dataesr/scientific-paragraphs-categorization huggingface dataset:
g. corporate society or laboratory (if eligible), title, field (discipline), key words, identifier, advisor(s) with full affiliation, members of jury with full affiliation, date (year of defense), research project with start and end dates (if eligible), funding agency (if eligible), protection (confidentiality), dissemination (address). Most of this information is part of usual library or graduate school records but not of IR metadata. Therefore, whenever possible ETD metadata for CRIS should be imported from a local database, an academic union catalogue or a national registry and not from an open repository which often contains poor information about PhD theses. Quality: Evaluation needs controlled, validated and quality data. Metadata can be very heterogeneous, with different information in the same field and different variants of the same information.
Interoperability In order to exploit ETD for research evaluation, ETD infrastructures, repositories and CRIS must connect and exchange data. Needed are compliant metadata and formats, not data silos with specific features. Interoperability problems are partly caused by non acceptance of a standard by the community  (Peponakis 2013). All solutions should therefore prefer accepted and already implemented standards, whenever possible. The well documented Novi Sad project can serve as a model, with the implementation of CERIF and the mapping of different formats and data to the CERIF specifications. CERIF appears to be the best choice for flexibility and interoperability. Yet, the format must be extended to integrate rich and complex metadata on ETD, in particular on the semantic layer enabling classifications of entities (types of theses, roles of persons…) and relations between entities (person/organization…).
Complementary material Print theses and dissertations have regularly been submitted together with complementary material, such as maps, tables, speech samples, photos or videos, in various formats and on different supports. In the digital environment of open repositories and added value services, these open data could become a rich source of research results and datasets, for reuse and other exploitation. With regards to CRIS, this material can and should be taken into account as research results, along with products or publications -not on the same level as big data from important scientific equipments but as small (dark, personal) data, related to individual work or specific research projects. This is not a major issue for CRIS but should be considered for further developments, with implications for CRIS formats, workflows, repositories and metadata.
Recommendations Based on the studies and experiences cited in our paper, we will issue five recommendations: 1. Whenever possible, ETD should be part of CRIS. 2. Only validated theses, after defense and controlled by national or local structures, should be taken into account. 3. Metadata should be as standard and as rich as possible and compliant with CERIF and OAI-PMH, even if not all ETD metadata are necessary for research evaluation. 4. Whenever possible, the metadata should be linked to the freely available full text deposited in an institutional or other open repository. 5. Special attention should be paid to complementary material submitted along with ETD, because of their interest for scientists (reuse) and evaluation (research results).
Methods Digital images of Ki67 IHC from 158 female patients (one millimeter-diameter tissue microarray (TMA) spot per patient) with an invasive ductal carcinoma of the breast were used for the study. The study was approved by the Lithuanian Bioethics Committee. The patients' consent to participate in the study was obtained. The TMA were constructed, stained, and scanned as previously described  [11]. Manual data (mD) were obtained in our previous study  [6]  by marking Ki67-positive and negative tumour cell profiles, using a stereological method for 2D object enumeration  [12]  implemented in the Stereology module (ADCIS, France) with a test grid of systematically sampled frames overlaid on a spot image in ImageScope (Aperio Technologies, USA). Automatic image processing was performed using the combination of the Genie and Nuclear algorithms from Aperio Technologies (Vista USA) calibrated in the previous study  [6].
The Genie software is used to isolate the epithelial compartment of the breast carcinoma and discard stromal and inflammatory components. Nuclear algorithm allows the refined segmentation of individual nuclei of cancer cell profiles and the color characterization of immunostained and counterstained nuclei. The dIHC Wizard workflow is presented in the Figure  1. The dD marks were produced from the multicolor mask image resulting from the automatic analysis. For this purpose, an Excess Red Green Blue image was computed (2R-G-B, 2G-R-B and 2B-R-G) and fixed thresholds applied to isolate the automatically labeled immunostained and counterstained epithelial nuclear profiles (Figure  2 ). The dD marks were collected from the centroid of the labeled nuclear profiles and stored into an XML file which was then overlaid on the original spot images to generate relevant XML tags along with the stereology grid (Figure  2 ).
