NAMED ENTITY RECOGNITION FROM BIOMEDICAL TEXT -AN INFORMATION EXTRACTION TASK

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N. Kanya

2016-07-01

Full Text Available Biomedical Text Mining targets the Extraction of significant information from biomedical archives. Bio TM encompasses Information Retrieval (IR and Information Extraction (IE. The Information Retrieval will retrieve the relevant Biomedical Literature documents from the various Repositories like PubMed, MedLine etc., based on a search query. The IR Process ends up with the generation of corpus with the relevant document retrieved from the Publication databases based on the query. The IE task includes the process of Preprocessing of the document, Named Entity Recognition (NER from the documents and Relationship Extraction. This process includes Natural Language Processing, Data Mining techniques and machine Language algorithm. The preprocessing task includes tokenization, stop word Removal, shallow parsing, and Parts-Of-Speech tagging. NER phase involves recognition of well-defined objects such as genes, proteins or cell-lines etc. This process leads to the next phase that is extraction of relationships (IE. The work was based on machine learning algorithm Conditional Random Field (CRF.

Tagline: Information Extraction for Semi-Structured Text Elements in Medical Progress Notes

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Finch, Dezon Kile

2012-01-01

Text analysis has become an important research activity in the Department of Veterans Affairs (VA). Statistical text mining and natural language processing have been shown to be very effective for extracting useful information from medical documents. However, neither of these techniques is effective at extracting the information stored in…

Knowledge Dictionary for Information Extraction on the Arabic Text Data

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Wahyu Jauharis Saputra

2013-04-01

Full Text Available Information extraction is an early stage of a process of textual data analysis. Information extraction is required to get information from textual data that can be used for process analysis, such as classification and categorization. A textual data is strongly influenced by the language. Arabic is gaining a significant attention in many studies because Arabic language is very different from others, and in contrast to other languages, tools and research on the Arabic language is still lacking. The information extracted using the knowledge dictionary is a concept of expression. A knowledge dictionary is usually constructed manually by an expert and this would take a long time and is specific to a problem only. This paper proposed a method for automatically building a knowledge dictionary. Dictionary knowledge is formed by classifying sentences having the same concept, assuming that they will have a high similarity value. The concept that has been extracted can be used as features for subsequent computational process such as classification or categorization. Dataset used in this paper was the Arabic text dataset. Extraction result was tested by using a decision tree classification engine and the highest precision value obtained was 71.0% while the highest recall value was 75.0%. 

Challenges for automatically extracting molecular interactions from full-text articles.

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McIntosh, Tara; Curran, James R

2009-09-24

The increasing availability of full-text biomedical articles will allow more biomedical knowledge to be extracted automatically with greater reliability. However, most Information Retrieval (IR) and Extraction (IE) tools currently process only abstracts. The lack of corpora has limited the development of tools that are capable of exploiting the knowledge in full-text articles. As a result, there has been little investigation into the advantages of full-text document structure, and the challenges developers will face in processing full-text articles. We manually annotated passages from full-text articles that describe interactions summarised in a Molecular Interaction Map (MIM). Our corpus tracks the process of identifying facts to form the MIM summaries and captures any factual dependencies that must be resolved to extract the fact completely. For example, a fact in the results section may require a synonym defined in the introduction. The passages are also annotated with negated and coreference expressions that must be resolved.We describe the guidelines for identifying relevant passages and possible dependencies. The corpus includes 2162 sentences from 78 full-text articles. Our corpus analysis demonstrates the necessity of full-text processing; identifies the article sections where interactions are most commonly stated; and quantifies the proportion of interaction statements requiring coherent dependencies. Further, it allows us to report on the relative importance of identifying synonyms and resolving negated expressions. We also experiment with an oracle sentence retrieval system using the corpus as a gold-standard evaluation set. We introduce the MIM corpus, a unique resource that maps interaction facts in a MIM to annotated passages within full-text articles. It is an invaluable case study providing guidance to developers of biomedical IR and IE systems, and can be used as a gold-standard evaluation set for full-text IR tasks.

Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction

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Darko Brodić

2010-05-01

Full Text Available Text line segmentation is an essential stage in off-line optical character recognition (OCR systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms.

Using text mining techniques to extract phenotypic information from the PhenoCHF corpus.

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Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

2015-01-01

Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our annotation is currently limited to a single

Automatic extraction of ontological relations from Arabic text

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Mohammed G.H. Al Zamil

2014-12-01

The proposed methodology has been designed to analyze Arabic text using lexical semantic patterns of the Arabic language according to a set of features. Next, the features have been abstracted and enriched with formal descriptions for the purpose of generalizing the resulted rules. The rules, then, have formulated a classifier that accepts Arabic text, analyzes it, and then displays related concepts labeled with its designated relationship. Moreover, to resolve the ambiguity of homonyms, a set of machine translation, text mining, and part of speech tagging algorithms have been reused. We performed extensive experiments to measure the effectiveness of our proposed tools. The results indicate that our proposed methodology is promising for automating the process of extracting ontological relations.

Extracting Characteristics of the Study Subjects from Full-Text Articles.

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Demner-Fushman, Dina; Mork, James G

Characteristics of the subjects of biomedical research are important in determining if a publication describing the research is relevant to a search. To facilitate finding relevant publications, MEDLINE citations provide Medical Subject Headings that describe the subjects' characteristics, such as their species, gender, and age. We seek to improve the recommendation of these headings by the Medical Text Indexer (MTI) that supports manual indexing of MEDLINE. To that end, we explore the potential of the full text of the publications. Using simple recall-oriented rule-based methods we determined that adding sentences extracted from the methods sections and captions to the abstracts prior to MTI processing significantly improved recall and F1 score with only a slight drop in precision. Improvements were also achieved in directly assigning several headings extracted from the full text. These results indicate the need for further development of automated methods capable of leveraging the full text for indexing.

An unsupervised text mining method for relation extraction from biomedical literature.

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Changqin Quan

Full Text Available The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1 Protein-protein interactions extraction, and (2 Gene-suicide association extraction. The evaluation of task (1 on the benchmark dataset (AImed corpus showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on gene-suicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method.

ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

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Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

2009-01-01

We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....

Extracting and connecting chemical structures from text sources using chemicalize.org.

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Southan, Christopher; Stracz, Andras

2013-04-23

Exploring bioactive chemistry requires navigating between structures and data from a variety of text-based sources. While PubChem currently includes approximately 16 million document-extracted structures (15 million from patents) the extent of public inter-document and document-to-database links is still well below any estimated total, especially for journal articles. A major expansion in access to text-entombed chemistry is enabled by chemicalize.org. This on-line resource can process IUPAC names, SMILES, InChI strings, CAS numbers and drug names from pasted text, PDFs or URLs to generate structures, calculate properties and launch searches. Here, we explore its utility for answering questions related to chemical structures in documents and where these overlap with database records. These aspects are illustrated using a common theme of Dipeptidyl Peptidase 4 (DPPIV) inhibitors. Full-text open URL sources facilitated the download of over 1400 structures from a DPPIV patent and the alignment of specific examples with IC50 data. Uploading the SMILES to PubChem revealed extensive linking to patents and papers, including prior submissions from chemicalize.org as submitting source. A DPPIV medicinal chemistry paper was completely extracted and structures were aligned to the activity results table, as well as linked to other documents via PubChem. In both cases, key structures with data were partitioned from common chemistry by dividing them into individual new PDFs for conversion. Over 500 structures were also extracted from a batch of PubMed abstracts related to DPPIV inhibition. The drug structures could be stepped through each text occurrence and included some converted MeSH-only IUPAC names not linked in PubChem. Performing set intersections proved effective for detecting compounds-in-common between documents and merged extractions. This work demonstrates the utility of chemicalize.org for the exploration of chemical structure connectivity between documents and

METHOD OF RARE TERM CONTRASTIVE EXTRACTION FROM NATURAL LANGUAGE TEXTS

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I. A. Bessmertny

2017-01-01

Full Text Available The paper considers a problem of automatic domain term extraction from documents corpus by means of a contrast collection. Existing contrastive methods successfully extract often used terms but mishandle rare terms. This could yield poorness of the resulting thesaurus. Assessment of point-wise mutual information is one of the known statistical methods of term extraction and it finds rare terms successfully. Although, it extracts many false terms at that. The proposed approach consists of point-wise mutual information application for rare terms extraction and filtering of candidates by criterion of joint occurrence with the other candidates. We build “documents-by-terms” matrix that is subjected to singular value decomposition to eliminate noise and reveal strong interconnections. Then we pass on to the resulting matrix “terms-by-terms” that reproduces strength of interconnections between words. This approach was approved on a documents collection from “Geology” domain with the use of contrast documents from such topics as “Politics”, “Culture”, “Economics” and “Accidents” on some Internet resources. The experimental results demonstrate operability of this method for rare terms extraction.

Terminology extraction from medical texts in Polish.

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Marciniak, Małgorzata; Mykowiecka, Agnieszka

2014-01-01

Hospital documents contain free text describing the most important facts relating to patients and their illnesses. These documents are written in specific language containing medical terminology related to hospital treatment. Their automatic processing can help in verifying the consistency of hospital documentation and obtaining statistical data. To perform this task we need information on the phrases we are looking for. At the moment, clinical Polish resources are sparse. The existing terminologies, such as Polish Medical Subject Headings (MeSH), do not provide sufficient coverage for clinical tasks. It would be helpful therefore if it were possible to automatically prepare, on the basis of a data sample, an initial set of terms which, after manual verification, could be used for the purpose of information extraction. Using a combination of linguistic and statistical methods for processing over 1200 children hospital discharge records, we obtained a list of single and multiword terms used in hospital discharge documents written in Polish. The phrases are ordered according to their presumed importance in domain texts measured by the frequency of use of a phrase and the variety of its contexts. The evaluation showed that the automatically identified phrases cover about 84% of terms in domain texts. At the top of the ranked list, only 4% out of 400 terms were incorrect while out of the final 200, 20% of expressions were either not domain related or syntactically incorrect. We also observed that 70% of the obtained terms are not included in the Polish MeSH. Automatic terminology extraction can give results which are of a quality high enough to be taken as a starting point for building domain related terminological dictionaries or ontologies. This approach can be useful for preparing terminological resources for very specific subdomains for which no relevant terminologies already exist. The evaluation performed showed that none of the tested ranking procedures were

Extracting BI-RADS Features from Portuguese Clinical Texts.

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Nassif, Houssam; Cunha, Filipe; Moreira, Inês C; Cruz-Correia, Ricardo; Sousa, Eliana; Page, David; Burnside, Elizabeth; Dutra, Inês

2012-01-01

In this work we build the first BI-RADS parser for Portuguese free texts, modeled after existing approaches to extract BI-RADS features from English medical records. Our concept finder uses a semantic grammar based on the BIRADS lexicon and on iterative transferred expert knowledge. We compare the performance of our algorithm to manual annotation by a specialist in mammography. Our results show that our parser's performance is comparable to the manual method.

Domain-independent information extraction in unstructured text

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Irwin, N.H. [Sandia National Labs., Albuquerque, NM (United States). Software Surety Dept.

1996-09-01

Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.

DiMeX: A Text Mining System for Mutation-Disease Association Extraction.

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Mahmood, A S M Ashique; Wu, Tsung-Jung; Mazumder, Raja; Vijay-Shanker, K

2016-01-01

The number of published articles describing associations between mutations and diseases is increasing at a fast pace. There is a pressing need to gather such mutation-disease associations into public knowledge bases, but manual curation slows down the growth of such databases. We have addressed this problem by developing a text-mining system (DiMeX) to extract mutation to disease associations from publication abstracts. DiMeX consists of a series of natural language processing modules that preprocess input text and apply syntactic and semantic patterns to extract mutation-disease associations. DiMeX achieves high precision and recall with F-scores of 0.88, 0.91 and 0.89 when evaluated on three different datasets for mutation-disease associations. DiMeX includes a separate component that extracts mutation mentions in text and associates them with genes. This component has been also evaluated on different datasets and shown to achieve state-of-the-art performance. The results indicate that our system outperforms the existing mutation-disease association tools, addressing the low precision problems suffered by most approaches. DiMeX was applied on a large set of abstracts from Medline to extract mutation-disease associations, as well as other relevant information including patient/cohort size and population data. The results are stored in a database that can be queried and downloaded at http://biotm.cis.udel.edu/dimex/. We conclude that this high-throughput text-mining approach has the potential to significantly assist researchers and curators to enrich mutation databases.

Vaccine adverse event text mining system for extracting features from vaccine safety reports.

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Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

2012-01-01

To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

MeInfoText 2.0: gene methylation and cancer relation extraction from biomedical literature

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Fang Yu-Ching

2011-12-01

Full Text Available Abstract Background DNA methylation is regarded as a potential biomarker in the diagnosis and treatment of cancer. The relations between aberrant gene methylation and cancer development have been identified by a number of recent scientific studies. In a previous work, we used co-occurrences to mine those associations and compiled the MeInfoText 1.0 database. To reduce the amount of manual curation and improve the accuracy of relation extraction, we have now developed MeInfoText 2.0, which uses a machine learning-based approach to extract gene methylation-cancer relations. Description Two maximum entropy models are trained to predict if aberrant gene methylation is related to any type of cancer mentioned in the literature. After evaluation based on 10-fold cross-validation, the average precision/recall rates of the two models are 94.7/90.1 and 91.8/90% respectively. MeInfoText 2.0 provides the gene methylation profiles of different types of human cancer. The extracted relations with maximum probability, evidence sentences, and specific gene information are also retrievable. The database is available at http://bws.iis.sinica.edu.tw:8081/MeInfoText2/. Conclusion The previous version, MeInfoText, was developed by using association rules, whereas MeInfoText 2.0 is based on a new framework that combines machine learning, dictionary lookup and pattern matching for epigenetics information extraction. The results of experiments show that MeInfoText 2.0 outperforms existing tools in many respects. To the best of our knowledge, this is the first study that uses a hybrid approach to extract gene methylation-cancer relations. It is also the first attempt to develop a gene methylation and cancer relation corpus.

Automatic extraction of property norm-like data from large text corpora.

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Kelly, Colin; Devereux, Barry; Korhonen, Anna

2014-01-01

Traditional methods for deriving property-based representations of concepts from text have focused on either extracting only a subset of possible relation types, such as hyponymy/hypernymy (e.g., car is-a vehicle) or meronymy/metonymy (e.g., car has wheels), or unspecified relations (e.g., car--petrol). We propose a system for the challenging task of automatic, large-scale acquisition of unconstrained, human-like property norms from large text corpora, and discuss the theoretical implications of such a system. We employ syntactic, semantic, and encyclopedic information to guide our extraction, yielding concept-relation-feature triples (e.g., car be fast, car require petrol, car cause pollution), which approximate property-based conceptual representations. Our novel method extracts candidate triples from parsed corpora (Wikipedia and the British National Corpus) using syntactically and grammatically motivated rules, then reweights triples with a linear combination of their frequency and four statistical metrics. We assess our system output in three ways: lexical comparison with norms derived from human-generated property norm data, direct evaluation by four human judges, and a semantic distance comparison with both WordNet similarity data and human-judged concept similarity ratings. Our system offers a viable and performant method of plausible triple extraction: Our lexical comparison shows comparable performance to the current state-of-the-art, while subsequent evaluations exhibit the human-like character of our generated properties.

Large-scale extraction of gene interactions from full-text literature using DeepDive.

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Mallory, Emily K; Zhang, Ce; Ré, Christopher; Altman, Russ B

2016-01-01

A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles. We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles. Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app russ.altman@stanford.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Text mining facilitates database curation - extraction of mutation-disease associations from Bio-medical literature.

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Ravikumar, Komandur Elayavilli; Wagholikar, Kavishwar B; Li, Dingcheng; Kocher, Jean-Pierre; Liu, Hongfang

2015-06-06

Advances in the next generation sequencing technology has accelerated the pace of individualized medicine (IM), which aims to incorporate genetic/genomic information into medicine. One immediate need in interpreting sequencing data is the assembly of information about genetic variants and their corresponding associations with other entities (e.g., diseases or medications). Even with dedicated effort to capture such information in biological databases, much of this information remains 'locked' in the unstructured text of biomedical publications. There is a substantial lag between the publication and the subsequent abstraction of such information into databases. Multiple text mining systems have been developed, but most of them focus on the sentence level association extraction with performance evaluation based on gold standard text annotations specifically prepared for text mining systems. We developed and evaluated a text mining system, MutD, which extracts protein mutation-disease associations from MEDLINE abstracts by incorporating discourse level analysis, using a benchmark data set extracted from curated database records. MutD achieves an F-measure of 64.3% for reconstructing protein mutation disease associations in curated database records. Discourse level analysis component of MutD contributed to a gain of more than 10% in F-measure when compared against the sentence level association extraction. Our error analysis indicates that 23 of the 64 precision errors are true associations that were not captured by database curators and 68 of the 113 recall errors are caused by the absence of associated disease entities in the abstract. After adjusting for the defects in the curated database, the revised F-measure of MutD in association detection reaches 81.5%. Our quantitative analysis reveals that MutD can effectively extract protein mutation disease associations when benchmarking based on curated database records. The analysis also demonstrates that incorporating

A Proposed Arabic Handwritten Text Normalization Method

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Tarik Abu-Ain

2014-11-01

Full Text Available Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and characters recognition. In the present article, a new method for text baseline detection, straightening, and slant correction for Arabic handwritten texts is proposed. The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direction features of the skeletons are extracted, and the candidate baseline regions are determined. After that, selection of the correct baseline region is done, and finally, the baselines of all components are aligned with the writing line.  The experiments are conducted on IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.

Automated Extraction of Substance Use Information from Clinical Texts.

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Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

2015-01-01

Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

Extracting Various Classes of Data From Biological Text Using the Concept of Existence Dependency.

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Taha, Kamal

2015-11-01

One of the key goals of biological natural language processing (NLP) is the automatic information extraction from biomedical publications. Most current constituency and dependency parsers overlook the semantic relationships between the constituents comprising a sentence and may not be well suited for capturing complex long-distance dependences. We propose in this paper a hybrid constituency-dependency parser for biological NLP information extraction called EDCC. EDCC aims at enhancing the state of the art of biological text mining by applying novel linguistic computational techniques that overcome the limitations of current constituency and dependency parsers outlined earlier, as follows: 1) it determines the semantic relationship between each pair of constituents in a sentence using novel semantic rules; and 2) it applies a semantic relationship extraction model that extracts information from different structural forms of constituents in sentences. EDCC can be used to extract different types of data from biological texts for purposes such as protein function prediction, genetic network construction, and protein-protein interaction detection. We evaluated the quality of EDCC by comparing it experimentally with six systems. Results showed marked improvement.

A method for extracting design rationale knowledge based on Text Mining

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Liu Jihong

2017-01-01

Full Text Available Capture design rationale (DR knowledge and presenting it to designers by good form, which have great significance for design reuse and design innovation. Since the 1970s design rationality began to develop, many teams have developed their own design rational system. However, the DR acquisition system is not intelligent enough, and it still requires designers to do a lot of operations. In addition, the existing design documents contain a large number of DR knowledge, but it has not been well excavated. Therefore, a method and system are needed to better extract DR knowledge in design documents. We have proposed a DRKH (design rationale knowledge hierarchy model for DR representation. The DRKH model has three layers, respectively as design intent layer, design decision layer and design basis layer. In this paper, we use text mining method to extract DR from design documents and construct DR model. Finally, the welding robot design specification is taken as an example to demonstrate the system interface.

Pharmspresso: a text mining tool for extraction of pharmacogenomic concepts and relationships from full text.

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Garten, Yael; Altman, Russ B

2009-02-05

Pharmacogenomics studies the relationship between genetic variation and the variation in drug response phenotypes. The field is rapidly gaining importance: it promises drugs targeted to particular subpopulations based on genetic background. The pharmacogenomics literature has expanded rapidly, but is dispersed in many journals. It is challenging, therefore, to identify important associations between drugs and molecular entities--particularly genes and gene variants, and thus these critical connections are often lost. Text mining techniques can allow us to convert the free-style text to a computable, searchable format in which pharmacogenomic concepts (such as genes, drugs, polymorphisms, and diseases) are identified, and important links between these concepts are recorded. Availability of full text articles as input into text mining engines is key, as literature abstracts often do not contain sufficient information to identify these pharmacogenomic associations. Thus, building on a tool called Textpresso, we have created the Pharmspresso tool to assist in identifying important pharmacogenomic facts in full text articles. Pharmspresso parses text to find references to human genes, polymorphisms, drugs and diseases and their relationships. It presents these as a series of marked-up text fragments, in which key concepts are visually highlighted. To evaluate Pharmspresso, we used a gold standard of 45 human-curated articles. Pharmspresso identified 78%, 61%, and 74% of target gene, polymorphism, and drug concepts, respectively. Pharmspresso is a text analysis tool that extracts pharmacogenomic concepts from the literature automatically and thus captures our current understanding of gene-drug interactions in a computable form. We have made Pharmspresso available at http://pharmspresso.stanford.edu.

Region-Based Building Rooftop Extraction and Change Detection

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Tian, J.; Metzlaff, L.; d'Angelo, P.; Reinartz, P.

2017-09-01

Automatic extraction of building changes is important for many applications like disaster monitoring and city planning. Although a lot of research work is available based on 2D as well as 3D data, an improvement in accuracy and efficiency is still needed. The introducing of digital surface models (DSMs) to building change detection has strongly improved the resulting accuracy. In this paper, a post-classification approach is proposed for building change detection using satellite stereo imagery. Firstly, DSMs are generated from satellite stereo imagery and further refined by using a segmentation result obtained from the Sobel gradients of the panchromatic image. Besides the refined DSMs, the panchromatic image and the pansharpened multispectral image are used as input features for mean-shift segmentation. The DSM is used to calculate the nDSM, out of which the initial building candidate regions are extracted. The candidate mask is further refined by morphological filtering and by excluding shadow regions. Following this, all segments that overlap with a building candidate region are determined. A building oriented segments merging procedure is introduced to generate a final building rooftop mask. As the last step, object based change detection is performed by directly comparing the building rooftops extracted from the pre- and after-event imagery and by fusing the change indicators with the roof-top region map. A quantitative and qualitative assessment of the proposed approach is provided by using WorldView-2 satellite data from Istanbul, Turkey.

Valx: A System for Extracting and Structuring Numeric Lab Test Comparison Statements from Text.

Science.gov (United States)

Hao, Tianyong; Liu, Hongfang; Weng, Chunhua

2016-05-17

To develop an automated method for extracting and structuring numeric lab test comparison statements from text and evaluate the method using clinical trial eligibility criteria text. Leveraging semantic knowledge from the Unified Medical Language System (UMLS) and domain knowledge acquired from the Internet, Valx takes seven steps to extract and normalize numeric lab test expressions: 1) text preprocessing, 2) numeric, unit, and comparison operator extraction, 3) variable identification using hybrid knowledge, 4) variable - numeric association, 5) context-based association filtering, 6) measurement unit normalization, and 7) heuristic rule-based comparison statements verification. Our reference standard was the consensus-based annotation among three raters for all comparison statements for two variables, i.e., HbA1c and glucose, identified from all of Type 1 and Type 2 diabetes trials in ClinicalTrials.gov. The precision, recall, and F-measure for structuring HbA1c comparison statements were 99.6%, 98.1%, 98.8% for Type 1 diabetes trials, and 98.8%, 96.9%, 97.8% for Type 2 diabetes trials, respectively. The precision, recall, and F-measure for structuring glucose comparison statements were 97.3%, 94.8%, 96.1% for Type 1 diabetes trials, and 92.3%, 92.3%, 92.3% for Type 2 diabetes trials, respectively. Valx is effective at extracting and structuring free-text lab test comparison statements in clinical trial summaries. Future studies are warranted to test its generalizability beyond eligibility criteria text. The open-source Valx enables its further evaluation and continued improvement among the collaborative scientific community.

Scene text recognition in mobile applications by character descriptor and structure configuration.

Science.gov (United States)

Yi, Chucai; Tian, Yingli

2014-07-01

Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

AN ITERATIVE SEGMENTATION METHOD FOR REGION OF INTEREST EXTRACTION

Directory of Open Access Journals (Sweden)

Volkan CETIN

2013-01-01

Full Text Available In this paper, a method is presented for applications which include mammographic image segmentation and region of interest extraction. Segmentation is a very critical and difficult stage to accomplish in computer aided detection systems. Although the presented segmentation method is developed for mammographic images, it can be used for any medical image which resembles the same statistical characteristics with mammograms. Fundamentally, the method contains iterative automatic thresholding and masking operations which is applied to the original or enhanced mammograms. Also the effect of image enhancement to the segmentation process was observed. A version of histogram equalization was applied to the images for enhancement. Finally, the results show that enhanced version of the proposed segmentation method is preferable because of its better success rate.

Measurement of the [Formula: see text] and [Formula: see text] production cross sections in multilepton final states using 3.2 fb[Formula: see text] of [Formula: see text] collisions at [Formula: see text] = 13 TeV with the ATLAS detector.

Science.gov (United States)

Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; Aben, R; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Agricola, J; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Ali, B; Aliev, M; Alimonti, G; Alison, J; Alkire, S P; Allbrooke, B M M; Allen, B W; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Alstaty, M; Alvarez Gonzalez, B; Álvarez Piqueras, D; Alviggi, M G; Amadio, B T; Amako, K; Amaral Coutinho, Y; Amelung, C; Amidei, D; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anders, J K; Anderson, K J; Andreazza, A; Andrei, V; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antel, C; Antonelli, M; Antonov, A; Anulli, F; Aoki, M; Aperio Bella, L; Arabidze, G; Arai, Y; Araque, J P; Arce, A T H; Arduh, F A; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Armitage, L J; Arnaez, O; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Artz, S; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Augsten, K; Avolio, G; Axen, B; Ayoub, M K; Azuelos, G; Baak, M A; Baas, A E; Baca, M J; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Bagiacchi, P; Bagnaia, P; Bai, Y; Baines, J T; Baker, O K; Baldin, E M; Balek, P; Balestri, T; Balli, F; Balunas, W K; Banas, E; Banerjee, Sw; Bannoura, A A E; Barak, L; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barklow, T; Barlow, N; Barnes, S L; Barnett, B M; Barnett, R M; Barnovska-Blenessy, Z; Baroncelli, A; Barone, G; Barr, A J; Barranco Navarro, L; Barreiro, F; Barreiro Guimarães da Costa, J; Bartoldus, R; Barton, A E; Bartos, P; Basalaev, A; Bassalat, A; Bates, R L; Batista, S J; Batley, J R; Battaglia, M; Bauce, M; Bauer, F; Bawa, H S; Beacham, J B; Beattie, M D; Beau, T; Beauchemin, P H; Bechtle, P; Beck, H P; Becker, K; Becker, M; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bednyakov, V A; Bedognetti, M; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Belanger-Champagne, C; Bell, A S; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Belyaev, N L; Benary, O; Benchekroun, D; Bender, M; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez, J; Benjamin, D P; Bensinger, J R; Bentvelsen, S; Beresford, L; Beretta, M; Berge, D; Bergeaas Kuutmann, E; Berger, N; Beringer, J; Berlendis, S; Bernard, N R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertram, I A; Bertsche, C; Bertsche, D; Besjes, G J; Bessidskaia Bylund, O; Bessner, M; Besson, N; Betancourt, C; Bethke, S; Bevan, A J; Bhimji, W; Bianchi, R M; Bianchini, L; Bianco, M; Biebel, O; Biedermann, D; Bielski, R; Biesuz, N V; Biglietti, M; De Mendizabal, J Bilbao; Bilokon, H; Bindi, M; Binet, S; Bingul, A; Bini, C; Biondi, S; Bjergaard, D M; Black, C W; Black, J E; Black, K M; Blackburn, D; Blair, R E; Blanchard, J-B; Blanco, J E; Blazek, T; Bloch, I; Blocker, C; Blum, W; Blumenschein, U; Blunier, S; Bobbink, G J; Bobrovnikov, V S; Bocchetta, S S; Bocci, A; Bock, C; Boehler, M; Boerner, D; Bogaerts, J A; Bogavac, D; Bogdanchikov, A G; Bohm, C; Boisvert, V; Bokan, P; Bold, T; Boldyrev, A S; Bomben, M; Bona, M; Boonekamp, M; Borisov, A; Borissov, G; Bortfeldt, J; Bortoletto, D; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Bossio Sola, J D; Boudreau, J; Bouffard, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Boutle, S K; Boveia, A; Boyd, J; Boyko, I R; Bracinik, J; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Braun, H M; Breaden Madden, W D; Brendlinger, K; Brennan, A J; Brenner, L; Brenner, R; Bressler, S; Bristow, T M; Britton, D; Britzger, D; Brochu, F M; Brock, I; Brock, R; Brooijmans, G; Brooks, T; Brooks, W K; Brosamer, J; Brost, E; Broughton, J H; de Renstrom, P A Bruckman; Bruncko, D; Bruneliere, R; Bruni, A; Bruni, G; Bruni, L S; Brunt, B H; Bruschi, M; Bruscino, N; Bryant, P; Bryngemark, L; Buanes, T; Buat, Q; Buchholz, P; Buckley, A G; Budagov, I A; Buehrer, F; Bugge, M K; Bulekov, O; Bullock, D; Burckhart, H; Burdin, S; Burgard, C D; Burghgrave, B; Burka, K; Burke, S; Burmeister, I; Burr, J T P; Busato, E; Büscher, D; Büscher, V; Bussey, P; Butler, J M; Buttar, C M; Butterworth, J M; Butti, P; Buttinger, W; Buzatu, A; Buzykaev, A R; Cabrera Urbán, S; Caforio, D; Cairo, V M; Cakir, O; Calace, N; Calafiura, P; Calandri, A; Calderini, G; Calfayan, P; Caloba, L P; Lopez, S Calvente; Calvet, D; Calvet, S; Calvet, T P; Toro, R Camacho; Camarda, S; Camarri, P; Cameron, D; Caminal Armadans, R; Camincher, C; Campana, S; Campanelli, M; Camplani, A; Campoverde, A; Canale, V; Canepa, A; Cano Bret, M; Cantero, J; Cantrill, R; Cao, T; Capeans Garrido, M D M; Caprini, I; Caprini, M; Capua, M; Caputo, R; Carbone, R M; Cardarelli, R; Cardillo, F; Carli, I; Carli, T; Carlino, G; Carminati, L; Caron, S; Carquin, E; Carrillo-Montoya, G D; Carter, J R; Carvalho, J; Casadei, D; Casado, M P; Casolino, M; Casper, D W; Castaneda-Miranda, E; Castelijn, R; Castelli, A; Gimenez, V Castillo; Castro, N F; Catinaccio, A; Catmore, J R; Cattai, A; Caudron, J; Cavaliere, V; Cavallaro, E; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Ceradini, F; Cerda Alberich, L; Cerio, B C; Cerqueira, A S; Cerri, A; Cerrito, L; Cerutti, F; Cerv, M; Cervelli, A; Cetin, S A; Chafaq, A; Chakraborty, D; Chan, S K; Chan, Y L; Chang, P; Chapman, J D; Charlton, D G; Chatterjee, A; Chau, C C; Chavez Barajas, C A; Che, S; Cheatham, S; Chegwidden, A; Chekanov, S; Chekulaev, S V; Chelkov, G A; Chelstowska, M A; Chen, C; Chen, H; Chen, K; Chen, S; Chen, S; Chen, X; Chen, Y; Cheng, H C; Cheng, H J; Cheng, Y; Cheplakov, A; Cheremushkina, E; Moursli, R Cherkaoui El; Chernyatin, V; Cheu, E; Chevalier, L; Chiarella, V; Chiarelli, G; Chiodini, G; Chisholm, A S; Chitan, A; Chizhov, M V; Choi, K; Chomont, A R; Chouridou, S; Chow, B K B; Christodoulou, V; Chromek-Burckhart, D; Chudoba, J; Chuinard, A J; Chwastowski, J J; Chytka, L; Ciapetti, G; Ciftci, A K; Cinca, D; Cindro, V; Cioara, I A; Ciocca, C; Ciocio, A; Cirotto, F; Citron, Z H; Citterio, M; Ciubancan, M; Clark, A; Clark, B L; Clark, M R; Clark, P J; Clarke, R N; Clement, C; Coadou, Y; Cobal, M; Coccaro, A; Cochran, J; Coffey, L; Colasurdo, L; Cole, B; Colijn, A P; Collot, J; Colombo, T; Compostella, G; Conde Muiño, P; Coniavitis, E; Connell, S H; Connelly, I A; Consorti, V; Constantinescu, S; Conti, G; Conventi, F; Cooke, M; Cooper, B D; Cooper-Sarkar, A M; Cormier, K J R; Cornelissen, T; Corradi, M; Corriveau, F; Corso-Radu, A; Cortes-Gonzalez, A; Cortiana, G; Costa, G; Costa, M J; Costanzo, D; Cottin, G; Cowan, G; Cox, B E; Cranmer, K; Crawley, S J; Cree, G; Crépé-Renaudin, S; Crescioli, F; Cribbs, W A; Crispin Ortuzar, M; Cristinziani, M; Croft, V; Crosetti, G; Cuhadar Donszelmann, T; Cummings, J; Curatolo, M; Cúth, J; Cuthbert, C; Czirr, H; Czodrowski, P; D'amen, G; D'Auria, S; D'Onofrio, M; De Sousa, M J Da Cunha Sargedas; Da Via, C; Dabrowski, W; Dado, T; Dai, T; Dale, O; Dallaire, F; Dallapiccola, C; Dam, M; Dandoy, J R; Dang, N P; Daniells, A C; Dann, N S; Danninger, M; Dano Hoffmann, M; Dao, V; Darbo, G; Darmora, S; Dassoulas, J; Dattagupta, A; Davey, W; David, C; Davidek, T; Davies, M; Davison, P; Dawe, E; Dawson, I; Daya-Ishmukhametova, R K; De, K; de Asmundis, R; De Benedetti, A; De Castro, S; De Cecco, S; De Groot, N; de Jong, P; De la Torre, H; De Lorenzi, F; De Maria, A; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Regie, J B De Vivie; Dearnaley, W J; Debbe, R; Debenedetti, C; Dedovich, D V; Dehghanian, N; Deigaard, I; Del Gaudio, M; Del Peso, J; Del Prete, T; Delgove, D; Deliot, F; Delitzsch, C M; Deliyergiyev, M; Dell'Acqua, A; Dell'Asta, L; Dell'Orso, M; Della Pietra, M; Della Volpe, D; Delmastro, M; Delsart, P A; DeMarco, D A; Demers, S; Demichev, M; Demilly, A; Denisov, S P; Denysiuk, D; Derendarz, D; Derkaoui, J E; Derue, F; Dervan, P; Desch, K; Deterre, C; Dette, K; Deviveiros, P O; Dewhurst, A; Dhaliwal, S; Di Ciaccio, A; Di Ciaccio, L; Di Clemente, W K; Di Donato, C; Di Girolamo, A; Di Girolamo, B; Di Micco, B; Di Nardo, R; Di Simone, A; Di Sipio, R; Di Valentino, D; Diaconu, C; Diamond, M; Dias, F A; Diaz, M A; Diehl, E B; Dietrich, J; Diglio, S; Dimitrievska, A; Dingfelder, J; Dita, P; Dita, S; Dittus, F; Djama, F; Djobava, T; Djuvsland, J I; do Vale, M A B; Dobos, D; Dobre, M; Doglioni, C; Dohmae, T; Dolejsi, J; Dolezal, Z; Dolgoshein, B A; Donadelli, M; Donati, S; Dondero, P; Donini, J; Dopke, J; Doria, A; Dova, M T; Doyle, A T; Drechsler, E; Dris, M; Du, Y; Duarte-Campderros, J; Duchovni, E; Duckeck, G; Ducu, O A; Duda, D; Dudarev, A; Duffield, E M; Duflot, L; Duguid, L; Dührssen, M; Dumancic, M; Dunford, M; Duran Yildiz, H; Düren, M; Durglishvili, A; Duschinger, D; Dutta, B; Dyndal, M; Eckardt, C; Ecker, K M; Edgar, R C; Edwards, N C; Eifert, T; Eigen, G; Einsweiler, K; Ekelof, T; El Kacimi, M; Ellajosyula, V; Ellert, M; Elles, S; Ellinghaus, F; Elliot, A A; Ellis, N; Elmsheuser, J; Elsing, M; Emeliyanov, D; Enari, Y; Endner, O C; Endo, M; Ennis, J S; Erdmann, J; Ereditato, A; Ernis, G; Ernst, J; Ernst, M; Errede, S; Ertel, E; Escalier, M; Esch, H; Escobar, C; Esposito, B; Etienvre, A I; Etzion, E; Evans, H; Ezhilov, A; Fabbri, F; Fabbri, L; Facini, G; Fakhrutdinov, R M; Falciano, S; Falla, R J; Faltova, J; Fang, Y; Fanti, M; Farbin, A; Farilla, A; Farina, C; Farina, E M; Farooque, T; Farrell, S; Farrington, S M; Farthouat, P; Fassi, F; Fassnacht, P; Fassouliotis, D; Faucci Giannelli, M; Favareto, A; Fawcett, W J; Fayard, L; Fedin, O L; Fedorko, W; Feigl, S; Feligioni, L; Feng, C; Feng, E J; Feng, H; Fenyuk, A B; Feremenga, L; Fernandez Martinez, P; Fernandez Perez, S; Ferrando, J; Ferrari, A; Ferrari, P; Ferrari, R; de Lima, D E Ferreira; Ferrer, A; Ferrere, D; Ferretti, C; Ferretto Parodi, A; Fiedler, F; Filipčič, A; Filipuzzi, M; Filthaut, F; Fincke-Keeler, M; Finelli, K D; Fiolhais, M C N; Fiorini, L; Firan, A; Fischer, A; Fischer, C; Fischer, J; Fisher, W C; Flaschel, N; Fleck, I; Fleischmann, P; Fletcher, G T; Fletcher, R R M; Flick, T; Floderus, A; Flores Castillo, L R; Flowerdew, M J; Forcolin, G T; Formica, A; Forti, A; Foster, A G; Fournier, D; Fox, H; Fracchia, S; Francavilla, P; Franchini, M; Francis, D; Franconi, L; Franklin, M; Frate, M; Fraternali, M; Freeborn, D; Fressard-Batraneanu, S M; Friedrich, F; Froidevaux, D; Frost, J A; Fukunaga, C; Fullana Torregrosa, E; Fusayasu, T; Fuster, J; Gabaldon, C; Gabizon, O; Gabrielli, A; Gabrielli, A; Gach, G P; Gadatsch, S; Gadomski, S; Gagliardi, G; Gagnon, L G; Gagnon, P; Galea, C; Galhardo, B; Gallas, E J; Gallop, B J; Gallus, P; Galster, G; Gan, K K; Gao, J; Gao, Y; Gao, Y S; Garay Walls, F M; García, C; García Navarro, J E; Garcia-Sciveres, M; Gardner, R W; Garelli, N; Garonne, V; Gascon Bravo, A; Gatti, C; Gaudiello, A; Gaudio, G; Gaur, B; Gauthier, L; Gavrilenko, I L; Gay, C; Gaycken, G; Gazis, E N; Gecse, Z; Gee, C N P; Geich-Gimbel, Ch; Geisen, M; Geisler, M P; Gemme, C; Genest, M H; Geng, C; Gentile, S; George, S; Gerbaudo, D; Gershon, A; Ghasemi, S; Ghazlane, H; Ghneimat, M; Giacobbe, B; Giagu, S; Giannetti, P; Gibbard, B; Gibson, S M; Gignac, M; Gilchriese, M; Gillam, T P S; Gillberg, D; Gilles, G; Gingrich, D M; Giokaris, N; Giordani, M P; Giorgi, F M; Giorgi, F M; Giraud, P F; Giromini, P; Giugni, D; Giuli, F; Giuliani, C; Giulini, M; Gjelsten, B K; Gkaitatzis, S; Gkialas, I; Gkougkousis, E L; Gladilin, L K; Glasman, C; Glatzer, J; Glaysher, P C F; Glazov, A; Goblirsch-Kolb, M; Godlewski, J; Goldfarb, S; Golling, T; Golubkov, D; Gomes, A; Gonçalo, R; Costa, J Goncalves Pinto Firmino Da; Gonella, G; Gonella, L; Gongadze, A; de la Hoz, S González; Gonzalez Parra, G; Gonzalez-Sevilla, S; Goossens, L; Gorbounov, P A; Gordon, H A; Gorelov, I; Gorini, B; Gorini, E; Gorišek, A; Gornicki, E; Goshaw, A T; Gössling, C; Gostkin, M I; Goudet, C R; Goujdami, D; Goussiou, A G; Govender, N; Gozani, E; Graber, L; Grabowska-Bold, I; Gradin, P O J; Grafström, P; Gramling, J; Gramstad, E; Grancagnolo, S; Gratchev, V; Gravila, P M; Gray, H M; Graziani, E; Greenwood, Z D; Grefe, C; Gregersen, K; Gregor, I M; Grenier, P; Grevtsov, K; Griffiths, J; Grillo, A A; Grimm, K; Grinstein, S; Gris, Ph; Grivaz, J-F; Groh, S; Grohs, J P; Gross, E; Grosse-Knetter, J; Grossi, G C; Grout, Z J; Guan, L; Guan, W; Guenther, J; Guescini, F; Guest, D; Gueta, O; Guido, E; Guillemin, T; Guindon, S; Gul, U; Gumpert, C; Guo, J; Guo, Y; Gupta, S; Gustavino, G; Gutierrez, P; Gutierrez Ortiz, N G; Gutschow, C; Guyot, C; Gwenlan, C; Gwilliam, C B; Haas, A; Haber, C; Hadavand, H K; Haddad, N; Hadef, A; Haefner, P; Hageböck, S; Hajduk, Z; Hakobyan, H; Haleem, M; Haley, J; Halladjian, G; Hallewell, G D; Hamacher, K; Hamal, P; Hamano, K; Hamilton, A; Hamity, G N; Hamnett, P G; Han, L; Hanagaki, K; Hanawa, K; Hance, M; Haney, B; Hanke, P; Hanna, R; Hansen, J B; Hansen, J D; Hansen, M C; Hansen, P H; Hara, K; Hard, A S; Harenberg, T; Hariri, F; Harkusha, S; Harrington, R D; Harrison, P F; Hartjes, F; Hartmann, N M; Hasegawa, M; Hasegawa, Y; Hasib, A; Hassani, S; Haug, S; Hauser, R; Hauswald, L; Havranek, M; Hawkes, C M; Hawkings, R J; Hayden, D; Hays, C P; Hays, J M; Hayward, H S; Haywood, S J; Head, S J; Heck, T; Hedberg, V; Heelan, L; Heim, S; Heim, T; Heinemann, B; Heinrich, J J; Heinrich, L; Heinz, C; Hejbal, J; Helary, L; Hellman, S; Helsens, C; Henderson, J; Henderson, R C W; Heng, Y; Henkelmann, S; Henriques Correia, A M; Henrot-Versille, S; Herbert, G H; Hernández Jiménez, Y; Herten, G; Hertenberger, R; Hervas, L; Hesketh, G G; Hessey, N P; Hetherly, J W; Hickling, R; Higón-Rodriguez, E; Hill, E; Hill, J C; Hiller, K H; Hillier, S J; Hinchliffe, I; Hines, E; Hinman, R R; Hirose, M; Hirschbuehl, D; Hobbs, J; Hod, N; Hodgkinson, M C; Hodgson, P; Hoecker, A; Hoeferkamp, M R; Hoenig, F; Hohn, D; Holmes, T R; Homann, M; Hong, T M; Hooberman, B H; Hopkins, W H; Horii, Y; Horton, A J; Hostachy, J-Y; Hou, S; Hoummada, A; Howarth, J; Hrabovsky, M; Hristova, I; Hrivnac, J; Hryn'ova, T; Hrynevich, A; Hsu, C; Hsu, P J; Hsu, S-C; Hu, D; Hu, Q; Huang, Y; Hubacek, Z; Hubaut, F; Huegging, F; Huffman, T B; Hughes, E W; Hughes, G; Huhtinen, M; Huo, P; Huseynov, N; Huston, J; Huth, J; Iacobucci, G; Iakovidis, G; Ibragimov, I; Iconomidou-Fayard, L; Ideal, E; Idrissi, Z; Iengo, P; Igonkina, O; Iizawa, T; Ikegami, Y; Ikeno, M; Ilchenko, Y; Iliadis, D; Ilic, N; Ince, T; Introzzi, G; Ioannou, P; Iodice, M; Iordanidou, K; Ippolito, V; Ishijima, N; Ishino, M; Ishitsuka, M; Ishmukhametov, R; Issever, C; Istin, S; Ito, F; Iturbe Ponce, J M; Iuppa, R; Iwanski, W; Iwasaki, H; Izen, J M; Izzo, V; Jabbar, S; Jackson, B; Jackson, M; Jackson, P; Jain, V; Jakobi, K B; Jakobs, K; Jakobsen, S; Jakoubek, T; Jamin, D O; Jana, D K; Jansen, E; Jansky, R; Janssen, J; Janus, M; Jarlskog, G; Javadov, N; Javůrek, T; Jeanneau, F; Jeanty, L; Jeng, G-Y; Jennens, D; Jenni, P; Jentzsch, J; Jeske, C; Jézéquel, S; Ji, H; Jia, J; Jiang, H; Jiang, Y; Jiggins, S; Jimenez Pena, J; Jin, S; Jinaru, A; Jinnouchi, O; Johansson, P; Johns, K A; Johnson, W J; Jon-And, K; Jones, G; Jones, R W L; Jones, S; Jones, T J; Jongmanns, J; Jorge, P M; Jovicevic, J; Ju, X; Juste Rozas, A; Köhler, M K; Kaczmarska, A; Kado, M; Kagan, H; Kagan, M; Kahn, S J; Kajomovitz, E; Kalderon, C W; Kaluza, A; Kama, S; Kamenshchikov, A; Kanaya, N; Kaneti, S; Kanjir, L; Kantserov, V A; Kanzaki, J; Kaplan, B; Kaplan, L S; Kapliy, A; Kar, D; Karakostas, K; Karamaoun, A; Karastathis, N; Kareem, M J; Karentzos, E; Karnevskiy, M; Karpov, S N; Karpova, Z M; Karthik, K; Kartvelishvili, V; Karyukhin, A N; Kasahara, K; Kashif, L; Kass, R D; Kastanas, A; Kataoka, Y; Kato, C; Katre, A; Katzy, J; Kawade, K; Kawagoe, K; Kawamoto, T; Kawamura, G; Kazama, S; Kazanin, V F; Keeler, R; Kehoe, R; Keller, J S; Kempster, J J; Keoshkerian, H; Kepka, O; Kerševan, B P; Kersten, S; Keyes, R A; Khader, M; Khalil-Zada, F; Khanov, A; Kharlamov, A G; Khoo, T J; Khovanskiy, V; Khramov, E; Khubua, J; Kido, S; Kim, H Y; Kim, S H; Kim, Y K; Kimura, N; Kind, O M; King, B T; King, M; King, S B; Kirk, J; Kiryunin, A E; Kishimoto, T; Kisielewska, D; Kiss, F; Kiuchi, K; Kivernyk, O; Kladiva, E; Klein, M H; Klein, M; Klein, U; Kleinknecht, K; Klimek, P; Klimentov, A; Klingenberg, R; Klinger, J A; Klioutchnikova, T; Kluge, E-E; Kluit, P; Kluth, S; Knapik, J; Kneringer, E; Knoops, E B F G; Knue, A; Kobayashi, A; Kobayashi, D; Kobayashi, T; Kobel, M; Kocian, M; Kodys, P; Koffas, T; Koffeman, E; Koi, T; Kolanoski, H; Kolb, M; Koletsou, I; Komar, A A; Komori, Y; Kondo, T; Kondrashova, N; Köneke, K; König, A C; Kono, T; Konoplich, R; Konstantinidis, N; Kopeliansky, R; Koperny, S; Köpke, L; Kopp, A K; Korcyl, K; Kordas, K; Korn, A; Korol, A A; Korolkov, I; Korolkova, E V; Kortner, O; Kortner, S; Kosek, T; Kostyukhin, V V; Kotwal, A; Kourkoumeli-Charalampidi, A; Kourkoumelis, C; Kouskoura, V; Kowalewska, A B; Kowalewski, R; Kowalski, T Z; Kozakai, C; Kozanecki, W; Kozhin, A S; Kramarenko, V A; Kramberger, G; Krasnopevtsev, D; Krasny, M W; Krasznahorkay, A; Kraus, J K; Kravchenko, A; Kretz, M; Kretzschmar, J; Kreutzfeldt, K; Krieger, P; Krizka, K; Kroeninger, K; Kroha, H; Kroll, J; Kroseberg, J; Krstic, J; Kruchonak, U; Krüger, H; Krumnack, N; Kruse, A; Kruse, M C; Kruskal, M; Kubota, T; Kucuk, H; Kuday, S; Kuechler, J T; Kuehn, S; Kugel, A; Kuger, F; Kuhl, A; Kuhl, T; Kukhtin, V; Kukla, R; Kulchitsky, Y; Kuleshov, S; Kuna, M; Kunigo, T; Kupco, A; Kurashige, H; Kurochkin, Y A; Kus, V; Kuwertz, E S; Kuze, M; Kvita, J; Kwan, T; Kyriazopoulos, D; La Rosa, A; La Rosa Navarro, J L; La Rotonda, L; Lacasta, C; Lacava, F; Lacey, J; Lacker, H; Lacour, D; Lacuesta, V R; Ladygin, E; Lafaye, R; Laforge, B; Lagouri, T; Lai, S; Lammers, S; Lampl, W; Lançon, E; Landgraf, U; Landon, M P J; Lang, V S; Lange, J C; Lankford, A J; Lanni, F; Lantzsch, K; Lanza, A; Laplace, S; Lapoire, C; Laporte, J F; Lari, T; Lasagni Manghi, F; Lassnig, M; Laurelli, P; Lavrijsen, W; Law, A T; Laycock, P; Lazovich, T; Lazzaroni, M; Le, B; Le Dortz, O; Le Guirriec, E; Quilleuc, E P Le; LeBlanc, M; LeCompte, T; Ledroit-Guillon, F; Lee, C A; Lee, S C; Lee, L; Lefebvre, G; Lefebvre, M; Legger, F; Leggett, C; Lehan, A; Lehmann Miotto, G; Lei, X; Leight, W A; Leisos, A; Leister, A G; Leite, M A L; Leitner, R; Lellouch, D; Lemmer, B; Leney, K J C; Lenz, T; Lenzi, B; Leone, R; Leone, S; Leonidopoulos, C; Leontsinis, S; Lerner, G; Leroy, C; Lesage, A A J; Lester, C G; Levchenko, M; Levêque, J; Levin, D; Levinson, L J; Levy, M; Lewis, D; Leyko, A M; Leyton, M; Li, B; Li, H; Li, H L; Li, L; Li, L; Li, Q; Li, S; Li, X; Li, Y; Liang, Z; Liberti, B; Liblong, A; Lichard, P; Lie, K; Liebal, J; Liebig, W; Limosani, A; Lin, S C; Lin, T H; Lindquist, B E; Lionti, A E; Lipeles, E; Lipniacka, A; Lisovyi, M; Liss, T M; Lister, A; Litke, A M; Liu, B; Liu, D; Liu, H; Liu, H; Liu, J; Liu, J B; Liu, K; Liu, L; Liu, M; Liu, M; Liu, Y L; Liu, Y; Livan, M; Lleres, A; Llorente Merino, J; Lloyd, S L; Lo Sterzo, F; Lobodzinska, E M; Loch, P; Lockman, W S; Loebinger, F K; Loevschall-Jensen, A E; Loew, K M; Loginov, A; Lohse, T; Lohwasser, K; Lokajicek, M; Long, B A; Long, J D; Long, R E; Longo, L; Looper, K A; Lopes, L; Lopez Mateos, D; Lopez Paredes, B; Lopez Paz, I; Lopez Solis, A; Lorenz, J; Lorenzo Martinez, N; Losada, M; Lösel, P J; Lou, X; Lounis, A; Love, J; Love, P A; Lu, H; Lu, N; Lubatti, H J; Luci, C; Lucotte, A; Luedtke, C; Luehring, F; Lukas, W; Luminari, L; Lundberg, O; Lund-Jensen, B; Luzi, P M; Lynn, D; Lysak, R; Lytken, E; Lyubushkin, V; Ma, H; Ma, L L; Ma, Y; Maccarrone, G; Macchiolo, A; Macdonald, C M; Maček, B; Machado Miguens, J; Madaffari, D; Madar, R; Maddocks, H J; Mader, W F; Madsen, A; Maeda, J; Maeland, S; Maeno, T; Maevskiy, A; Magradze, E; Mahlstedt, J; Maiani, C; Maidantchik, C; Maier, A A; Maier, T; Maio, A; Majewski, S; Makida, Y; Makovec, N; Malaescu, B; Malecki, Pa; Maleev, V P; Malek, F; Mallik, U; Malon, D; Malone, C; Maltezos, S; Malyukov, S; Mamuzic, J; Mancini, G; Mandelli, B; Mandelli, L; Mandić, I; Maneira, J; Filho, L Manhaes de Andrade; Manjarres Ramos, J; Mann, A; Manousos, A; Mansoulie, B; Mansour, J D; Mantifel, R; Mantoani, M; Manzoni, S; Mapelli, L; Marceca, G; March, L; Marchiori, G; Marcisovsky, M; Marjanovic, M; Marley, D E; Marroquim, F; Marsden, S P; Marshall, Z; Marti-Garcia, S; Martin, B; Martin, T A; Martin, V J; Latour, B Martin Dit; Martinez, M; Martinez Outschoorn, V I; Martin-Haugh, S; Martoiu, V S; Martyniuk, A C; Marx, M; Marzin, A; Masetti, L; Mashimo, T; Mashinistov, R; Masik, J; Maslennikov, A L; Massa, I; Massa, L; Mastrandrea, P; Mastroberardino, A; Masubuchi, T; Mättig, P; Mattmann, J; Maurer, J; Maxfield, S J; Maximov, D A; Mazini, R; Mazza, S M; Mc Fadden, N C; Goldrick, G Mc; Mc Kee, S P; McCarn, A; McCarthy, R L; McCarthy, T G; McClymont, L I; McDonald, E F; McFarlane, K W; Mcfayden, J A; Mchedlidze, G; McMahon, S J; McPherson, R A; Medinnis, M; Meehan, S; Mehlhase, S; Mehta, A; Meier, K; Meineck, C; Meirose, B; Melini, D; Mellado Garcia, B R; Melo, M; Meloni, F; Mengarelli, A; Menke, S; Meoni, E; Mergelmeyer, S; Mermod, P; Merola, L; Meroni, C; Merritt, F S; Messina, A; Metcalfe, J; Mete, A S; Meyer, C; Meyer, C; Meyer, J-P; Meyer, J; Meyer Zu Theenhausen, H; Miano, F; Middleton, R P; Miglioranzi, S; Mijović, L; Mikenberg, G; Mikestikova, M; Mikuž, M; Milesi, M; Milic, A; Miller, D W; Mills, C; Milov, A; Milstead, D A; Minaenko, A A; Minami, Y; Minashvili, I A; Mincer, A I; Mindur, B; Mineev, M; Ming, Y; Mir, L M; Mistry, K P; Mitani, T; Mitrevski, J; Mitsou, V A; Miucci, A; Miyagawa, P S; Mjörnmark, J U; Moa, T; Mochizuki, K; Mohapatra, S; Molander, S; Moles-Valls, R; Monden, R; Mondragon, M C; Mönig, K; Monk, J; Monnier, E; Montalbano, A; Montejo Berlingen, J; Monticelli, F; Monzani, S; Moore, R W; Morange, N; Moreno, D; Moreno Llácer, M; Morettini, P; Morgenstern, S; Mori, D; Mori, T; Morii, M; Morinaga, M; Morisbak, V; Moritz, S; Morley, A K; Mornacchi, G; Morris, J D; Mortensen, S S; Morvaj, L; Mosidze, M; Moss, J; Motohashi, K; Mount, R; Mountricha, E; Mouraviev, S V; Moyse, E J W; Muanza, S; Mudd, R D; Mueller, F; Mueller, J; Mueller, R S P; Mueller, T; Muenstermann, D; Mullen, P; Mullier, G A; Munoz Sanchez, F J; Murillo Quijada, J A; Murray, W J; Musheghyan, H; Muškinja, M; Myagkov, A G; Myska, M; Nachman, B P; Nackenhorst, O; Nagai, K; Nagai, R; Nagano, K; Nagasaka, Y; Nagata, K; Nagel, M; Nagy, E; Nairz, A M; Nakahama, Y; Nakamura, K; Nakamura, T; Nakano, I; Namasivayam, H; Naranjo Garcia, R F; Narayan, R; Narrias Villar, D I; Naryshkin, I; Naumann, T; Navarro, G; Nayyar, R; Neal, H A; Nechaeva, P Yu; Neep, T J; Nef, P D; Negri, A; Negrini, M; Nektarijevic, S; Nellist, C; Nelson, A; Nemecek, S; Nemethy, P; Nepomuceno, A A; Nessi, M; Neubauer, M S; Neumann, M; Neves, R M; Nevski, P; Newman, P R; Nguyen, D H; Manh, T Nguyen; Nickerson, R B; Nicolaidou, R; Nielsen, J; Nikiforov, A; Nikolaenko, V; Nikolic-Audit, I; Nikolopoulos, K; Nilsen, J K; Nilsson, P; Ninomiya, Y; Nisati, A; Nisius, R; Nobe, T; Nodulman, L; Nomachi, M; Nomidis, I; Nooney, T; Norberg, S; Nordberg, M; Norjoharuddeen, N; Novgorodova, O; Nowak, S; Nozaki, M; Nozka, L; Ntekas, K; Nurse, E; Nuti, F; O'grady, F; O'Neil, D C; O'Rourke, A A; O'Shea, V; Oakham, F G; Oberlack, H; Obermann, T; Ocariz, J; Ochi, A; Ochoa, I; Ochoa-Ricoux, J P; Oda, S; Odaka, S; Ogren, H; Oh, A; Oh, S H; Ohm, C C; Ohman, H; Oide, H; Okawa, H; Okumura, Y; Okuyama, T; Olariu, A; Oleiro Seabra, L F; Olivares Pino, S A; Oliveira Damazio, D; Olszewski, A; Olszowska, J; Onofre, A; Onogi, K; Onyisi, P U E; Oreglia, M J; Oren, Y; Orestano, D; Orlando, N; Orr, R S; Osculati, B; Ospanov, R; Garzon, G Otero Y; Otono, H; Ouchrif, M; Ould-Saada, F; Ouraou, A; Oussoren, K P; Ouyang, Q; Owen, M; Owen, R E; Ozcan, V E; Ozturk, N; Pachal, K; Pacheco Pages, A; Pacheco Rodriguez, L; Padilla Aranda, C; Pagáčová, M; Pagan Griso, S; Paige, F; Pais, P; Pajchel, K; Palacino, G; Palazzo, S; Palestini, S; Palka, M; Pallin, D; Palma, A; St Panagiotopoulou, E; Pandini, C E; Panduro Vazquez, J G; Pani, P; Panitkin, S; Pantea, D; Paolozzi, L; Papadopoulou, Th D; Papageorgiou, K; Paramonov, A; Paredes Hernandez, D; Parker, A J; Parker, M A; Parker, K A; Parodi, F; Parsons, J A; Parzefall, U; Pascuzzi, V R; Pasqualucci, E; Passaggio, S; Pastore, Fr; Pásztor, G; Pataraia, S; Pater, J R; Pauly, T; Pearce, J; Pearson, B; Pedersen, L E; Pedersen, M; Lopez, S Pedraza; Pedro, R; Peleganchuk, S V; Pelikan, D; Penc, O; Peng, C; Peng, H; Penwell, J; Peralva, B S; Perego, M M; Perepelitsa, D V; Perez Codina, E; Perini, L; Pernegger, H; Perrella, S; Peschke, R; Peshekhonov, V D; Peters, K; Peters, R F Y; Petersen, B A; Petersen, T C; Petit, E; Petridis, A; Petridou, C; Petroff, P; Petrolo, E; Petrov, M; Petrucci, F; Pettersson, N E; Peyaud, A; Pezoa, R; Phillips, P W; Piacquadio, G; Pianori, E; Picazio, A; Piccaro, E; Piccinini, M; Pickering, M A; Piegaia, R; Pilcher, J E; Pilkington, A D; Pin, A W J; Pinamonti, M; Pinfold, J L; Pingel, A; Pires, S; Pirumov, H; Pitt, M; Plazak, L; Pleier, M-A; Pleskot, V; Plotnikova, E; Plucinski, P; Pluth, D; Poettgen, R; Poggioli, L; Pohl, D; Polesello, G; Poley, A; Policicchio, A; Polifka, R; Polini, A; Pollard, C S; Polychronakos, V; Pommès, K; Pontecorvo, L; Pope, B G; Popeneciu, G A; Popovic, D S; Poppleton, A; Pospisil, S; Potamianos, K; Potrap, I N; Potter, C J; Potter, C T; Poulard, G; Poveda, J; Pozdnyakov, V; Pozo Astigarraga, M E; Pralavorio, P; Pranko, A; Prell, S; Price, D; Price, L E; Primavera, M; Prince, S; Proissl, M; Prokofiev, K; Prokoshin, F; Protopopescu, S; Proudfoot, J; Przybycien, M; Puddu, D; Purohit, M; Puzo, P; Qian, J; Qin, G; Qin, Y; Quadt, A; Quayle, W B; Queitsch-Maitland, M; Quilty, D; Raddum, S; Radeka, V; Radescu, V; Radhakrishnan, S K; Radloff, P; Rados, P; Ragusa, F; Rahal, G; Raine, J A; Rajagopalan, S; Rammensee, M; Rangel-Smith, C; Ratti, M G; Rauscher, F; Rave, S; Ravenscroft, T; Ravinovich, I; Raymond, M; Read, A L; Readioff, N P; Reale, M; Rebuzzi, D M; Redelbach, A; Redlinger, G; Reece, R; Reeves, K; Rehnisch, L; Reichert, J; Reisin, H; Rembser, C; Ren, H; Rescigno, M; Resconi, S; Rezanova, O L; Reznicek, P; Rezvani, R; Richter, R; Richter, S; Richter-Was, E; Ricken, O; Ridel, M; Rieck, P; Riegel, C J; Rieger, J; Rifki, O; Rijssenbeek, M; Rimoldi, A; Rimoldi, M; Rinaldi, L; Ristić, B; Ritsch, E; Riu, I; Rizatdinova, F; Rizvi, E; Rizzi, C; Robertson, S H; Robichaud-Veronneau, A; Robinson, D; Robinson, J E M; Robson, A; Roda, C; Rodina, Y; Rodriguez Perez, A; Rodriguez Rodriguez, D; Roe, S; Rogan, C S; Røhne, O; Romaniouk, A; Romano, M; Romano Saez, S M; Romero Adam, E; Rompotis, N; Ronzani, M; Roos, L; Ros, E; Rosati, S; Rosbach, K; Rose, P; Rosenthal, O; Rosien, N-A; Rossetti, V; Rossi, E; Rossi, L P; Rosten, J H N; Rosten, R; Rotaru, M; Roth, I; Rothberg, J; Rousseau, D; Royon, C R; Rozanov, A; Rozen, Y; Ruan, X; Rubbo, F; Rudolph, M S; Rühr, F; Ruiz-Martinez, A; Rurikova, Z; Rusakovich, N A; Ruschke, A; Russell, H L; Rutherfoord, J P; Ruthmann, N; Ryabov, Y F; Rybar, M; Rybkin, G; Ryu, S; Ryzhov, A; Rzehorz, G F; Saavedra, A F; Sabato, G; Sacerdoti, S; Sadrozinski, H F-W; Sadykov, R; Safai Tehrani, F; Saha, P; Sahinsoy, M; Saimpert, M; Saito, T; Sakamoto, H; Sakurai, Y; Salamanna, G; Salamon, A; Loyola, J E Salazar; Salek, D; De Bruin, P H Sales; Salihagic, D; Salnikov, A; Salt, J; Salvatore, D; Salvatore, F; Salvucci, A; Salzburger, A; Sammel, D; Sampsonidis, D; Sanchez, A; Sánchez, J; Sanchez Martinez, V; Sandaker, H; Sandbach, R L; Sander, H G; Sandhoff, M; Sandoval, C; Sandstroem, R; Sankey, D P C; Sannino, M; Sansoni, A; Santoni, C; Santonico, R; Santos, H; Santoyo Castillo, I; Sapp, K; Sapronov, A; Saraiva, J G; Sarrazin, B; Sasaki, O; Sasaki, Y; Sato, K; Sauvage, G; Sauvan, E; Savage, G; Savard, P; Sawyer, C; Sawyer, L; Saxon, J; Sbarra, C; Sbrizzi, A; Scanlon, T; Scannicchio, D A; Scarcella, M; Scarfone, V; Schaarschmidt, J; Schacht, P; Schachtner, B M; Schaefer, D; Schaefer, R; Schaeffer, J; Schaepe, S; Schaetzel, S; Schäfer, U; Schaffer, A C; Schaile, D; Schamberger, R D; Scharf, V; Schegelsky, V A; Scheirich, D; Schernau, M; Schiavi, C; Schier, S; Schillo, C; Schioppa, M; Schlenker, S; Schmidt-Sommerfeld, K R; Schmieden, K; Schmitt, C; Schmitt, S; Schmitz, S; Schneider, B; Schnoor, U; Schoeffel, L; Schoening, A; Schoenrock, B D; Schopf, E; Schott, M; Schovancova, J; Schramm, S; Schreyer, M; Schuh, N; Schulte, A; Schultens, M J; Schultz-Coulon, H-C; Schulz, H; Schumacher, M; Schumm, B A; Schune, Ph; Schwartzman, A; Schwarz, T A; Schwegler, Ph; Schweiger, H; Schwemling, Ph; Schwienhorst, R; Schwindling, J; Schwindt, T; Sciolla, G; Scuri, F; Scutti, F; Searcy, J; Seema, P; Seidel, S C; Seiden, A; Seifert, F; Seixas, J M; Sekhniaidze, G; Sekhon, K; Sekula, S J; Seliverstov, D M; Semprini-Cesari, N; Serfon, C; Serin, L; Serkin, L; Sessa, M; Seuster, R; Severini, H; Sfiligoj, T; Sforza, F; Sfyrla, A; Shabalina, E; Shaikh, N W; Shan, L Y; Shang, R; Shank, J T; Shapiro, M; Shatalov, P B; Shaw, K; Shaw, S M; Shcherbakova, A; Shehu, C Y; Sherwood, P; Shi, L; Shimizu, S; Shimmin, C O; Shimojima, M; Shiyakova, M; Shmeleva, A; Shoaleh Saadi, D; Shochet, M J; Shojaii, S; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sickles, A M; Sidebo, P E; Sidiropoulou, O; Sidorov, D; Sidoti, A; Siegert, F; Sijacki, Dj; Silva, J; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simon, D; Simon, M; Sinervo, P; Sinev, N B; Sioli, M; Siragusa, G; Sivoklokov, S Yu; Sjölin, J; Skinner, M B; Skottowe, H P; Skubic, P; Slater, M; Slavicek, T; Slawinska, M; Sliwa, K; Slovak, R; Smakhtin, V; Smart, B H; Smestad, L; Smiesko, J; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, M N K; Smith, R W; Smizanska, M; Smolek, K; Snesarev, A A; Snyder, S; Sobie, R; Socher, F; Soffer, A; Soh, D A; Sokhrannyi, G; Sanchez, C A Solans; Solar, M; Soldatov, E Yu; Soldevila, U; Solodkov, A A; Soloshenko, A; Solovyanov, O V; Solovyev, V; Sommer, P; Son, H; Song, H Y; Sood, A; Sopczak, A; Sopko, V; Sorin, V; Sosa, D; Sotiropoulou, C L; Soualah, R; Soukharev, A M; South, D; Sowden, B C; Spagnolo, S; Spalla, M; Spangenberg, M; Spanò, F; Sperlich, D; Spettel, F; Spighi, R; Spigo, G; Spiller, L A; Spousta, M; Denis, R D St; Stabile, A; Stamen, R; Stamm, S; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stanitzki, M M; Stapnes, S; Starchenko, E A; Stark, G H; Stark, J; Staroba, P; Starovoitov, P; Stärz, S; Staszewski, R; Steinberg, P; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stewart, G A; Stillings, J A; Stockton, M C; Stoebe, M; Stoicea, G; Stolte, P; Stonjek, S; Stradling, A R; Straessner, A; Stramaglia, M E; Strandberg, J; Strandberg, S; Strandlie, A; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Stroynowski, R; Strubig, A; Stucci, S A; Stugu, B; Styles, N A; Su, D; Su, J; Subramaniam, R; Suchek, S; Sugaya, Y; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, S; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, S; Svatos, M; Swiatlowski, M; Sykora, I; Sykora, T; Ta, D; Taccini, C; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takai, H; Takashima, R; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tan, K G; Tanaka, J; Tanaka, R; Tanaka, S; Tannenwald, B B; Araya, S Tapia; Tapprogge, S; Tarem, S; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Tavares Delgado, A; Tayalati, Y; Taylor, A C; Taylor, G N; Taylor, P T E; Taylor, W; Teischinger, F A; Teixeira-Dias, P; Temming, K K; Temple, D; Ten Kate, H; Teng, P K; Teoh, J J; Tepel, F; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Theveneaux-Pelzer, T; Thomas, J P; Thomas-Wilsker, J; Thompson, E N; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Tibbetts, M J; Ticse Torres, R E; Tikhomirov, V O; Tikhonov, Yu A; Timoshenko, S; Tipton, P; Tisserant, S; Todome, K; Todorov, T; Todorova-Nova, S; Tojo, J; Tokár, S; Tokushuku, K; Tolley, E; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Tong, B; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Trofymov, A; Troncon, C; Trottier-McDonald, M; Trovatelli, M; Truong, L; Trzebinski, M; Trzupek, A; Tseng, J C-L; Tsiareshka, P V; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsui, K M; Tsukerman, I I; Tsulaia, V; Tsuno, S; Tsybychev, D; Tudorache, A; Tudorache, V; Tuna, A N; Tupputi, S A; Turchikhin, S; Turecek, D; Turgeman, D; Turra, R; Turvey, A J; Tuts, P M; Tyndel, M; Ucchielli, G; Ueda, I; Ughetto, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Unverdorben, C; Urban, J; Urquijo, P; Urrejola, P; Usai, G; Usanova, A; Vacavant, L; Vacek, V; Vachon, B; Valderanis, C; Valdes Santurio, E; Valencic, N; Valentinetti, S; Valero, A; Valery, L; Valkar, S; Vallecorsa, S; Valls Ferrer, J A; Van Den Wollenberg, W; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vanguri, R; Vaniachine, A; Vankov, P; Vardanyan, G; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vasquez, J G; Vazeille, F; Vazquez Schroeder, T; Veatch, J; Veloce, L M; Veloso, F; Veneziano, S; Ventura, A; Venturi, M; Venturi, N; Venturini, A; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Viazlo, O; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Vigani, L; Vigne, R; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinogradov, V B; Vittori, C; Vivarelli, I; Vlachos, S; Vlasak, M; Vogel, M; Vokac, P; Volpi, G; Volpi, M; von der Schmitt, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, P; Wagner, W; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wallangen, V; Wang, C; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, T; Wang, W; Wang, X; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Washbrook, A; Watkins, P M; Watson, A T; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, M D; Werner, P; Wessels, M; Wetter, J; Whalen, K; Whallon, N L; Wharton, A M; White, A; White, M J; White, R; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilk, F; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winston, O J; Winter, B T; Wittgen, M; Wittkowski, J; Wolter, M W; Wolters, H; Worm, S D; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yakabe, R; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yang, Z; Yao, W-M; Yap, Y C; Yasu, Y; Yatsenko, E; Wong, K H Yau; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yuen, S P Y; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zakharchuk, N; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zeng, J C; Zeng, Q; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, G; Zhang, H; Zhang, J; Zhang, L; Zhang, R; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zwalinski, L

