Quantifying syntax similarity with a polynomial representation of dependency trees

Part-of-Speech (POS) tagging is a fundamental sequence labeling problem in Natural Language Processing. Recent deep learning sequential models combine the forward and backward word informatio for POS tagging. The information of contextual words to the current word play a vital role in capturing the non-continuous relationship. We have proposed Monotonic chunk-wise attention with CNN-GRU-Softmax (MCCGS), a deep learning architecture that adheres to these essential information. This architecture consists of Input Encoder (IE), encodes word and character-level, Contextual Encoder (CE), assigns the weightage to adjacent word and Disambiguator (D), which resolves intra-label dependencies as core components. Moreover, different morphological features have been integrated into the core components of MCCGS architecture as MCCGS-IE, MCCGS-CE and MCCGS-D. The MCCGS architecture is validated on the 21 languages from Universal Dependency (UD) treebank. The state-of-the-art models, Type constraints, Retrofitting, Distant Supervision from Disparate Sources and Position-aware Self Attention, MCCGS and its variants such as MCCGS-IE, MCCGS-CE and MCCGS-D are obtained mean accuracy 83.65%, 81.29%, 84.10%, 90.18%, 90.40%, 91.40%, 90.90%, 92.30%, respectively. The proposed model architecture provides state-of-the-art accuracy on the low resource languages as Marathi (93.58%), Tamil (87.50%), Telugu (96.69%) and Sanskrit (97.28%) from UD treebank and Hindi (95.64%) and Urdu (87.47%) from Hindi-Urdu multi-representational treebank.

Automatic dependency parsing of Thai sentences has been underexplored, as evidenced by the lack of large Thai dependency treebanks with complete dependency structures and the lack of a published evaluation of state-of-the-art models, especially transformer-based parsers. In this work, we addressed these gaps by introducing the Thai Universal Dependency Treebank (TUD), a new Thai treebank consisting of 3,627 trees annotated according to the Universal Dependencies (UD) framework. We then benchmarked 92 dependency parsing models that incorporate pretrained transformers on Thai-PUD and our TUD, achieving state-of-the-art results and shedding light on the optimal model components for Thai dependency parsing. Our error analysis of the models also reveals that polyfunctional words, serial verb construction, and lack of rich morphosyntactic features present main challenges for Thai dependency parsing.

This paper describes the development of the first Universal Dependencies (UD) treebank for St. Lawrence Island Yupik, an endangered language spoken in the Bering Strait region. While the UD guidelines provided a general framework for our annotations, language-specific decisions were made necessary by the rich morphology of the polysynthetic language. Most notably, we annotated a corpus at the morpheme level as well as the word level. The morpheme level annotation was conducted using an existing morphological analyzer and manual disambiguation. By comparing the two resulting annotation schemes, we argue that morpheme-level annotation is essential for polysynthetic languages like St. Lawrence Island Yupik. Word-level annotation results in degenerate trees for some Yupik sentences and often fails to capture syntactic relations that can be manifested at the morpheme level. Dependency parsing experiments provide further support for morpheme-level annotation. Implications for UD annotation of other polysynthetic languages are discussed.

In this paper, we present a first attempt at enriching German Universal Dependencies (UD) treebanks with enhanced dependencies. Similarly to the converter for English (Schuster and Manning, 2016), we develop a rule-based system for deriving enhanced dependencies from the basic layer, covering three linguistic phenomena: relative clauses, coordination, and raising/control. For quality control, we manually correct or validate a set of 196 sentences, finding that around 90% of added relations are correct. Our data analysis reveals that difficulties arise mainly due to inconsistencies in the basic layer annotations. We show that the English system is in general applicable to German data, but that adapting to the particularities of the German treebanks and language increases precision and recall by up to 10%. Comparing the application of our converter on gold standard dependencies vs. automatic parses, we find that F1 drops by around 10% in the latter setting due to error propagation. Finally, an enhanced UD parser trained on a converted treebank performs poorly when evaluated against our annotations, indicating that more work remains to be done to create gold standard enhanced German treebanks.

This paper presents a Parallel Universal Dependency (PUD) treebank for the Indo-Aryan language, Bengali. The treebank consists of 1000 Bengali sentences created using a parallel corpus of English-Bengali and Hindi-Bengali. The number of tokens reported for the 200 manually annotated sentences are 2622. Both the English and the Hindi corpus was taken from the Universal Dependency (UD) repository and subsequently the English corpus was chosen as the source text. The corpus was then translated in Bengali from scratch by the author, who is also a native speaker of the language, and thereafter annotated based on universal parts of speech tag, language specific parts of speech tag and on syntactic levels. The paper also illustrates the linguistic analysis of the PUD treebank and concludes with the kappa score.

