Miracle-dz/UniFAR-FTUs huggingface dataset:
CLAWS4: The Tagging of the British National Corpus

The main purpose of this paper is to describe the CLAWS4 general-purpose grammatical tagger, used for the tagging of the 100-million-word British National Corpus, of which c.70 million words have been tagged at the time of writing (April 1994)) We will emphasise the goals of (a) gener~d-purpose adaptability, (b) incorporation of linguistic knowledge to improve quality ,and consistency, and (c) accuracy, measured consistently and in a linguistically informed way. The British National Corpus (BNC) consists of c.100 million words of English written texts and spoken transcriptions, sampled from a comprehensive range of text types. The BNC includes 10 million words of spoken h'mguage, c.45% of which is impromptu conversation (see Crowdy, forthcoming). It also includes ,an immense variety of written texts, including unpublished materials. The gr,'unmatical tagging of the corpus has therefore required the 'super-robustness' of a tagger which can adapt well to virtually all kinds of text. The tagger also has had to be versatile in dealing with different tagsets (sets of grammatical category labels-see 3 below) and accepting text in varied input formats. For the purposes of the BNC, l, he tagger has been requircd both to accept and to output text in a corpus-oriented TEl-confonnant mark-up definition known as CDIF (Corpus Document Interchange Format), but within this format many variant fornaats (affecting, for example, segmentation into words and sentences) can be readily accepted. In addition, CLAWS al-
On the Relevance of Syntactic and Discourse Features for Author Profiling and Identification

The majority of approaches to author profiling and author identification focus mainly on lexical features, i.e., on the content of a text. We argue that syntactic and discourse features play a significantly more prominent role than they were given in the past. We show that they achieve state-of-the-art performance in author and gender identification on a literary corpus while keeping the feature set small: the used feature set is composed of only 188 features and still outperforms the winner of the PAN 2014 shared task on author verification in the literary genre.
Dissemination: Science and Sensibilities

This article resulted from the 2017 Canadian Psychological Association award for Distinguished Contributions to the International Advancement of Psychology to the author. The author is a developer of cognitive–behavioural therapies, and has had the good fortune to promote this work in a broad range of countries and cultures. This article presents a dualistic portrayal of dissemination of evidence-based psychotherapy. The article opens with some of the key theoretical and research-based considerations in the development and evaluation of evidence-based practice, and how these issues are manifested in cross-cultural dissemination. The latter part of the article offers a more personal reflection on the sensibilities of cross-cultural dissemination, and offers personal reflections on the practice of dissemination science. Cet article fait suite à l’obtention, par l’auteur, du Prix pour contributions remarquables à l’avancement international de la psychologie 2017, décerné par la Société canadienne de psychologie. L’auteur, qui a défini des thérapies cognitivo-comportementales, a eu la chance de présenter son travail dans une multitude de pays et de cultures. Cet article présente un double portrait de la diffusion de la psychothérapie fondée sur des bases factuelles. Il débute par la présentation de certaines des principales considérations théoriques et basées sur la recherche en matière d’établissement et d’évaluation de la pratique factuelle, puis examine en quoi ces questions se manifestent dans la diffusion multiculturelle. La dernière partie de l’article offre une réflexion personnalisée sur les sensibilités dans le cadre d’une diffusion multiculturelle ainsi que des pensées personnelles sur la pratique de la science de la diffusion.
Diagnostic operationalization and phenomenological heterogeneity in psychiatry: the case of attention deficit hyperactivity disorder

Introduction. We assessed the impact of polythetic conceptualizations of mental disorders on the validity and reliability of psychiatric diagnosis, with a specific focus on two levels of heterogeneity: phenomenological and pathophysiological. Objective. We investigated this issue using attention deficit hyperactivity disorder (ADHD) as an example. Method. We examined individuals from two samples enriched for psychopathology (n = 1 255 children in Porto Alegre and 1 257 children in São Paulo, Brazil). We conducted a series of data analyses to investigate phenomenological heterogeneity, including confirmatory factor analysis. We also investigated pathophysiological heterogeneity using symptom-level regressions between ADHD symptoms and four neurocognitive processes consistently linked to ADHD (working memory, inhibitory control, intra-subject variability in reaction times, and temporal processing). Lastly, we assessed the performance of polythetic systems for reliability testing inter-rater and test-rest reliability of two well-known symptomatic scales. Results. Among the 116 200 possible combinations of symptoms to achieve DSM symptomatic threshold for categorical ADHD diagnosis, we found 173 combinations in the two independent samples, and only four were replicated in both samples (2.3%). We also found that the number of ADHD symptoms is a poor indicator of variation in the general ADHD latent trait. Overall, symptoms did not have specific profiles of associations with any of the neurocognitive processes. Reliability analyses revealed that increasing the number of items augments overall reliability of measurements. Discussion and conclusion. Our findings illustrate both potential benefits and problems inherent to the polythetic system for ADHD. Implications for the search of mechanisms underlying psychiatric disorders are discussed.
Comparison of active learning methods for automatic document classification

