Definitional verbal patterns for semantic relation extraction

In this paper we present a description of the role of definitional verbal patterns for the extraction of semantic relations. Several studies show that semantic relations can be extracted from analytic definitions contained in machine-readable dictionaries (MRDs). In addition, definitions found in specialised texts are a good starting point to search for different types of definitions where other semantic relations occur. The extraction of definitional knowledge from specialised corpora represents another interesting approach for the extraction of semantic relations. Here, we present a descriptive analysis of definitional verbal patterns in Spanish and the first steps towards the development of a system for the automatic extraction of definitional knowledge.

Automatic Extraction of Polar Adjectives for the Creation of Polarity Lexicons

Automatic creation of polarity lexicons is a crucial issue to be solved in order to reduce time andefforts in the first steps of Sentiment Analysis. In this paper we present a methodology based onlinguistic cues that allows us to automatically discover, extract and label subjective adjectivesthat should be collected in a domain-based polarity lexicon. For this purpose, we designed abootstrapping algorithm that, from a small set of seed polar adjectives, is capable to iterativelyidentify, extract and annotate positive and negative adjectives. Additionally, the methodautomatically creates lists of highly subjective elements that change their prior polarity evenwithin the same domain. The algorithm proposed reached a precision of 97.5% for positiveadjectives and 71.4% for negative ones in the semantic orientation identification task.

Semantic web adoption: online tools for web evaluation and metadata extraction

This work briefly analyses the difficulties to adopt the Semantic Web, and in particular proposes systems to know the present level of migration to the different technologies that make up the Semantic Web. It focuses on the presentation and description of two tools, DigiDocSpider and DigiDocMetaEdit, designed with the aim of verifYing, evaluating, and promoting its implementation.

A survey on transfer-based approaches to MT using feature structures

Aquest treball és una revisió d'alguns sistemes de Traducció Automàtica que segueixen l'estratègia de Transfer i fan servir estructures de trets com a eina de representació. El treball s'integra dins el projecte MLAP-9315, projecte que investiga la reutilització de les especificacions lingüístiques del projecte EUROTRA per estàndards industrials.

Monetary policy with signal extraction from the bond market

Monetary policy is conducted in an environment of uncertainty. This paper sets upa model where the central bank uses real-time data from the bond market togetherwith standard macroeconomic indicators to estimate the current state of theeconomy more efficiently, while taking into account that its own actions influencewhat it observes. The timeliness of bond market data allows for quicker responsesof monetary policy to disturbances compared to the case when the central bankhas to rely solely on collected aggregate data. The information content of theterm structure creates a link between the bond market and the macroeconomythat is novel to the literature. To quantify the importance of the bond market asa source of information, the model is estimated on data for the United Statesand Australia using Bayesian methods. The empirical exercise suggests that thereis some information in the US term structure that helps the Federal Reserve toidentify shocks to the economy on a timely basis. Australian bond prices seemto be less informative than their US counterparts, perhaps because Australia is arelatively small and open economy.

Audit risk and rent extraction: Evidence from a randomized evaluation in Brazil

We report results from a randomized policy experiment designed to test whether increasedaudit risk deters rent extraction in local public procurement and service delivery in Brazil. Ourestimates suggest that temporarily increasing annual audit risk by about 20 percentage pointsreduced the proportion of irregular local procurement processes by about 17 percentage points.This reduction was driven entirely by irregularities involving mismanagement or corruption. Incontrast, we find no evidence that increased audit risk affected the quality of publicly providedpreventive and primary health care services -measured based on user satisfaction surveys- orcompliance with national regulations of the conditional cash transfer program "Bolsa Família".