We present scalable Universal Dependency (UD) treebank synthesis techniques that exploit advances in language representation modeling which leverage vast amounts of unlabeled general-purpose multilingual text. We introduce a data augmentation technique that uses synthetic treebanks to improve production-grade parsers. The synthetic treebanks are generated using a state-of-the-art biaffine parser adapted with pretrained Transformer models, such as Multilingual BERT (M-BERT). The new parser improves LAS by up to two points on seven languages. The production models’ LAS performance improves as the augmented treebanks scale in size, surpassing performance of production models trained on originally annotated UD treebanks.

BackgroundWith the development of cancer precision medicine, a huge amount of high-dimensional cancer information has rapidly accumulated regarding gene alterations, diseases, therapeutic interventions and various annotations. The information is highly fragmented across multiple different sources, making it highly challenging to effectively utilize and exchange the information. Therefore, it is essential to create a resource platform containing well-aggregated, carefully mined, and easily accessible data for effective knowledge sharing.MethodsIn this study, we have developed “Consensus Cancer Core” (Tri©DB), a new integrative cancer precision medicine knowledgebase and reporting system by mining and harmonizing multifaceted cancer data sources, and presenting them in a centralized platform with enhanced functionalities for accessibility, annotation and analysis.ResultsThe knowledgebase provides the currently most comprehensive information on cancer precision medicine covering more than 40 annotation entities, many of which are novel and have never been explored previously. Tri©DB offers several unique features: (i) harmonizing the cancer-related information from more than 30 data sources into one integrative platform for easy access; (ii) utilizing a variety of data analysis and graphical tools for enhanced user interaction with the high-dimensional data; (iii) containing a newly developed reporting system for automated annotation and therapy matching for external patient genomic data. Benchmark test indicated that Tri©DB is able to annotate 46% more treatments than two officially recognized resources, oncoKB and MCG. Tri©DB was further shown to have achieved 94.9% concordance with administered treatments in a real clinical trial.ConclusionsThe novel features and rich functionalities of the new platform will facilitate full access to cancer precision medicine data in one single platform and accommodate the needs of a broad range of researchers not only in translational medicine, but also in basic biomedical research. We believe that it will help to promote knowledge sharing in cancer precision medicine. Tri©DB is freely available at www.biomeddb.org, and is hosted on a cutting-edge technology architecture supporting all major browsers and mobile handsets.

GBS_insertPreviewButtonPopup('ISBN:9780748620562); This book is for students of translation, languages and linguistics who would like to enhance their understanding of the relationships between these areas of study. The book uses explanation, discussion and practice to make explicit the forms of knowledge of language and of translation that makes translators successful. Chapters on the development of translation studies in the west and on contemporary approaches to translation provide the disciplinary context within which the processes and products of translating are studied. The theoretical and academic context for the chapters in which application is focal is provided by the book's flexible and forward-looking approach to meaning and translation. Meaning is seen as a temporary relationship between participants in language events and translation as a creative activity that contributes to such events. From this position, interaction between language study, linguistics and translation studies is seen as mutually enriching. Five practical chapters cover sounds and rhythms, lexis, collocation and semantic prosody, texture, register, cohesion, coherence, implicature, speech and text acts, text and genre analysis, clausal thematicity and transitivity and the expression through language choices of ideological positions. Key Features Each chapter provides examples for analysis and translating practice based on a variety of text types, including poems, prose, drama, newspaper and journal articles, promotional materials and texts for tourists. Examples are drawn mainly from Danish, English, French, German, Italian and Spanish, but most practice sections can be used for analysis and translation into any language from English The book can be used at both undergraduate and postgraduate levels. "

The role of network reliability in the analysis of Critical Infrastructures (CI) is investigated showing that the traditional approach must be extended in two directions: to include the packet propagation time along the links for real time analysis, and to include networks in which many sources may be variously connected to many sinks. A case study of a SCADA system controlling a power grid, originated from the EU Project MICIE (MICIE — Tool for systemic risk analysis and secure mediation of data exchanged across linked CI information infrastructures) [6], is examined in details, by considering the system in normal operation and when perturbed by malicious attacks. The paper describes an analytical model that can provide timely and accurate information about the reliability status of the system, and that can rapidly be adapted to the changing configurations of the interacting networks. The aim of this work is to explore the feasibility of providing the human operators with a reliability monitor that assists them in checking the status of the system.

INTRODUCTION: Ninety percent of American adults have cell phones and half of them download applications (apps). We conducted a review of mobile health apps related to contraception and family planning. The primary objective of our study was to identify the number and type of contraception-related mobile apps and to perform review of content of those apps. METHODS: We searched the iOS mobile platform for the key words related to contraception and family planning between June and July 2014. A total of 289 apps were identified of which 129 were excluded as a result of a lack of contraception related information. We performed review of the remaining apps to identify themes and categories. RESULTS: Of 160 apps with contraception-related content 16 (10%) were primarily targeted toward health care providers. These included journals textbooks and reference guides. A total of 144 (90%) apps targeted toward patients were menstrual cycle trackers (40) birth control reminders (26) games (16) sexual health information apps (40) and apps to locate family planning centers (22). Only 20 patient apps had comprehensive information about multiple birth control methods. CONCLUSION: Mobile apps are an increasingly used means of accessing medical information. Accurate and comprehensive information about contraception is available in few apps. IMPLICATIONS: We are planning to perform clinical studies to identify the usefulness of such apps in clinical care. These studies may help us to understand the role of mobile health apps as a supplement to clinical care.