Last but not least, the mD and/or cD sets are qualityassured and contain information on exact location of the cells in the image, therefore, can be utilized as standard criterion templates to validate, calibrate, and train DIA tools. On a more global perspective, the reference data libraries may serve as benchmark datasets for automated DIA -the demand well-recognized and addressed in computational neuroscience and bioimage informatics, in general, with tasks of much higher complexity than the digital IHC  [14, 15].
Acknowledgements This research is funded by  European Social Fund  under the Global Grant measure. Publication of this supplement has been funded by 12th  European Congress on Digital Pathology. This article has been published as part of Diagnostic Pathology Volume 9 Supplement 1, 2014: Selected articles from the 12th European Congress on Digital Pathology. The full contents of the supplement are available online at http://www. diagnosticpathology. org/ supplements/9/S1.
QCD resummation predictions for the production of charged (W ) and neutral (Z ) heavy gauge bosons decaying leptonically are presented. The results of our resummation code at next-to-leading order and next-to-leading logarithmic (NLO+NLL) accuracy are compared to Monte Carlo predictions obtained with PYTHIA at leading order (LO) supplemented with parton showers (PS) and FEWZ at NLO and next-to-next-to-leading order (NNLO) for the p T -differential and total cross sections in the Sequential Standard Model (SSM) and general SU(2)×SU(2)×U(1) models. The LO+PS Monte Carlo and NNLO fixed-order predictions are shown to agree approximately with those at NLO+NLL at small and intermediate p T , respectively, and the importance of resummation for total cross sections is shown to increase with the gauge boson mass.
For SM weak gauge boson production, the importance of resummation calculations has been demonstrated most recently using Soft-Collinear Effective Theory (SCET) by an improved agreement with Tevatron and LHC data and reduced theoretical scale uncertainties  [71] [72] [73]. In the context of new physics searches at the LHC, soft-gluon resummation has already been applied to the production of Z bosons  [74]  as well as to the production of supersymmetric (SUSY) particles such as squarks and gluinos  [75] , sleptons  [76] [77] [78] [79] , and gauginos  [80] [81] [82] [83]. For the Z boson and weak SUSY channels, the NLO+NLL code RESUMMINO is publicly available  [84]. We have now also added the possibility to make predictions for W bosons with general gauge couplings for transverse momentum (p T ) spectra, resummed as p T → 0 in impact parameter space, and for total cross sections, resummed near partonic threshold in Mellin space.
1 he results of our resummation code are compared using different benchmark models to p T distributions and total cross sections obtained with the LO+PS Monte Carlo generator PYTHIA  [68] , in which we have implemented the new weak bosons including the interferences with the SM gauge bosons. In addition, we compare with the theoretical predictions in fixed order perturbation theory at NLO and NNLO QCD calculated with the FEWZ program, which unfortunately lacks the interference terms  [69, 70]. The theoretical uncertainties are estimated by variations of the renormalisation/factorisation scales and parton distribution functions (PDFs). Using the example of Z bosons, we demonstrate that the resummation contributions become more important with increasing mass of the new gauge boson, which will further increase their importance in future LHC analyses.
Perturbative QCD at NLO and NNLO In fixed-order perturbative QCD, the hadronic production of Z and W bosons can be calculated at NLO, O(α 2 α s ), and NNLO, O(α 2 α 2 s ), with the publicly available program FEWZ  [69, 70]  in a fully exclusive way and including the leptonic decay of the gauge bosons with full spin correlations and finite width effects. FEWZ thus allows one to investigate the total production cross section as well as the transverse momentum and invariant/transverse mass spectra under arbitrary kinematic cuts on the gauge boson and/or lepton-pair. Unfortunately, since the code assumes the existence of one neutral/charged vector boson only, the important interference effects between two different gauge bosons are not taken into account. The pure SM background is, however, far below the new physics signal, at least for the new gauge boson masses and models considered here, and can thus safely be neglected.