2017-01-01

A measurement of the [Formula: see text] and [Formula: see text] production cross sections in final states with either two same-charge muons, or three or four leptons (electrons or muons) is presented. The analysis uses a data sample of proton-proton collisions at [Formula: see text] TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015, corresponding to a total integrated luminosity of 3.2 fb[Formula: see text]. The inclusive cross sections are extracted using likelihood fits to signal and control regions, resulting in [Formula: see text] pb and [Formula: see text] pb, in agreement with the Standard Model predictions.

Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) final report

Energy Technology Data Exchange (ETDEWEB)

Kegelmeyer, Philip W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shead, Timothy M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dunlavy, Daniel M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2013-09-01

This SAND report summarizes the activities and outcomes of the Network and Ensemble Enabled Entity Extraction in Information Text (NEEEEIT) LDRD project, which addressed improving the accuracy of conditional random fields for named entity recognition through the use of ensemble methods.

Antibacterial, Antioxidant, and Anticholinesterase Activities of Plant Seed Extracts from Brazilian Semiarid Region

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Davi Felipe Farias

2013-01-01

Full Text Available The antimicrobial, antioxidant, and anticholinesterase activities of ethanolic seed extracts of twenty-one plant species from Brazilian semiarid region were investigated. The extracts were tested for antimicrobial activity against six bacteria strains and three yeasts. Six extracts presented activity against the Gram (− organism Salmonella choleraesuis and the Gram (+ organisms Staphylococcus aureus and Bacillus subtilis. The MIC values ranged from 4.96 to 37.32 mg/mL. The Triplaris gardneriana extract presented activity against the three species, with MIC values 18.8, 13.76, and 11.15 mg/mL, respectively. Five extracts presented antioxidant activity, with EC50 values ranging from 69.73 μg/mL (T. gardneriana to 487.51 μg/mL (Licania rigida. For the anticholinesterase activity, eleven extracts were capable of inhibiting the enzyme activity. From those, T. gardneriana, Parkia platycephala and Connarus detersus presented the best activities, with inhibition values of 76.7, 71.5, and 91.9%, respectively. The extracts that presented antimicrobial activity were tested for hemolytic assay against human A, B, and O blood types and rabbit blood. From those, only the Myracrodruon urundeuva extract presented activity (about 20% of hemolysis at the lowest tested concentration, 1.9 µg/mL. Infrared spectroscopy of six representative extracts attested the presence of tannins, polyphenols, and flavonoids, which was confirmed by a qualitative phytochemical assay.

Understanding disciplinary vocabularies using a full-text enabled domain-independent term extraction approach.

Science.gov (United States)

Yan, Erjia; Williams, Jake; Chen, Zheng

2017-01-01

Publication metadata help deliver rich analyses of scholarly communication. However, research concepts and ideas are more effectively expressed through unstructured fields such as full texts. Thus, the goals of this paper are to employ a full-text enabled method to extract terms relevant to disciplinary vocabularies, and through them, to understand the relationships between disciplines. This paper uses an efficient, domain-independent term extraction method to extract disciplinary vocabularies from a large multidisciplinary corpus of PLoS ONE publications. It finds a power-law pattern in the frequency distributions of terms present in each discipline, indicating a semantic richness potentially sufficient for further study and advanced analysis. The salient relationships amongst these vocabularies become apparent in application of a principal component analysis. For example, Mathematics and Computer and Information Sciences were found to have similar vocabulary use patterns along with Engineering and Physics; while Chemistry and the Social Sciences were found to exhibit contrasting vocabulary use patterns along with the Earth Sciences and Chemistry. These results have implications to studies of scholarly communication as scholars attempt to identify the epistemological cultures of disciplines, and as a full text-based methodology could lead to machine learning applications in the automated classification of scholarly work according to disciplinary vocabularies.

Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

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Gil-beom Lee

2017-03-01

Full Text Available Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos.

The Fractal Patterns of Words in a Text: A Method for Automatic Keyword Extraction.

Science.gov (United States)

Najafi, Elham; Darooneh, Amir H

2015-01-01

A text can be considered as a one dimensional array of words. The locations of each word type in this array form a fractal pattern with certain fractal dimension. We observe that important words responsible for conveying the meaning of a text have dimensions considerably different from one, while the fractal dimensions of unimportant words are close to one. We introduce an index quantifying the importance of the words in a given text using their fractal dimensions and then ranking them according to their importance. This index measures the difference between the fractal pattern of a word in the original text relative to a shuffled version. Because the shuffled text is meaningless (i.e., words have no importance), the difference between the original and shuffled text can be used to ascertain degree of fractality. The degree of fractality may be used for automatic keyword detection. Words with the degree of fractality higher than a threshold value are assumed to be the retrieved keywords of the text. We measure the efficiency of our method for keywords extraction, making a comparison between our proposed method and two other well-known methods of automatic keyword extraction.

The Fractal Patterns of Words in a Text: A Method for Automatic Keyword Extraction

Science.gov (United States)

Najafi, Elham; Darooneh, Amir H.

2015-01-01

A text can be considered as a one dimensional array of words. The locations of each word type in this array form a fractal pattern with certain fractal dimension. We observe that important words responsible for conveying the meaning of a text have dimensions considerably different from one, while the fractal dimensions of unimportant words are close to one. We introduce an index quantifying the importance of the words in a given text using their fractal dimensions and then ranking them according to their importance. This index measures the difference between the fractal pattern of a word in the original text relative to a shuffled version. Because the shuffled text is meaningless (i.e., words have no importance), the difference between the original and shuffled text can be used to ascertain degree of fractality. The degree of fractality may be used for automatic keyword detection. Words with the degree of fractality higher than a threshold value are assumed to be the retrieved keywords of the text. We measure the efficiency of our method for keywords extraction, making a comparison between our proposed method and two other well-known methods of automatic keyword extraction. PMID:26091207

Automated extraction of metastatic liver cancer regions from abdominal contrast CT images

International Nuclear Information System (INIS)

Yamakawa, Junki; Matsubara, Hiroaki; Kimura, Shouta; Hasegawa, Junichi; Shinozaki, Kenji; Nawano, Shigeru

2010-01-01

In this paper, automated extraction of metastatic liver cancer regions from abdominal contrast X-ray CT images is investigated. Because even in Japan, cases of metastatic liver cancers are increased due to recent Europeanization and/or Americanization of Japanese eating habits, development of a system for computer aided diagnosis of them is strongly expected. Our automated extraction procedure consists of following four steps; liver region extraction, density transformation for enhancement of cancer regions, segmentation for obtaining candidate cancer regions, and reduction of false positives by shape feature. Parameter values used in each step of the procedure are decided based on density and shape features of typical metastatic liver cancers. In experiments using practical 20 cases of metastatic liver tumors, it is shown that 56% of true cancers can be detected successfully from CT images by the proposed procedure. (author)

Extracting of implicit information in English advertising texts with phonetic and lexical-morphological means

Directory of Open Access Journals (Sweden)

Traikovskaya Natalya Petrovna

2015-12-01

Full Text Available The article deals with phonetic and lexical-morphological language means participating in the process of extracting implicit information in English-speaking advertising texts for men and women. The functioning of phonetic means of the English language is not the basis for implication of information in advertising texts. Lexical and morphological means play the role of markers of relevant information, playing the role of the activator ofimplicit information in the texts of advertising.

Lithium NLP: A System for Rich Information Extraction from Noisy User Generated Text on Social Media

OpenAIRE

Bhargava, Preeti; Spasojevic, Nemanja; Hu, Guoning

2017-01-01

In this paper, we describe the Lithium Natural Language Processing (NLP) system - a resource-constrained, high- throughput and language-agnostic system for information extraction from noisy user generated text on social media. Lithium NLP extracts a rich set of information including entities, topics, hashtags and sentiment from text. We discuss several real world applications of the system currently incorporated in Lithium products. We also compare our system with existing commercial and acad...

Combining automatic table classification and relationship extraction in extracting anticancer drug-side effect pairs from full-text articles.

Science.gov (United States)

Xu, Rong; Wang, QuanQiu

2015-02-01

Anticancer drug-associated side effect knowledge often exists in multiple heterogeneous and complementary data sources. A comprehensive anticancer drug-side effect (drug-SE) relationship knowledge base is important for computation-based drug target discovery, drug toxicity predication and drug repositioning. In this study, we present a two-step approach by combining table classification and relationship extraction to extract drug-SE pairs from a large number of high-profile oncological full-text articles. The data consists of 31,255 tables downloaded from the Journal of Oncology (JCO). We first trained a statistical classifier to classify tables into SE-related and -unrelated categories. We then extracted drug-SE pairs from SE-related tables. We compared drug side effect knowledge extracted from JCO tables to that derived from FDA drug labels. Finally, we systematically analyzed relationships between anti-cancer drug-associated side effects and drug-associated gene targets, metabolism genes, and disease indications. The statistical table classifier is effective in classifying tables into SE-related and -unrelated (precision: 0.711; recall: 0.941; F1: 0.810). We extracted a total of 26,918 drug-SE pairs from SE-related tables with a precision of 0.605, a recall of 0.460, and a F1 of 0.520. Drug-SE pairs extracted from JCO tables is largely complementary to those derived from FDA drug labels; as many as 84.7% of the pairs extracted from JCO tables have not been included a side effect database constructed from FDA drug labels. Side effects associated with anticancer drugs positively correlate with drug target genes, drug metabolism genes, and disease indications. Copyright © 2014 Elsevier Inc. All rights reserved.

Building a protein name dictionary from full text: a machine learning term extraction approach

Directory of Open Access Journals (Sweden)

Campagne Fabien

2005-04-01

Full Text Available Abstract Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. Results We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. Conclusion This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt.

A Method for Automatic Extracting Intracranial Region in MR Brain Image

Science.gov (United States)

Kurokawa, Keiji; Miura, Shin; Nishida, Makoto; Kageyama, Yoichi; Namura, Ikuro

It is well known that temporal lobe in MR brain image is in use for estimating the grade of Alzheimer-type dementia. It is difficult to use only region of temporal lobe for estimating the grade of Alzheimer-type dementia. From the standpoint for supporting the medical specialists, this paper proposes a data processing approach on the automatic extraction of the intracranial region from the MR brain image. The method is able to eliminate the cranium region with the laplacian histogram method and the brainstem with the feature points which are related to the observations given by a medical specialist. In order to examine the usefulness of the proposed approach, the percentage of the temporal lobe in the intracranial region was calculated. As a result, the percentage of temporal lobe in the intracranial region on the process of the grade was in agreement with the visual sense standards of temporal lobe atrophy given by the medical specialist. It became clear that intracranial region extracted by the proposed method was good for estimating the grade of Alzheimer-type dementia.

A crowdsourcing workflow for extracting chemical-induced disease relations from free text.

Science.gov (United States)

Li, Tong Shu; Bravo, Àlex; Furlong, Laura I; Good, Benjamin M; Su, Andrew I

2016-01-01

Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available athttps://github.com/SuLab/crowd_cid_relexDatabase URL:https://github.com/SuLab/crowd_cid_relex. © The Author(s) 2016. Published by Oxford University Press.

A crowdsourcing workflow for extracting chemical-induced disease relations from free text

Science.gov (United States)

Li, Tong Shu; Bravo, Àlex; Furlong, Laura I.; Good, Benjamin M.; Su, Andrew I.

2016-01-01

Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505 F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available at https://github.com/SuLab/crowd_cid_relex Database URL: https://github.com/SuLab/crowd_cid_relex PMID:27087308

Improving the extraction of complex regulatory events from scientific text by using ontology-based inference

Directory of Open Access Journals (Sweden)

Kim Jung-jae

2011-10-01

Full Text Available Abstract Background The extraction of complex events from biomedical text is a challenging task and requires in-depth semantic analysis. Previous approaches associate lexical and syntactic resources with ontologies for the semantic analysis, but fall short in testing the benefits from the use of domain knowledge. Results We developed a system that deduces implicit events from explicitly expressed events by using inference rules that encode domain knowledge. We evaluated the system with the inference module on three tasks: First, when tested against a corpus with manually annotated events, the inference module of our system contributes 53.2% of correct extractions, but does not cause any incorrect results. Second, the system overall reproduces 33.1% of the transcription regulatory events contained in RegulonDB (up to 85.0% precision and the inference module is required for 93.8% of the reproduced events. Third, we applied the system with minimum adaptations to the identification of cell activity regulation events, confirming that the inference improves the performance of the system also on this task. Conclusions Our research shows that the inference based on domain knowledge plays a significant role in extracting complex events from text. This approach has great potential in recognizing the complex concepts of such biomedical ontologies as Gene Ontology in the literature.

Keyword Extraction from Arabic Legal Texts

Science.gov (United States)

Rammal, Mahmoud; Bahsoun, Zeinab; Al Achkar Jabbour, Mona

2015-01-01

Purpose: The purpose of this paper is to apply local grammar (LG) to develop an indexing system which automatically extracts keywords from titles of Lebanese official journals. Design/methodology/approach: To build LG for our system, the first word that plays the determinant role in understanding the meaning of a title is analyzed and grouped as…

Page segmentation and text extraction from gray-scale images in microfilm format

Science.gov (United States)

Yuan, Qing; Tan, Chew Lim

2000-12-01

The paper deals with a suitably designed system that is being used to separate textual regions from graphics regions and locate textual data from textured background. We presented a method based on edge detection to automatically locate text in some noise infected grayscale newspaper images with microfilm format. The algorithm first finds the appropriate edges of textual region using Canny edge detector, and then by edge merging it makes use of edge features to do block segmentation and classification, afterwards feature aided connected component analysis was used to group homogeneous textual regions together within the scope of its bounding box. We can obtain an efficient block segmentation with reduced memory size by introducing the TLC. The proposed method has been used to locate text in a group of newspaper images with multiple page layout. Initial results are encouraging, we would expand the experiment data to over 300 microfilm images with different layout structures, promising result is anticipated with corresponding modification on the prototype of former algorithm to make it more robust and suitable to different cases.

Automatic Extraction and Size Distribution of Landslides in Kurdistan Region, NE Iraq

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Arsalan A. Othman

2013-05-01

Full Text Available This study aims to assess the localization and size distribution of landslides using automatic remote sensing techniques in (semi- arid, non-vegetated, mountainous environments. The study area is located in the Kurdistan region (NE Iraq, within the Zagros orogenic belt, which is characterized by the High Folded Zone (HFZ, the Imbricated Zone and the Zagros Suture Zone (ZSZ. The available reference inventory includes 3,190 landslides mapped from sixty QuickBird scenes using manual delineation. The landslide types involve rock falls, translational slides and slumps, which occurred in different lithological units. Two hundred and ninety of these landslides lie within the ZSZ, representing a cumulated surface of 32 km2. The HFZ implicates 2,900 landslides with an overall coverage of about 26 km2. We first analyzed cumulative landslide number-size distributions using the inventory map. We then proposed a very simple and robust algorithm for automatic landslide extraction using specific band ratios selected upon the spectral signatures of bare surfaces as well as posteriori slope and the normalized difference vegetation index (NDVI thresholds. The index is based on the contrast between landslides and their background, whereas the landslides have high reflections in the green and red bands. We applied the slope threshold map to remove low slope areas, which have high reflectance in red and green bands. The algorithm was able to detect ~96% of the recent landslides known from the reference inventory on a test site. The cumulative landslide number-size distribution of automatically extracted landslide is very similar to the one based on visual mapping. The automatic extraction is therefore adapted for the quantitative analysis of landslides and thus can contribute to the assessment of hazards in similar regions.

Using Semantic Linking to Understand Persons’ Networks Extracted from Text

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Alessio Palmero Aprosio

2017-11-01

Full Text Available In this work, we describe a methodology to interpret large persons’ networks extracted from text by classifying cliques using the DBpedia ontology. The approach relies on a combination of NLP, Semantic web technologies, and network analysis. The classification methodology that first starts from single nodes and then generalizes to cliques is effective in terms of performance and is able to deal also with nodes that are not linked to Wikipedia. The gold standard manually developed for evaluation shows that groups of co-occurring entities share in most of the cases a category that can be automatically assigned. This holds for both languages considered in this study. The outcome of this work may be of interest to enhance the readability of large networks and to provide an additional semantic layer on top of cliques. This would greatly help humanities scholars when dealing with large amounts of textual data that need to be interpreted or categorized. Furthermore, it represents an unsupervised approach to automatically extend DBpedia starting from a corpus.

In situ genomic DNA extraction for PCR analysis of regions of interest in four plant species and one filamentous fungi

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Luis E. Rojas

2014-07-01

Full Text Available The extraction methods of genomic DNA are usually laborious and hazardous to human health and the environment by the use of organic solvents (chloroform and phenol. In this work a protocol for in situ extraction of genomic DNA by alkaline lysis is validated. It was used in order to amplify regions of DNA in four species of plants and fungi by polymerase chain reaction (PCR. From plant material of Saccharum officinarum L., Carica papaya L. and Digitalis purpurea L. it was possible to extend different regions of the genome through PCR. Furthermore, it was possible to amplify a fragment of avr-4 gene DNA purified from lyophilized mycelium of Mycosphaerella fijiensis. Additionally, it was possible to amplify the region ap24 transgene inserted into the genome of banana cv. `Grande naine' (Musa AAA. Key words: alkaline lysis, Carica papaya L., Digitalis purpurea L., Musa, Saccharum officinarum L.

Detecting text in natural scenes with multi-level MSER and SWT

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Lu, Tongwei; Liu, Renjun

2018-04-01

The detection of the characters in the natural scene is susceptible to factors such as complex background, variable viewing angle and diverse forms of language, which leads to poor detection results. Aiming at these problems, a new text detection method was proposed, which consisted of two main stages, candidate region extraction and text region detection. At first stage, the method used multiple scale transformations of original image and multiple thresholds of maximally stable extremal regions (MSER) to detect the text regions which could detect character regions comprehensively. At second stage, obtained SWT maps by using the stroke width transform (SWT) algorithm to compute the candidate regions, then using cascaded classifiers to propose non-text regions. The proposed method was evaluated on the standard benchmark datasets of ICDAR2011 and the datasets that we made our own data sets. The experiment results showed that the proposed method have greatly improved that compared to other text detection methods.

Selection/extraction of spectral regions for autofluorescence spectra measured in the oral cavity

NARCIS (Netherlands)

Skurichina, M; Paclik, P; Duin, RPW; de Veld, D; Sterenborg, HJCM; Witjes, MJH; Roodenburg, JLN; Fred, A; Caelli, T; Duin, RPW; Campilho, A; DeRidder, D

2004-01-01

Recently a number of successful algorithms to select/extract discriminative spectral regions was introduced. These methods may be more beneficial than the standard feature selection/extraction methods for spectral classification. In this paper, on the example of autofluorescence spectra measured in

Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

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Y Yang, M.; Wang, J.; Zhang, Q.

2017-07-01

Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

DISCOURSES OF ROUTINE AND AFFECTS IN THE TEXT OF REGIONAL SPACE (on the example of Volgograd region

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J. A. Drozdova

2016-01-01

Full Text Available The article discusses social space, which is the region of the text that is defined by a set of messages sent to settlements, streets, squares, monuments, buildings, and a system of signs that reflect possible interpretations of the actors, due to the peculiarities of the subjective state, language and experience. Using the methods of discursive and semiotic interpretation, we can distinguish two components of a heterogeneous, multi-code text — space of routine and space of affects. Space of routine presupposes a rational perception of space, rational response, it is a formation of traditions, attitudes, norms of conduct governing the behavior of social actors in a specific spatio-temporal locality. Changes in the perception of the usual attributes of the regional landscape can in a certain sense and individual context trigger affective reactions. The followihg factors form the space of the affects: sensual perception of space, emotional stimulation and intrapsychic representation, the sense of injury/cure, dangers/safety, negativity/ pleasure, shame/pride, or a combination of them. Dualism in the perception of space, its dialectical nature, congruence, flexibility, variability, the conflict of local and individual meanings, existing practices, patterns, mentalities and cultures, situations, the media are a condition of existence, and labeling of the regional text, updating its discursiveness and research. 

Improving the extraction of complex regulatory events from scientific text by using ontology-based inference.

Science.gov (United States)

Kim, Jung-Jae; Rebholz-Schuhmann, Dietrich

2011-10-06

The extraction of complex events from biomedical text is a challenging task and requires in-depth semantic analysis. Previous approaches associate lexical and syntactic resources with ontologies for the semantic analysis, but fall short in testing the benefits from the use of domain knowledge. We developed a system that deduces implicit events from explicitly expressed events by using inference rules that encode domain knowledge. We evaluated the system with the inference module on three tasks: First, when tested against a corpus with manually annotated events, the inference module of our system contributes 53.2% of correct extractions, but does not cause any incorrect results. Second, the system overall reproduces 33.1% of the transcription regulatory events contained in RegulonDB (up to 85.0% precision) and the inference module is required for 93.8% of the reproduced events. Third, we applied the system with minimum adaptations to the identification of cell activity regulation events, confirming that the inference improves the performance of the system also on this task. Our research shows that the inference based on domain knowledge plays a significant role in extracting complex events from text. This approach has great potential in recognizing the complex concepts of such biomedical ontologies as Gene Ontology in the literature.