High Impact Data Visualization withPower View, Power Map, and Power BIhelps youtake business intelligence delivery to a new level that is interactive, engaging, even fun, all while driving commercial success through sound decision-making. Learn to harness the power of Microsofts flagship, self-service business intelligence suite to deliver compelling and interactive insight with remarkable ease. Learn the essential techniques needed to enhance the look and feel of reports and dashboards so that you can seize your audiences attention and provide them with clear and accurate information. Also learn to integrate data from a variety of sources and create coherent data models displaying clear metrics and attributes. Power View is Microsoft's ground-breaking tool for ad-hoc data visualization and analysis. It's designed to produce elegant and visually arresting output. It's also built to enhance user experience through polished interactivity. Power Map is a similarly powerful mechanism for analyzing data across geographic and political units. Power Query lets you load, shape and streamline data from multiple sources. PowerPivot can extend and develop data into a dynamic model. Power BI allows you to share your findings with colleagues, and present your insights to clients. High Impact Data Visualization withPower View, Power Map, and Power BIhelps you master this suite of powerful tools from Microsoft. You'll learn to identify data sources, and to save time by preparing your underlying data correctly. You'll also learn to deliver your powerful visualizations and analyses through the cloud to PCs, tablets and smartphones. Simple techniques take raw data and convert it into information. Slicing and dicing metrics delivers interactive insight. Visually arresting output grabs and focuses attention on key indicators. What youll learnProduce designer output that will astound your bosses and peers. Drive business intelligence from Excel using BI in the Cloud. Gather source data from corporate and public sources. Integrate charts, maps, and tables to deliver visually stunning information. Discover new insights as you chop and tweak your data as never before. Adapt delivery to mobile devices. Outshine competing products and enhance existing skills. Who this book is for High Impact Data Visualization withPower View, Power Map, and Power BIis written for any Excel or SharePoint user. Business Intelligence developers, power users, IT managers, finance experts, and more can use this book to outshine the competition by producing high-impact business intelligence reporting on a variety of devices from a variety of sources.

Current search tools on the Web, such as general-purpose search engines (e.g. Google) and domain-specific portals (e.g. MEDLINEplus), do not provide search procedures that guide users to form appropriately ordered sub-goals. The lack of such procedural knowledge often leads users searching in unfamiliar domains to retrieve incomplete information. In critical domains such as in healthcare, such ineffective searches can have dangerous consequences. To address this situation, we developed a new type of domain portal called a Strategy Hub. Strategy Hubs provide the critical search procedures and associated high-quality links that enable users to find comprehensive and accurate information. This paper describes how we collaborated with skin cancer physicians to systematically identify generalizeable search procedures to find comprehensive information about melanoma, and how these search procedures were made available through the Strategy Hub for healthcare. A pilot study suggests that this approach can improve the efficacy, efficiency, and satisfaction of even expert searchers. We conclude with insights on how to refine the design of the Strategy Hub, and how it can be used to provide search procedures across domains.

Eight years' experience of clinical activity in an outpatient fracture clinic

As one of the most critical functions of traffic information infrastructure, traffic information perception could provide essential data and decision-making support for traffic application scenarios such as traffic situation prediction and signal control. Currently, the common traffic information perception means mainly include geomagnetic coil, radar, video, infrared, etc., but these single traffic information perception devices generally lack of comprehensive information perception and high accuracy. In this paper, the traffic information perception technology based on the radar and video fusion is investigated, which organically integrates the detection data of millimeter wave radar and visual sensors. A large-scale, accurate and comprehensive traffic information perception is realized with the purpose of establishing the foundation for the development of intelligent and informative traffic.

Insight into the needs and experiences of family members is an initial but necessary step in providing appropriate care for both family members and the patient. This literature review aims to structure the available scientific knowledge on needs and experiences of family members of intensive care unit patients with particular extension to coma patients. Qualitative as well as quantitative studies are discussed. Literature review. Needs are divided into four categories: cognitive, emotional, social and practical needs. The need for accurate and comprehensible information that leaves room for hope is universal. Family members want to speak to a doctor every day about the condition of and the prognosis for the patient, and want a nurse to explain to them about the care, the unit, the equipment and what they can do for the patient during visiting hours. Family members place great importance on being called at home if the condition of the patient changes. Emotional needs as hope, reassurance and being able to remain in the vicinity of the patient are crucial. Family members always give priority to the welfare of their relative. In their confused state, they often do not get around to paying attention to themselves. Caregivers underestimate all of the needs of family members and do not do enough to meet these needs. Priority needs should be central in the nurses' approach of family members. The initiative for meeting the needs must be with the caregivers. Future, focused and well-designed qualitative research over a longer period of time could clarify the process that family members go through and explain the results of quantitative studies.