The moments of the PDFs are obtained through a numerical fit to the publicly available PDF parameterisations in x-space. Our NLO fixed order and NLO+NLL resummation calculations have been implemented in the computer code RESUMMINO that is publicly available  [84]. For our numerical results at both NLO and NLO+NLL, we employ the PDF parameterisation of MSTW 2008 NLO and estimate the theoretical scale error by varying again simultaneously the renormalisation and factorisation scales by a factor of two about the new gauge boson mass.
The total cross sections were shown to be stabilised at NLO+NLL compared to the NLO predictions with respect to variations of the renormalisation and factorisation scales, so that the theoretical error became dominated for large masses by the PDF uncertainties. Full agreement could be found at LO with PYTHIA and at NLO with FEWZ -albeit only without interference. The interference effects were shown to depend strongly on the Model New gauge boson Previous mass limit [TeV] New mass limit  [  Table  6. Previously obtained exclusion limits, using ATLAS  [21, 35]  and CMS data  [47, 61]  for the SSM as well as low-energy and precision data for the UU and NU models  [3] , and new exclusion limits, including all interference effects and NLO+NLL corrections, for W and Z gauge bosons. minimal cut on the invariant mass of the lepton pair, and the resummation contributions were shown to become increasingly important with the new gauge boson mass.
Acknowledgment We thank  A. Papaefstathiou  for his efforts to bring the W implementations in MC@NLO and POWHEG in agreement with our results. This work has been supported by the  BMBF Theorie-Verbund , by a  Ph. D. fellowship of the French Ministry for Education and Research , and by the  Theory-LHC-France initiative  of the  CNRS/IN2P3.
In 2009 the authors developed an open source Java application and framework, GraphsJ, to help the students in their approach to the study of graph algorithms, by guiding them to understand their logical structures through experiments on numerical instances. After four years, the availability of Java 7 and of new tools suggested the implementation of a new major release. We present a new major release, GraphsJ 3, whose implementation in Java 7 maintains the main characteristics of a useful educational application: Portability, extensibility, ease of use and availability as open source software. The new release provides a redesigned architecture, implemented through cutting-edge languages and technologies and a robust Mavenbased build. The presented Java framework constitutes a further step towards the implementation of didactic instruments for the teaching of graph theory.
INTRODUCTION GraphsJ is an open source Java framework designed and implemented in 2009 at the University of Bologna to help students in their approach to the study of graph algorithms. The framework was implemented so as to be portable and easy to use and includes a library that anyone can easily use to develop custom algorithms. We refer the reader to  (Costa et al. , 2010)  and to  (Costa, 2009)  for a detailed description of GraphsJ. In the present paper we present a new major release, GraphsJ 3, whose implementation targets Java 7. The new release maintains the main characteristics that a useful educational application should have, namely: • Portability: It should run on most operating systems • Extensibility: Even non-experienced programmers should be able to quickly create and run a new algorithm • Ease of use: It should enable students to enjoy their learning experience • Availability as open source software At the didactic home page http://www.
JCS • Critical path: Algorithm (CPM) developed in the mid Fifties,  (Siemens, 1971)  Main characteristics: The implementation of GraphsJ 3 includes a number of innovative concepts and techniques: • Simplified and modular OOP architecture, inspired by Domain Driven Design (DDD) • Cutting-edge language and technologies, especially Java 7, JavaFX 2, XStream and Spring 3 • Simplified, automated and robust build process, based on Maven 3 • Open source availability on a shared Maven repository.