Smoke regions extraction based on two steps segmentation and motion detection in early fire

Science.gov (United States)

Jian, Wenlin; Wu, Kaizhi; Yu, Zirong; Chen, Lijuan

2018-03-01

Aiming at the early problems of video-based smoke detection in fire video, this paper proposes a method to extract smoke suspected regions by combining two steps segmentation and motion characteristics. Early smoldering smoke can be seen as gray or gray-white regions. In the first stage, regions of interests (ROIs) with smoke are obtained by using two step segmentation methods. Then, suspected smoke regions are detected by combining the two step segmentation and motion detection. Finally, morphological processing is used for smoke regions extracting. The Otsu algorithm is used as segmentation method and the ViBe algorithm is used to detect the motion of smoke. The proposed method was tested on 6 test videos with smoke. The experimental results show the effectiveness of our proposed method over visual observation.

Antibacterial, Antioxidant, and Anticholinesterase Activities of Plant Seed Extracts from Brazilian Semiarid Region

OpenAIRE

Davi Felipe Farias; Terezinha Maria Souza; Martônio Ponte Viana; Bruno Marques Soares; Arcelina Pacheco Cunha; Ilka Maria Vasconcelos; Nágila Maria Pontes Silva Ricardo; Paulo Michel Pinheiro Ferreira; Vânia Maria Maciel Melo; Ana Fontenele Urano Carvalho

2013-01-01

The antimicrobial, antioxidant, and anticholinesterase activities of ethanolic seed extracts of twenty-one plant species from Brazilian semiarid region were investigated. The extracts were tested for antimicrobial activity against six bacteria strains and three yeasts. Six extracts presented activity against the Gram (−) organism Salmonella choleraesuis and the Gram (+) organisms Staphylococcus aureus and Bacillus subtilis. The MIC values ranged from 4.96 to 37.32 mg/mL. The Triplaris gardner...

EnvMine: A text-mining system for the automatic extraction of contextual information

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de Lorenzo Victor

2010-06-01

Full Text Available Abstract Background For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles. So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations from textual sources of any kind. Results EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings. Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude, thus allowing the calculation of distance between the individual locations. Conclusion EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical

The 2 mrad crossing-angle ILC interaction region and extraction line

CERN Document Server

Appleby, Robert; Bambade, Philip; Dadoun, Olivier; Parker, Brett; Keller, Lewis; Moffeit, Kenneth C; Nosochkov, Yuri; Seryi, Andrei; Spencer, Cherrill M; Carter, John; Napoly, Olivier

2006-01-01

A complete optics design for the 2mrad crossing angle interaction region and extraction line was presented at Snowmass 2005. Since this time, the design task force has been working on developing and improving the performance of the extraction line. The work has focused on optimising the final doublet parameters and on reducing the power losses resulting from the disrupted beam transport. In this paper, the most recent status of the 2mrad layout and the corresponding performance are presented.

A novel airport extraction model based on saliency region detection for high spatial resolution remote sensing images

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Lv, Wen; Zhang, Libao; Zhu, Yongchun

2017-06-01

The airport is one of the most crucial traffic facilities in military and civil fields. Automatic airport extraction in high spatial resolution remote sensing images has many applications such as regional planning and military reconnaissance. Traditional airport extraction strategies usually base on prior knowledge and locate the airport target by template matching and classification, which will cause high computation complexity and large costs of computing resources for high spatial resolution remote sensing images. In this paper, we propose a novel automatic airport extraction model based on saliency region detection, airport runway extraction and adaptive threshold segmentation. In saliency region detection, we choose frequency-tuned (FT) model for computing airport saliency using low level features of color and luminance that is easy and fast to implement and can provide full-resolution saliency maps. In airport runway extraction, Hough transform is adopted to count the number of parallel line segments. In adaptive threshold segmentation, the Otsu threshold segmentation algorithm is proposed to obtain more accurate airport regions. The experimental results demonstrate that the proposed model outperforms existing saliency analysis models and shows good performance in the extraction of the airport.

Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles.

Science.gov (United States)

Xu, Rong; Wang, QuanQiu

2015-06-01

Targeted anticancer drugs such as imatinib, trastuzumab and erlotinib dramatically improved treatment outcomes in cancer patients, however, these innovative agents are often associated with unexpected side effects. The pathophysiological mechanisms underlying these side effects are not well understood. The availability of a comprehensive knowledge base of side effects associated with targeted anticancer drugs has the potential to illuminate complex pathways underlying toxicities induced by these innovative drugs. While side effect association knowledge for targeted drugs exists in multiple heterogeneous data sources, published full-text oncological articles represent an important source of pivotal, investigational, and even failed trials in a variety of patient populations. In this study, we present an automatic process to extract targeted anticancer drug-associated side effects (drug-SE pairs) from a large number of high profile full-text oncological articles. We downloaded 13,855 full-text articles from the Journal of Oncology (JCO) published between 1983 and 2013. We developed text classification, relationship extraction, signaling filtering, and signal prioritization algorithms to extract drug-SE pairs from downloaded articles. We extracted a total of 26,264 drug-SE pairs with an average precision of 0.405, a recall of 0.899, and an F1 score of 0.465. We show that side effect knowledge from JCO articles is largely complementary to that from the US Food and Drug Administration (FDA) drug labels. Through integrative correlation analysis, we show that targeted drug-associated side effects positively correlate with their gene targets and disease indications. In conclusion, this unique database that we built from a large number of high-profile oncological articles could facilitate the development of computational models to understand toxic effects associated with targeted anticancer drugs. Copyright © 2015 Elsevier Inc. All rights reserved.

Fuzzy-Based Segmentation for Variable Font-Sized Text Extraction from Images/Videos

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Samabia Tehsin

2014-01-01

Full Text Available Textual information embedded in multimedia can provide a vital tool for indexing and retrieval. A lot of work is done in the field of text localization and detection because of its very fundamental importance. One of the biggest challenges of text detection is to deal with variation in font sizes and image resolution. This problem gets elevated due to the undersegmentation or oversegmentation of the regions in an image. The paper addresses this problem by proposing a solution using novel fuzzy-based method. This paper advocates postprocessing segmentation method that can solve the problem of variation in text sizes and image resolution. The methodology is tested on ICDAR 2011 Robust Reading Challenge dataset which amply proves the strength of the recommended method.

Emotion Discrimination using spatially Compact Regions of Interest extracted from Imaging EEG Activity

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Jorge Ivan Padilla-Buritica

2016-07-01

Full Text Available Lately, research on computational models of emotion had been getting much attention due to their potential for understanding the mechanisms of emotions and their promising broad range of applications that potentially bridge the gap between human and machine interactions. We propose a new method for emotion classification that relies on features extracted from those active brain areas that are most likely related to emotions. To this end, we carry out the selection of spatially compact regions of interest that are computed using the brain neural activity reconstructed from electroencephalography data. Throughout this study, we consider three representative feature extraction methods widely applied to emotion detection tasks, including Power spectral density, Wavelet, and Hjorth parameters. Further feature selection is carried out using principal component analysis. For validation purpose, these features are used to feed a support vector machine classifier that is trained under the leave-one-out cross-validation strategy. Obtained results on real affective data show that incorporation of the proposed training method in combination with the enhanced spatial resolution provided by the source estimation allows improving the performed accuracy of discrimination in most of the considered emotions, namely: dominance, valence, and linking.

Combining position weight matrices and document-term matrix for efficient extraction of associations of methylated genes and diseases from free text.

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Arwa Bin Raies

Full Text Available BACKGROUND: In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually. METHODOLOGY: We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text. CONCLUSION: The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download.

Visual Saliency Models for Text Detection in Real World.

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Renwu Gao

Full Text Available This paper evaluates the degree of saliency of texts in natural scenes using visual saliency models. A large scale scene image database with pixel level ground truth is created for this purpose. Using this scene image database and five state-of-the-art models, visual saliency maps that represent the degree of saliency of the objects are calculated. The receiver operating characteristic curve is employed in order to evaluate the saliency of scene texts, which is calculated by visual saliency models. A visualization of the distribution of scene texts and non-texts in the space constructed by three kinds of saliency maps, which are calculated using Itti's visual saliency model with intensity, color and orientation features, is given. This visualization of distribution indicates that text characters are more salient than their non-text neighbors, and can be captured from the background. Therefore, scene texts can be extracted from the scene images. With this in mind, a new visual saliency architecture, named hierarchical visual saliency model, is proposed. Hierarchical visual saliency model is based on Itti's model and consists of two stages. In the first stage, Itti's model is used to calculate the saliency map, and Otsu's global thresholding algorithm is applied to extract the salient region that we are interested in. In the second stage, Itti's model is applied to the salient region to calculate the final saliency map. An experimental evaluation demonstrates that the proposed model outperforms Itti's model in terms of captured scene texts.

Combining Position Weight Matrices and Document-Term Matrix for Efficient Extraction of Associations of Methylated Genes and Diseases from Free Text

KAUST Repository

Bin Raies, Arwa

2013-10-16

Background:In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually.Methodology:We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs) for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text.Conclusion:The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download. © 2013 Bin Raies et al.

Sliding Window-Based Region of Interest Extraction for Finger Vein Images

Science.gov (United States)

Yang, Lu; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2013-01-01

Region of Interest (ROI) extraction is a crucial step in an automatic finger vein recognition system. The aim of ROI extraction is to decide which part of the image is suitable for finger vein feature extraction. This paper proposes a finger vein ROI extraction method which is robust to finger displacement and rotation. First, we determine the middle line of the finger, which will be used to correct the image skew. Then, a sliding window is used to detect the phalangeal joints and further to ascertain the height of ROI. Last, for the corrective image with certain height, we will obtain the ROI by using the internal tangents of finger edges as the left and right boundary. The experimental results show that the proposed method can extract ROI more accurately and effectively compared with other methods, and thus improve the performance of finger vein identification system. Besides, to acquire the high quality finger vein image during the capture process, we propose eight criteria for finger vein capture from different aspects and these criteria should be helpful to some extent for finger vein capture. PMID:23507824

Efficient extraction of protein-protein interactions from full-text articles.

Science.gov (United States)

Hakenberg, Jörg; Leaman, Robert; Vo, Nguyen Ha; Jonnalagadda, Siddhartha; Sullivan, Ryan; Miller, Christopher; Tari, Luis; Baral, Chitta; Gonzalez, Graciela

2010-01-01

Proteins and their interactions govern virtually all cellular processes, such as regulation, signaling, metabolism, and structure. Most experimental findings pertaining to such interactions are discussed in research papers, which, in turn, get curated by protein interaction databases. Authors, editors, and publishers benefit from efforts to alleviate the tasks of searching for relevant papers, evidence for physical interactions, and proper identifiers for each protein involved. The BioCreative II.5 community challenge addressed these tasks in a competition-style assessment to evaluate and compare different methodologies, to make aware of the increasing accuracy of automated methods, and to guide future implementations. In this paper, we present our approaches for protein-named entity recognition, including normalization, and for extraction of protein-protein interactions from full text. Our overall goal is to identify efficient individual components, and we compare various compositions to handle a single full-text article in between 10 seconds and 2 minutes. We propose strategies to transfer document-level annotations to the sentence-level, which allows for the creation of a more fine-grained training corpus; we use this corpus to automatically derive around 5,000 patterns. We rank sentences by relevance to the task of finding novel interactions with physical evidence, using a sentence classifier built from this training corpus. Heuristics for paraphrasing sentences help to further remove unnecessary information that might interfere with patterns, such as additional adjectives, clauses, or bracketed expressions. In BioCreative II.5, we achieved an f-score of 22 percent for finding protein interactions, and 43 percent for mapping proteins to UniProt IDs; disregarding species, f-scores are 30 percent and 55 percent, respectively. On average, our best-performing setup required around 2 minutes per full text. All data and pattern sets as well as Java classes that

Carniola oživljena: Changing Practice in Citing Slovenian Regions in English Texts

Directory of Open Access Journals (Sweden)

Donald F. Reindl

2010-05-01

Full Text Available The past century has witnessed a striking change in the representation of Slovenia’s traditional regions in English texts. After the Second World War, Slovenians progressively replaced the traditional English exonyms for these regions with endonyms in English texts. This trend was accompanied by published works and teaching practice that increasingly insisted on the exclusive use of endonyms in English texts. However, following the dissolution of Yugoslavia and Slovenian independence, there has been a return to the traditional English exonyms. This article maps this changing practice through selected English texts from the past three centuries. It also addresses a number of pitfalls connected with the use of endonyms as well as persistent questions regarding the use of endonyms. Because English is a global language, the choices made by those writing in English directly affect how Slovenia and Slovenian identity are represented at the global level. As such, the conclusions of this paper apply directly to Slovenian-English translation practice and indirectly to Slovenian literature and culture conveyed through English translation.

Towards A Model Of Knowledge Extraction Of Text Mining For Palliative Care Patients In Panama.

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Denis Cedeno Moreno

2015-08-01

Full Text Available Solutions using information technology is an innovative way to manage the information hospice patients in hospitals in Panama. The application of techniques of text mining for the domain of medicine especially information from electronic health records of patients in palliative care is one of the most recent and promising research areas for the analysis of textual data. Text mining is based on new knowledge extraction from unstructured natural language data. We may also create ontologies to describe the terminology and knowledge in a given domain. In an ontology conceptualization of a domain that may be general or specific formalized. Knowledge can be used for decision making by health specialists or can help in research topics for improving the health system.

Text Line Detection from Rectangle Traffic Panels of Natural Scene

Science.gov (United States)

Wang, Shiyuan; Huang, Linlin; Hu, Jian

2018-01-01

Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

Clinical records anonymisation and text extraction (CRATE): an open-source software system.

Science.gov (United States)

Cardinal, Rudolf N

2017-04-26

Electronic medical records contain information of value for research, but contain identifiable and often highly sensitive confidential information. Patient-identifiable information cannot in general be shared outside clinical care teams without explicit consent, but anonymisation/de-identification allows research uses of clinical data without explicit consent. This article presents CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system with separable functions: (1) it anonymises or de-identifies arbitrary relational databases, with sensitivity and precision similar to previous comparable systems; (2) it uses public secure cryptographic methods to map patient identifiers to research identifiers (pseudonyms); (3) it connects relational databases to external tools for natural language processing; (4) it provides a web front end for research and administrative functions; and (5) it supports a specific model through which patients may consent to be contacted about research. Creation and management of a research database from sensitive clinical records with secure pseudonym generation, full-text indexing, and a consent-to-contact process is possible and practical using entirely free and open-source software.

Extracting recurrent scenarios from narrative texts using a Bayesian network: application to serious occupational accidents with movement disturbance.

Science.gov (United States)

Abdat, F; Leclercq, S; Cuny, X; Tissot, C

2014-09-01

A probabilistic approach has been developed to extract recurrent serious Occupational Accident with Movement Disturbance (OAMD) scenarios from narrative texts within a prevention framework. Relevant data extracted from 143 accounts was initially coded as logical combinations of generic accident factors. A Bayesian Network (BN)-based model was then built for OAMDs using these data and expert knowledge. A data clustering process was subsequently performed to group the OAMDs into similar classes from generic factor occurrence and pattern standpoints. Finally, the Most Probable Explanation (MPE) was evaluated and identified as the associated recurrent scenario for each class. Using this approach, 8 scenarios were extracted to describe 143 OAMDs in the construction and metallurgy sectors. Their recurrent nature is discussed. Probable generic factor combinations provide a fair representation of particularly serious OAMDs, as described in narrative texts. This work represents a real contribution to raising company awareness of the variety of circumstances, in which these accidents occur, to progressing in the prevention of such accidents and to developing an analysis framework dedicated to this kind of accident. Copyright © 2014 Elsevier Ltd. All rights reserved.

VisualUrText: A Text Analytics Tool for Unstructured Textual Data

Science.gov (United States)

Zainol, Zuraini; Jaymes, Mohd T. H.; Nohuddin, Puteri N. E.

2018-05-01

The growing amount of unstructured text over Internet is tremendous. Text repositories come from Web 2.0, business intelligence and social networking applications. It is also believed that 80-90% of future growth data is available in the form of unstructured text databases that may potentially contain interesting patterns and trends. Text Mining is well known technique for discovering interesting patterns and trends which are non-trivial knowledge from massive unstructured text data. Text Mining covers multidisciplinary fields involving information retrieval (IR), text analysis, natural language processing (NLP), data mining, machine learning statistics and computational linguistics. This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram. This tool, VisualUrText, is developed to assist students and researchers for extracting interesting patterns and trends in document analyses.

Interdisciplinary Approach to the Mental Lexicon: Neural Network and Text Extraction From Long-term Memory

Directory of Open Access Journals (Sweden)

Vardan G. Arutyunyan

2013-01-01

Full Text Available The paper touches upon the principles of mental lexicon organization in the light of recent research in psycho- and neurolinguistics. As a focal point of discussion two main approaches to mental lexicon functioning are considered: modular or dual-system approach, developed within generativism and opposite single-system approach, representatives of which are the connectionists and supporters of network models. The paper is an endeavor towards advocating the viewpoint that mental lexicon is complex psychological organization based upon specific composition of neural network. In this regard, the paper further elaborates on the matter of storing text in human mental space and introduces a model of text extraction from long-term memory. Based upon data available, the author develops a methodology of modeling structures of knowledge representation in the systems of artificial intelligence.

Text-in-context: a method for extracting findings in mixed-methods mixed research synthesis studies.

Science.gov (United States)

Sandelowski, Margarete; Leeman, Jennifer; Knafl, Kathleen; Crandell, Jamie L

2013-06-01

Our purpose in this paper is to propose a new method for extracting findings from research reports included in mixed-methods mixed research synthesis studies. International initiatives in the domains of systematic review and evidence synthesis have been focused on broadening the conceptualization of evidence, increased methodological inclusiveness and the production of evidence syntheses that will be accessible to and usable by a wider range of consumers. Initiatives in the general mixed-methods research field have been focused on developing truly integrative approaches to data analysis and interpretation. The data extraction challenges described here were encountered, and the method proposed for addressing these challenges was developed, in the first year of the ongoing (2011-2016) study: Mixed-Methods Synthesis of Research on Childhood Chronic Conditions and Family. To preserve the text-in-context of findings in research reports, we describe a method whereby findings are transformed into portable statements that anchor results to relevant information about sample, source of information, time, comparative reference point, magnitude and significance and study-specific conceptions of phenomena. The data extraction method featured here was developed specifically to accommodate mixed-methods mixed research synthesis studies conducted in nursing and other health sciences, but reviewers might find it useful in other kinds of research synthesis studies. This data extraction method itself constitutes a type of integration to preserve the methodological context of findings when statements are read individually and in comparison to each other. © 2012 Blackwell Publishing Ltd.

Antibacterial, antioxidant, and anticholinesterase activities of plant seed extracts from Brazilian semiarid region.

Science.gov (United States)

Farias, Davi Felipe; Souza, Terezinha Maria; Viana, Martônio Ponte; Soares, Bruno Marques; Cunha, Arcelina Pacheco; Vasconcelos, Ilka Maria; Ricardo, Nágila Maria Pontes Silva; Ferreira, Paulo Michel Pinheiro; Melo, Vânia Maria Maciel; Carvalho, Ana Fontenele Urano

2013-01-01

The antimicrobial, antioxidant, and anticholinesterase activities of ethanolic seed extracts of twenty-one plant species from Brazilian semiarid region were investigated. The extracts were tested for antimicrobial activity against six bacteria strains and three yeasts. Six extracts presented activity against the Gram (-) organism Salmonella choleraesuis and the Gram (+) organisms Staphylococcus aureus and Bacillus subtilis. The MIC values ranged from 4.96 to 37.32 mg/mL. The Triplaris gardneriana extract presented activity against the three species, with MIC values 18.8, 13.76, and 11.15 mg/mL, respectively. Five extracts presented antioxidant activity, with EC50 values ranging from 69.73 μ g/mL (T. gardneriana) to 487.51 μ g/mL (Licania rigida). For the anticholinesterase activity, eleven extracts were capable of inhibiting the enzyme activity. From those, T. gardneriana, Parkia platycephala and Connarus detersus presented the best activities, with inhibition values of 76.7, 71.5, and 91.9%, respectively. The extracts that presented antimicrobial activity were tested for hemolytic assay against human A, B, and O blood types and rabbit blood. From those, only the Myracrodruon urundeuva extract presented activity (about 20% of hemolysis at the lowest tested concentration, 1.9 µg/mL). Infrared spectroscopy of six representative extracts attested the presence of tannins, polyphenols, and flavonoids, which was confirmed by a qualitative phytochemical assay.

Measurement of charged particle multiplicities and densities in [Formula: see text] collisions at [Formula: see text]TeV in the forward region.

Science.gov (United States)

Aaij, R; Adeva, B; Adinolfi, M; Affolder, A; Ajaltouni, Z; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amerio, S; Amhis, Y; Anderlini, L; Anderson, J; Andreassen, R; Andreotti, M; Andrews, J E; Appleby, R B; Aquines Gutierrez, O; Archilli, F; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Bachmann, S; Back, J J; Badalov, A; Balagura, V; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Batozskaya, V; Bauer, Th; Bay, A; Beddow, J; Bedeschi, F; Bediaga, I; Belogurov, S; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bettler, M-O; van Beuzekom, M; Bien, A; Bifani, S; Bird, T; Bizzeti, A; Bjørnstad, P M; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Bondar, A; Bondar, N; Bonivento, W; Borghi, S; Borgia, A; Borsato, M; Bowcock, T J V; Bowen, E; Bozzi, C; Brambach, T; Vanden Brand, J; Bressieux, J; Brett, D; Britsch, M; Britton, T; Brook, N H; Brown, H; Bursche, A; Busetto, G; Buytaert, J; Cadeddu, S; Calabrese, R; Callot, O; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carranza-Mejia, H; Carson, L; Carvalho Akiba, K; Casse, G; Cassina, L; Castillo Garcia, L; Cattaneo, M; Cauet, Ch; Cenci, R; Charles, M; Charpentier, Ph; Cheung, S-F; Chiapolini, N; Chrzaszcz, M; Ciba, K; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coca, C; Coco, V; Cogan, J; Cogneras, E; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombes, M; Coquereau, S; Corti, G; Counts, I; Couturier, B; Cowan, G A; Craik, D C; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Dalseno, J; David, P; David, P N Y; Davis, A; De Bonis, I; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Silva, W; De Simone, P; Decamp, D; Deckenhoff, M; Del Buono, L; Déléage, N; Derkach, D; Deschamps, O; Dettori, F; Di Canto, A; Dijkstra, H; Donleavy, S; Dordei, F; Dorigo, M; Dorosz, P; Dosil Suárez, A; Dossett, D; Dovbnya, A; Dupertuis, F; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Easo, S; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; El Rifai, I; Elsasser, Ch; Esen, S; Falabella, A; Färber, C; Farinelli, C; Farry, S; Ferguson, D; Fernandez Albor, V; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fiore, M; Fiorini, M; Fitzpatrick, C; Fontana, M; Fontanelli, F; Forty, R; Francisco, O; Frank, M; Frei, C; Frosini, M; Fu, J; Furfaro, E; Gallas Torreira, A; Galli, D; Gandelman, M; Gandini, P; Gao, Y; Garofoli, J; Garra Tico, J; Garrido, L; Gaspar, C; Gauld, R; Gavardi, L; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianelle, A; Giani, S; Gibson, V; Giubega, L; Gligorov, V V; Göbel, C; Golubkov, D; Golutvin, A; Gomes, A; Gordon, H; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graziani, G; Grecu, A; Greening, E; Gregson, S; Griffith, P; Grillo, L; Grünberg, O; Gui, B; Gushchin, E; Guz, Yu; Gys, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Hafkenscheid, T W; Haines, S C; Hall, S; Hamilton, B; Hampson, T; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hartmann, T; He, J; Head, T; Heijne, V; Hennessy, K; Henrard, P; Henry, L; Hernando Morata, J A; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hoballah, M; Hombach, C; Hulsbergen, W; Hunt, P; Hussain, N; Hutchcroft, D; Hynds, D; Iakovenko, V; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jans, E; Jaton, P; Jawahery, A; Jing, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kaballo, M; Kandybei, S; Kanso, W; Karacson, M; Karbach, T M; Kelsey, M; Kenyon, I R; Ketel, T; Khanji, B; Khurewathanakul, C; Klaver, S; Kochebina, O; Komarov, I; Koopman, R F; Koppenburg, P; Korolev, M; Kozlinskiy, A; Kravchuk, L; Kreplin, K; Kreps, M; Krocker, G; Krokovny, P; Kruse, F; Kucharczyk, M; Kudryavtsev, V; Kurek, K; Kvaratskheliya, T; La Thi, V N; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lambert, R W; Lanciotti, E; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Lefèvre, R; Leflat, A; Lefrançois, J; Leo, S; Leroy, O; Lesiak, T; Leverington, B; Li, Y; Liles, M; Lindner, R; Linn, C; Lionetto, F; Liu, B; Liu, G; Lohn, S; Longstaff, I; Lopes, J H; Lopez-March, N; Lowdon, P; Lu, H; Lucchesi, D; Luisier, J; Luo, H; Luppi, E; Lupton, O; Machefert, F; Machikhiliyan, I V; Maciuc, F; Maev, O; Malde, S; Manca, G; Mancinelli, G; Manzali, M; Maratas, J; Marconi, U; Marino, P; Märki, R; Marks, J; Martellotti, G; Martens, A; Martín Sánchez, A; Martinelli, M; Martinez Santos, D; Martinez Vidal, F; Martins Tostes, D; Massafferri, A; Matev, R; Mathe, Z; Matteuzzi, C; Mazurov, A; McCann, M; McCarthy, J; McNab, A; McNulty, R; McSkelly, B; Meadows, B; Meier, F; Meissner, M; Merk, M; Milanes, D A; Minard, M-N; Molina Rodriguez, J; Monteil, S; Moran, D; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Mountain, R; Muheim, F; Müller, K; Muresan, R; Muryn, B; Muster, B; Naik, P; Nakada, T; Nandakumar, R; Nasteva, I; Needham, M; Neri, N; Neubert, S; Neufeld, N; Nguyen, A D; Nguyen, T D; Nguyen-Mau, C; Nicol, M; Niess, V; Niet, R; Nikitin, N; Nikodem, T; Novoselov, A; Oblakowska-Mucha, A; Obraztsov, V; Oggero, S; Ogilvy, S; Okhrimenko, O; Oldeman, R; Onderwater, G; Orlandea, M; Otalora Goicochea, J M; Owen, P; Oyanguren, A; Pal, B K; Palano, A; Palombo, F; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Pappalardo, L; Parkes, C; Parkinson, C J; Passaleva, G; Patel, G D; Patel, M; Patrignani, C; Pavel-Nicorescu, C; Pazos Alvarez, A; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perez Trigo, E; Perret, P; Perrin-Terrin, M; Pescatore, L; Pesen, E; Pessina, G; Petridis, K; Petrolini, A; Picatoste Olloqui, E; Pietrzyk, B; Pilař, T; Pinci, D; Pistone, A; Playfer, S; Plo Casasus, M; Polci, F; Polok, G; Poluektov, A; Polycarpo, E; Popov, A; Popov, D; Popovici, B; Potterat, C; Powell, A; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Rachwal, B; Rademacker, J H; Rakotomiaramanana, B; Rama, M; Rangel, M S; Raniuk, I; Rauschmayr, N; Raven, G; Redford, S; Reichert, S; Reid, M M; Dos Reis, A C; Ricciardi, S; Richards, A; Rinnert, K; Rives Molina, V; Roa Romero, D A; Robbe, P; Roberts, D A; Rodrigues, A B; Rodrigues, E; Rodriguez Perez, P; Roiser, S; Romanovsky, V; Romero Vidal, A; Rotondo, M; Rouvinet, J; Ruf, T; Ruffini, F; Ruiz, H; Ruiz Valls, P; Sabatino, G; Saborido Silva, J J; Sagidova, N; Sail, P; Saitta, B; Salustino Guimaraes, V; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santovetti, E; Sapunov, M; Sarti, A; Satriano, C; Satta, A; Savrie, M; Savrina, D; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmidt, B; Schneider, O; Schopper, A; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Seco, M; Semennikov, A; Senderowska, K; Sepp, I; Serra, N; Serrano, J; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, O; Shevchenko, V; Shires, A; Silva Coutinho, R; Simi, G; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, N A; Smith, E; Smith, E; Smith, J; Smith, M; Snoek, H; Sokoloff, M D; Soler, F J P; Soomro, F; Souza, D; De Paula, B Souza; Spaan, B; Sparkes, A; Spinella, F; Spradlin, P; Stagni, F; Stahl, S; Steinkamp, O; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Stroili, R; Subbiah, V K; Sun, L; Sutcliffe, W; Swientek, S; Syropoulos, V; Szczekowski, M; Szczypka, P; Szilard, D; Szumlak, T; T'Jampens, S; Teklishyn, M; Tellarini, G; Teodorescu, E; Teubert, F; Thomas, C; Thomas, E; van Tilburg, J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Torr, N; Tournefier, E; Tourneur, S; Tran, M T; Tresch, M; Tsaregorodtsev, A; Tsopelas, P; Tuning, N; Ubeda Garcia, M; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vagnoni, V; Valenti, G; Vallier, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vázquez Sierra, C; Vecchi, S; Velthuis, J J; Veltri, M; Veneziano, G; Vesterinen, M; Viaud, B; Vieira, D; Vilasis-Cardona, X; Vollhardt, A; Volyanskyy, D; Voong, D; Vorobyev, A; Vorobyev, V; Voß, C; Voss, H; de Vries, J A; Waldi, R; Wallace, C; Wallace, R; Wandernoth, S; Wang, J; Ward, D R; Watson, N K; Webber, A D; Websdale, D; Whitehead, M; Wicht, J; Wiechczynski, J; Wiedner, D; Wiggers, L; Wilkinson, G; Williams, M P; Williams, M; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wright, S; Wu, S; Wyllie, K; Xie, Y; Xing, Z; Yang, Z; Yuan, X; Yushchenko, O; Zangoli, M; Zavertyaev, M; Zhang, F; Zhang, L; Zhang, W C; Zhang, Y; Zhelezov, A; Zhokhov, A; Zhong, L; Zvyagin, A

Charged particle multiplicities are studied in proton-proton collisions in the forward region at a centre-of-mass energy of [Formula: see text]TeV with data collected by the LHCb detector. The forward spectrometer allows access to a kinematic range of [Formula: see text] in pseudorapidity, momenta greater than [Formula: see text] and transverse momenta greater than [Formula: see text]. The measurements are performed using events with at least one charged particle in the kinematic acceptance. The results are presented as functions of pseudorapidity and transverse momentum and are compared to predictions from several Monte Carlo event generators.

