicity and flags can be fully recovered. All the other steps are intrisically surjective: step 2 because there is no uniqueness of Ecore's representation of types, especially for non-generic types; step 9 because Ecore does not take into account declaration order; step 3 because it erases behavioral elements of the metamodel; steps 6 and 7 because they discard information about inheritance. Only the first steps 1 to 4 of the transformation are specific to Ecore.
IMPLEMENTATION The transformation supports all the syntactical constructs of Ecore  (Steinberg et al. , 2009) , but it assumes that the source metamodel validates correctly against all the Ecore constraints implemented in EMF, including the constraints at the warning level. Some of the patterns that are interpreted by Ecore's supporting tool such as the Java code generator are not recognized: hash maps are treated like lists of pairs; sets and bags are mapped to lists. Step 4 can easily be extended to specialize the generated type in these specific cases. Feature maps, that is, groups made of a n. * attribute f and of derived volatile transient features s that subset f by key s, are ignored. Any feature map f is transformed into a list of items; and subset features s are eliminated at step 3.
The deep copying mechanism can be customized in two ways: every time an object is copied, a hook allows customizing the class of the resulting object depending on the class of the source object; and for every feature in the target class, a hook allows customizing how the value is obtained. By default, the value of a feature having the same name in the source object is copied. The Java code for steps 1 to 9 contains 1300 SLOC. The QVT-Operational script for step 10 is made of 185 SLOC. The Acceleo template for step 11 contains 40 SLOC. The code is available at https://bitbucket. org/jbuisson/ecore2coq.
VALIDATION First we ensure the transformation produces correct types, i. e. , that the produced scripts compile. We fetch (meta)metamodels from four third-party open-source projects: EMF, Eclipse's OCL, Xtext extras, and Dresden OCL. Then we consider all the 151 (meta)metamodels that pass Ecore's validator. This test suite contains synthetic cases, as well as realworld (meta)metamodels such as Ecore, UML and OCL, containing up to 247 classes, each having up to 8 super types and up to 11 levels of inheritance. The suite covers all the synctactical constructs of Ecore. Of the resulting Coq scripts, 147 scripts compile correctly; Coq runs out of memory for 2 of them; it issues a "non strictly positive occurrence" error for 2 scripts. Examination of the erroneous scripts highlights the anti-pattern of Figure  9.
Coq's error can be avoided by using the definition T' instead of T, but Coq has restrictions on this form for mutually-recursive definitions. This anti-pattern needs further investigation. Second we ensure that the generated types are actually usable in the context of proof-carrying code  (Necula, 1997) , following the approach depicted in Figure  1  in the context of SosADL  (Oquendo et al. , 2016). Given a concrete grammar, Xtext  (Bettini, 2013)  generates an Ecore metamodel that contains 85 classes, and which is in turn transformed to Coq types. We use these Coq types to mechanize the type system. Then we design an ad-hoc transformation that transforms instances of the metamodel (SosADL architecture descriptions) to Gallina terms, whose types are the generated Coq types. We instrument SosADL's type checker to produce a Gallina term that witnesses the architecture description is well typed.
The fact that Coq successfully compiles the generated proof term shows that the transformation produces correct and usable types. In this paper, we propose a transformation from Ecore metamodels to inductive types. This transformation allows to set up a model-driven language engineering chain, e. g. , involving Xtext and, at the same time, to specify the language using a proof assistant, such as Coq, and then prove properties of this specification. In comparison to previous work  (Djeddai et al. , 2012; Klint and van der Storm, 2016) , our transformation has fewer constraints on the source Ecore metamodel and ensures stronger typing in the generated inductive types, but it is not bijective. To validate our proposal, we implement the transformation using QVT-Operational, Acceleo, and EMF-and-Java.
Then we fetch 151 (meta)metamodels, which contains both synthetic and real-world (meta)metamodels coming from public repositories. 147 of the generated Coq scripts compile successfully; 2 make Coq run out of memory; the last 2 ones need further study in order to handle the corresponding specific pattern. To our knowledge, no previous work discusses nor deals with this pattern. In future work, we will study how additional parts of such infrastructure can be automatically derived from the Ecore metamodel, such that model-driven engineering better integrates with proof assistants.
sonnei (n = 187) and S. flexneri 2a (n = 179) from the UK sampled between 2008 and 2014. Here, in this allied study, we integrate this new cross sectional data from the UK with existing reference datasets of Shigella WGSA subtypes and AMR determinants from around the world to identify those responsible for shigellosis in the UK. By providing the context necessary for interpreting national surveillance patterns, we reveal important qualitative insights on the importation and domestic transmission of Shigella in the UK, as well as on the prevalence and mobility of AMR among these globally-important pathogens.