Language and Libraries GraphsJ 3 is written in Java 7. With respect to the previous release (GraphsJ) it makes use of the most recent and elegant language constructs available in Java 7, such as the try-with-resources block or the diamond operator. In addition to the language, a set of libraries was employed for the creation of the new system: • JavaFX 2: Oracle's RIA (= Rich Internet Application) framework, providing a far more colorful and intense user experience than Swing, as well as a more modern programming interface. Unlike JavaFX 1, JavaFX 2 introduces types that can be accessed by any JVM language, support for GUIs designed in FXML (a dedicated XML syntax) and configurable build tools that proved to be very useful for the packaging of the finished application • XStream: A library dedicated to XML serialization The new architecture: GraphsJ 3 is not a monolithic project: Actually, it is now just the toplevel module in a stack of 10 different components.
The overall architecture diagram, depicted in Fig. 1 , shows that modularization and strong separation between layers are among the key principles driving the development of GraphsJ 3. The three identifiable macro-blocks are Helios, Arcontes and GraphsJ 3 (see http://gianlucacosta. info): • Helios is a general-purpose library. Module helioscore is the most basic module and provides core utilities. On top of it, helios-fx, helios-xml and helios-spring introduce specific types • Arcontes is the library describing the graph domain and providing visual components for the user. The very first module in the stack dealing with the graph model is arcontes-core, while arcontes-fx introduces JavaFX controls such as the graph canvas and the related utilities. Finally, arcontes-test is a small library supporting the creation of graph-oriented unit tests • GraphsJ is the final product: A JavaFX application built on top of Helios and Arcontes.
The core of the application is graphsj-sdk: By describing its own model using the concepts introduced by Arcontes, it provides classes and interfaces that developers can use to create new scenarios to be plugged into GraphsJ. The algorithms available in the program (that can be reused to compose more sophisticated algorithms, or even within another application) are contained in graphsj-algorithms. Finally, graphsj itself is just a program managing the document workspace (opening and saving files, for example) and showing the graph canvas provided by arcontes-fx.
Helios Helios is an open source, general-purpose Java library currently composed by 4 modules: • Helios-core is the most general module, providing support for common development issues such as simplified event handling, conversions, serialization and I/O, predicates and conditions, collections, regular expressions: Helios is open source and is designed to be an evolving project. New types are constantly added to the library, to support the creation of new software and, at the same time, to isolate and reuse valuable structures and techniques. For example, Helios 1. 3 was released together with EasyPmd 3, a NetBeans plugin that requires the support of helios-core and introduces new abstractions in the fields of I/O management and regular expression parsing.
Arcontes Arcontes is an open source Java library describing the graph domain and providing a visual toolkit for rendering and editing graphs. Arcontes was designed to be the kernel of GraphsJ 3, introducing concepts and utilities required by the application. However, it is totally independent of GraphsJ and can be easily referenced by any Java software. Arcontes is composed by 3 modules: • Arcontes-core, that contains: (i) basic types such as Graph, Vertex, Link, …, which define the graph structures and (ii) the declaration of Algorithm -the interface for graph algorithms, as well as a default implementation and related utilities • Arcontes-fx, that provides a suite of JavaFX components for graph rendering. The main types in the module are the interfaces GraphRenderer and GraphCanvas, along with their default implementations: DefaultGraphRenderer is a readonly panel showing a graph, while DefaultGraphCanvas adds event handling on top of it, in order to support user interaction • Arcontes-test, a very simple set of utilities that simplify test fixtures for graph algorithms Arcontes widely relies on Helios, starting from the meta-information management package provided by helios-core, especially for its rendering engine.
DISCUSSION The new technologies employed and the totally redesigned architecture do not conclude the series of Science Publications JCS innovations introduced by GraphsJ 3: Such a complex software system required a modern build process, needed to efficiently manage its creation and maintenance-which is why Maven 3 was chosen. Maven is an elegant and open source build tool focusing on the following principles: • Knowledge accumulation: Maven provides a flexible, plugin-based cycle and plugins exist for almost any issue that could arise during software development, from resource filtering to packaging, from license headers in source files to jar signing. It also provides a plugin for Apache Ant, to save previous investments in that tool. As a further step of reuse, Maven introduces the concept of project inheritance, enabling users to create derivative, customized projects based on a shared template.
