Decreasing lexical data sparsity in statistical syntactic parsing - experiments with named entities

In this paper we present preliminary experiments that aim to reduce lexical data sparsity in statistical parsing by exploiting information about named entities. Words in the WSJ corpus are mapped to named entity clusters and a latent variable constituency parser is trained and tested on the transformed corpus. We explore two different methods for mapping words to entities, and look at the effect of mapping various subsets of named entity types. Thus far, results show no improvement in parsing accuracy over the best baseline score; we identify possible problems and outline suggestions for future directions

DCU at the TREC 2008 Blog Track

In this paper we describe our system, experiments and re- sults from our participation in the Blog Track at TREC 2008. Dublin City University participated in the adhoc re- trieval, opinion finding and polarised opinion finding tasks. For opinion finding, we used a fusion of approaches based on lexicon features, surface features and syntactic features. Our experiments evaluated the relative usefulness of each of the feature sets and achieved a significant improvement on the baseline

Isolation and characterization of a Caenorhabditis elegans SRC loss-of-function allele using reverse genetics

The vertebrate proto-oncogene Src is a protein-tyrosine kinase that has been implicated as a component of receptor-mediated signal transduction pathways important for cell growth and differentiation. Consistent with this notion, overexpression or activation of Src by mutation induces neoplastic transformation in cell culture, leads to tumorigenesis in laboratory animals, and has been observed in a number of human tumors. Despite years of intensive investigation, neither its role in oncogenesis nor its normal, biological role is understood. To diminish the issue of redundancy that has complicated analysis of Src function in vertebrates and Drosophila, I have chosen to study Src function in the genetically less complex nematode Caenorhabditis elegans. The gene src-1 encodes a protein with significant structural and sequence identity to vertebrate c-Src. The first part of this dissertation describes a set of biochemical experiments supporting the hypothesis that SRC-1 is the ortholog of vertebrate pp60c-src. The second part of this dissertation describes the isolation and characterization of a src-1 loss-of-function allele using a reverse genetic approach. src-1(cj293) is a deletion allele generated by N-ethyl-N-nitrosourea mutagenesis that encodes a truncated, kinase-inactive protein. It is a recessive maternal effect lethal allele that interacts genetically with components of a conserved Wnt signaling pathway providing the first direct connection between two intensively studied vertebrate signaling pathways: Src and Wnt. The genetic interactions identified in combination with the embryonic defects observed in src-1( cj293) animals suggest that SRC-1 normally plays a role in regulating spindle orientation, morphogenesis, and cell fate decisions of developing C. elegans embryos. This study lays the ground work for additional genetic and biochemical analyses that will help define the molecular details of SRC-1 signaling. Such experiments will shed light not only on the biological role SRC-1 plays in C. elegans development, but also the biological role of Src-family kinases in general. Ultimately, these analyses may provide insight into the mode of action of oncogenic Src mutants

Manometry-Based Cough Identification Algorithm

Gastroesophageal reflux disease (GERD) is a common cause of chronic cough. For the diagnosis and treatment of GERD, it is desirable to quantify the temporal correlation between cough and reflux events. Cough episodes can be identified on esophageal manometric recordings as short-duration, rapid pressure rises. The present study aims at facilitating the detection of coughs by proposing an algorithm for the classification of cough events using manometric recordings. The algorithm detects cough episodes based on digital filtering, slope and amplitude analysis, and duration of the event. The algorithm has been tested on in vivo data acquired using a single-channel intra-esophageal manometric probe that comprises a miniature white-light interferometric fiber optic pressure sensor. Experimental results demonstrate the feasibility of using the proposed algorithm for identifying cough episodes based on real-time recordings using a single channel pressure catheter. The presented work can be integrated with commercial reflux pH/impedance probes to facilitate simultaneous 24-hour ambulatory monitoring of cough and reflux events, with the ultimate goal of quantifying the temporal correlation between the two types of events

Exploring the Overlap Between Dyslexia and Speech Sound Production Deficits

Purpose Children with dyslexia have speech production deficits in a variety of spoken language contexts. In this article, we discuss the nature of speech production errors in children with dyslexia, including those who have a history of speech sound disorder and those who do not, to familiarize speech-language pathologists with speech production-specific risk factors that may help predict or identify dyslexia in young children. Method In this tutorial, we discuss the role of a phonological deficit in children with dyslexia and how this may manifest as speech production errors, sometimes in conjunction with a speech sound disorder but sometimes not. We also briefly review other factors outside the realm of phonology that may alert the speech-language pathologist to possible dyslexia. Results Speech-language pathologists possess unique knowledge that directly contributes to the identification and remediation of children with dyslexia. We present several clinical recommendations related to speech production deficits in children with dyslexia. We also review what is known about how and when children with speech sound disorder are most at risk for dyslexia. Conclusion Speech-language pathologists have a unique opportunity to assist in the identification of young children who are at risk for dyslexia

Proposed Lake Arthur Detention Basin Expansion City of Port Arthur, Jefferson County, Texas