flexneri 2a representative subsample, and investigate geographical associations. Specifically, this included representatives of all PGs (n = 9) and all PG3 S. flexneri 2a isolates (n = 69) (Supplementary Data). Bioinformatic analyses. DNA was extracted and isolates whole genome sequenced as previously described  13. Whole genome sequence phylogenetic trees were constructed through mapping of sequence data (using smalt, http://www. sanger. ac. uk/science/tools/smalt-0) to reference genomes (S. flexneri 2a 2457 T, S. sonnei 53 G), followed by removal of mobile (plasmids, insertion sequences, other described mobile islands  6, 24  ) and repetitive elements (through removal of known repeat regions and repeat mapping discard), and sites of recombination (using gubbins  25  ), followed by extraction of variable sites (using snp_sites  26  ).
Acknowledgements The authors are grateful to the administrative, sequencing and pathogen informatics teams at the  Wellcome Trust Sanger Institute  and helpful scientists who commented on the work in progress during formal and informal presentations. The authors also thank  John Were  for his contribution to managing epidemiological data. This work was supported by  Wellcome Trust  grant number  206194 , and KSB is supported by a  Wellcome Trust   Clinical Research Career Development Fellowship  ( 106690/A/14/Z ).
4 I ). Chromosome breaks were never observed in oocytes coming from Plk4 flox/wt ; Cre -mice or Plk4 wt/wt ; Cre + female mice (our negative controls that do not overexpress Plk4) or in the mCherry-Plk4 cRNA-injected oocytes (Fig. S2 C ). Furthermore, we know that recombination and repair of the mCherry-Plk4 transgene did happen in all Plk4 OE oocytes from both lines, since 100% of them were positive for mCherry-Plk4. Therefore, it can be excluded that the break took place early on during oocyte growth. Our data strongly support Plk4 OE oocytes were imaged directly upon isolation. Gray, chromosome; pink, kinetochores; green, MTs. MII, metaphase II. (B) Upper panels correspond to the merge of transmitted light images with the mCherry-Plk4 fluorescent image in cRNA-injected (left) versus transgenic Plk4 OE (right) oocytes observed in prophase I (mCherry-Plk4, magenta).
Plk4 and pericentrin levels in Plk4OE oocytes over endogenous protein in control oocytes were quantified on summed Z-projections (70 Z, spaced every 0. 5 µm, arbitrary units). SIM acquisitions were treated in Fiji after reconstruction and realignment then rendered in Imaris 3D viewer after calibration. The total and local MT fluorescence signal intensities were measured in oocytes expressing EB3-GFP on summed Z-stack projections (six Z planes spaced every 4 µm). Timing of bipolarization was assessed in oocytes expressing EB3-GFP imaged at 10-min intervals. Statistical analyses were performed using Graphpad Prism 5. 0 software. ns, nonsignificant (P > 0. 05); *, P < 0. 05; **, P < 0. 01; ***, P < 0. 001; and ****, P < 0. 0001. Online supplemental material Fig. S1  shows quantification of the pericentrin and Plk4 signals in the whole oocyte and SIM acquisition of aMTOCs in Plk4 OE oocytes.
Acknowledgments We thank  Ludovic Dumont  and  Anchi Chang , masters students, for their help at the beginning of the project;  Carole Pennetier  and  Manon Chartier  at the  Curie Institute for genotyping; Adel Al Jord from our laboratory  for critical reading of the manuscript;  Lucie Sengmanivong  from the  Nikon Imaging Centre at Institut Curie-Centre National de la Recherche Scientifique (Paris, France );  Guillaume Halet  for the gift of the HistoneH2B-GFP plasmid;  Andrew Holland  for the gift of the anti-Plk4 antibody; and  Katia Ancelin  and  Edith Heard  at the  Curie Institute  for the DNA-FISH protocol. M. Łuksza was supported by a  Fondation ARC pour la Recherche sur le Cancer  fellowship. This work was supported by a grant from the  Ligue Contre le Cancer  ( EL/2012/LNCC/ MHV ), the  Agence Nationale de la Recherche (ANR-DIV ACEN  to  M.
