This paper describes ongoing work carried out in the European project PAL which will support childre in their diabetes self-management as well as assist health professionals and parents involved in the diabete regimen of the child. Here, we will focus on the construction of the PAL ontology which has been assemble from several independently developed sub-ontologies and which are brought together by a set of hand-writte interface axioms, expressed in OWL.We will describe in detail how the triple model of RDF has been extende towards transaction time in order to represent time-varying data. Examples of queries and rules involvin temporal information will be presented as well. The approach is currently been in use in diabetes camps. Copyright © 2016.Fundacao para a Ciencia e Tecnologia (FCT); Institute for Systems and Technologies of Information, Control and Communication (INSTICC)

OBJECTIVE: Calcitriol analogues might represent an interesting new therapy for benign prostate hyperplasia (BPH). We here report the preclinical characterization of BXL-628, an analogue selected for an ongoing double-blind, randomized, placebo-controlled phase II trial in BPH. DESIGN: Experiments with BXL-628 were carried out in human BPH cells and in the ventral prostate of intact and castrated rats. METHODS: BPH cell and rat prostate growth were evaluated along with morphological and biochemical hallmarks of apoptosis. RESULTS: BXL-628 inhibited human BPH cell proliferation and induced apoptosis even in the presence of androgens or growth factors. It also decreased prostate growth to an extent similar to finasteride, inducing DNA fragmentation and apoptosis, both in intact and in testosterone-supplemented castrated rats. Accordingly, BXL-628, like finasteride, increased the expression of clusterin, a prostatic atrophy marker. However, BXL-628 did not inhibit 5 alpha-reductase 1 and 2, did not bind to the androgen receptor (AR) in BPH homogenates and did not affect AR-coupled luciferase activity. In addition, BXL-628 did not affect rat pituitary and testis activity or calcemia. CONCLUSIONS: BXL-628 inhibited in vitro and in vivo prostate cell proliferation, and therefore might represent a novel, interesting option for the treatment of BPH.

This video paper describes the practical outcome of the first milestone of a project aiming at setting up a so-called Hybrid Team that can accomplish a wide variety of different tasks. In general, the aim is to realize and examine the collaboration of augmented humans with autonomous robots, virtual characters and SoftBots (purely software based agents) working together in a Hybrid Team to accomplish common tasks. The accompanying video shows a customized packaging scenario and can be downloaded from http://hysociatea.dfki.de/?p=441.

Temporal encoding schemes using RDF and OWL are often plagued by a massive proliferation of useless “container” objects. Reasoning and querying with such representations is extremely complex, expensive, and error-prone. We present a temporal extension of the Hayes and ter Horst entailment rules for RDFS and OWL [2,7] which apply to the TBox, RBox, and ABox of an ontology in order to make implicit knowledge explicit. The extension requires only some lightweight forms of reasoning and is realized by adding two further temporal arguments, thus replacing a triple by a quintuple. The approach has been implemented in the forward chaining engine HFC. Our decision was motivated by experiences we have gained in former projects that have dealt with the representation of changing information over time in description logic ontologies. In order to verify the superiority of the approach, we compare the quintuple-based approach with a semantic-preserving encoding scheme for N-ary relations through RDF triples, as proposed by the Semantic Web Best Practices Group of the W3C. The comparison is carried out on a theoretical as well as on a practical level, both in the space and the time domain when computing the deductive closure w.r.t. the triple- and quintuple-based temporal entailment rules.

In this poster submission, we describe the actual state of development of textual analysis and ontology-based information extraction in real world applications, as they are defined in the context of the European R&D project “MUSING” dealing with Business Intelligence. We present in some details the actual state of ontology development, including a time and domain ontologies, which are guiding information extraction onto an ontology population task.

We describe an implemented hybrid reasoning architecture that is used in an EU-funded project called MUSING (www.musing.eu) which is dedicated towards the investigation of semantic-based business intelligence solutions. The reasoning platform builds on publicly available software, such as Pellet, OWLIM, Jena, and Sesame. The project uses and extends existing OWL ontologies (e.g., PROTON) and assumes rule-based reasoning to take place on top of OWL. We describe the pros and cons of each subsystem w.r.t. the needs we have encountered during our investigation. We explain the specific reasoning architecture that is based on a sequence and a fixpoint computation of three reasoners which we might sloppily write as Pellet + (OWLIM + Jena)^*. Pellet is used for checking the initial consistency of the ontology, whereas OWLIM and Jena are employed to execute rules outside the expressiveness of OWL. However, OWLIM is way much faster than Jena, but neither has means to do numerical comparison nor arithmetic. We explain our choice why SWRL is not enough and why we believe that binary OWL properties lead to an unwanted proliferation of objects, making representation and reasoning extremely complex.

Abstract We present a simple and intuitive unsound corpus-driven approximation method for turning unification-based grammars, such as HPSG, CLE, or PATR-II into context-free grammars (CFGs). Our research is motivated by the idea that we can exploit (large-scale), hand-written unification grammars not only for the purpose of describing natural language and obtaining a syntactic structure (and perhaps a semantic form), but also to address several other very practical topics. Firstly, to speed up deep parsing by having a cheap recognition pre-flter (the approximated CFG). Secondly, to obtain an indirect stochastic parsing model for the unification grammar through a trained PCFG, obtained from the approximated CFG. This gives us an efficient disambiguation model for the unification-based grammar. Thirdly, to generate domain-specific subgrammars for application areas such as information extraction or question answering. And finally, to compile context-free language models which assist the acoustic model of a speech recognizer. The approximation method is unsound in that it does not generate a CFG whose language is a true superset of the language accepted by the original unification-based grammar. It is a corpus-driven method in that it relies on a corpus of parsed sentences and generates broader CFGs when given more input samples. Our open approach can be fine-tuned in different directions, allowing us to monotonically come close to the original parse trees by shifting more information into the context-free symbols. The approach has been fully implemented inJAVA.

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure, called the text chart. We describe details of the integration methods, and show how information extraction and language checking applications for realworld German text benefit from a deep grammatical analysis.

We describe a novel method for coping with ungrammatical input based on the use of chart-like data structures, which permit anytime processing. Priority is given to deep syntactic analysis. Should this fail, the best partial analyses are selected, according to a shortest-paths algorithm, and assembled in a robust processing phase. The method has been applied in a speech translation project with large HPSG grammars.

This paper describes new and improved techniques which help a unification-based parser to process input efficiently and robustly. In combination these methods result in a speed-up in parsing time of more than an order of magnitude. The methods are correct in the sense that none of them rule out legal rule applications.

In this paper a speech-to-speech translator from German to English is presented. Beside the traditional processing steps it takes advantage of acoustically detected prosodic phrase boundaries and focus. The prosodic phrase boundaries reduce search space during syntactic parsing and rule out analysis trees during semantic parsing. The prosodic focus faciliates a "shallow" translation based on the best word chain in cases where the deep analysis fails. 1. INTRODUCTION Integration of prosody into a speech-to-speech translator as an additional speech-language interface is a current topic of research. Within the VERBMOBIL project, which aims at translation of spontaneously spoken dialogues, a special experimental system called INTARC was designed which performs translation in an incremental manner. For this purpose time synchronous versions of traditional processing steps such as word recognition, parsing, semantic analysis, and transfer had to be developed. In part completely new algorith...

Morphotactics and allomorphy are usually modeled in different components, leading to interface problems. To describe both uniformly, we define finite automata (FA) for allomorphy in the same feature description language used for morphotactics. Nonphonologically conditioned allomorphy is problematic in FA models but submits readily to treatment in a uniform formalism.