Newspaper archives + text mining = rich sources of historical geo-spatial data

Science.gov (United States)

Yzaguirre, A.; Smit, M.; Warren, R.

2016-04-01

Newspaper archives are rich sources of cultural, social, and historical information. These archives, even when digitized, are typically unstructured and organized by date rather than by subject or location, and require substantial manual effort to analyze. The effort of journalists to be accurate and precise means that there is often rich geo-spatial data embedded in the text, alongside text describing events that editors considered to be of sufficient importance to the region or the world to merit column inches. A regional newspaper can add over 100,000 articles to its database each year, and extracting information from this data for even a single country would pose a substantial Big Data challenge. In this paper, we describe a pilot study on the construction of a database of historical flood events (location(s), date, cause, magnitude) to be used in flood assessment projects, for example to calibrate models, estimate frequency, establish high water marks, or plan for future events in contexts ranging from urban planning to climate change adaptation. We then present a vision for extracting and using the rich geospatial data available in unstructured text archives, and suggest future avenues of research.

The Texts of the Agency's Co-operation Agreements with Regional Intergovernmental Organizations

International Nuclear Information System (INIS)

1961-01-01

The texts of the Agency's agreements for co-operation with the regional inter-governmental organizations listed below, together with the respective protocols authenticating them, are reproduced in this document in the order in which the agreements entered into force, for the information of all Members of the Agency

The Texts of the Agency's Co-operation Agreements with Regional Intergovernmental Organizations

Energy Technology Data Exchange (ETDEWEB)

NONE

1961-02-07

The texts of the Agency's agreements for co-operation with the regional inter-governmental organizations listed below, together with the respective protocols authenticating them, are reproduced in this document in the order in which the agreements entered into force, for the information of all Members of the Agency.

The Texts of the Agency's Co-operation Agreements with Regional Intergovernmental Organizations

International Nuclear Information System (INIS)

1961-01-01

The texts of the Agency's agreements for co-operation with the regional inter-governmental organizations listed below, together with the respective protocols authenticating them, are reproduced in this document in the order in which the agreements entered into force, for the information of all Members of the Agency [es

Simple and efficient method for region of interest value extraction from picture archiving and communication system viewer with optical character recognition software and macro program.

Science.gov (United States)

Lee, Young Han; Park, Eun Hae; Suh, Jin-Suck

2015-01-01

The objectives are: 1) to introduce a simple and efficient method for extracting region of interest (ROI) values from a Picture Archiving and Communication System (PACS) viewer using optical character recognition (OCR) software and a macro program, and 2) to evaluate the accuracy of this method with a PACS workstation. This module was designed to extract the ROI values on the images of the PACS, and created as a development tool by using open-source OCR software and an open-source macro program. The principal processes are as follows: (1) capture a region of the ROI values as a graphic file for OCR, (2) recognize the text from the captured image by OCR software, (3) perform error-correction, (4) extract the values including area, average, standard deviation, max, and min values from the text, (5) reformat the values into temporary strings with tabs, and (6) paste the temporary strings into the spreadsheet. This principal process was repeated for the number of ROIs. The accuracy of this module was evaluated on 1040 recognitions from 280 randomly selected ROIs of the magnetic resonance images. The input times of ROIs were compared between conventional manual method and this extraction module-assisted input method. The module for extracting ROI values operated successfully using the OCR and macro programs. The values of the area, average, standard deviation, maximum, and minimum could be recognized and error-corrected with AutoHotkey-coded module. The average input times using the conventional method and the proposed module-assisted method were 34.97 seconds and 7.87 seconds, respectively. A simple and efficient method for ROI value extraction was developed with open-source OCR and a macro program. Accurate inputs of various numbers from ROIs can be extracted with this module. The proposed module could be applied to the next generation of PACS or existing PACS that have not yet been upgraded. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research.

Science.gov (United States)

Bravo, Àlex; Piñero, Janet; Queralt-Rosinach, Núria; Rautschka, Michael; Furlong, Laura I

2015-02-21

Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases. By exploiting morpho-syntactic information of the text, BeFree is able to identify gene-disease, drug-disease and drug-target associations with state-of-the-art performance. The application of BeFree to real-case scenarios shows its effectiveness in extracting information relevant for translational research. We show the value of the gene-disease associations extracted by BeFree through a number of analyses and integration with other data sources. BeFree succeeds in identifying genes associated to a major cause of morbidity worldwide, depression, which are not present in other public resources. Moreover, large-scale extraction and analysis of gene-disease associations, and integration with current biomedical knowledge, provided interesting insights on the kind of information that can be found in the literature, and raised challenges regarding data prioritization and curation. We found that only a small proportion of the gene-disease associations discovered by using BeFree is collected in expert-curated databases. Thus, there is a pressing need to find alternative strategies to manual curation, in order to review, prioritize and curate text-mining data and incorporate it into domain-specific databases. We present our strategy for data prioritization and discuss its implications for supporting biomedical research and applications. BeFree is a novel text mining system that performs competitively for the identification of gene-disease, drug-disease and drug-target associations. Our analyses show that mining only a

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

Science.gov (United States)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER)system.

Science.gov (United States)

Pandey, Abhishek; Kreimeyer, Kory; Foster, Matthew; Botsis, Taxiarchis; Dang, Oanh; Ly, Thomas; Wang, Wei; Forshee, Richard

2018-01-01

Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

Salient Region Detection by Fusing Foreground and Background Cues Extracted from Single Image

Directory of Open Access Journals (Sweden)

Qiangqiang Zhou

2016-01-01

Full Text Available Saliency detection is an important preprocessing step in many application fields such as computer vision, robotics, and graphics to reduce computational cost by focusing on significant positions and neglecting the nonsignificant in the scene. Different from most previous methods which mainly utilize the contrast of low-level features, various feature maps are fused in a simple linear weighting form. In this paper, we propose a novel salient object detection algorithm which takes both background and foreground cues into consideration and integrate a bottom-up coarse salient regions extraction and a top-down background measure via boundary labels propagation into a unified optimization framework to acquire a refined saliency detection result. Wherein the coarse saliency map is also fused by three components, the first is local contrast map which is in more accordance with the psychological law, the second is global frequency prior map, and the third is global color distribution map. During the formation of background map, first we construct an affinity matrix and select some nodes which lie on border as labels to represent the background and then carry out a propagation to generate the regional background map. The evaluation of the proposed model has been implemented on four datasets. As demonstrated in the experiments, our proposed method outperforms most existing saliency detection models with a robust performance.

The regional economic impact of oil and gas extraction in Texas

International Nuclear Information System (INIS)

Lee, Jim

2015-01-01

This paper empirically investigates the regional economic impact of oil and gas extraction in Texas during the recent shale oil boom. Regressions with county-level data over the period 2009–2014 support smaller multiplier effects on local employment and income than corresponding estimates drawn from popular input–output-based studies. Economic impacts were larger for extraction from gas wells than oil wells, while the drilling phase generated comparable impacts. Estimates of economic impacts are greater in a dynamic spatial panel model that allows for spillover effects across local economies as well as over time. - Highlights: • Economic impacts and multiplier effects differ between oil and gas wells in Texas. • Interactions among local economies raise employment and income effects. • Impacts persist over time, raising the long-run multipliers. • Greater economic impacts from newly drilled wells than legacy wells.

Larvicidal, antimicrobial and brine shrimp activities of extracts from Cissampelos mucronata and Tephrosia villosa from coast region, Tanzania

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Erasto Paul

2011-04-01

Full Text Available Abstract Background The leaves and roots of Cissampelos mucronata A. Rich (Menispermaceae are widely used in the tropics and subtropics to manage various ailments such as gastro-intestinal complaints, menstrual problems, venereal diseases and malaria. In the Coast region, Tanzania, roots are used to treat wounds due to extraction of jigger. Leaves of Tephrosia villosa (L Pers (Leguminosae are reported to be used in the treatment of diabetes mellitus in India. In this study, extracts from the roots and aerial parts of C. mucronata and extracts from leaves, fruits, twigs and roots of T. villosa were evaluated for larvicidal activity, brine shrimps toxicity and antimicrobial activity. Methods Powdered materials from C. mucronata were extracted sequentially by dichloromethane followed by ethanol while materials from T.villosa were extracted by ethanol only. The extracts obtained were evaluated for larvicidal activity using Culex quinquefasciatus Say larvae, cytotoxicity using brine shrimp larvae and antimicrobial activity using bacteria and fungi. Results Extracts from aerial parts of C. Mucronata exhibited antibacterial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Salmonella typhi, Vibrio cholera, Bacillus anthracis, Streptococcus faecalis and antifungal activity against Candida albicans and Cryptococcus neoformans. They exhibited very low toxicity to brine shrimps and had no larvicidal activity. The root extracts exhibited good larvicidal activity but weak antimicrobial activity. The root dichloromethane extracts from C. mucronata was found to be more toxic with an LC50 value of 59.608 μg/mL while ethanolic extracts from root were not toxic with LC50>100 μg/mL. Ethanol extracts from fruits and roots of T. villosa were found to be very toxic with LC50 values of 9.690 μg/mL and 4.511 μg/mL, respectively, while, ethanol extracts from leaves and twigs of T. villosa were found to be non toxic (LC50>100 �

The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records

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Shah Anoop D

2012-08-01

Full Text Available Abstract Background Electronic health records are invaluable for medical research, but much information is stored as free text rather than in a coded form. For example, in the UK General Practice Research Database (GPRD, causes of death and test results are sometimes recorded only in free text. Free text can be difficult to use for research if it requires time-consuming manual review. Our aim was to develop an automated method for extracting coded information from free text in electronic patient records. Methods We reviewed the electronic patient records in GPRD of a random sample of 3310 patients who died in 2001, to identify the cause of death. We developed a computer program called the Freetext Matching Algorithm (FMA to map diagnoses in text to the Read Clinical Terminology. The program uses lookup tables of synonyms and phrase patterns to identify diagnoses, dates and selected test results. We tested it on two random samples of free text from GPRD (1000 texts associated with death in 2001, and 1000 general texts from cases and controls in a coronary artery disease study, comparing the output to the U.S. National Library of Medicine’s MetaMap program and the gold standard of manual review. Results Among 3310 patients registered in the GPRD who died in 2001, the cause of death was recorded in coded form in 38.1% of patients, and in the free text alone in 19.4%. On the 1000 texts associated with death, FMA coded 683 of the 735 positive diagnoses, with precision (positive predictive value 98.4% (95% confidence interval (CI 97.2, 99.2 and recall (sensitivity 92.9% (95% CI 90.8, 94.7. On the general sample, FMA detected 346 of the 447 positive diagnoses, with precision 91.5% (95% CI 88.3, 94.1 and recall 77.4% (95% CI 73.2, 81.2, which was similar to MetaMap. Conclusions We have developed an algorithm to extract coded information from free text in GP records with good precision. It may facilitate research using free text in electronic patient

ZK DrugResist 2.0: A TextMiner to extract semantic relations of drug resistance from PubMed.

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Khalid, Zoya; Sezerman, Osman Ugur

2017-05-01

Extracting useful knowledge from an unstructured textual data is a challenging task for biologists, since biomedical literature is growing exponentially on a daily basis. Building an automated method for such tasks is gaining much attention of researchers. ZK DrugResist is an online tool that automatically extracts mutations and expression changes associated with drug resistance from PubMed. In this study we have extended our tool to include semantic relations extracted from biomedical text covering drug resistance and established a server including both of these features. Our system was tested for three relations, Resistance (R), Intermediate (I) and Susceptible (S) by applying hybrid feature set. From the last few decades the focus has changed to hybrid approaches as it provides better results. In our case this approach combines rule-based methods with machine learning techniques. The results showed 97.67% accuracy with 96% precision, recall and F-measure. The results have outperformed the previously existing relation extraction systems thus can facilitate computational analysis of drug resistance against complex diseases and further can be implemented on other areas of biomedicine. Copyright © 2017 Elsevier Inc. All rights reserved.

Recognizing Cursive Typewritten Text Using Segmentation-Free System

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Mohammad S. Khorsheed

2015-01-01

Full Text Available Feature extraction plays an important role in text recognition as it aims to capture essential characteristics of the text image. Feature extraction algorithms widely range between robust and hard to extract features and noise sensitive and easy to extract features. Among those feature types are statistical features which are derived from the statistical distribution of the image pixels. This paper presents a novel method for feature extraction where simple statistical features are extracted from a one-pixel wide window that slides across the text line. The feature set is clustered in the feature space using vector quantization. The feature vector sequence is then injected to a classification engine for training and recognition purposes. The recognition system is applied to a data corpus which includes cursive Arabic text of more than 600 A4-size sheets typewritten in multiple computer-generated fonts. The system performance is compared to a previously published system from the literature with a similar engine but a different feature set.

Towards a realistic 3D simulation of the extraction region in ITER NBI relevant ion source

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Mochalskyy, S.; Wünderlich, D.; Fantz, U.; Franzen, P.; Minea, T.

2015-03-01

The development of negative ion (NI) sources for ITER is strongly accompanied by modelling activities. The ONIX code addresses the physics of formation and extraction of negative hydrogen ions at caesiated sources as well as the amount of co-extracted electrons. In order to be closer to the experimental conditions the code has been improved. It includes now the bias potential applied to first grid (plasma grid) of the extraction system, and the presence of Cs+ ions in the plasma. The simulation results show that such aspects play an important role for the formation of an ion-ion plasma in the boundary region by reducing the depth of the negative potential well in vicinity to the plasma grid that limits the extraction of the NIs produced at the Cs covered plasma grid surface. The influence of the initial temperature of the surface produced NI and its emission rate on the NI density in the bulk plasma that in turn affects the beam formation region was analysed. The formation of the plasma meniscus, the boundary between the plasma and the beam, was investigated for the extraction potentials of 5 and 10 kV. At the smaller extraction potential the meniscus moves closer to the plasma grid but as in the case of 10 kV the deepest meniscus bend point is still outside of the aperture. Finally, a plasma containing the same amount of NI and electrons (nH- =ne =1017 m-3) , representing good source conditioning, was simulated. It is shown that at such conditions the extracted NI current can reach values of ˜32 mA cm-2 using ITER-relevant extraction potential of 10 kV and ˜19 mA cm-2 at 5 kV. These results are in good agreement with experimental measurements performed at the small scale ITER prototype source at the test facility BATMAN.

Marker Registration Technique for Handwritten Text Marker in Augmented Reality Applications

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Thanaborvornwiwat, N.; Patanukhom, K.

2018-04-01

Marker registration is a fundamental process to estimate camera poses in marker-based Augmented Reality (AR) systems. We developed AR system that creates correspondence virtual objects on handwritten text markers. This paper presents a new method for registration that is robust for low-content text markers, variation of camera poses, and variation of handwritten styles. The proposed method uses Maximally Stable Extremal Regions (MSER) and polygon simplification for a feature point extraction. The experiment shows that we need to extract only five feature points per image which can provide the best registration results. An exhaustive search is used to find the best matching pattern of the feature points in two images. We also compared performance of the proposed method to some existing registration methods and found that the proposed method can provide better accuracy and time efficiency.

Antioxidant and antitopoisomerase activities in plant extracts of some Colombian flora from La Marcada Natural Regional Park

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Jaime Niño

2011-09-01

Full Text Available Many plants have been used to treat some diseases and infections since time immemorial, and this potential has been exploited by the pharmaceutical industry in the search of new analgesic, anticarcinogenic and antimicrobial agents, among other active agents. in order to contribute with bioprospection studies on the Colombian flora, 35 extracts from 13 plant species belonging to seven families (Apocynaceae, Cactaceae, Costaceae, Eremolepidaceae, Passifloraceae, Solanaceae and Urticaceae were collected from La Marcada Natural Regional Park (LMNRP, Colombia. Dichloromethane, n-hexane and aqueous-methanol crude extracts were prepared and evaluated for their activity against Saccharomyces cerevisiae RS322N, R52Y and RS321 strains in the yeast mutant assay and their antioxidant capacity through the DPPH test. The dichloromethane extract from Myriocarpa stipitata (Urticaceae showed moderate inhibitory activity against the three S. cerevisiae strains tested. The capacity of the dichloromethane extract from M. stipitata to inhibit the enzyme topoisomerase I and to cause DNA damage was inferred from these results. In the DPPH assay, the n-hexane crude extract from Costus sp. (Costaceae showed good antioxidant activity (48%; in addition, the crude dichloromethane and aqueous-methanol extracts from Rhipsalis micrantha (Cactaceae showed moderate antioxidant activity with percentage of 29 and 21%, respectively. Rev. Biol. Trop. 59 (3: 1089-1097. Epub 2011 September 01.Desde tiempos inmemoriales, muchas plantas han sido usadas para el tratamiento de varias enfermedades e infecciones, este potencial ha sido explotado por la industria farmacéutica en la búsqueda de nuevos agentes analgésicos, anticancerígenos y antimicrobianos, entre otros. Consientes con esto, se evaluó la actividad de 35 extractos de 13 especies de plantas recolectadas en el Parque Regional Natural La Marcada (PRNLM, Colombia contra las cepas mutadas de Saccharomyces cerevisiae RS322N, R

Automated recognition of brain region mentions in neuroscience literature

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Leon French

2009-09-01

Full Text Available The ability to computationally extract mentions of neuroanatomical regions from the literature would assist linking to other entities within and outside of an article. Examples include extracting reports of connectivity or region-specific gene expression. To facilitate text mining of neuroscience literature we have created a corpus of manually annotated brain region mentions. The corpus contains 1,377 abstracts with 18,242 brain region annotations. Interannotator agreement was evaluated for a subset of the documents, and was 90.7% and 96.7% for strict and lenient matching respectively. We observed a large vocabulary of over 6,000 unique brain region terms and 17,000 words. For automatic extraction of brain region mentions we evaluated simple dictionary methods and complex natural language processing techniques. The dictionary methods based on neuroanatomical lexicons recalled 36% of the mentions with 57% precision. The best performance was achieved using a conditional random field (CRF with a rich feature set. Features were based on morphological, lexical, syntactic and contextual information. The CRF recalled 76% of mentions at 81% precision, by counting partial matches recall and precision increase to 86% and 92% respectively. We suspect a large amount of error is due to coordinating conjunctions, previously unseen words and brain regions of less commonly studied organisms. We found context windows, lemmatization and abbreviation expansion to be the most informative techniques. The corpus is freely available at http://www.chibi.ubc.ca/WhiteText/.

Numerical analysis of electronegative plasma in the extraction region of negative hydrogen ion sources

International Nuclear Information System (INIS)

Kuppel, S.; Matsushita, D.; Hatayama, A.; Bacal, M.

2011-01-01

This numerical study focuses on the physical mechanisms involved in the extraction of volume-produced H - ions from a steady state laboratory negative hydrogen ion source with one opening in the plasma electrode (PE) on which a dc-bias voltage is applied. A weak magnetic field is applied in the source plasma transversely to the extracted beam. The goal is to highlight the combined effects of the weak magnetic field and the PE bias voltage (upon the extraction process of H - ions and electrons). To do so, we focus on the behavior of electrons and volume-produced negative ions within a two-dimensional model using the particle-in-cell method. No collision processes are taken into account, except for electron diffusion across the magnetic field using a simple random-walk model at each time step of the simulation. The results show first that applying the magnetic field (without PE bias) enhances H - ion extraction, while it drastically decreases the extracted electron current. Secondly, the extracted H - ion current has a maximum when the PE bias is equal to the plasma potential, while the extracted electron current is significantly reduced by applying the PE bias. The underlying mechanism leading to the above results is the gradual opening by the PE bias of the equipotential lines towards the parts of the extraction region facing the PE. The shape of these lines is due originally to the electron trapping by the magnetic field.

Numerical analysis of electronegative plasma in the extraction region of negative hydrogen ion sources

Science.gov (United States)

Kuppel, S.; Matsushita, D.; Hatayama, A.; Bacal, M.

2011-01-01

This numerical study focuses on the physical mechanisms involved in the extraction of volume-produced H- ions from a steady state laboratory negative hydrogen ion source with one opening in the plasma electrode (PE) on which a dc-bias voltage is applied. A weak magnetic field is applied in the source plasma transversely to the extracted beam. The goal is to highlight the combined effects of the weak magnetic field and the PE bias voltage (upon the extraction process of H- ions and electrons). To do so, we focus on the behavior of electrons and volume-produced negative ions within a two-dimensional model using the particle-in-cell method. No collision processes are taken into account, except for electron diffusion across the magnetic field using a simple random-walk model at each time step of the simulation. The results show first that applying the magnetic field (without PE bias) enhances H- ion extraction, while it drastically decreases the extracted electron current. Secondly, the extracted H- ion current has a maximum when the PE bias is equal to the plasma potential, while the extracted electron current is significantly reduced by applying the PE bias. The underlying mechanism leading to the above results is the gradual opening by the PE bias of the equipotential lines towards the parts of the extraction region facing the PE. The shape of these lines is due originally to the electron trapping by the magnetic field.

Computerized extraction of information on the quality of diabetes care from free text in electronic patient records of general practitioners

NARCIS (Netherlands)

Voorham, Jaco; Denig, Petra

2007-01-01

Objective: This study evaluated a computerized method for extracting numeric clinical measurements related to diabetes care from free text in electronic patient records (EPR) of general practitioners. Design and Measurements: Accuracy of this number-oriented approach was compared to manual chart

Ordering Operations in Square Root Extractions, Analyzing Some Early Medieval Sanskrit Mathematical Texts with the Help of Speech Act Theory

Science.gov (United States)

Keller, Agathe

Procedures for extracting square roots written in Sanskrit in two treatises and their commentaries from the fifth to the twelfth centuries are explored with the help of Textology and Speech Act Theory. An analysis of the number and order of the steps presented in these texts is used to show that their aims were not limited to only describing how to carry out the algorithm. The intentions of authors of these Sanskrit mathematical texts are questioned by taking into account the expressivity of relationships established between the world and the text.1

Towards a realistic 3D simulation of the extraction region in ITER NBI relevant ion source

International Nuclear Information System (INIS)

Mochalskyy, S.; Wünderlich, D.; Fantz, U.; Franzen, P.; Minea, T.

2015-01-01

The development of negative ion (NI) sources for ITER is strongly accompanied by modelling activities. The ONIX code addresses the physics of formation and extraction of negative hydrogen ions at caesiated sources as well as the amount of co-extracted electrons. In order to be closer to the experimental conditions the code has been improved. It includes now the bias potential applied to first grid (plasma grid) of the extraction system, and the presence of Cs + ions in the plasma. The simulation results show that such aspects play an important role for the formation of an ion–ion plasma in the boundary region by reducing the depth of the negative potential well in vicinity to the plasma grid that limits the extraction of the NIs produced at the Cs covered plasma grid surface. The influence of the initial temperature of the surface produced NI and its emission rate on the NI density in the bulk plasma that in turn affects the beam formation region was analysed. The formation of the plasma meniscus, the boundary between the plasma and the beam, was investigated for the extraction potentials of 5 and 10 kV. At the smaller extraction potential the meniscus moves closer to the plasma grid but as in the case of 10 kV the deepest meniscus bend point is still outside of the aperture. Finally, a plasma containing the same amount of NI and electrons (n H − =n e =10 17 m −3 ), representing good source conditioning, was simulated. It is shown that at such conditions the extracted NI current can reach values of ∼32 mA cm −2 using ITER-relevant extraction potential of 10 kV and ∼19 mA cm −2 at 5 kV. These results are in good agreement with experimental measurements performed at the small scale ITER prototype source at the test facility BATMAN. (paper)

Characterization and Antioxidant Properties of Six Algerian Propolis Extracts: Ethyl Acetate Extracts Inhibit Myeloperoxidase Activity

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Yasmina Mokhtaria Boufadi

2014-02-01

Full Text Available Because propolis contains many types of antioxidant compounds such as polyphenols and flavonoids, it can be useful in preventing oxidative damages. Ethyl acetate extracts of propolis from several Algerian regions show high activity by scavenging free radicals, preventing lipid peroxidation and inhibiting myeloperoxidase (MPO. By fractioning and assaying ethyl acetate extracts, it was observed that both polyphenols and flavonoids contribute to these activities. A correlation was observed between the polyphenol content and the MPO inhibition. However, it seems that kaempferol, a flavonoid, contributes mainly to the MPO inhibition. This molecule is in a high amount in the ethyl acetate extract and demonstrates the best efficiency towards the enzyme with an inhibiting concentration at 50% of 4 ± 2 µM.

Extraction of events and rules of land use/cover change from the policy text

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Lin, Guangfa; Xia, Beicheng; Huang, Wangli; Jiang, Huixian; Chen, Youfei

2007-06-01

The database of recording the snapshots of land parcels history is the foundation for the most of the models on simulating land use/cover change (LUCC) process. But the sequences of temporal snapshots are not sufficient to deduce and describe the mechanism of LUCC process. The temporal relationship between scenarios of LUCC we recorded could not be transfer into causal relationship categorically, which was regarded as a key factor in spatial-temporal reasoning. The proprietor of land parcels adapted themselves to the policies from governments and the change of production market, and then made decisions in this or that way. The occurrence of each change of a land parcel in an urban area was often related with one or more decision texts when it was investigated on the local scale with high resolution of the background scene. These decision texts may come from different sections of a hierarchical government system on different levels, such as villages or communities, towns or counties, cities, provinces or even the paramount. All these texts were balance results between advantages and disadvantages of different interest groups. They are the essential forces of LUCC in human dimension. Up to now, a methodology is still wanted for on how to express these forces in a simulation system using GIS as a language. The presented paper was part of our initial research on this topic. The term "Event" is a very important concept in the frame of "Object-Oriented" theory in computer science. While in the domain of temporal GIS, the concept of event was developed in another category. The definitions of the event and their transformation relationship were discussed in this paper on three modeling levels as real world level, conceptual level and programming level. In this context, with a case study of LUCC in recent 30 years in Xiamen city of Fujian province, P. R. China, the paper focused on how to extract information of events and rules from the policy files collected and integrate

Review: Regional land subsidence accompanying groundwater extraction

Science.gov (United States)

Galloway, Devin L.; Burbey, Thomas J.

2011-01-01

The extraction of groundwater can generate land subsidence by causing the compaction of susceptible aquifer systems, typically unconsolidated alluvial or basin-fill aquifer systems comprising aquifers and aquitards. Various ground-based and remotely sensed methods are used to measure and map subsidence. Many areas of subsidence caused by groundwater pumping have been identified and monitored, and corrective measures to slow or halt subsidence have been devised. Two principal means are used to mitigate subsidence caused by groundwater withdrawal—reduction of groundwater withdrawal, and artificial recharge. Analysis and simulation of aquifer-system compaction follow from the basic relations between head, stress, compressibility, and groundwater flow and are addressed primarily using two approaches—one based on conventional groundwater flow theory and one based on linear poroelasticity theory. Research and development to improve the assessment and analysis of aquifer-system compaction, the accompanying subsidence and potential ground ruptures are needed in the topic areas of the hydromechanical behavior of aquitards, the role of horizontal deformation, the application of differential synthetic aperture radar interferometry, and the regional-scale simulation of coupled groundwater flow and aquifer-system deformation to support resource management and hazard mitigation measures.

WATERSHED ALGORITHM BASED SEGMENTATION FOR HANDWRITTEN TEXT IDENTIFICATION

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P. Mathivanan

2014-02-01

Full Text Available In this paper we develop a system for writer identification which involves four processing steps like preprocessing, segmentation, feature extraction and writer identification using neural network. In the preprocessing phase the handwritten text is subjected to slant removal process for segmentation and feature extraction. After this step the text image enters into the process of noise removal and gray level conversion. The preprocessed image is further segmented by using morphological watershed algorithm, where the text lines are segmented into single words and then into single letters. The segmented image is feature extracted by Daubechies’5/3 integer wavelet transform to reduce training complexity [1, 6]. This process is lossless and reversible [10], [14]. These extracted features are given as input to our neural network for writer identification process and a target image is selected for each training process in the 2-layer neural network. With the several trained output data obtained from different target help in text identification. It is a multilingual text analysis which provides simple and efficient text segmentation.

Chemical content and antimicrobial properties of three different extracts of Mentha pulegium leaves from Mugla Region, Turkey.

Science.gov (United States)

Ceyhan-Güvensen, Nur; Keskin, Dilek

2016-11-01

The extract of ethanol, methanol and DMSO of pennyroyal leaves from Mugla Region (Turkey) were tested for antimicrobial activity against eleven bacterial and one yeast strain by disc diffusion method. Among the extracts assayed, the methanol extract of pennyroyal leaves exhibited significant antimicrobial activity against Salmonella typhimurium and Staphylococcus aureus with 20 mm diameter inhibition zone. The DMSO extract of pennyroyal leaves displayed significant activity against S.aureus (19 mm) and Bacillus subtilis (21mm) showing inhibition zone of 19 mm and 21 mm diameter, while the ethanolic extract showed significant antimicrobial activity against S.aureus (17mm) and Klebsiella pneumoniae (20mm) inhibition zones.? On comparint the MIC value of ethanol, methanol and DMSO leaf extract, methanolic extract of pennyroyal presented best activity (MIC 8 mg ml-1) against S. typhimurium CCM 583 and S.aureus ATCC 6538/P. Analyses of GC/MS determined eleven compounds viz., neophytadiene (69.95%), Pulejon 7.85%, Pinane 4.81%, Bicyclo (3.1.1 Heptane 2.6.6.6 trimethyl) 4.68%. In conclusion, methanolic extracts of M. pulegium showed antimicrobial activity because of high neophytadiene content.

Social Media Text Classification by Enhancing Well-Formed Text Trained Model

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Phat Jotikabukkana

2016-09-01

Full Text Available Social media are a powerful communication tool in our era of digital information. The large amount of user-generated data is a useful novel source of data, even though it is not easy to extract the treasures from this vast and noisy trove. Since classification is an important part of text mining, many techniques have been proposed to classify this kind of information. We developed an effective technique of social media text classification by semi-supervised learning utilizing an online news source consisting of well-formed text. The computer first automatically extracts news categories, well-categorized by publishers, as classes for topic classification. A bag of words taken from news articles provides the initial keywords related to their category in the form of word vectors. The principal task is to retrieve a set of new productive keywords. Term Frequency-Inverse Document Frequency weighting (TF-IDF and Word Article Matrix (WAM are used as main methods. A modification of WAM is recomputed until it becomes the most effective model for social media text classification. The key success factor was enhancing our model with effective keywords from social media. A promising result of 99.50% accuracy was achieved, with more than 98.5% of Precision, Recall, and F-measure after updating the model three times.

Productive Regions: Criteria and Classification

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Vlasyuk L. I.