Getting correctly labelled data is an important preliminary stage for many supervisedmachine learning problems, but it can also be really difficult to perform. Sometimes, toobtain a good model, it could require tens or hundreds of thousands of examples andexamples usually does not come with labels. Active Learning is a methodology that canradically accelerate the labelling process and reduce costs for many machine learningprojects. This methodology prioritises which data is most confusing and requests justthose labels instead of collecting all the labels for all the data at once.The aim of this work is to implement an Active Learning methodology that helps toautomate the capture of relevant information from Key Investment Information Docu-ments (KIID). Those documents aim to help investors to understand the nature and keyrisks of investment products in order to make a more informed investment decision.Until now, data extraction was done through a specific labelling application developedby the company where this project was performed. This application is able to extractpieces of text from KIIDs, to assign its surrounding information and to query a certainhuman oracle (or expert) the correct label (whether the piece of text is associated or notto a specific type of information). The database obtained after this process is used in asupervised machine learning task to obtain a model that allows to recognise the type ofinformation of a piece of text. The incorporation of the Active Learning methodologyto this application will drastically reduce the query phase i.e. the most expensive partof the whole process.The machine learning algorithm used for classification is the well-known Support Vec-tor Machines. The examples are translated into binary vectors throughUni-grams andBi-grams which means generating a vocabulary ofoneandtwowords and identifyingwhether the text feature contains theseN-grams (N= 1 or 2) or not.Three of the most common Active Learning strategies have been implemented inorder to compare between them and with the passive learning method. Active learn-ing strategies implemented are:uncertainty sampling,query by committeeanddensity-weightedmethods. All of them compared with the passive learning method,randomsampling. 10-fold cross-validation is used to assess each of the approaches implementedand three evaluation measures are applied: recall, accuracy and computational time
Rapid communications Detection of a novel human coronavirus by real-time reverse-transcription polymerase chain reaction

Rapid communications Detection of a novel human coronavirus by real-time reverse-transcription polymerase chain reaction 3 by VM Corman, I Eckerle, T Bleicker, A Zaki, O Landt, M Eschbach-Bludau, S van Boheemen, R Gopal, M Ballhause, TM Bestebroer, D Muth, MA Müller, JF Drexler, M Zambon, AD Osterhaus, RM Fouchier, C Drosten Novel coronavirus associated with severe respiratory disease: Case definition and public health measures 9 by N Danielsson, on behalf of the ECDC Internal Response Team, M Catchpole
Enhancement of SMN2 Exon 7 Inclusion by Antisense Oligonucleotides Targeting the Exon

Several strategies have been pursued to increase the extent of exon 7 inclusion during splicing of SMN2 (survival of motor neuron 2) transcripts, for eventual therapeutic use in spinal muscular atrophy (SMA), a genetic neuromuscular disease. Antisense oligonucleotides (ASOs) that target an exon or its flanking splice sites usually promote exon skipping. Here we systematically tested a large number of ASOs with a 2′-O-methoxy-ethyl ribose (MOE) backbone that hybridize to different positions of SMN2 exon 7, and identified several that promote greater exon inclusion, others that promote exon skipping, and still others with complex effects on the accumulation of the two alternatively spliced products. This approach provides positional information about presumptive exonic elements or secondary structures with positive or negative effects on exon inclusion. The ASOs are effective not only in cell-free splicing assays, but also when transfected into cultured cells, where they affect splicing of endogenous SMN transcripts. The ASOs that promote exon 7 inclusion increase full-length SMN protein levels, demonstrating that they do not interfere with mRNA export or translation, despite hybridizing to an exon. Some of the ASOs we identified are sufficiently active to proceed with experiments in SMA mouse models.
The Quality of the Catalan and Spanish Education Systems: A Perspective from PISA