-H. Verlhac  and  R. Basto ,  14-CE11 ), a  Fondation pour la Recherche Médicale Label  ( DEQ20150331758  to  M. -H. Verlhac ), and an  Institut National du Cancer grant  ( PLB IO 2016-270-TRAN ). This work has received support from the  Fondation Bettencourt Schueller , support under the program " Investissements d'Avenir " launched by the  French government  and implemented by the  Agence Nationale de la Recherche  ( ANR-10-LABX-54   MEMO LIFE ,  ANR-11-IDEX-0001-02 PSL* Research University ). The work was also supported by  Biotechnology and Biological Sciences Research Council  funding to  K. T. Jones  (Mechanisms of DNA damage and repair in mature oocytes, BBS RC,  BB/L006006/1 ) and  American Institute for Cancer Research  (now  Worldwide Cancer Research ;  13-0170 ) to  V. Marthiens  and  R.
We highlighted a correlation between ADC measurement error and the distance of ROIs from the magnetic centre. The error increased with bottom-shift (up to 24 % when located 8 cm out of isocentre). Conversely, with regard to lateral-shift we found no correlation with the magnitude of errors. This result can be explained by non-uniformity of gradient-fields. As we found a correlation between variability of ADC assessments and contour segmentations, we concluded that partial volume effect was a major contributor to the variability. A visual review of outliers in clinical data confirmed high variation of signal intensity in the tissue surrounding these lymph nodes. Consequently, even a small variation in segmentations led to a significant modification of ADC assessments (Fig. 6 ) We recommend measuring ADC by drawing ROIs smaller than the anatomical limits of the area of interest.
How to optimize segmentation margins must be further investigated. We found excellent repeatability and good reproducibility. This suggest that, if ADC intended to evaluate response to treatment, changes inferior to [-13 %; +15 %] may not be clinically relevant. However, longitudinal reproducibility would require further clinical studies to take into account all variability factors. According to our dataset, the averaged ADC value for healthy subject's cervical lymph nodes 0. 87. 10 -3 ± 0. 12. 10 -  mm 2 /s. Our results are well supported by the literature. Regarding the correlation between variability of ADC assessments and contour segmentation, heterogeneous segmentation methods are available but several studies documented the reproducibility issues  [23] [24] [25]  affecting these methods.
This statement is sustained by the initiation of spermatozoa movement following pHi alkalinization Fig. 4. Effects of ion deprivation on percentage of motile spermatozoa and VAP after 1 and 5 min after activation. Motile spermatozoa (A, P=0. 006 at 1 min and P=0. 000 at 5 min after activation), VAP (B); VAP, Velocity of the Average Path. VAP in Na + -free ASW was not measured because of low number of motile spermatozoa. No movement of spermatozoa was observed in ion-free ASW. Sperm VAP was not significantly affected by a lack of Ca 2+ , K + or Mg 2+ in ASW. ASW, artificial seawater; different letters refer to significantly different results (mean±s. e. m. ; lower case letters, 1 min after sperm activation; upper case letters, 5 min after sperm activation; n=5 oysters). Data were compared using one-way ANOVA and Fisher a posteriori test.
Statistical analysis Data were presented as mean±s. e. m. Percentage data were arcsin square-root transformed. Normality (Shapiro-Wilk test) and homogeneity of variances (Levene's test) were verified. Data were compared using one-way ANOVA. When significant differences were observed, a Fisher a posteriori test was used. Experimental results were considered significant at P<0. 05. Statistical analyses were performed using Statistica 6 software (StatSoft). *concentration of the ion studied in ASW is low and did not need to be substituted using choline chloride to maintain ASW osmotic pressure.
Funding This work was supported by  CRB-anim  ( ANR-11-INBS-003 ) and Reproseed ( FP7-KBBE-2009-3 ). Additional funding (to M. S. ) was provided by  JihočeskáUniverzita v C ̌eských Budějovicıćh  and the  South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses (CENAKVA ,  CZ. 1. 05/2. 1. 00/01. 0024 ).
One recording was obtained at end of March, six in April, two in June, one in July and one in August (Table  1 ). Data were acquired using a HTI-92-WB hydrophone (High Tech Inc. , Long Beach, MS, USA) with a sensitivity of À155 dB re 1 V/lPa and flat frequency response from 2 Hz to 50 kHz connected to an EA-SDA14 compact autonomous recorder (RTSys â , France). The device was 1 RMC Water Agency/Androm ede Oc eanologie, data from the cartography platform Medtrix (www. medtrix. fr) bottom-moored with the hydrophone at 1 m from the seafloor (Fig. 1 ). It acquired sounds continuously at a 176 kHz sampling rate and 24 bit resolution. At each recording date, the recorder was submerged in the afternoon and recovered the next morning for a duration of at least 14 h. Recordings were made during the night because many temperate fishes usually vocalize and produce choruses predominantly at night  (Cato 1978; McCauley and Cato 2000).