2012-03-01

Full Text Available An official statistical dataset for 80 territorial subjects of the Russian Federation for 2000, 2007 and 2009 has proved the hypothesis that, under the neoclassical concept, the resources move to regions with the highest marginal productivity of the factors of production, which leads to the accumulation of investment resources, while providing financial and social efficiency. Based on cluster analysis by three performance criteria, productive regions are identified, which are dominated by regions productive in the extraction of minerals. It is shown that the stability of the factors’ distribution in space determines the current and future specialization of regional economies

Semantic Document Image Classification Based on Valuable Text Pattern

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Hossein Pourghassem

2011-01-01

Full Text Available Knowledge extraction from detected document image is a complex problem in the field of information technology. This problem becomes more intricate when we know, a negligible percentage of the detected document images are valuable. In this paper, a segmentation-based classification algorithm is used to analysis the document image. In this algorithm, using a two-stage segmentation approach, regions of the image are detected, and then classified to document and non-document (pure region regions in the hierarchical classification. In this paper, a novel valuable definition is proposed to classify document image in to valuable or invaluable categories. The proposed algorithm is evaluated on a database consisting of the document and non-document image that provide from Internet. Experimental results show the efficiency of the proposed algorithm in the semantic document image classification. The proposed algorithm provides accuracy rate of 98.8% for valuable and invaluable document image classification problem.

Application of Text Analytics to Extract and Analyze Material–Application Pairs from a Large Scientific Corpus

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Nikhil Kalathil

2018-01-01

Full Text Available When assessing the importance of materials (or other components to a given set of applications, machine analysis of a very large corpus of scientific abstracts can provide an analyst a base of insights to develop further. The use of text analytics reduces the time required to conduct an evaluation, while allowing analysts to experiment with a multitude of different hypotheses. Because the scope and quantity of metadata analyzed can, and should, be large, any divergence from what a human analyst determines and what the text analysis shows provides a prompt for the human analyst to reassess any preliminary findings. In this work, we have successfully extracted material–application pairs and ranked them on their importance. This method provides a novel way to map scientific advances in a particular material to the application for which it is used. Approximately 438,000 titles and abstracts of scientific papers published from 1992 to 2011 were used to examine 16 materials. This analysis used coclustering text analysis to associate individual materials with specific clean energy applications, evaluate the importance of materials to specific applications, and assess their importance to clean energy overall. Our analysis reproduced the judgments of experts in assigning material importance to applications. The validated methods were then used to map the replacement of one material with another material in a specific application (batteries.

Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

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André SANTOS

2012-07-01

Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

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Anália LOURENÇO

2013-07-01

Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

Text mining in livestock animal science: introducing the potential of text mining to animal sciences.

Science.gov (United States)

Sahadevan, S; Hofmann-Apitius, M; Schellander, K; Tesfaye, D; Fluck, J; Friedrich, C M

2012-10-01

In biological research, establishing the prior art by searching and collecting information already present in the domain has equal importance as the experiments done. To obtain a complete overview about the relevant knowledge, researchers mainly rely on 2 major information sources: i) various biological databases and ii) scientific publications in the field. The major difference between the 2 information sources is that information from databases is available, typically well structured and condensed. The information content in scientific literature is vastly unstructured; that is, dispersed among the many different sections of scientific text. The traditional method of information extraction from scientific literature occurs by generating a list of relevant publications in the field of interest and manually scanning these texts for relevant information, which is very time consuming. It is more than likely that in using this "classical" approach the researcher misses some relevant information mentioned in the literature or has to go through biological databases to extract further information. Text mining and named entity recognition methods have already been used in human genomics and related fields as a solution to this problem. These methods can process and extract information from large volumes of scientific text. Text mining is defined as the automatic extraction of previously unknown and potentially useful information from text. Named entity recognition (NER) is defined as the method of identifying named entities (names of real world objects; for example, gene/protein names, drugs, enzymes) in text. In animal sciences, text mining and related methods have been briefly used in murine genomics and associated fields, leaving behind other fields of animal sciences, such as livestock genomics. The aim of this work was to develop an information retrieval platform in the livestock domain focusing on livestock publications and the recognition of relevant data from

Monitoring interaction and collective text production through text mining

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Macedo, Alexandra Lorandi

2014-04-01

Full Text Available This article presents the Concepts Network tool, developed using text mining technology. The main objective of this tool is to extract and relate terms of greatest incidence from a text and exhibit the results in the form of a graph. The Network was implemented in the Collective Text Editor (CTE which is an online tool that allows the production of texts in synchronized or non-synchronized forms. This article describes the application of the Network both in texts produced collectively and texts produced in a forum. The purpose of the tool is to offer support to the teacher in managing the high volume of data generated in the process of interaction amongst students and in the construction of the text. Specifically, the aim is to facilitate the teacher’s job by allowing him/her to process data in a shorter time than is currently demanded. The results suggest that the Concepts Network can aid the teacher, as it provides indicators of the quality of the text produced. Moreover, messages posted in forums can be analyzed without their content necessarily having to be pre-read.

Text data extraction for a prospective, research-focused data mart: implementation and validation

Directory of Open Access Journals (Sweden)

Hinchcliff Monique

2012-09-01

Full Text Available Abstract Background Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of ‘machine generated’ sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Methods Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. Results There was a near perfect (99.5% agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Conclusions Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor to parse, abstract and assemble

The Texts of the Agency's Co-operation Agreements with Regional Intergovernmental Organizations; Texte des Accords de Cooperation Conclus entre L'Agence et des Organisations Intergouvernementales Regionales

Energy Technology Data Exchange (ETDEWEB)

NONE

1961-02-07

The texts of the Agency's agreements for co-operation with the regional inter-governmental organizations listed below, together with the respective protocols authenticating them, are reproduced in this document in the order in which the agreements entered into force, for the information of all Members of the Agency [French] Le present document reproduit le texte des accords de cooperation que l'Agence a conclus avec les organisations intergouvernementales regionales enumerees ci-apres, ainsi que celui des protocoles validant lesdits accords. Le texte de ces instruments, classes dans l'ordre chronologique de leur entree en vigueur, est communique, pour information, a tous les Membres de l'Agence.

Antimicrobial potential of ethanol extracts of plants against gramnegative bacilli isolated from cervicovaginal mucosa of sheep bred in the region of Petrolina-PE

Directory of Open Access Journals (Sweden)

Valdenice Félix da Silva

2014-02-01

Full Text Available Reproductive tract infections are the main causes of losses from the low reproductive efficiency of sheep. Gram negative bacilli belonging to the normal flora of the genital region can trigger diseases. The pathogenicity of these agents is expressed when females are with weakened immune system, either by food or stress management. Flaws in and concern about antibiotic residues in animal production have prompted research regarding alternatives for the treatment of diseases. The herbal medicine hás been considered in this context is the subject of numerous studies. This study aimed to evaluate the antibacterial potential of ethanol extracts of plants belonging to the flora of the Northeast against gram negative bacilli isolated from cervical-vaginal mucosa of sheep. Six plants were selected from Caatinga biome: Encholirium spectabile, Bromelia laciniosa, Neoglaziovia variegata, Amburana cearensis Hymenaea martiana and Selaginella convoluta. The plant material was processed to obtain the crude extract. This was tested by microdilution plate and determining the minimum bactericidal concentration, the second document of Clinical and Laboratory Standards Institute (CLSI and the extracts diluted in water and alcohol. We used 43 gram negative isolates, as follows: 14 E. coli, 10 Enterobacter spp., 10 Acinetobacter spp. 9 and Klebsiella spp. In the aqueous dilution Klebsiella spp. showed response only to species B. laciniosa, S. convoluta and H. martiana. All tested extracts showed antibacterial activity against Acinetobacter spp and no activity against E. coli and Enterobacter spp. Among the extracts diluted in water H. martiana showed the highest antibacterial activity. In all dilution alcoholic extracts showed inhibitory activity against all bacterial genera, but no statistical difference between them.

Data-driven haemodynamic response function extraction using Fourier-wavelet regularised deconvolution

Directory of Open Access Journals (Sweden)

Roerdink Jos BTM

2008-04-01

Full Text Available Abstract Background We present a simple, data-driven method to extract haemodynamic response functions (HRF from functional magnetic resonance imaging (fMRI time series, based on the Fourier-wavelet regularised deconvolution (ForWaRD technique. HRF data are required for many fMRI applications, such as defining region-specific HRFs, effciently representing a general HRF, or comparing subject-specific HRFs. Results ForWaRD is applied to fMRI time signals, after removing low-frequency trends by a wavelet-based method, and the output of ForWaRD is a time series of volumes, containing the HRF in each voxel. Compared to more complex methods, this extraction algorithm requires few assumptions (separability of signal and noise in the frequency and wavelet domains and the general linear model and it is fast (HRF extraction from a single fMRI data set takes about the same time as spatial resampling. The extraction method is tested on simulated event-related activation signals, contaminated with noise from a time series of real MRI images. An application for HRF data is demonstrated in a simple event-related experiment: data are extracted from a region with significant effects of interest in a first time series. A continuous-time HRF is obtained by fitting a nonlinear function to the discrete HRF coeffcients, and is then used to analyse a later time series. Conclusion With the parameters used in this paper, the extraction method presented here is very robust to changes in signal properties. Comparison of analyses with fitted HRFs and with a canonical HRF shows that a subject-specific, regional HRF significantly improves detection power. Sensitivity and specificity increase not only in the region from which the HRFs are extracted, but also in other regions of interest.

Comparison of mentha extracts obtained by different extraction methods

Directory of Open Access Journals (Sweden)

Milić Slavica

2006-01-01

Full Text Available The different methods of mentha extraction, such as steam distillation, extraction by methylene chloride (Soxhlet extraction and supercritical fluid extraction (SFE by carbon dioxide (CO J were investigated. SFE by CO, was performed at pressure of 100 bar and temperature of40°C. The extraction yield, as well as qualitative and quantitative composition of obtained extracts, determined by GC-MS method, were compared.

Algorithm based on regional separation for automatic grain boundary extraction using improved mean shift method

Science.gov (United States)

Zhenying, Xu; Jiandong, Zhu; Qi, Zhang; Yamba, Philip

2018-06-01

Metallographic microscopy shows that the vast majority of metal materials are composed of many small grains; the grain size of a metal is important for determining the tensile strength, toughness, plasticity, and other mechanical properties. In order to quantitatively evaluate grain size in metals, grain boundaries must be identified in metallographic images. Based on the phenomenon of grain boundary blurring or disconnection in metallographic images, this study develops an algorithm based on regional separation for automatically extracting grain boundaries by an improved mean shift method. Experimental observation shows that the grain boundaries obtained by the proposed algorithm are highly complete and accurate. This research has practical value because the proposed algorithm is suitable for grain boundary extraction from most metallographic images.

Benchmarking infrastructure for mutation text mining.

Science.gov (United States)

Klein, Artjom; Riazanov, Alexandre; Hindle, Matthew M; Baker, Christopher Jo

2014-02-25

Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption.

Benchmarking infrastructure for mutation text mining

Science.gov (United States)

2014-01-01

Background Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. Results We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. Conclusion We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption. PMID:24568600

Review of particle-in-cell modeling for the extraction region of large negative hydrogen ion sources for fusion

Science.gov (United States)

Wünderlich, D.; Mochalskyy, S.; Montellano, I. M.; Revel, A.

2018-05-01

Particle-in-cell (PIC) codes are used since the early 1960s for calculating self-consistently the motion of charged particles in plasmas, taking into account external electric and magnetic fields as well as the fields created by the particles itself. Due to the used very small time steps (in the order of the inverse plasma frequency) and mesh size, the computational requirements can be very high and they drastically increase with increasing plasma density and size of the calculation domain. Thus, usually small computational domains and/or reduced dimensionality are used. In the last years, the available central processing unit (CPU) power strongly increased. Together with a massive parallelization of the codes, it is now possible to describe in 3D the extraction of charged particles from a plasma, using calculation domains with an edge length of several centimeters, consisting of one extraction aperture, the plasma in direct vicinity of the aperture, and a part of the extraction system. Large negative hydrogen or deuterium ion sources are essential parts of the neutral beam injection (NBI) system in future fusion devices like the international fusion experiment ITER and the demonstration reactor (DEMO). For ITER NBI RF driven sources with a source area of 0.9 × 1.9 m2 and 1280 extraction apertures will be used. The extraction of negative ions is accompanied by the co-extraction of electrons which are deflected onto an electron dump. Typically, the maximum negative extracted ion current is limited by the amount and the temporal instability of the co-extracted electrons, especially for operation in deuterium. Different PIC codes are available for the extraction region of large driven negative ion sources for fusion. Additionally, some effort is ongoing in developing codes that describe in a simplified manner (coarser mesh or reduced dimensionality) the plasma of the whole ion source. The presentation first gives a brief overview of the current status of the ion

11. Russian Conference on Extraction. Abstracts

International Nuclear Information System (INIS)

Zolotov, Yu.A.

1998-01-01

Results of fundamental and applied investigations in the region of chemistry of extraction, technology and analytical chemistry are presented. Modern state of theoretical and experimental investigations in the region of thermodynamics and kinetics of extraction by organic phosphorus compounds, organic nitrogen compounds and their mixtures are described. Date on mass exchange, extraction process simulation, extraction apparatuses are given

The Texts of the Agency's Co-operation Agreements with Regional Intergovernmental Organizations; Teksty Soglashenij o Sotrudnichestve Mezhdu Agentstvom i Regional 'Nymi Mezhpravitel' Stvennymi Organizacijami

Energy Technology Data Exchange (ETDEWEB)

NONE

1961-02-07

The texts of the Agency's agreements for co-operation with the regional inter-governmental organizations listed below, together with the respective protocols authenticating them, are reproduced in this document in the order in which the agreements entered into force, for the information of all Members of the Agency [Russian] Teksty soglashenii Agentstva o sotrudnichestve s perechislennymi nizhe regional'nymi mezhpravitel'stvennymi organizacijami vmeste s sootvetstvujushhimi protokolami, udostoverjajushhimi ih autentichnost'; soglashenija perechisleny v porjadke vstuplenija ih v silu.

Text mining patents for biomedical knowledge.

Science.gov (United States)

Rodriguez-Esteban, Raul; Bundschus, Markus

2016-06-01

Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Percutaneous self-injury to the femoral region caused by bur breakage during surgical extraction of a patient's impacted third molar.

Science.gov (United States)

Yu, Tae Hoon; Lee, Jun; Kim, Bong Chul

2015-10-01

Extraction of an impacted third molar is one of the most frequently performed techniques in oral and maxillofacial surgery. Surgeons can suffer numerous external injuries while extracting a tooth, with percutaneous injuries to the hand being the most commonly reported. In this article, we present a case involving a percutaneous injury of the surgeon's femoral region caused by breakage of the fissure bur connected to the handpiece during extraction of the third molar. We also propose precautions to prevent such injuries and steps to be undertaken when they occur.

Income and employment effects of shale gas extraction windfalls: Evidence from the Marcellus region

International Nuclear Information System (INIS)

Paredes, Dusan; Komarek, Timothy; Loveridge, Scott

2015-01-01

New technologies combining hydraulic fracturing and horizontal drilling in oil and gas extraction are creating a sudden expansion of production. Residents of places where deep underground oil and gas deposits are found want to know about the broader economic, social, and environmental impacts of these activities that generate windfall income for some residents. We first review the literature on windfall spending patterns. Then, using the Marcellus region, the earliest area to be tapped using the new techniques, we estimate county-level employment and income effects. For robustness, we employ two methods. Using a propensity score matching approach we find no effect of fracking on income or employment. A panel-fixed effect regression approach suggests statistically significant employment effects in six out of seven alternative specifications, but significant income effects in only one out of seven specifications. In short, the income spillover effects in the Marcellus region appear to be minimal, meaning there's little incentive at the county level to incur current or potential future costs that may be associated with this activity. We conclude with some ideas on how localities might employ policies that would allow natural gas extraction to move forward, benefitting landowners, while establishing some financial safeguards for the broader community. - Highlights: • We examine the effect of fracking on local employment and income. • The differing policies in the Marcellus region provide a natural policy experiment. • Propensity score matching shows no income or employment growth from fracking. • Panel data estimates show weak impacts on employment and income. • We suggest ways to address possible future environmental consequences

A methodology for semiautomatic taxonomy of concepts extraction from nuclear scientific documents using text mining techniques

International Nuclear Information System (INIS)

Braga, Fabiane dos Reis

2013-01-01

This thesis presents a text mining method for semi-automatic extraction of taxonomy of concepts, from a textual corpus composed of scientific papers related to nuclear area. The text classification is a natural human practice and a crucial task for work with large repositories. The document clustering technique provides a logical and understandable framework that facilitates the organization, browsing and searching. Most clustering algorithms using the bag of words model to represent the content of a document. This model generates a high dimensionality of the data, ignores the fact that different words can have the same meaning and does not consider the relationship between them, assuming that words are independent of each other. The methodology presents a combination of a model for document representation by concepts with a hierarchical document clustering method using frequency of co-occurrence concepts and a technique for clusters labeling more representatives, with the objective of producing a taxonomy of concepts which may reflect a structure of the knowledge domain. It is hoped that this work will contribute to the conceptual mapping of scientific production of nuclear area and thus support the management of research activities in this area. (author)

Text data extraction for a prospective, research-focused data mart: implementation and validation.

Science.gov (United States)

Hinchcliff, Monique; Just, Eric; Podlusky, Sofia; Varga, John; Chang, Rowland W; Kibbe, Warren A

2012-09-13

Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of 'machine generated' sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. There was a near perfect (99.5%) agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor) to parse, abstract and assemble structured data from text data contained in the electronic health

Multi-resolution analysis for region of interest extraction in thermographic nondestructive evaluation

Science.gov (United States)

Ortiz-Jaramillo, B.; Fandiño Toro, H. A.; Benitez-Restrepo, H. D.; Orjuela-Vargas, S. A.; Castellanos-Domínguez, G.; Philips, W.

2012-03-01

Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs. In this paper, we present a methodology for ROI extraction in INDT tasks. The methodology deals with the difficulties due to the non-uniform heating. The non-uniform heating affects low spatial/frequencies and hinders the detection of relevant points in the image. In this paper, a methodology for ROI extraction in INDT using multi-resolution analysis is proposed, which is robust to ROI low contrast and non-uniform heating. The former methodology includes local correlation, Gaussian scale analysis and local edge detection. In this methodology local correlation between image and Gaussian window provides interest points related to ROIs. We use a Gaussian window because thermal behavior is well modeled by Gaussian smooth contours. Also, the Gaussian scale is used to analyze details in the image using multi-resolution analysis avoiding low contrast, non-uniform heating and selection of the Gaussian window size. Finally, local edge detection is used to provide a good estimation of the boundaries in the ROI. Thus, we provide a methodology for ROI extraction based on multi-resolution analysis that is better or equal compared with the other dedicate algorithms proposed in the state of art.

Quantitative methodology to extract regional magnetotelluric impedances and determine the dimension of the conductivity structure

Energy Technology Data Exchange (ETDEWEB)

Groom, R [PetRos EiKon Incorporated, Ontario (Canada); Kurtz, R; Jones, A; Boerner, D [Geological Survey of Canada, Ontario (Canada)

1996-05-01

This paper describes a systematic method for determining the appropriate dimensionality of magnetotelluric (MT) data from a site, and illustrates the application of this method to analyze both synthetic data and real data. Additionally, it describes the extraction of regional impedance responses from multiple sites. This method was examined extensively with synthetic data, and proven to be successful. It was demonstrated for two neighboring sites that the analysis methodology can be extremely useful in unraveling the bulk regional response when hidden by strong three-dimensional effects. Although there may still be some uncertainties remaining in the true levels for the regional responses for stations LIT000 and LITW02, the analysis has provided models which not only fit the data but are consistent for neighboring sites. It was suggested from these data that the stations are seeing significantly different structures. 12 refs.

SparkText: Biomedical Text Mining on Big Data Framework.

Science.gov (United States)

Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Mining biological networks from full-text articles.

Science.gov (United States)

Czarnecki, Jan; Shepherd, Adrian J

2014-01-01

The study of biological networks is playing an increasingly important role in the life sciences. Many different kinds of biological system can be modelled as networks; perhaps the most important examples are protein-protein interaction (PPI) networks, metabolic pathways, gene regulatory networks, and signalling networks. Although much useful information is easily accessible in publicly databases, a lot of extra relevant data lies scattered in numerous published papers. Hence there is a pressing need for automated text-mining methods capable of extracting such information from full-text articles. Here we present practical guidelines for constructing a text-mining pipeline from existing code and software components capable of extracting PPI networks from full-text articles. This approach can be adapted to tackle other types of biological network.

Measurement of [Formula: see text] polarisation in [Formula: see text] collisions at [Formula: see text] = 7 TeV.

Science.gov (United States)

Aaij, R; Adeva, B; Adinolfi, M; Affolder, A; Ajaltouni, Z; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amerio, S; Amhis, Y; An, L; Anderlini, L; Anderson, J; Andreassen, R; Andreotti, M; Andrews, J E; Appleby, R B; Aquines Gutierrez, O; Archilli, F; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Bachmann, S; Back, J J; Badalov, A; Balagura, V; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Batozskaya, V; Bauer, Th; Bay, A; Beddow, J; Bedeschi, F; Bediaga, I; Belogurov, S; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bettler, M-O; van Beuzekom, M; Bien, A; Bifani, S; Bird, T; Bizzeti, A; Bjørnstad, P M; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Bondar, A; Bondar, N; Bonivento, W; Borghi, S; Borgia, A; Borsato, M; Bowcock, T J V; Bowen, E; Bozzi, C; Brambach, T; van den Brand, J; Bressieux, J; Brett, D; Britsch, M; Britton, T; Brook, N H; Brown, H; Bursche, A; Busetto, G; Buytaert, J; Cadeddu, S; Calabrese, R; Callot, O; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carranza-Mejia, H; Carson, L; Carvalho Akiba, K; Casse, G; Cassina, L; Castillo Garcia, L; Cattaneo, M; Cauet, Ch; Cenci, R; Charles, M; Charpentier, Ph; Cheung, S-F; Chiapolini, N; Chrzaszcz, M; Ciba, K; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coca, C; Coco, V; Cogan, J; Cogneras, E; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombes, M; Coquereau, S; Corti, G; Corvo, M; Counts, I; Couturier, B; Cowan, G A; Craik, D C; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Dalseno, J; David, P; David, P N Y; Davis, A; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Silva, W; De Simone, P; Decamp, D; Deckenhoff, M; Del Buono, L; Déléage, N; Derkach, D; Deschamps, O; Dettori, F; Di Canto, A; Dijkstra, H; Donleavy, S; Dordei, F; Dorigo, M; Dosil Suárez, A; Dossett, D; Dovbnya, A; Dupertuis, F; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Easo, S; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; El Rifai, I; Elsasser, Ch; Esen, S; Evans, T; Falabella, A; Färber, C; Farinelli, C; Farry, S; Ferguson, D; Fernandez Albor, V; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fiore, M; Fiorini, M; Firlej, M; Fitzpatrick, C; Fiutowski, T; Fontana, M; Fontanelli, F; Forty, R; Francisco, O; Frank, M; Frei, C; Frosini, M; Fu, J; Furfaro, E; Gallas Torreira, A; Galli, D; Gandelman, M; Gandini, P; Gao, Y; Garofoli, J; Garra Tico, J; Garrido, L; Gaspar, C; Gauld, R; Gavardi, L; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianelle, A; Giani, S; Gibson, V; Giubega, L; Gligorov, V V; Göbel, C; Golubkov, D; Golutvin, A; Gomes, A; Gordon, H; Gotti, C; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graziani, G; Grecu, A; Greening, E; Gregson, S; Griffith, P; Grillo, L; Grünberg, O; Gui, B; Gushchin, E; Guz, Yu; Gys, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hall, S; Hamilton, B; Hampson, T; Han, X; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hartmann, T; He, J; Head, T; Heijne, V; Hennessy, K; Henrard, P; Henry, L; Hernando Morata, J A; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hoballah, M; Hombach, C; Hulsbergen, W; Hunt, P; Hussain, N; Hutchcroft, D; Hynds, D; Iakovenko, V; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jalocha, J; Jans, E; Jaton, P; Jawahery, A; Jezabek, M; Jing, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kaballo, M; Kandybei, S; Kanso, W; Karacson, M; Karbach, T M; Kelsey, M; Kenyon, I R; Ketel, T; Khanji, B; Khurewathanakul, C; Klaver, S; Kochebina, O; Kolpin, M; Komarov, I; Koopman, R F; Koppenburg, P; Korolev, M; Kozlinskiy, A; Kravchuk, L; Kreplin, K; Kreps, M; Krocker, G; Krokovny, P; Kruse, F; Kucharczyk, M; Kudryavtsev, V; Kurek, K; Kvaratskheliya, T; La Thi, V N; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lambert, R W; Lanciotti, E; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Lefèvre, R; Leflat, A; Lefrançois, J; Leo, S; Leroy, O; Lesiak, T; Leverington, B; Li, Y; Liles, M; Lindner, R; Linn, C; Lionetto, F; Liu, B; Liu, G; Lohn, S; Longstaff, I; Longstaff, I; Lopes, J H; Lopez-March, N; Lowdon, P; Lu, H; Lucchesi, D; Luisier, J; Luo, H; Lupato, A; Luppi, E; Lupton, O; Machefert, F; Machikhiliyan, I V; Maciuc, F; Maev, O; Malde, S; Manca, G; Mancinelli, G; Manzali, M; Maratas, J; Marchand, J F; Marconi, U; Marino, P; Märki, R; Marks, J; Martellotti, G; Martens, A; Martín Sánchez, A; Martinelli, M; Martinez Santos, D; Martinez Vidal, F; Martins Tostes, D; Massafferri, A; Matev, R; Mathe, Z; Matteuzzi, C; Mazurov, A; McCann, M; McCarthy, J; McNab, A; McNulty, R; McSkelly, B; Meadows, B; Meier, F; Meissner, M; Merk, M; Milanes, D A; Minard, M-N; Molina Rodriguez, J; Monteil, S; Moran, D; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Moron, J; Mountain, R; Muheim, F; Müller, K; Muresan, R; Muster, B; Naik, P; Nakada, T; Nandakumar, R; Nasteva, I; Needham, M; Neri, N; Neubert, S; Neufeld, N; Neuner, M; Nguyen, A D; Nguyen, T D; Nguyen-Mau, C; Nicol, M; Niess, V; Niet, R; Nikitin, N; Nikodem, T; Novoselov, A; Oblakowska-Mucha, A; Obraztsov, V; Oggero, S; Ogilvy, S; Okhrimenko, O; Oldeman, R; Onderwater, G; Orlandea, M; Otalora Goicochea, J M; Owen, P; Oyanguren, A; Pal, B K; Palano, A; Palombo, F; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Parkes, C; Parkinson, C J; Passaleva, G; Patel, G D; Patel, M; Patrignani, C; Pazos Alvarez, A; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perez Trigo, E; Perret, P; Perrin-Terrin, M; Pescatore, L; Pesen, E; Petridis, K; Petrolini, A; Picatoste Olloqui, E; Pietrzyk, B; Pilař, T; Pinci, D; Pistone, A; Playfer, S; Plo Casasus, M; Polci, F; Polok, G; Poluektov, A; Polycarpo, E; Popov, A; Popov, D; Popovici, B; Potterat, C; Powell, A; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Rachwal, B; Rademacker, J H; Rakotomiaramanana, B; Rama, M; Rangel, M S; Raniuk, I; Rauschmayr, N; Raven, G; Redford, S; Reichert, S; Reid, M M; Dos Reis, A C; Ricciardi, S; Richards, A; Rinnert, K; Rives Molina, V; Roa Romero, D A; Robbe, P; Rodrigues, A B; Rodrigues, E; Rodriguez Perez, P; Roiser, S; Romanovsky, V; Romero Vidal, A; Rotondo, M; Rouvinet, J; Ruf, T; Ruffini, F; Ruiz, H; Ruiz Valls, P; Sabatino, G; Saborido Silva, J J; Sagidova, N; Sail, P; Saitta, B; Salustino Guimaraes, V; Sanchez Mayordomo, C; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santovetti, E; Sapunov, M; Sarti, A; Satriano, C; Satta, A; Savrie, M; Savrina, D; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmidt, B; Schneider, O; Schopper, A; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Seco, M; Semennikov, A; Senderowska, K; Sepp, I; Serra, N; Serrano, J; Sestini, L; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, V; Shires, A; Silva Coutinho, R; Simi, G; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, N A; Smith, E; Smith, E; Smith, J; Smith, M; Snoek, H; Sokoloff, M D; Soler, F J P; Soomro, F; Souza, D; Souza De Paula, B; Spaan, B; Sparkes, A; Spinella, F; Spradlin, P; Stagni, F; Stahl, S; Steinkamp, O; Stenyakin, O; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Stroili, R; Subbiah, V K; Sun, L; Sutcliffe, W; Swientek, K; Swientek, S; Syropoulos, V; Szczekowski, M; Szczypka, P; Szilard, D; Szumlak, T; T'Jampens, S; Teklishyn, M; Tellarini, G; Teodorescu, E; Teubert, F; Thomas, C; Thomas, E; van Tilburg, J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Torr, N; Tournefier, E; Tourneur, S; Tran, M T; Tresch, M; Tsaregorodtsev, A; Tsopelas, P; Tuning, N; Ubeda Garcia, M; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vagnoni, V; Valenti, G; Vallier, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vázquez Sierra, C; Vecchi, S; Velthuis, J J; Veltri, M; Veneziano, G; Vesterinen, M; Viaud, B; Vieira, D; Vieites Diaz, M; Vilasis-Cardona, X; Vollhardt, A; Volyanskyy, D; Voong, D; Vorobyev, A; Vorobyev, V; Voß, C; Voss, H; de Vries, J A; Waldi, R; Wallace, C; Wallace, R; Walsh, J; Wandernoth, S; Wang, J; Ward, D R; Watson, N K; Webber, A D; Websdale, D; Whitehead, M; Wicht, J; Wiedner, D; Wiggers, L; Wilkinson, G; Williams, M P; Williams, M; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wright, S; Wu, S; Wyllie, K; Xie, Y; Xing, Z; Xu, Z; Yang, Z; Yuan, X; Yushchenko, O; Zangoli, M; Zavertyaev, M; Zhang, F; Zhang, L; Zhang, W C; Zhang, Y; Zhelezov, A; Zhokhov, A; Zhong, L; Zvyagin, A

The polarisation of prompt [Formula: see text] mesons is measured by performing an angular analysis of [Formula: see text] decays using proton-proton collision data, corresponding to an integrated luminosity of 1.0[Formula: see text], collected by the LHCb detector at a centre-of-mass energy of 7 TeV. The polarisation is measured in bins of transverse momentum [Formula: see text] and rapidity [Formula: see text] in the kinematic region [Formula: see text] and [Formula: see text], and is compared to theoretical models. No significant polarisation is observed.

EXTRACT

DEFF Research Database (Denmark)

Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra

2016-01-01

The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have the...... and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/......., organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual...

SparkText: Biomedical Text Mining on Big Data Framework.

Directory of Open Access Journals (Sweden)

Zhan Ye

Full Text Available Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment.In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM, and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes.This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Methanol extract of Nigella sativa seed induces changes in the levels of neurotransmitter amino acids in male rat brain regions.