For Catalonia and Spain, public perception is that the PISA reports show that their education systems are underperforming. The goal of this chapter is to quantify how much of the Catalan and Spanish PISA score can be attributed to the education levels of parents and what part must instead be explained by other factors. To do so we use standard statistical techniques to examine how the Catalan and Spanish PISA score would have compared with other countries and regions if all had the same parental education levels and immigration levels. For Spain the main results show that there is a sizable increase in PISA scores relative to the rest of Europe when parental schooling is accounted for. But Spain's performance is rather poor to start out with and only rises to somewhat above average when accounting for parental education levels. For Catalonia accounting for parental education levels leads to small improvements in the PISA score compared to other Spanish regions and to Flanders, Lombardy, and Denmark. Moreover, immigration or the concentration of immigrants at some schools accounts for little of the below average performance of Catalonia.
Towards development and use of in-house component framework: results and expectations

In recent times, considerable attention is being paid to the development of software applications using software components. One of their main advantages is that they are reusable assets. Software product line is a wide spread approach toward software reuse in many organizations. The paper presents the SME experience for using software components in projects for development of Web applications in the finance and crediting domain. The experience is based on development and usage of components based technology framework allowing business function components creation and integration. The implementation results are presented as comparison of collected statistics for two similar projects - project 1 is developed before the framework establishment and component creation, while project 2 is executed and implemented after completion of the framework and some of the components. Though it seems clear that using component framework has some obvious advantages, such as reducing project design and development time and less human and financial resources, often there are some major risks in COTS implementation that have to be considered in future projects.
An Experimental Technique for Characterizing Slow-Wave Characteristics of MIS-Like Transmission Lines Using Aqueous Dielectrics

This work is a study of the dielectric propagation properties of laminar substrates, which are known to support low dispersion modes with very small phase velocities. Slow modes are linked to a polarization mode supported by the insulator-semiconductor interface. The mode spectrum of metal-insulator-semiconductor lines is controlled by the substrate resistivity and the ratio of the semiconductor to insulator layer thicknesses. An experimental investigation of substrate modes normally requires the laborious fabrication of many specimens to cover a useful range of parameter variation. In this paper, we present an experimental platform that supports slow-wave propagation and allows easy adjustment of the parameters affecting the interfacial polarization mechanism.
Self-Exciting Point Process Modeling of Crime

Highly clustered event sequences are observed in certain types of crime data, such as burglary and gang violence, due to crime-specific patterns of criminal behavior. Similar clustering patterns are observed by seismologists, as earthquakes are well known to increase the risk of subsequent earthquakes, or aftershocks, near the location of an initial event. Space–time clustering is modeled in seismology by self-exciting point processes and the focus of this article is to show that these methods are well suited for criminological applications. We first review self-exciting point processes in the context of seismology. Next, using residential burglary data provided by the Los Angeles Police Department, we illustrate the implementation of self-exciting point process models in the context of urban crime. For this purpose we use a fully nonparametric estimation methodology to gain insight into the form of the space–time triggering function and temporal trends in the background rate of burglary.
Reach for gold

Duplicates in a database are one of the prime causes of poor data quality and are at the same time among the most difficult data quality problems to alleviate. To detect and remove such duplicates, many commercial and academic products and methods have been developed. The evaluation of such systems is usually in need of pre-classified results. Such gold standards are often expensive to come by (much manual classification is necessary), not representative (too small or too synthetic), and proprietary and thus preclude repetition (company-internal data). This lament has been uttered in many papers and even more paper reviews. The proposed annealing standard is a structured set of duplicate detection results, some of which are manually verified and some of which are merely validated by many classifiers. As more and more classifiers are evaluated against the annealing standard, more and more results are verified and validation becomes more and more confident. We formally define gold, silver, and the annealing standard and their maintenance. Experiments show how quickly an annealing standard converges to a gold standard. Finally, we provide an annealing standard for 750,000 CDs to the duplicate detection community.
A Mathematical and Physical Analysis of Circuit Jitter with Application to Cryptographic Random Bit Generation

2 Acknowledgements. 3 Table of Figures . 5 Table of Tables . 5 1 Background. 6 1.1 Cryptography . 6 1.2 Random Number Generators . 7 1.3 Jitter. 9 2 Methodology. 10 2.1 Development Environment . 10 2.1.1 Hardware. 10 2.1.2 Software Design Flow. 10 2.2 Testing Environment and Procedures . 11 2.2.1 Jitter Measurement. 11 2.2.2 Oscilloscope. 14 3 Results and Analysis . 15 3.1 Ring Oscillator . 15 3.2 Theoretical Analysis . 18 3.2.1 Central Limit Theorem . 19 3.2.2 Correlated Noise Sources. 20 3.3 Experimental Analysis . 21 3.3.1 Basic Jitter Statistics . 21 3.3.2 N-Cycle Accumulation . 22 3.3.3 Jitter Density . 27 3.3.4 Periodic Noise and Filtering . 29 3.4 Modeling. 32 4 Future Work . 34 5 Conclusion . 35 References. 36
High-achieving, low-income students’ perspectives of how schools can promote the academic achievement of students living in poverty