Judicial presence and rent extraction

We estimate the effect of state judiciary presence on rent extraction in Brazilian local governments.We measure rents as irregularities related to waste or corruption uncovered by auditors.Our unique dataset at the level of individual inspections allows us to separately examine extensiveand intensive margins of rent extraction. The identification strategy is based on an institutionalrule of state judiciary branches according to which prosecutors and judges tend to be assigned tothe most populous among contiguous counties forming a judiciary district. Our research designexploits this rule by comparing counties that are largest in their district to counties with identicalpopulation size from other districts in the same state, where they are not the most populous. IVestimates suggest that state judiciary presence reduces the share of inspections with irregularitiesrelated to waste or corruption by about 10 percent or 0.3 standard deviations. In contrast, we findno effect on the intensive margin of rent extraction. Finally, our estimates suggest that judicialpresence reduces rent extraction only for first-term mayors.

Simple and fast methods based on solid-phase extraction coupled to liquid chromatography with UV detection for the monitoring of caffeine in natural and waste waters as marker of anthropogenic impact

Two concentration methods for fast and routine determination of caffeine (using HPLC-UV detection) in surface, and wastewater are evaluated. Both methods are based on solid-phase extraction (SPE) concentration with octadecyl silica sorbents. A common “offline” SPE procedure shows that quantitative recovery of caffeine is obtained with 2 mL of an elution mixture solvent methanol-water containing at least 60% methanol. The method detection limit is 0.1 μg L−1 when percolating 1 L samples through the cartridge. The development of an “online” SPE method based on a mini-SPE column, containing 100 mg of the same sorbent, directly connected to the HPLC system allows the method detection limit to be decreased to 10 ng L−1 with a sample volume of 100 mL. The “offline” SPE method is applied to the analysis of caffeine in wastewater samples, whereas the “on-line” method is used for analysis in natural waters from streams receiving significant water intakes from local wastewater treatment plants

Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals

Background: oscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies. Oscillatory burst events should consequently play a specific functional role, distinct from background EEG activity – especially for cognitive tasks (e.g. working memory tasks), binding mechanisms and perceptual dynamics (e.g. visual binding), or in clinical contexts (e.g. effects of brain disorders). However extracting oscillatory events in single trials, with a reliable and consistent method, is not a simple task. Results: in this work we propose a user-friendly stand-alone toolbox, which models in a reasonable time a bump time-frequency model from the wavelet representations of a set of signals. The software is provided with a Matlab toolbox which can compute wavelet representations before calling automatically the stand-alone application. Conclusion: The tool is publicly available as a freeware at the address: http:// www.bsp.brain.riken.jp/bumptoolbox/toolbox_home.html

A Robust Multiple Feature Approach To Endpoint Detection In Car Environment Based On Advanced Classifiers

In this paper we propose an endpoint detection system based on the use of several features extracted from each speech frame, followed by a robust classifier (i.e Adaboost and Bagging of decision trees, and a multilayer perceptron) and a finite state automata (FSA). We present results for four different classifiers. The FSA module consisted of a 4-state decision logic that filtered false alarms and false positives. We compare the use of four different classifiers in this task. The look ahead of the method that we propose was of 7 frames, which are the number of frames that maximized the accuracy of the system. The system was tested with real signals recorded inside a car, with signal to noise ratio that ranged from 6 dB to 30dB. Finally we present experimental results demonstrating that the system yields robust endpoint detection.

Repurposing Social Tagging Data for Extraction of Domain-level Concepts

The World Wide Web, the world¿s largest resource for information, has evolved from organizing information using controlled, top-down taxonomies to a bottom up approach that emphasizes assigning meaning to data via mechanisms such as the Social Web (Web 2.0). Tagging adds meta-data, (weak semantics) to the content available on the web. This research investigates the potential for repurposing this layer of meta-data. We propose a multi-phase approach that exploits user-defined tags to identify and extract domain-level concepts. We operationalize this approach and assess its feasibility by application to a publicly available tag repository. The paper describes insights gained from implementing and applying the heuristics contained in the approach, as well as challenges and implications of repurposing tags for extraction of domain-level concepts.