Science.gov (United States)

El-Naggar, Tarek; Carretero, María Emilia; Arce, Carmen; Gómez-Serranillos, María Pilar

2017-12-01

Nigella sativa L. (Ranunculaceae) (NS) has been used for medicinal and culinary purposes. Different parts of the plant are used to treat many disorders. This study investigates the effects of NS methanol extract on brain neurotransmitter amino acid levels. We measured the changes in aspartate, glutamate, glycine and γ-aminobutyric acid in five brain regions of male Wistar rats after methanol extract treatment. Animals were injected intraperitoneally with saline solution (controls) or NS methanol extract (equivalent of 2.5 g/kg body weight) and sacrificed 1 h later or after administering 1 daily dose for 8 days. The neurotransmitters were measured in the hypothalamus, cortex, striatum, hippocampus and thalamus by HPLC. Results showed significant changes in amino acids compared to basal values. Glutamate increased significantly (16-36%) in the regions analyzed except the striatum. Aspartate in the hypothalamus (50 and 76%) and glycine in hippocampus (32 and 25%), thalamus (66 and 29%) and striatum (75 and 48%) also increased with the two treatment intervals. γ-Aminobutyric acid significantly increased in the hippocampus (38 and 32%) and thalamus (22 and 40%) but decreased in the cortex and hypothalamus although in striatum only after eight days of treatment (24%). Our results suggest that injected methanol extract modifies amino acid levels in the rat brain regions. These results could be of interest since some neurodegenerative diseases are related to amino acid level imbalances in the central nervous system, suggesting the prospect for therapeutic use of NS against these disorders.

Extraction of Lesion-Partitioned Features and Retrieval of Contrast-Enhanced Liver Images

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Mei Yu

2012-01-01

Full Text Available The most critical step in grayscale medical image retrieval systems is feature extraction. Understanding the interrelatedness between the characteristics of lesion images and corresponding imaging features is crucial for image training, as well as for features extraction. A feature-extraction algorithm is developed based on different imaging properties of lesions and on the discrepancy in density between the lesions and their surrounding normal liver tissues in triple-phase contrast-enhanced computed tomographic (CT scans. The algorithm includes mainly two processes: (1 distance transformation, which is used to divide the lesion into distinct regions and represents the spatial structure distribution and (2 representation using bag of visual words (BoW based on regions. The evaluation of this system based on the proposed feature extraction algorithm shows excellent retrieval results for three types of liver lesions visible on triple-phase scans CT images. The results of the proposed feature extraction algorithm show that although single-phase scans achieve the average precision of 81.9%, 80.8%, and 70.2%, dual- and triple-phase scans achieve 86.3% and 88.0%.

Stereoscopic Visual Attention-Based Regional Bit Allocation Optimization for Multiview Video Coding

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Dai Qionghai

2010-01-01

Full Text Available We propose a Stereoscopic Visual Attention- (SVA- based regional bit allocation optimization for Multiview Video Coding (MVC by the exploiting visual redundancies from human perceptions. We propose a novel SVA model, where multiple perceptual stimuli including depth, motion, intensity, color, and orientation contrast are utilized, to simulate the visual attention mechanisms of human visual system with stereoscopic perception. Then, a semantic region-of-interest (ROI is extracted based on the saliency maps of SVA. Both objective and subjective evaluations of extracted ROIs indicated that the proposed SVA model based on ROI extraction scheme outperforms the schemes only using spatial or/and temporal visual attention clues. Finally, by using the extracted SVA-based ROIs, a regional bit allocation optimization scheme is presented to allocate more bits on SVA-based ROIs for high image quality and fewer bits on background regions for efficient compression purpose. Experimental results on MVC show that the proposed regional bit allocation algorithm can achieve over % bit-rate saving while maintaining the subjective image quality. Meanwhile, the image quality of ROIs is improved by  dB at the cost of insensitive image quality degradation of the background image.

SparkText: Biomedical Text Mining on Big Data Framework

Science.gov (United States)

He, Karen Y.; Wang, Kai

2016-01-01

Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

Systematically extracting metal- and solvent-related occupational information from free-text responses to lifetime occupational history questionnaires.

Science.gov (United States)

Friesen, Melissa C; Locke, Sarah J; Tornow, Carina; Chen, Yu-Cheng; Koh, Dong-Hee; Stewart, Patricia A; Purdue, Mark; Colt, Joanne S

2014-06-01

Lifetime occupational history (OH) questionnaires often use open-ended questions to capture detailed information about study participants' jobs. Exposure assessors use this information, along with responses to job- and industry-specific questionnaires, to assign exposure estimates on a job-by-job basis. An alternative approach is to use information from the OH responses and the job- and industry-specific questionnaires to develop programmable decision rules for assigning exposures. As a first step in this process, we developed a systematic approach to extract the free-text OH responses and convert them into standardized variables that represented exposure scenarios. Our study population comprised 2408 subjects, reporting 11991 jobs, from a case-control study of renal cell carcinoma. Each subject completed a lifetime OH questionnaire that included verbatim responses, for each job, to open-ended questions including job title, main tasks and activities (task), tools and equipment used (tools), and chemicals and materials handled (chemicals). Based on a review of the literature, we identified exposure scenarios (occupations, industries, tasks/tools/chemicals) expected to involve possible exposure to chlorinated solvents, trichloroethylene (TCE) in particular, lead, and cadmium. We then used a SAS macro to review the information reported by study participants to identify jobs associated with each exposure scenario; this was done using previously coded standardized occupation and industry classification codes, and a priori lists of associated key words and phrases related to possibly exposed tasks, tools, and chemicals. Exposure variables representing the occupation, industry, and task/tool/chemicals exposure scenarios were added to the work history records of the study respondents. Our identification of possibly TCE-exposed scenarios in the OH responses was compared to an expert's independently assigned probability ratings to evaluate whether we missed identifying

Development and Validation of a HPLC-UV Method for Extraction Optimization and Biological Evaluation of Hot-Water and Ethanolic Extracts of Dendropanax morbifera Leaves

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Hyung-Jae Choi

2018-03-01

Full Text Available Dendropanax morbifera Leveille (Araliaceae has been used in traditional oriental remedies for cancer, inflammation, diabetes, and thrombosis. However, a validated analytical method, standardization, and optimization of extraction conditions with respect to biological activity have not been reported. In this study, a simple and validated HPLC method for identifying and quantifying active substances in D. morbifera was developed. Hot water and ethanolic D. morbifera leaf extracts from different production regions were prepared and evaluated with regard to their chemical compositions and biological activities. The contents of active compounds such as rutin and chlorogenic acid were determined in four samples collected from different regions. The 80% ethanolic extract showed the best antioxidant activity, phenolic content, reducing power, and xanthine oxidase (XO inhibitory activity. The validated HPLC method confirmed the presence of chlorogenic acid and rutin in D. morbifera leaf extracts. The antioxidant and XO inhibitory activity of D. morbifera extract could be attributed to the marker compounds. Collectively, these results suggest that D. morbifera leaves could be beneficial for the treatment or prevention of hyperuricemia-related disease, and the validated HPLC method could be a useful tool for the quality control of food or drug formulations containing D. morbifera.

Utilization of Lavandula angustifolia Miller extracts as naturalrepellents, pharmaceutical and industrial auxiliaries

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AYOE YUSUFOGLU

2004-01-01

Full Text Available Essential oils, absolutes and concretes were prepared from the flowers and leaves of the plant Lavandula angustifolia Miller cultivated in the Bosphorus region of Istanbul, Turkey. The difference in the chemical composition of the mentioned extracts was investigated and compared by using a combination of capillary GC-MS with the aim of offering them as repellent, pharmaceutical and industrial auxiliaries. The IR-spectra, the yields and the physico-chemical data of the extracts were also analysed.

Pedestrian detection in thermal images: An automated scale based region extraction with curvelet space validation

Science.gov (United States)

Lakshmi, A.; Faheema, A. G. J.; Deodhare, Dipti

2016-05-01

Pedestrian detection is a key problem in night vision processing with a dozen of applications that will positively impact the performance of autonomous systems. Despite significant progress, our study shows that performance of state-of-the-art thermal image pedestrian detectors still has much room for improvement. The purpose of this paper is to overcome the challenge faced by the thermal image pedestrian detectors, which employ intensity based Region Of Interest (ROI) extraction followed by feature based validation. The most striking disadvantage faced by the first module, ROI extraction, is the failed detection of cloth insulted parts. To overcome this setback, this paper employs an algorithm and a principle of region growing pursuit tuned to the scale of the pedestrian. The statistics subtended by the pedestrian drastically vary with the scale and deviation from normality approach facilitates scale detection. Further, the paper offers an adaptive mathematical threshold to resolve the problem of subtracting the background while extracting cloth insulated parts as well. The inherent false positives of the ROI extraction module are limited by the choice of good features in pedestrian validation step. One such feature is curvelet feature, which has found its use extensively in optical images, but has as yet no reported results in thermal images. This has been used to arrive at a pedestrian detector with a reduced false positive rate. This work is the first venture made to scrutinize the utility of curvelet for characterizing pedestrians in thermal images. Attempt has also been made to improve the speed of curvelet transform computation. The classification task is realized through the use of the well known methodology of Support Vector Machines (SVMs). The proposed method is substantiated with qualified evaluation methodologies that permits us to carry out probing and informative comparisons across state-of-the-art features, including deep learning methods, with six

Automatic Road Centerline Extraction from Imagery Using Road GPS Data

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Chuqing Cao

2014-09-01

Full Text Available Road centerline extraction from imagery constitutes a key element in numerous geospatial applications, which has been addressed through a variety of approaches. However, most of the existing methods are not capable of dealing with challenges such as different road shapes, complex scenes, and variable resolutions. This paper presents a novel method for road centerline extraction from imagery in a fully automatic approach that addresses the aforementioned challenges by exploiting road GPS data. The proposed method combines road color feature with road GPS data to detect road centerline seed points. After global alignment of road GPS data, a novel road centerline extraction algorithm is developed to extract each individual road centerline in local regions. Through road connection, road centerline network is generated as the final output. Extensive experiments demonstrate that our proposed method can rapidly and accurately extract road centerline from remotely sensed imagery.

Recognition of pornographic web pages by classifying texts and images.

Science.gov (United States)

Hu, Weiming; Wu, Ou; Chen, Zhouyao; Fu, Zhouyu; Maybank, Steve

2007-06-01

With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image classifier, the object's contour-based features are extracted to recognize pornographic images. In the text and image fusion algorithm, the Bayes theory is used to combine the recognition results from images and texts. Experimental results demonstrate that the continuous text classifier outperforms the traditional keyword-statistics-based classifier, the contour-based image classifier outperforms the traditional skin-region-based image classifier, the results obtained by our fusion algorithm outperform those by either of the individual classifiers, and our framework can be adapted to different categories of Web pages.

An Approach to Retrieval of OCR Degraded Text

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Yuen-Hsien Tseng

1998-12-01

Full Text Available The major problem with retrieval of OCR text is the unpredictable distortion of characters due to recognition errors. Because users have no ideas of such distortion, the terms they query can hardly match the terms stored in the OCR text exactly. Thus retrieval effectiveness is significantly reduced , especially for low-quality input. To reduce the losses from retrieving such noisy OCR text, a fault-tolerant retrieval strategy based on automatic keyword extraction and fuzzy matching is proposed. In this strategy, terms, correct or not, and their term frequencies are extracted from the noisy text and presented for browsing and selection in response to users' initial queries , With theunderstanding of the real terms stored in the noisy text and of their estimated frequency distributions, users may then choose appropriate terms for a more effective searching, A text retrieval system based on this strategy has been built. Examples to show the effectiveness are demonstrated. Finally, some OCR issues for further enhancingretrieval effectiveness are discussed.

Imitating manual curation of text-mined facts in biomedicine.

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Raul Rodriguez-Esteban

2006-09-01

Full Text Available Text-mining algorithms make mistakes in extracting facts from natural-language texts. In biomedical applications, which rely on use of text-mined data, it is critical to assess the quality (the probability that the message is correctly extracted of individual facts--to resolve data conflicts and inconsistencies. Using a large set of almost 100,000 manually produced evaluations (most facts were independently reviewed more than once, producing independent evaluations, we implemented and tested a collection of algorithms that mimic human evaluation of facts provided by an automated information-extraction system. The performance of our best automated classifiers closely approached that of our human evaluators (ROC score close to 0.95. Our hypothesis is that, were we to use a larger number of human experts to evaluate any given sentence, we could implement an artificial-intelligence curator that would perform the classification job at least as accurately as an average individual human evaluator. We illustrated our analysis by visualizing the predicted accuracy of the text-mined relations involving the term cocaine.

Information extraction system

Science.gov (United States)

Lemmond, Tracy D; Hanley, William G; Guensche, Joseph Wendell; Perry, Nathan C; Nitao, John J; Kidwell, Paul Brandon; Boakye, Kofi Agyeman; Glaser, Ron E; Prenger, Ryan James

2014-05-13

An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

Application of Text Mining to Extract Hotel Attributes and Construct Perceptual Map of Five Star Hotels from Online Review: Study of Jakarta and Singapore Five-Star Hotels

Directory of Open Access Journals (Sweden)

Arga Hananto

2015-12-01

Full Text Available The use of post-purchase online consumer review in hotel attributes study was still scarce in the literature. Arguably, post purchase online review data would gain more accurate attributes thatconsumers actually consider in their purchase decision. This study aims to extract attributes from two samples of five-star hotel reviews (Jakarta and Singapore with text mining methodology. In addition,this study also aims to describe positioning of five-star hotels in Jakarta and Singapore based on the extracted attributes using Correspondence Analysis. This study finds that reviewers of five star hotels in both cities mentioned similar attributes such as service, staff, club, location, pool and food. Attributes derived from text mining seem to be viable input to build fairly accurate positioning map of hotels. This study has demonstrated the viability of online review as a source of data for hotel attribute and positioning studies.

Text mining of web-based medical content

CERN Document Server

Neustein, Amy

2014-01-01

Text Mining of Web-Based Medical Content examines web mining for extracting useful information that can be used for treating and monitoring the healthcare of patients. This work provides methodological approaches to designing mapping tools that exploit data found in social media postings. Specific linguistic features of medical postings are analyzed vis-a-vis available data extraction tools for culling useful information.

Extracted atmospheric impairments on earth-sky signal quality in tropical regions at Ku-band

Science.gov (United States)

Al-Saegh, Ali Mohammed; Sali, Aduwati; Mandeep, J. S.; Ismail, Alyani

2013-11-01

Atmospheric condition variations were shown to have a major effect on the earth sky signal quality at Ku band. Moreover, such variations increased in the tropical regions as compared to temperate areas due to their different weather parameters. With the increase of recent satellite communication technology applications throughout the tropical countries and lack of information regarding the atmospheric impairments analysis, simulation and mitigation techniques, there is an ever increasing need for extracting a unique and accurate performance of the signal quality effects during highly natural tropical weather impairments. This paper presents a new method developed for proper analysis with distinctive and highly realistic performance evaluation for signal quality during the atmospheric conditions variations in 14 tropical areas from the four continents analyzed based on actual measured parameters. The method implementation includes signal attenuation, carrier to noise ratio, symbol energy to noise ratio, and symbol error rate at different areas and different modulation schemes. Furthermore, for improvement in analysis in terms of covering more remarkable regions in tropics, the paper provides new measurements data with analysis for certain region in tropics used as a test bed and to add measurement data of such area to the world's data base for future researchers. The results show a significant investigation and performance observation in terms of weather impairments in tropical regions in general and each region in that area in particular regarding the signal attenuation and error rates accompanied for several transmission schemes.

Bollywood Movie Corpus for Text, Images and Videos

OpenAIRE

Madaan, Nishtha; Mehta, Sameep; Saxena, Mayank; Aggarwal, Aditi; Agrawaal, Taneea S; Malhotra, Vrinda

2017-01-01

In past few years, several data-sets have been released for text and images. We present an approach to create the data-set for use in detecting and removing gender bias from text. We also include a set of challenges we have faced while creating this corpora. In this work, we have worked with movie data from Wikipedia plots and movie trailers from YouTube. Our Bollywood Movie corpus contains 4000 movies extracted from Wikipedia and 880 trailers extracted from YouTube which were released from 1...

Economic Growth, Convergence and Innovation in the EU Regions

Directory of Open Access Journals (Sweden)

Tiiu Paas

2012-12-01

Full Text Available The paper focuses on quantitative assessment of the innovation’s role in explaining regional disparities and convergence in Europe. The empirical part of the study bases on the regional GDP pc and innovation indicators on the EU-27 NUTS2 level regions. Based on the selected set of initial regional innovation indicators and using the principal components factor analysis method, three composite indicators of regional innovation capacity are extracted. Estimating convergence equations, we noticed that regional innovations tend to increase inter-regional differences, at least during the short-run period. Thus, if regional income convergence is a policy target, additional policy measures beside innovation activities should be effectively implemented.

EXTRACTION OF MONOAZO DYES BY HYDROPHILIC EXTRACTANTS FROM AQUEOUS SOLUTIONS

Directory of Open Access Journals (Sweden)

Y. I. Korenman

2012-01-01

Full Text Available The extraction of mono azo dyes E102, E122, E110, E124, E129 from aqueous solutions with hydrophilic solvents (alcohols, esters, ketones and polymers (poly-N-vinylamides, polyethylene glycol was studied. The main regularities of extraction are established. The distribution coefficients and degree of extraction of dyes was estimate. The influence of the nature of solvents and polymers on the extraction of dyes from aqueous solutions are established.

Evaluation of emergency medical text processor, a system for cleaning chief complaint text data.

Science.gov (United States)

Travers, Debbie A; Haas, Stephanie W

2004-11-01

Emergency Medical Text Processor (EMT-P) version 1, a natural language processing system that cleans emergency department text (e.g., chst pn, chest pai), was developed to maximize extraction of standard terms (e.g., chest pain). The authors compared the number of standard terms extracted from raw chief complaint (CC) data with that for CC data cleaned with EMT-P and evaluated the accuracy of EMT-P. This cross-sectional observation study included CC text entries for all emergency department visits to three tertiary care centers in 2001. Terms were extracted from CC entries before and after cleaning with EMT-P. Descriptive statistics included number and percentage of all entries (tokens) and all unique entries (types) that matched a standard term from the Unified Medical Language System (UMLS). An expert panel rated the accuracy of the CC-UMLS term matches; inter-rater reliability was measured with kappa. The authors collected 203,509 CC entry tokens, of which 63,946 were unique entry types. For the raw data, 89,337 tokens (44%) and 5,081 types (8%) matched a standard term. After EMT-P cleaning, 168,050 tokens (83%) and 44,430 types (69%) matched a standard term. The expert panel reached consensus on 201 of the 222 CC-UMLS term matches reviewed (kappa=0.69-0.72). Ninety-six percent of the 201 matches were rated equivalent or related. Thirty-eight percent of the nonmatches were found to match UMLS concepts. EMT-P version 1 is relatively accurate, and cleaning with EMT-P improved the CC-UMLS term match rate over raw data. The authors identified areas for improvement in future EMT-P versions and issues to be resolved in developing a standard CC terminology.

The Text of the Agreement of 8 July Extending the Asian Regional Co-Operative Project on Food Irradiation. Extension Agreement

International Nuclear Information System (INIS)

1983-12-01

The text of the Agreement to Extend the Agreement of 23 May 1980 Establishing the Asian Regional Co-operative Project on Food Irradiation within the framework of the Regional Co-operative Agreement for Research, Development and Training Related to Nuclear Science and Technology of 1972, as extended in 1977 and in 1982, is reproduced herein for the information of all Members

Lung region extraction based on the model information and the inversed MIP method by using chest CT images

International Nuclear Information System (INIS)

Tomita, Toshihiro; Miguchi, Ryosuke; Okumura, Toshiaki; Yamamoto, Shinji; Matsumoto, Mitsuomi; Tateno, Yukio; Iinuma, Takeshi; Matsumoto, Toru.

1997-01-01

We developed a lung region extraction method based on the model information and the inversed MIP method in the Lung Cancer Screening CT (LSCT). Original model is composed of typical 3-D lung contour lines, a body axis, an apical point, and a convex hull. First, the body axis. the apical point, and the convex hull are automatically extracted from the input image Next, the model is properly transformed to fit to those of input image by the affine transformation. Using the same affine transformation coefficients, typical lung contour lines are also transferred, which correspond to rough contour lines of input image. Experimental results applied for 68 samples showed this method quite promising. (author)

Regionalism, Regionalization and Regional Development

Directory of Open Access Journals (Sweden)

Liviu C. Andrei

2016-03-01

Full Text Available Sustained development is a concept associating other concepts, in its turn, in the EU practice, e.g. regionalism, regionalizing and afferent policies, here including structural policies. This below text, dedicated to integration concepts, will limit on the other hand to regionalizing, otherwise an aspect typical to Europe and to the EU. On the other hand, two aspects come up to strengthen this field of ideas, i.e. the region (al-regionalism-(regional development triplet has either its own history or precise individual outline of terms.

Larvicidal, antimicrobial and brine shrimp activities of extracts from Cissampelos mucronata and Tephrosia villosa from coast region, Tanzania.

Science.gov (United States)

Nondo, Ramadhani S O; Mbwambo, Zakaria H; Kidukuli, Abdul W; Innocent, Ester M; Mihale, Matobola J; Erasto, Paul; Moshi, Mainen J

2011-04-23

The leaves and roots of Cissampelos mucronata A. Rich (Menispermaceae) are widely used in the tropics and subtropics to manage various ailments such as gastro-intestinal complaints, menstrual problems, venereal diseases and malaria. In the Coast region, Tanzania, roots are used to treat wounds due to extraction of jigger. Leaves of Tephrosia villosa (L) Pers (Leguminosae) are reported to be used in the treatment of diabetes mellitus in India. In this study, extracts from the roots and aerial parts of C. mucronata and extracts from leaves, fruits, twigs and roots of T. villosa were evaluated for larvicidal activity, brine shrimps toxicity and antimicrobial activity. Powdered materials from C. mucronata were extracted sequentially by dichloromethane followed by ethanol while materials from T.villosa were extracted by ethanol only. The extracts obtained were evaluated for larvicidal activity using Culex quinquefasciatus Say larvae, cytotoxicity using brine shrimp larvae and antimicrobial activity using bacteria and fungi. Extracts from aerial parts of C. Mucronata exhibited antibacterial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Salmonella typhi, Vibrio cholera, Bacillus anthracis, Streptococcus faecalis and antifungal activity against Candida albicans and Cryptococcus neoformans. They exhibited very low toxicity to brine shrimps and had no larvicidal activity. The root extracts exhibited good larvicidal activity but weak antimicrobial activity. The root dichloromethane extracts from C. mucronata was found to be more toxic with an LC50 value of 59.608 μg/mL while ethanolic extracts from root were not toxic with LC50>100 μg/mL). Ethanol extracts from fruits and roots of T. villosa were found to be very toxic with LC50 values of 9.690 μg/mL and 4.511 μg/mL, respectively, while, ethanol extracts from leaves and twigs of T. villosa were found to be non toxic (LC50>100 μg/mL). These results support the use of C. mucronata in

Text Detection in Natural Scene Images by Stroke Gabor Words.

Science.gov (United States)

Yi, Chucai; Tian, Yingli

2011-01-01

In this paper, we propose a novel algorithm, based on stroke components and descriptive Gabor filters, to detect text regions in natural scene images. Text characters and strings are constructed by stroke components as basic units. Gabor filters are used to describe and analyze the stroke components in text characters or strings. We define a suitability measurement to analyze the confidence of Gabor filters in describing stroke component and the suitability of Gabor filters on an image window. From the training set, we compute a set of Gabor filters that can describe principle stroke components of text by their parameters. Then a K -means algorithm is applied to cluster the descriptive Gabor filters. The clustering centers are defined as Stroke Gabor Words (SGWs) to provide a universal description of stroke components. By suitability evaluation on positive and negative training samples respectively, each SGW generates a pair of characteristic distributions of suitability measurements. On a testing natural scene image, heuristic layout analysis is applied first to extract candidate image windows. Then we compute the principle SGWs for each image window to describe its principle stroke components. Characteristic distributions generated by principle SGWs are used to classify text or nontext windows. Experimental results on benchmark datasets demonstrate that our algorithm can handle complex backgrounds and variant text patterns (font, color, scale, etc.).

Text mining by Tsallis entropy

Science.gov (United States)

Jamaati, Maryam; Mehri, Ali

2018-01-01

Long-range correlations between the elements of natural languages enable them to convey very complex information. Complex structure of human language, as a manifestation of natural languages, motivates us to apply nonextensive statistical mechanics in text mining. Tsallis entropy appropriately ranks the terms' relevance to document subject, taking advantage of their spatial correlation length. We apply this statistical concept as a new powerful word ranking metric in order to extract keywords of a single document. We carry out an experimental evaluation, which shows capability of the presented method in keyword extraction. We find that, Tsallis entropy has reliable word ranking performance, at the same level of the best previous ranking methods.

Relating interesting quantitative time series patterns with text events and text features

Science.gov (United States)

Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

2013-12-01

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

Science.gov (United States)

Renganathan, Vinaitheerthan

2017-07-01

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

Simulation studies of the extraction region from glow discharge ion sources

International Nuclear Information System (INIS)

Abdelrahman, M.M.

2012-01-01

This paper studies the influence of various parameters and conditions on the performance of an ion-beam extraction system, the trajectories of the particles in the beam being simulated by a commercial software (SIMION 3D). Space-charge effects are accounted for and criteria allowing optimization of the system are proposed. Ion beam trajectories with and without space charge have been determined and, from the results, optimum extraction conditions have been deduced. Simulation of singly charged ion trajectories for a concave meniscus with 3.5 mm curvature radius was studied with and without space charge has been done using a singly charge argon ion trajectories. Firstly, for a concave meniscus with 3.5 mm curvature radius, the influence of the current density on the ion beam shape was investigated. Furthermore, influence of the extraction voltage applied to the extraction electrode on the ion beam envelope was studied. Finally, the influence of the extraction gap width on the ion beam envelope was also studied

Text Mining for Protein Docking.

Directory of Open Access Journals (Sweden)

Varsha D Badal

2015-12-01

Full Text Available The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking. Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu. The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound

Arabic text preprocessing for the natural language processing applications

International Nuclear Information System (INIS)

Awajan, A.

2007-01-01

A new approach for processing vowelized and unvowelized Arabic texts in order to prepare them for Natural Language Processing (NLP) purposes is described. The developed approach is rule-based and made up of four phases: text tokenization, word light stemming, word's morphological analysis and text annotation. The first phase preprocesses the input text in order to isolate the words and represent them in a formal way. The second phase applies a light stemmer in order to extract the stem of each word by eliminating the prefixes and suffixes. The third phase is a rule-based morphological analyzer that determines the root and the morphological pattern for each extracted stem. The last phase produces an annotated text where each word is tagged with its morphological attributes. The preprocessor presented in this paper is capable of dealing with vowelized and unvowelized words, and provides the input words along with relevant linguistics information needed by different applications. It is designed to be used with different NLP applications such as machine translation text summarization, text correction, information retrieval and automatic vowelization of Arabic Text. (author)

A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI.

Science.gov (United States)

Ji, Dong Xu; Foong, Kelvin Weng Chiong; Ong, Sim Heng

2013-09-01

Extraction of the mandible from 3D volumetric images is frequently required for surgical planning and evaluation. Image segmentation from MRI is more complex than CT due to lower bony signal-to-noise. An automated method to extract the human mandible body shape from magnetic resonance (MR) images of the head was developed and tested. Anonymous MR images data sets of the head from 12 subjects were subjected to a two-stage rule-constrained region growing approach to derive the shape of the body of the human mandible. An initial thresholding technique was applied followed by a 3D seedless region growing algorithm to detect a large portion of the trabecular bone (TB) regions of the mandible. This stage is followed with a rule-constrained 2D segmentation of each MR axial slice to merge the remaining portions of the TB regions with lower intensity levels. The two-stage approach was replicated to detect the cortical bone (CB) regions of the mandibular body. The TB and CB regions detected from the preceding steps were merged and subjected to a series of morphological processes for completion of the mandibular body region definition. Comparisons of the accuracy of segmentation between the two-stage approach, conventional region growing method, 3D level set method, and manual segmentation were made with Jaccard index, Dice index, and mean surface distance (MSD). The mean accuracy of the proposed method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of CRG is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of the 3D level set method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The proposed method shows improvement in accuracy over CRG and 3D level set. Accurate segmentation of the body of the human mandible from MR images is achieved with the

Text Mining of Supreme Administrative Court Jurisdictions

OpenAIRE

Feinerer, Ingo; Hornik, Kurt

2007-01-01

Within the last decade text mining, i.e., extracting sensitive information from text corpora, has become a major factor in business intelligence. The automated textual analysis of law corpora is highly valuable because of its impact on a company's legal options and the raw amount of available jurisdiction. The study of supreme court jurisdiction and international law corpora is equally important due to its effects on business sectors. In this paper we use text mining methods to investigate Au...

IMPACT OF ENVIRONMENTAL MANAGEMENT ON THE SOCIO-ECONOMIC DEVELOPMENT OF ARCHANGELSK REGION

Directory of Open Access Journals (Sweden)

A.G. Shelomentsev

2009-12-01

Full Text Available This article includes the analysis of a role of process of extraction and processing of the natural resources, mastered in territory of region on socio-economic development of the Arkhangelsk region. Features of dynamics of density of kinds of natural resources on indicators and spheres of influence are revealed. Also in this paper prospect of development and an opportunity of increase of a role of environmental management in socio-economic development of the Arkhangelsk region are considered.

Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

Science.gov (United States)

Elayavilli, Ravikumar Komandur; Liu, Hongfang

2016-01-01

Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological

Transductive Pattern Learning for Information Extraction

National Research Council Canada - National Science Library

McLernon, Brian; Kushmerick, Nicholas

2006-01-01

.... We present TPLEX, a semi-supervised learning algorithm for information extraction that can acquire extraction patterns from a small amount of labelled text in conjunction with a large amount of unlabelled text...

Estimation of regional air-quality damages from Marcellus Shale natural gas extraction in Pennsylvania

International Nuclear Information System (INIS)

Litovitz, Aviva; Abramzon, Shmuel; Curtright, Aimee; Samaras, Constantine; Burger, Nicholas

2013-01-01

This letter provides a first-order estimate of conventional air pollutant emissions, and the monetary value of the associated environmental and health damages, from the extraction of unconventional shale gas in Pennsylvania. Region-wide estimated damages ranged from $7.2 to $32 million dollars for 2011. The emissions from Pennsylvania shale gas extraction represented only a few per cent of total statewide emissions, and the resulting statewide damages were less than those estimated for each of the state’s largest coal-based power plants. On the other hand, in counties where activities are concentrated, NO x emissions from all shale gas activities were 20–40 times higher than allowable for a single minor source, despite the fact that individual new gas industry facilities generally fall below the major source threshold for NO x . Most emissions are related to ongoing activities, i.e., gas production and compression, which can be expected to persist beyond initial development and which are largely unrelated to the unconventional nature of the resource. Regulatory agencies and the shale gas industry, in developing regulations and best practices, should consider air emissions from these long-term activities, especially if development occurs in more populated areas of the state where per-ton emissions damages are significantly higher. (letter)

Facial Feature Extraction Using Frequency Map Series in PCNN

Directory of Open Access Journals (Sweden)

Rencan Nie

2016-01-01

Full Text Available Pulse coupled neural network (PCNN has been widely used in image processing. The 3D binary map series (BMS generated by PCNN effectively describes image feature information such as edges and regional distribution, so BMS can be treated as the basis of extracting 1D oscillation time series (OTS for an image. However, the traditional methods using BMS did not consider the correlation of the binary sequence in BMS and the space structure for every map. By further processing for BMS, a novel facial feature extraction method is proposed. Firstly, consider the correlation among maps in BMS; a method is put forward to transform BMS into frequency map series (FMS, and the method lessens the influence of noncontinuous feature regions in binary images on OTS-BMS. Then, by computing the 2D entropy for every map in FMS, the 3D FMS is transformed into 1D OTS (OTS-FMS, which has good geometry invariance for the facial image, and contains the space structure information of the image. Finally, by analyzing the OTS-FMS, the standard Euclidean distance is used to measure the distances for OTS-FMS. Experimental results verify the effectiveness of OTS-FMS in facial recognition, and it shows better recognition performance than other feature extraction methods.