Children and adolescents from low-income families now comprise a majority of public school students nationally. As the number of students from low-income backgrounds increases, so does the achievement gap between them and their wealthier peers. This phenomenological qualitative study examined a national sample of high-achieving, low-income middle school students’ (N = 24) perspectives on what schools can do to promote the academic achievement of students from low-income backgrounds. Three main themes and seven subthemes were identified: create a culture of hope, develop relational networks, and establish meaningful parent–school collaborations. Implications for counselors and educators serving youth living in poverty are discussed.
Challenges of networked media: integrating the navigational features of browsing histories and media playlists into a media browser

One of the goals of the Continuous Media Web project<sup>1</sup> is to integrate digital media with the World Wide Web: media documents can hyperlink to and from other documents in the same way that HTML pages do. The dual capabilities of hyperlinking (1) to other documents while viewing a media clip, and (2) into precise time intervals in a media clip, enable greatly improved user interaction with media. We discuss the idea of a novel <i>media browser</i> application, which merges the concept of a traditional media player that presents video and audio to the user, with a Web browser that provides hyperlinking and navigation between networked (media) documents. The particular issue we address in this article concerns the primary navigational features: a media player relies on a <i>playlist</i> while a Web browser uses a <i>browsing history</i> for navigation. We discuss design and user interface issues that arise when integrating these two navigational features in a media browser.
Primary Analysis of the Expressed Sequence Tags in a Pentastomid Nymph cDNA Library

Background Pentastomiasis is a rare zoonotic disease caused by pentastomids. Despite their worm-like appearance, they are commonly placed into a separate sub-class of the subphylum Crustacea, phylum Arthropoda. However, until now, the systematic classification of the pentastomids and the diagnosis of pentastomiasis are immature, and genetic information about pentastomid nylum is almost nonexistent. The objective of this study was to obtain information on pentastomid nymph genes and identify the gene homologues related to host-parasite interactions or stage-specific antigens. Methodology/Principal Findings Total pentastomid nymph RNA was used to construct a cDNA library and 500 colonies were sequenced. Analysis shows one hundred and ninety-seven unigenes were identified. In which, 147 genes were annotated, and 75 unigenes (53.19%) were mapped to 82 KEGG pathways, including 29 metabolism pathways, 29 genetic information processing pathways, 4 environmental information processing pathways, 7 cell motility pathways and 5 organismal systems pathways. Additionally, two host-parasite interaction-related gene homologues, a putative Kunitz inhibitor and a putative cysteine protease. Conclusion/Significance We first successfully constructed a cDNA library and gained a number of expressed sequence tags (EST) from pentastomid nymphs, which will lay the foundation for the further study on pentastomids and pentastomiasis.
Technical challenges and directions for digital forensics

Digital forensics is concerned with the investigation of any suspected crime or misbehaviour that may be manifested by digital evidence. The digital evidence may be manifest in various forms. It may be manifest on digital electronic devices or computers that are simply passive repositories of evidence that documents the activity, or it may consist of information or meta-information resident on the devices or computers that have been used to actually facilitate the activity, or that have been targeted by the activity. In each of these three cases, we have recorded digital evidence of the activity. This paper examines some recent advances in digital forensics and some important emerging challenges. It considers the following topics: tools and their evolution; the implications of large volumes of data; the impact of embedded and special-purpose computer systems; corporate governance and its implications for 'forensic readiness'; and the role of forensics in securing the Internet.
PeaPaw

Performance and energy are two major concerns for application development on heterogeneous platforms. It is challenging for application developers to fully exploit the performance/energy potential of heterogeneous platforms. One reason is the lack of reliable prediction of the system’s performance/energy before application implementation. Another reason is that a heterogeneous platform presents a large design space for workload partitioning between different processors. To reduce such development cost, this article proposes a framework, PeaPaw, to assist application developers to identify a workload partition (WP) that has high potential leading to high performance or energy efficiency before actual implementation. The PeaPaw framework includes both analytical performance/energy models and two sets of workload partitioning guidelines. Based on the design goal, application developers can obtain a workload partitioning guideline from PeaPaw for a given platform and follow it to design one or multiple WPs for a given workload. Then PeaPaw can be used to estimate the performance/energy of the designed WPs, and the WP with the best estimated performance/energy can be selected for actual implementation. To demonstrate the effectiveness of PeaPaw, we have conducted three case studies. Results from these case studies show that PeaPaw can faithfully estimate the performance/energy relationships of WPs and provide effective workload partitioning guidelines.