Evaluation of the indication for surgical extraction of third molars according to the oral surgeon and the primary care dentist. Experience in the Master of Oral Surgery and Implantology at Barcelona University Dental School

Introduction: Third molar extraction is the most frequent procedure in oral surgery. The present study evaluates the indication of third molar extraction as established by the primary care dentist (PCD) and the oral surgeon, and compares the justification for extraction with the principal reason for patient consultation. Patients and method: A descriptive study was made of 319 patients subjected to surgical removal of a third molar in the context of the Master of Oral Surgery and Implantology (Barcelona University Dental School, Barcelona, Spain) between July 2004 and March 2005. The following parameters were evaluated: sex, age, molar, type of impaction, position according to the classifications of Pell and Gregory and of Winter, and the reasons justifying extraction. Results: The lower third molars were the most commonly extracted molars (73.7%). A total of 69.6% of the teeth were covered by soft tissues only. Fifty-six percent of the lower molars corresponded to Pell and Gregory Class IIB, while 42.1% were in the vertical position. The most common reason for patient reference to our Service of Oral Surgery on the part of the PCD was prophylactic removal (51.0% versus 46.1% in the case of the oral surgeon). Discussion and conclusions. Our results show prophylaxis to be the principal indication of third molar extraction, followed by orthodontic reasons. Regarding third molars with associated clinical symptoms or signs, infectious disease-including pericoronitis- was the pathology most often observed by the oral surgeon, followed by caries. This order of frequency was seen to invert in the case of third molars referred for extraction by the PCD. A vertical position predominated among the third molars with associated pathology

Social network extraction and analysis based on multimodal dyadic interaction

Social interactions are a very important component in people"s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times" Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links" weights are a measure of the"influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

Feature Selection, Ranking of Each Feature and Classification for the Diagnosis of Community Acquired Legionella Pneumonia

Diagnosis of community acquired legionella pneumonia (CALP) is currently performed by means of laboratory techniques which may delay diagnosis several hours. To determine whether ANN can categorize CALP and non-legionella community-acquired pneumonia (NLCAP) and be standard for use by clinicians, we prospectively studied 203 patients with community-acquired pneumonia (CAP) diagnosed by laboratory tests. Twenty one clinical and analytical variables were recorded to train a neural net with two classes (LCAP or NLCAP class). In this paper we deal with the problem of diagnosis, feature selection, and ranking of the features as a function of their classification importance, and the design of a classifier the criteria of maximizing the ROC (Receiving operating characteristics) area, which gives a good trade-off between true positives and false negatives. In order to guarantee the validity of the statistics; the train-validation-test databases were rotated by the jackknife technique, and a multistarting procedure was done in order to make the system insensitive to local maxima.

Retrospective study of 145 supernumerary teeth

Objective: The goal of the present retrospective study is to describe the distribution of the supernumerary teeth in a population of patients that have been attended at the Public Clinic of the Department of Oral Surgery. Background: Supernumerary teeth and multiple hyperdontia are usually associated with different syndromes, such as Gardner syndrome, or with facial fissures; however, they can appear in patients without any pathology. Their prevalence oscillates to 0.5-3.8% in patients with permanent teeth and to 0.35-0.6% in patients with primary teeth. Patients and Methods: A total of 36,057 clinical histories of patients that were admitted at the clinic between September of 1991 and March of 2003 were revised. The following data were extrapolated: age, sex, number of extracted supernumerary teeth, localization, morphology and type of supernumerary teeth. Consequently, 102 patients were included into the present study. Results: Of the 147 supernumerary teeth identified in the oral cavities of patients 145 were extracted. The most frequent supernumerary teeth identified were mesiodens (46.9%), followed by premolars (24.1%) and fourth molars or distal molars (18%). As for location, 74.5% of the supernumerary teeth were found in the superior maxillary bone and 46.9% of the supernumerary teeth were present in the palatine/lingual area. Heteromorphology was found in two thirds of the supernumerary teeth, with conical shape being the most frequent. Finally, 29.7% of the supernumerary teeth had occlusion with permanent teeth, and mesiodens were the predominating type of supernumerary teeth that showed this feature. Conclusions: Mesiodens very frequently cause retention of permanent incisors, which erupt spontaneously after the extraction of supernumerary teeth, if there is sufficient space in the dental arch and if they conserve the eruptive force. Generally, supernumerary premolars are eumorphic and are casually discovered during radiological exam, if not producing any symptomology.