The modules in the stack of GraphsJ 3 are all based on a parent project • Versioning and dependency management: Unlike. NET, Java does not natively introduce constraints on the version of its artifacts (for example, jar files). This means that, when working with a wide network of dependencies, as is the case of GraphsJ 3, it might be easy to forget a required library or, even worse, to use some wrong, incompatible version Maven supports the user in two main ways: • All artifacts (JARs, POMs, WARs, EARs, NBMs, …) are uniquely identified by the tuple (groupId, artifactId, version) • Every project can declare its own dependencies (using, for each of them, the above coordinates) and Maven will automatically download them and their dependencies, recursively, from centralized repositories The <dependency> tag is one of the most flexible and effective configuration points in Maven's Project Object Model (POM) and significantly simplifies the setup of a project.
At the same time, AAL is based on a temporal logic semantics making it machine readable. Such semantics allows early expression simplifications, well-formedness checking and verification of expected properties. We start such a work in  [15]  using the mCRL2 model-checker. We are currently developing a Web based framework called AccLab 8 , to support these concepts. Accountability clauses written in AAL are quite close to natural language. However, there is still work to fill the gap with data protection legislation. The exact shape of AAL is not definitive since more experiments will be needed. We have started thinking on design and verification but one important aspect is to develop techniques for manual and automatic clauses enforcement.
Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of pre-generated utterances, or (b) using statistics to determine the generation decisions of an existing generator. Both approaches rely on the existence of a handcrafted generation component, which is likely to limit their scalability to new domains. The first contribution of this paper is to present BAGEL, a fully data-driven generation method which treats the language generation task as a search for the most likely sequence of semantic concepts and realisation phrases according to Factored Language Models (FLMs). As domain utterances are not readily available for most NLG tasks, a large creative effort is required to produce the data necessary to represent human linguistic variation for non-trivial domains.
An automated evaluation shows that BAGEL outperforms utterance class LM baselines on this domain. A human evaluation of 600 resynthesized dialogue extracts shows that BAGEL's FLM output produces utterances comparable to a handcrafted baseline, while the perceptron classifier performs worse. Interestingly, human judges find the system sampling from the N-best list to be more natural than a system always returning the 1-best utterance. The judges are also more willing to interact with the N-best system in the future. These results suggest that capturing the large variation found in human language using data-driven methods is beneficial for dialogue interaction.
Introduction The field of natural language generation (NLG) was one of the last areas of computational linguistics to embrace statistical methods, perhaps because of the difficulty of collecting semantically-annotated corpora. Over the past decade, statistical NLG has followed two lines of research. The first one, pioneered by  Langkilde and Knight (1998) , introduces statistics in the generation process by training a model which reranks candidate outputs of a handcrafted generator. Their HALOGEN system uses an n-gram language model trained on news articles. HALOGEN is thus domain-independent, and it was successfully ported to a specific dialogue system domain  (Chambers and Allen 2004). However, its performance depends largely on the granularity of the underlying meaning representation, which typically includes syntactic and lexical information.
This paper is based on the assumption that learning to produce paraphrases can be facilitated by collecting data from a large sample of annotators. However, this requires that the meaning representation should (a) be simple enough to be understood by untrained annotators, and (b) provide useful generalisation properties for generating unseen inputs. Section 3 describes BAGEL's meaning representation, which satisfies both requirements. Section 4 then details how our meaning representation is mapped to a phrase sequence, using cascaded Factored improving the expressiveness of statistical generators. Section 8 discusses how BAGEL's expressiveness could be improved by including RST relations. Language models (LMs) have previously been used for language generation in order to remove the need for a handcrafted overgeneration phase  (Oh and Rudnicky 2002; Ratnaparkhi 2002).