Terracon Consultants, Inc. (Terracon) was contracted by the City of Port Arthur (client) to conduct a cultural resources survey of an approximately 54-acre project area in Port Arthur, Jefferson County, Texas in advance of the proposed expansion of an existing detention basin. Since the proposed undertaking will occur on land owned or controlled by a political subdivision of the State of Texas, and because funding for this project will come, in part, from the Federal Emergency Management Agency (FEMA), this project required compliance with the Antiquities Code of Texas (Texas Natural Resources Code Chapter 191) and its implementing rules and regulations (Texas Administrative Code Chapter 26) and Section 106 of the National Historic Preservation Act (NHPA), (54 USC § 306101) and its implementing rules and regulations, 36 CFR 800. This project was conducted under Antiquities Permit #9109. The proposed project area comprises a 54-acre tract of land located between Texas State Highway 347 and U.S. Route 69 in Port Arthur, Texas. Terracon archeologists excavated a total of eleven (11) shovel tests to a depth of 80 centimeters (cm) below surface, or to sediments inferred to predate human occupation in the area. The removed sediment was passed through ¼-inch hardware mesh to screen for artifacts. No cultural materials were identified during the survey. Additionally, to comply with Section 106 of the NRHP, adjacent parcels were evaluated to determine whether historic properties might be present and subject to visual effects from the project. No such historic properties were identified. Fieldwork was conducted between October 15 and October 17, 2019 by Michael Hogan (Staff Archeologist) and Amani Bourji (Field Technician) under the supervision of Jenni Hatchett Kimbell (Principal Investigator). The report was authored by Michael Hogan and Jenni Hatchett Kimbell. Given the absence of known prehistoric or historical-period resources within the proposed project area, Terracon recommends that the expansion of the Lake Arthur detention basin proceed as planned. Should human remains, historic properties, or buried cultural materials be encountered during construction or disturbance activities, work should cease in the immediate vicinity and Terracon, the Texas Historical Commission (THC) Archeology Division, or other proper authorities should be contacted

Proposed Texas Pipeline LTD Star 12,000-Foot-Long Power Transmission Line on University of Texas Lands, Ward County, Texas

Terracon Consultants, Inc. (Terracon) was contracted by PNM Resources to conduct a Phase I archeological survey on lands owned by The University of Texas System in Ward County, Texas, the location of a proposed 12,000-foot-long power transmission line. Since the proposed undertaking will occur on land owned by a public institution of higher education, this project required compliance under the jurisdiction of the Antiquities Code of Texas (Natural Resources Code, Chapter 191) and its implementing rules (Texas Administrative Code, Title 13, Chapter 26). The proposed project area comprises an easement approximately 12,000 feet (2.27 miles) long and approximately 30 feet wide. The total area covered is approximately 8.26 acres. Terracon archeologists excavated a total of forty (40) shovel tests to a depth of 80 centimeters (cm) below surface (bs), or to sediments predating human occupation in the area. The removed sediment was passed through ¼” hardware mesh to recover artifacts. One prehistoric archeological site, 41WR139, was recorded during the survey. The portion of the site that is within the project area is not eligible for inclusion in the National Register of Historic Places (NRHP) or for designation as a State Antiquities Landmark (SAL). Jenni Hatchett Kimbell served as Principal Investigator under Texas Antiquities Permit No. 8996. Fieldwork was conducted between July 16 and July 17, 2019 by Michael Hogan (Staff Archeologist) and Edgar Vazquez (Staff Archeologist). The report was authored by Michael Hogan and Jenni Hatchett Kimbell. Project records will be curated at the Texas Archeological Research Laboratory (TARL) at the University of Texas at Austin. Given the absence of NRHP-eligible archeological sites within the proposed project area, Terracon recommends that the installation of the power transmission line proceed as planned. In the event that human remains, historic properties, or buried cultural materials are encountered during construction or disturbance activities, work should cease in the immediate area but can continue where no cultural materials are present. TNMP Environmental Services Department should be contacted

LFG without C-structures

We explore the use of two dependency parsers, Malt and MST, in a Lexical Functional Grammar parsing pipeline. We compare this to the traditional LFG parsing pipeline which uses constituency parsers. We train the dependency parsers not on classical LFG f-structures but rather on modified dependency-tree versions of these in which all words in the input sentence are represented and multiple heads are removed. For the purposes of comparison, we also modify the existing CFG-based LFG parsing pipeline so that these "LFG-inspired" dependency trees are produced. We find that the differences in parsing accuracy over the various parsing architectures is small

Handling unknown words in statistical latent-variable parsing models for Arabic, English and French

This paper presents a study of the impact of using simple and complex morphological clues to improve the classification of rare and unknown words for parsing. We compare this approach to a language-independent technique often used in parsers which is based solely on word frequencies. This study is applied to three languages that exhibit different levels of morphological expressiveness: Arabic, French and English. We integrate information about Arabic affixes and morphotactics into a PCFG-LA parser and obtain stateof-the-art accuracy. We also show that these morphological clues can be learnt automatically from an annotated corpus

From news to comment: Resources and benchmarks for parsing the language of web 2.0

We investigate the problem of parsing the noisy language of social media. We evaluate four all-Street-Journal-trained statistical parsers (Berkeley, Brown, Malt and MST) on a new dataset containing 1,000 phrase structure trees for sentences from microblogs (tweets) and discussion forum posts. We compare the four parsers on their ability to produce Stanford dependencies for these Web 2.0 sentences. We find that the parsers have a particular problem with tweets and that a substantial part of this problem is related to POS tagging accuracy. We attempt three retraining experiments involving Malt, Brown and an in-house Berkeley-style parser and obtain a statistically significant improvement for all three parsers