Data diagnostics for acoustic feature identification Long-term spectrograms of the entire night (12 h) and around dusk (5 h) were built with routines developed on Matlab â (R2012a) to visualize biogenic sound production. These long-term spectrograms, combined with a more detailed manual scrolling of the audio files, were used to explore P. oceanica soundscapes, assess the quality of the recordings and more particularly, the presence of low-frequency noise that acoustically masks fish sounds  (Radford et al. 2014). Based on these diagnostics, one particular sound, aurally sounding like a /kwa/ (Audio S1), appeared to potentially meet the criteria proposed for acoustic monitoring features. We focussed on this particular sound to assess whether it represents an appropriate candidate for PAM of Posidonia meadows.
Sound selection The long-term spectrograms were used to identify the time period of highest abundance of the /kwa/ that was used as subsampling unit for manual sound selection. Sound selection was carried out using RavenPro Sound Analysis Software 1. 5 (Cornell Lab of Ornithology, USA) on audio files sub-sampled at 4 kHz. Each identifiable / kwa/ during 2 h of the peak sound production period (i. e. the chorus) was manually selected in order to carefully describe sounds and their variability in detail. To validate the temporal subsampling method, the acoustic features of the /kwa/ selected during the 2-h subsampling  period were compared to the ones selected during the rest of the night (files from the randomly chosen meadow e). Paired Student's t-tests with a significance level (a) of 0. 05 were used to test for differences.
Sound description Acoustic features typically used for fish sound description were extracted from the sound selections (Fig. 2 ). These included call duration, peak frequency (i. e. dominant  frequency), pulse period and number of pulses (e. g. Amorim et al. 2008 ). However, these features do not allow to describe the complexity and diversity of the signal. Consequently, additional acoustic features were considered, including parameters used for characterizing harmonic or pseudo-harmonic 2   (Watkins 1968 ) sounds emitted by anurans and primates (e. g. Gerhardt 1981; Price et al. 2015)  and for describing transient sounds  (Tucker and Brown 2005). Some features (e. g. duration, bandwidth, minimal and maximal frequency) were calculated within the selection box using RavenPro, while most features were extracted from the selection box using custom-made Matlab â codes.
Occurrence The presence of the /kwa/ was assessed for all recordings allowing to determine the extent of spatial and temporal occurrence. The selections from meadow e (14 consecutive hours, from 6 P. M. to 8 A. M. ) used to test acoustic differences between the /kwas/ of the period of highest abundance at dusk and the rest of the night were also used to illustrate night-time patterns. Because selecting each /kwa/ over 14 h (from 6 P. M. to 8 A. M. ) is extremely time-consuming considering the high number of /kwas/ present (7284 selections for meadow e), data from only one recording were used. Furthermore, the presence of the dusk chorus is also indicative of the night-time pattern in /kwa/ abundance. To evaluate the presence and relative abundance of the /kwa/ compared to other fish calls present in meadows, the /kwas/ and all other fish sound types of one entire night were also manually selected and their night-time patterns compared to the one of the /kwa/.
/Kwa/diversity Visual inspection during the manual selection procedure suggested the existence of different types of /kwa/, particularly with respect to the spectral content and contour's shape (Fig. 4 ). Cluster analysis was conducted to quantify this signal diversity. To reduce the dimensions for cluster analysis and eliminate redundancy due to high intercorrelation of the acoustic variables Principal Component Analysis (PCA) was performed. The PCA was conducted using all acoustic features of subset №1, because receivedlevel dependent parameters may be linked to factors such as the distance of the vocalizing animals. The scores of the first three principal components of the PCA were used as input for the cluster analysis. Because the distribution of the PCA scores was multimodal, we considered the data to be distributed as a finite Gaussian mixture.
For a given number of clusters, the maximum likelihood estimators of the mean and covariance matrix of each Gaussian component of the mixture were found using an expectation-maximization algorithm  (McLachlan and Peel 2000). The minimum of the distribution of the Bayesian Inference Criteria (BIC) was used to estimate the optimal number of clusters  (Penny et al. 2007 ). The clustering was realized using the gmdistribution. fit function of the Statistics Toolbox in Matlab â (R2012a).