The Extraction of Road Boundary from Crowdsourcing Trajectory Using Constrained Delaunay Triangulation

Directory of Open Access Journals (Sweden)

YANG Wei

2017-02-01

Full Text Available Extraction of road boundary accurately from crowdsourcing trajectory lines is still a hard work.Therefore,this study presented a new approach to use vehicle trajectory lines to extract road boundary.Firstly, constructing constrained Delaunay triangulation within interpolated track lines to calculate road boundary descriptors using triangle edge length and Voronoi cell.Road boundary recognition model was established by integrating the two boundary descriptors.Then,based on seed polygons,a regional growing method was proposed to extract road boundary. Finally, taxi GPS traces in Beijing were used to verify the validity of the novel method, and the results also showed that our method was suitable for GPS traces with disparity density,complex road structure and different time interval.

Macroalgae Extracts From Antarctica Have Antimicrobial and Anticancer Potential

Directory of Open Access Journals (Sweden)

Rosiane M. Martins

2018-03-01

Full Text Available Background: Macroalgae are sources of bioactive compounds due to the large number of secondary metabolites they synthesize. The Antarctica region is characterized by extreme weather conditions and abundant aggregations of macroalgae. However, current knowledge on their biodiversity and their potential for bio-prospecting is still fledging. This study evaluates the antimicrobial and cytotoxic activity of different extracts of four macroalgae (Cystosphaera jacquinotii, Iridaea cordata, Himantothallus grandifolius, and Pyropia endiviifolia from the Antarctic region against cancer and non-cancer cell lines.Methods: The antimicrobial activity of macroalgae was evaluated by the broth microdilution method. Extracts were assessed against Staphylococcus aureus ATCC 19095, Enterococcus faecalis ATCC 4083, Escherichia coli ATCC29214, Pseudomonas aeruginosa ATCC 9027, Candida albicans ATCC 62342, and the clinical isolates from the human oral cavity, namely, C. albicans (3, C. parapsilosis, C. glabrata, C. lipolytica, and C. famata. Cytotoxicity against human epidermoid carcinoma (A-431 and mouse embryonic fibroblast (NIH/3T3 cell lines was evaluated with MTT colorimetric assay.Results: An ethyl acetate extract of H. grandifolius showed noticeable antifungal activity against all fungal strains tested, including fluconazole-resistant samples. Cytotoxicity investigation with a cancer cell line revealed that the ethyl acetate extract of I. cordata was highly cytotoxic against A-431 cancer cell line, increasing the inhibitory ratio to 91.1 and 95.6% after 24 and 48 h exposure, respectively, for a concentration of 500 μg mL−1. Most of the algal extracts tested showed little or no cytotoxicity against fibroblasts.Conclusion: Data suggest that macroalgae extracts from Antarctica may represent a source of therapeutic agents.HIGHLIGHTSDifferent macroalgae samples from Antarctica were collected and the lyophilized biomass of each macroalgae was extracted

Conversation Thread Extraction and Topic Detection in Text-Based Chat

National Research Council Canada - National Science Library

Adams, Paige H

2008-01-01

Text-based chat systems are widely used within the Department of Defense, but the standard systems available do not provide robust capabilities for search, information retrieval, or information assurance...

INFORMATION EXTRACTION IN TOMB PIT USING HYPERSPECTRAL DATA

Directory of Open Access Journals (Sweden)

X. Yang

2018-04-01

Full Text Available Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics. In this paper, the hyperspectral imaging technology is adopted to recognize the bottom images of an ancient tomb located in Shanxi province. There are many black remains on the bottom surface of the tomb, which are suspected to be some meaningful texts or paintings. Firstly, the hyperspectral data is preprocessing to get the reflectance of the region of interesting. For the convenient of compute and storage, the original reflectance value is multiplied by 10000. Secondly, this article uses three methods to extract the symbols at the bottom of the ancient tomb. Finally we tried to use morphology to connect the symbols and gave fifteen reference images. The results show that the extraction of information based on hyperspectral data can obtain a better visual experience, which is beneficial to the study of ancient tombs by researchers, and provides some references for archaeological research findings.

Text messaging in health care: a systematic review of impact studies.

Science.gov (United States)

Yeager, Valerie A; Menachemi, Nir

2011-01-01

Studies suggest text messaging is beneficial to health care; however, no one has synthesized the overall evidence on texting interventions. In response to this need, we conducted a systematic review of the impacts of text messaging in health care. PubMed database searches and subsequent reference list reviews sought English-language, peer-reviewed studies involving text messaging in health care. Commentaries, conference proceedings, and feasibilities studies were excluded. Data was extracted using an article coding sheet and input into a database for analysis. Of the 61 papers reviewed, 50 articles (82%) found text messaging had a positive effect on the primary outcome. Average sample sizes in articles reporting positive findings (n=813) were significantly larger than those that did not find a positive impact (n=178) on outcomes (p = 0.032). Articles were categorized into focal groups as follows: 27 articles (44.3%) investigated the impact of texting on disease management, 24 articles (39.3%) focused texting's impact to public health related outcomes, and 10 articles (16.4%) examined texting and its influence on administrative processes. Articles in focal groups differed by the purpose of the study, direction of the communication, and where they were published, but not in likelihood of reporting a positive impact from texting. Current evidence indicates that text messaging health care interventions are largely beneficial clinically, in public health related uses, and in terms of administrative processes. However, despite the promise of these findings, literature gaps exist, especially in primary care settings, across geographic regions and with vulnerable populations.

The text of an African regional co-operative agreement for research, development and training related to nuclear science and technology

International Nuclear Information System (INIS)

1990-04-01

The document reproduces the text of an African Regional Co-operative Agreement for Research, Development and Training Related to Nuclear Science and Technology among African Member States that was endorsed by the Board of Governors on 21 February 1990

Estimation of Cross-Lingual News Similarities Using Text-Mining Methods

Directory of Open Access Journals (Sweden)

Zhouhao Wang

2018-01-01

Full Text Available In this research, two estimation algorithms for extracting cross-lingual news pairs based on machine learning from financial news articles have been proposed. Every second, innumerable text data, including all kinds news, reports, messages, reviews, comments, and tweets are generated on the Internet, and these are written not only in English but also in other languages such as Chinese, Japanese, French, etc. By taking advantage of multi-lingual text resources provided by Thomson Reuters News, we developed two estimation algorithms for extracting cross-lingual news pairs from multilingual text resources. In our first method, we propose a novel structure that uses the word information and the machine learning method effectively in this task. Simultaneously, we developed a bidirectional Long Short-Term Memory (LSTM based method to calculate cross-lingual semantic text similarity for long text and short text, respectively. Thus, when an important news article is published, users can read similar news articles that are written in their native language using our method.

Process for the gas extraction of coal

Energy Technology Data Exchange (ETDEWEB)

Urquhart, D B

1976-05-20

The object of the invention is a process for the hydroextraction of coal is treated with water and carbon monoxide at a temperature in the region of 300 - 380/sup 0/C. After treatment is completed, the gases are separated from the treated gas; the treated coal is then extracted with an extraction medium during the gas phase at a temperature of at least 400/sup 0/C, the remainder is separated from the gas phase and the coal extract is obtained from the extraction medium. Hydrogenation is preferably carried out at a temperature in the region of 320 - 370/sup 0/C and at a pressure of 200 - 400 at. The time required for treatment with carbon monoxide and water is 1/4 - 2 hours, and in special cases 3/4 - 1 1/2 hours. The coal material itself is nutty slack, of which more than 95% of the coal particles pass through a 1.5 mm mesh sieve. After the hydrogenation the extraction is carried out at a temperature in the region of 400 - 450/sup 0/C. The patent claims relate to the types of extraction media used.

Strategies to Increase Accuracy in Text Classification

NARCIS (Netherlands)

D. Blommesteijn (Dennis)

2014-01-01

htmlabstractText classification via supervised learning involves various steps from processing raw data, features extraction to training and validating classifiers. Within these steps implementation decisions are critical to the resulting classifier accuracy. This paper contains a report of the

Anti Epileptic Activity of Morinda citrifolia Linn Fruit Extract

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P. Muralidharan

2010-01-01

Full Text Available Fruit extract of Morinda citrifolia (Noni, a medicinal plant used in many neuro protective ayurvedic preparations was evaluated for its protective effect against seizures induced by Maximal Electro Shock (MES method in rats. A daily dose of 200 and 400 mg/kg of the extract was administered to the animals for 15 days, after which seizures were induced by maximum electro shock method and the duration of various phases of epileptic attacks were recorded and compared with the control animals. A significant (P<0.01 and P<0.001 reduction in the time taken for righting reflex (recovery was noted in the experimental animals. The levels of biogenic amines such as dopamine, serotonin and nor-adrenaline in the forebrain region were also estimated and a significant level of restoration was opserved in the extract treated animals. Significant results were opserved in the estimated parameters thereby justifying the use of this medicinal plant in the treatment of epilepsy.

Low-Level Color and Texture Feature Extraction of Coral Reef Components

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Ma. Sheila Angeli Marcos

2003-06-01

Full Text Available The purpose of this study is to develop a computer-based classifier that automates coral reef assessmentfrom digitized underwater video. We extract low-level color and texture features from coral images toserve as input to a high-level classifier. Low-level features for color were labeled blue, green, yellow/brown/orange, and gray/white, which are described by the normalized chromaticity histograms of thesemajor colors. The color matching capability of these features was determined through a technique called“Histogram Backprojection”. The low-level texture feature marks a region as coarse or fine dependingon the gray-level variance of the region.

Uniform distributions of glucose oxidation and oxygen extraction in gray matter of normal human brain: No evidence of regional differences of aerobic glycolysis.

Science.gov (United States)

Hyder, Fahmeed; Herman, Peter; Bailey, Christopher J; Møller, Arne; Globinsky, Ronen; Fulbright, Robert K; Rothman, Douglas L; Gjedde, Albert

2016-05-01

Regionally variable rates of aerobic glycolysis in brain networks identified by resting-state functional magnetic resonance imaging (R-fMRI) imply regionally variable adenosine triphosphate (ATP) regeneration. When regional glucose utilization is not matched to oxygen delivery, affected regions have correspondingly variable rates of ATP and lactate production. We tested the extent to which aerobic glycolysis and oxidative phosphorylation power R-fMRI networks by measuring quantitative differences between the oxygen to glucose index (OGI) and the oxygen extraction fraction (OEF) as measured by positron emission tomography (PET) in normal human brain (resting awake, eyes closed). Regionally uniform and correlated OEF and OGI estimates prevailed, with network values that matched the gray matter means, regardless of size, location, and origin. The spatial agreement between oxygen delivery (OEF≈0.4) and glucose oxidation (OGI ≈ 5.3) suggests that no specific regions have preferentially high aerobic glycolysis and low oxidative phosphorylation rates, with globally optimal maximum ATP turnover rates (VATP ≈ 9.4 µmol/g/min), in good agreement with (31)P and (13)C magnetic resonance spectroscopy measurements. These results imply that the intrinsic network activity in healthy human brain powers the entire gray matter with ubiquitously high rates of glucose oxidation. Reports of departures from normal brain-wide homogeny of oxygen extraction fraction and oxygen to glucose index may be due to normalization artefacts from relative PET measurements. © The Author(s) 2016.

Supercritical extraction of pupunha (Guilielma speciosa oil in a fixed bed using carbon dioxide

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Araújo M.E.

2000-01-01

Full Text Available The pupunha (Guilielma speciosa is the fruit of a palm tree typical of the Brazilian Northern region, whose stem is used as a source of heart of palm. The fruit, which is about 65% pulp, is a source of oil and carotenes. In the present work, an analysis of the kinetics of supercritical extraction of oil from the pupunha pulp is presented. Carbon dioxide was used as solvent. The extractions were carried out at 25 MPa and 323 K and 30 MPa and 318 K. The chemical composition of the extracts in terms of fatty acids was determined by gas chromatography. The amount of oleic acid, a saturated fatty acid, in the CO2 extracts was larger than that in the extract obtained with hexane. The overall extraction curves were modeled using the single-parameter model proposed in the literature to describe the desorption of toluene from activated coal.

AUTOMATIC RAILWAY POWER LINE EXTRACTION USING MOBILE LASER SCANNING DATA

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S. Zhang

2016-06-01

Full Text Available Research on power line extraction technology using mobile laser point clouds has important practical significance on railway power lines patrol work. In this paper, we presents a new method for automatic extracting railway power line from MLS (Mobile Laser Scanning data. Firstly, according to the spatial structure characteristics of power-line and trajectory, the significant data is segmented piecewise. Then, use the self-adaptive space region growing method to extract power lines parallel with rails. Finally use PCA (Principal Components Analysis combine with information entropy theory method to judge a section of the power line whether is junction or not and which type of junction it belongs to. The least squares fitting algorithm is introduced to model the power line. An evaluation of the proposed method over a complicated railway point clouds acquired by a RIEGL VMX450 MLS system shows that the proposed method is promising.

A Novel Approach in Text-Independent Speaker Recognition in Noisy Environment

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Nona Heydari Esfahani

2014-10-01

Full Text Available In this paper, robust text-independent speaker recognition is taken into consideration. The proposed method performs on manual silence-removed utterances that are segmented into smaller speech units containing few phones and at least one vowel. The segments are basic units for long-term feature extraction. Sub-band entropy is directly extracted in each segment. A robust vowel detection method is then applied on each segment to separate a high energy vowel that is used as unit for pitch frequency and formant extraction. By applying a clustering technique, extracted short-term features namely MFCC coefficients are combined with long term features. Experiments using MLP classifier show that the average speaker accuracy recognition rate is 97.33% for clean speech and 61.33% in noisy environment for -2db SNR, that shows improvement compared to other conventional methods.

Chemical composition of hydroethanolic extracts from Siparuna guianensis, medicinal plant used as anxiolytics in Amazon region

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Giuseppina Negri

2012-10-01

Full Text Available Siparuna guianensis Aubl., Siparunaceae, is used as anxiolytic plants in folk medicine by South-American indians, "caboclos" and river-dwellers. This work focused the evaluation of phenolic composition of hydroethanolic extract of S. guianensis through HPLC-DAD-ESI/MS/MS. The constituents exhibited protonated, deprotonated and sodiated molecules and the MS/MS fragmentation of protonated, deprotonated and sodiated molecules provided product ions with rich structural information. Vicenin-2 (apigenin-6,8-di-C-glucoside was the main constituent found in S. guianensis together quercetin-3,7-di-O-rhamnoside and kaempferol-3,7di-O-rhamnoside. A commercial extract of Passiflora incarnata (Phytomedicine was used as surrogate standard and also was analyzed through HPLC-DAD-ESI/ MS/MS, showing flavones C-glycosides as constituents, among them, vicenin-2 and vitexin. The main constituent was vitexin. Flavonols triglycosides was also found in low content in S. guianensis and were tentatively characterized as quercetin-3O-rutinoside-7-O-rhamnoside, quercetin-3-O-pentosyl-pentoside-7-O-rhamnoside and kaempferol-3-O-pentosyl-pentoside-7-O-rhamnoside. Apigenin and kaempferol derivatives had been reported as anxiolytic agents. Flavonoids present in this extract were correlated with flavonoids reported as anxiolytics.

Chemical composition of hydroethanolic extracts from Siparuna guianensis, medicinal plant used as anxiolytics in Amazon region

Directory of Open Access Journals (Sweden)

Giuseppina Negri

2012-03-01

Full Text Available Siparuna guianensis Aubl., Siparunaceae, is used as anxiolytic plants in folk medicine by South-American indians, "caboclos" and river-dwellers. This work focused the evaluation of phenolic composition of hydroethanolic extract of S. guianensis through HPLC-DAD-ESI/MS/MS. The constituents exhibited protonated, deprotonated and sodiated molecules and the MS/MS fragmentation of protonated, deprotonated and sodiated molecules provided product ions with rich structural information. Vicenin-2 (apigenin-6,8-di-C-glucoside was the main constituent found in S. guianensis together quercetin-3,7-di-O-rhamnoside and kaempferol-3,7di-O-rhamnoside. A commercial extract of Passiflora incarnata (Phytomedicine was used as surrogate standard and also was analyzed through HPLC-DAD-ESI/ MS/MS, showing flavones C-glycosides as constituents, among them, vicenin-2 and vitexin. The main constituent was vitexin. Flavonols triglycosides was also found in low content in S. guianensis and were tentatively characterized as quercetin-3O-rutinoside-7-O-rhamnoside, quercetin-3-O-pentosyl-pentoside-7-O-rhamnoside and kaempferol-3-O-pentosyl-pentoside-7-O-rhamnoside. Apigenin and kaempferol derivatives had been reported as anxiolytic agents. Flavonoids present in this extract were correlated with flavonoids reported as anxiolytics.

Finding text in color images

Science.gov (United States)

Zhou, Jiangying; Lopresti, Daniel P.; Tasdizen, Tolga

1998-04-01

In this paper, we consider the problem of locating and extracting text from WWW images. A previous algorithm based on color clustering and connected components analysis works well as long as the color of each character is relatively uniform and the typography is fairly simple. It breaks down quickly, however, when these assumptions are violated. In this paper, we describe more robust techniques for dealing with this challenging problem. We present an improved color clustering algorithm that measures similarity based on both RGB and spatial proximity. Layout analysis is also incorporated to handle more complex typography. THese changes significantly enhance the performance of our text detection procedure.

Sivers asymmetry extracted in SIDIS at the hard scales of the Drell–Yan process at COMPASS

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C. Adolph

2017-07-01

Full Text Available Eight proton transverse-spin-dependent azimuthal asymmetries are extracted in four regions of the photon virtuality Q2 from the COMPASS 2010 semi-inclusive hadron measurements in deep inelastic muon–nucleon scattering. These Q2 regions correspond to the four regions of the di-muon mass Q2 used in the ongoing analyses of the COMPASS Drell–Yan measurements, which allows for a future direct comparison of the nucleon transverse-momentum-dependent parton distribution functions extracted from these two alternative measurements. In addition, for the azimuthal asymmetries induced by the Sivers transverse-momentum-dependent parton distribution function various two-dimensional kinematic dependences are presented. The integrated Sivers asymmetries are found to be positive with an accuracy that appears to be sufficient to test the sign change of the Sivers function predicted by Quantum Chromodynamics.

Nonlocal Intracranial Cavity Extraction

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José V. Manjón

2014-01-01

Full Text Available Automatic and accurate methods to estimate normalized regional brain volumes from MRI data are valuable tools which may help to obtain an objective diagnosis and followup of many neurological diseases. To estimate such regional brain volumes, the intracranial cavity volume (ICV is often used for normalization. However, the high variability of brain shape and size due to normal intersubject variability, normal changes occurring over the lifespan, and abnormal changes due to disease makes the ICV estimation problem challenging. In this paper, we present a new approach to perform ICV extraction based on the use of a library of prelabeled brain images to capture the large variability of brain shapes. To this end, an improved nonlocal label fusion scheme based on BEaST technique is proposed to increase the accuracy of the ICV estimation. The proposed method is compared with recent state-of-the-art methods and the results demonstrate an improved performance both in terms of accuracy and reproducibility while maintaining a reduced computational burden.

EXTRACT: interactive extraction of environment metadata and term suggestion for metagenomic sample annotation.

Science.gov (United States)

Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra; Pereira, Emiliano; Schnetzer, Julia; Arvanitidis, Christos; Jensen, Lars Juhl

2016-01-01

The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have therefore developed an interactive annotation tool, EXTRACT, which helps curators identify and extract standard-compliant terms for annotation of metagenomic records and other samples. Behind its web-based user interface, the system combines published methods for named entity recognition of environment, organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed. Database URL: https://extract.hcmr.gr/. © The Author(s) 2016. Published by Oxford University Press.

Source of spill ripple in the RF-KO slow-extraction method with FM and AM

CERN Document Server

Noda, K; Shibuya, S; Muramatsu, M; Uesugi, T; Kanazawa, M; Torikoshi, M; Takada, E; Yamada, S

2002-01-01

The RF-knockout (RF-KO) slow-extraction method with frequency modulation (FM) and amplitude modulation (AM) has brought high-accuracy irradiation to the treatment of a cancer tumor moving with respiration, because of a quick response to beam start/stop. However, a beam spill extracted from a synchrotron ring through RF-KO slow-extraction has a huge ripple with a frequency of around 1 kHz related to the FM. The spill ripple will disturb the lateral dose distribution in the beam scanning methods. Thus, the source of the spill ripple has been investigated through experiments and simulations. There are two tune regions for the extraction process through the RF-KO method: the extraction region and the diffusion region. The particles in the extraction region can be extracted due to amplitude growth through the transverse RF field, only when its frequency matches with the tune in the extraction region. For a large chromaticity, however, the particles in the extraction region can be extracted through the synchrotron ...

Neogeography: The Treasure of User Volunteered Text

NARCIS (Netherlands)

Habib, Mena Badieh

Neogeography is the combination of user generated data and experiences with mapping technologies. This poster presents a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSs. The project intends to

Effect of two different germplasm of Mucuna pruriens seed extracts against some fish pathogens

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M. Marimuthu M

2015-07-01

Full Text Available To investigate the two different germplasm of Mucuna seeds were collected from agro geographical regions was evaluated for its antibacterial activities. Antibacterial activity of the seed extracts was studied against the fish pathogens of Aeromonas hydrophila, Pseudomonas fluorescens, Vibrio cholera and Klebsiella pneumonia using agar well diffusion method. Results showed that methanol and ethanol extracts showed more potent antibacterial activity than other solvent extracts. The results were expressed as mean ± SD. The results obtained in the study shows that velvet bean black seed extract has more antibacterial activity against fish pathogens. The antibacterial activity of all the Mucuna seed extracts are comparable ad their potential as alternative in the treatment of infectious by these microorganisms was present in the fish. Susceptibility testing is conducted on isolates using drug selected on the basis of their importance to human medicine and use I fish production.

A STUDY OF TEXT MINING METHODS, APPLICATIONS,AND TECHNIQUES

OpenAIRE

R. Rajamani*1 & S. Saranya2

2017-01-01

Data mining is used to extract useful information from the large amount of data. It is used to implement and solve different types of research problems. The research related areas in data mining are text mining, web mining, image mining, sequential pattern mining, spatial mining, medical mining, multimedia mining, structure mining and graph mining. Text mining also referred to text of data mining, it is also called knowledge discovery in text (KDT) or knowledge of intelligent text analysis. T...

Antibacterial Activity of Medicinal Aqueous Plant Extracts against Mycobacterium tuberculosis

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Muna Mohammed Buzayan

2012-09-01

Full Text Available Tuberculosis (TB remains a serious health problem in many regions of the world, and the development of resistance to antibiotics by this microbe created the need for new drugs to replace those which have lost effectiveness. This study assesses the medicinal anti-Mycobacterium tuberculosis properties of natural products obtained from plants collected from Eastern Libya. In this study aqueous extracts of nine different plants were assayed for their Mycobacterium tuberculosis inhibitory activity using the BACTEC MGIT960 susceptibility test method. The aqueous extracts of Ceratonia siliqua L, Helichrysum stoechas (L. Moench and Thymus algeriensis did not show any activity against M. tuberculosis in different concentrations. The aqueous extract of Marrubium vulgare L. from Syria showed high activity against M. tuberculosis. Marrubium alysson L., Marrubium vulgare L., Pistacia lentiscus L, Quercus coccifera L, Thymus capitatus (L. Hoffm. & Link, showed varying degrees of activity against M. tuberculosis. The results of this study show that aqueous extracts from six different medicinal plants have different effects against M. tuberculosis in vitro.

Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation

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Peng Shao

2014-08-01

Full Text Available The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.

Studies on in-vitro antioxidant activity of marine edible seaweeds from the east coastal region of Peninsular Malaysia using different extraction methods

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Tam Siow Foon

2013-10-01

Full Text Available Objective: To determine the antioxidant activity of two edible marine seaweeds Eucheuma cottonii and Padina sp.. Methods: The two extraction methods such as conventional and soxhlet extraction were used to isolate the secondary metabolites using methanol as a solvent medium. Total phenolic content of crude seaweeds extract were analysed by standard FC method. The different antioxidant assays DPPH, ferric reducing antioxidant power and β-carotene bleaching assays confirmed the antioxidant activities. Results: DPPH and ferric reducing antioxidant power assays showed the positive correlation with expressed higher total phenolic content in the seaweeds extract. Also β-carotene bleaching assay lower activity compare with BHT as reference control. Additionally IR spectra showed the phenolic related functional groups are present in the solvent extract. The phenolic related compounds are mainly responsible for higher rate of antioxidant activity. Conclusions: The methanolic extracts of Padina sp. showed better radical scavenging and higher phenolic contents than the Eucheuma cottonii. And also the soxhlet extraction showed higher yield and better radical scavenging activity compared to conventional method. Moreover the studies confirmed both seaweeds are an effective candidate for the control the free radical scavenging activity.

A Probabilistic Approach for Breast Boundary Extraction in Mammograms

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Hamed Habibi Aghdam

2013-01-01

Full Text Available The extraction of the breast boundary is crucial to perform further analysis of mammogram. Methods to extract the breast boundary can be classified into two categories: methods based on image processing techniques and those based on models. The former use image transformation techniques such as thresholding, morphological operations, and region growing. In the second category, the boundary is extracted using more advanced techniques, such as the active contour model. The problem with thresholding methods is that it is a hard to automatically find the optimal threshold value by using histogram information. On the other hand, active contour models require defining a starting point close to the actual boundary to be able to successfully extract the boundary. In this paper, we propose a probabilistic approach to address the aforementioned problems. In our approach we use local binary patterns to describe the texture around each pixel. In addition, the smoothness of the boundary is handled by using a new probability model. Experimental results show that the proposed method reaches 38% and 50% improvement with respect to the results obtained by the active contour model and threshold-based methods respectively, and it increases the stability of the boundary extraction process up to 86%.

Linking Video and Text via Representations of Narrative

OpenAIRE

Salway, Andrew; Graham, Mike; Tomadaki, Eleftheria; Xu, Yan

2003-01-01

The ongoing TIWO project is investigating the synthesis of language technologies, like information extraction and corpus-based text analysis, video data modeling and knowledge representation. The aim is to develop a computational account of how video and text can be integrated by representations of narrative in multimedia systems. The multimedia domain is that of film and audio description – an emerging text type that is produced specifically to be informative about the events and objects dep...

Stemming Malay Text and Its Application in Automatic Text Categorization

Science.gov (United States)

Yasukawa, Michiko; Lim, Hui Tian; Yokoo, Hidetoshi

In Malay language, there are no conjugations and declensions and affixes have important grammatical functions. In Malay, the same word may function as a noun, an adjective, an adverb, or, a verb, depending on its position in the sentence. Although extensively simple root words are used in informal conversations, it is essential to use the precise words in formal speech or written texts. In Malay, to make sentences clear, derivative words are used. Derivation is achieved mainly by the use of affixes. There are approximately a hundred possible derivative forms of a root word in written language of the educated Malay. Therefore, the composition of Malay words may be complicated. Although there are several types of stemming algorithms available for text processing in English and some other languages, they cannot be used to overcome the difficulties in Malay word stemming. Stemming is the process of reducing various words to their root forms in order to improve the effectiveness of text processing in information systems. It is essential to avoid both over-stemming and under-stemming errors. We have developed a new Malay stemmer (stemming algorithm) for removing inflectional and derivational affixes. Our stemmer uses a set of affix rules and two types of dictionaries: a root-word dictionary and a derivative-word dictionary. The use of set of rules is aimed at reducing the occurrence of under-stemming errors, while that of the dictionaries is believed to reduce the occurrence of over-stemming errors. We performed an experiment to evaluate the application of our stemmer in text mining software. For the experiment, text data used were actual web pages collected from the World Wide Web to demonstrate the effectiveness of our Malay stemming algorithm. The experimental results showed that our stemmer can effectively increase the precision of the extracted Boolean expressions for text categorization.

CONAN : Text Mining in the Biomedical Domain

NARCIS (Netherlands)

Malik, R.

2006-01-01

This thesis is about Text Mining. Extracting important information from literature. In the last years, the number of biomedical articles and journals is growing exponentially. Scientists might not find the information they want because of the large number of publications. Therefore a system was

The effect of alcoholic extract of Panicum miliaceum L. seed on hippocampus neuronal density in male mouse

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Arezoo Bornarodi

2017-08-01

Full Text Available Background: Hippocampus organization is a part of temporal lobe, which consists of several sections including hippocampal body, dentate gyrus and subiculum. Panicum miliaceum L. contains proteins, vitamins and antioxidants for human health. This study was conducted to examine the effect of the alcoholic extract of the seed of Panicum miliaceum L. plant on hippocampus neuronal density. Materials and Methods: In this experimental study, 24 male mice were divided into 4 groups (n=6, each group. The alcoholic extract of the seed of the Panicum miliaceum L. plant was prepared by soxhlet extraction. Three doses of the extract 25, 50, 75 mg/kg were intraperitoneally injected to 3 treatment groups for 21 days and the control group received normal saline injection. At the end of the experiment, the animals were anesthetized and after perfusion, their brains were removed from the skull. After tissue processing, slices of the brain were prepared and stained. Then, different regions of the hippocampus were photographed and neuronal densities were evaluated. Results: Results showed that the neuronal density in the CA1, CA3 regions of the group treated with 50 mg/kg of the alcoholic extract and in all regions of hippocampus (CA1,CA2,CA3 in groups treated with dose of 75 mg/kg of the alcoholic extract had a significant increase compared to the control group (P<0.05. Conclusion: The present study shows that the alcoholic extract of the seed of Panicum miliaceum L. plant increases neuronal density and induces neurogenesis in the mouse hippocampus.

Regional Business Cycles in East Asia: Synchronization and its Determinants

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Young-Joon Park

2013-06-01

Full Text Available This paper analyzes the dynamics and nature of regional business cycle synchronization for East Asian countries in the period of 2000:Q1-2011:Q4. Estimating a dynamic two-factor model extracts the common factor and the nation- specific factor from both the macroeconomic aggregates and plausible driving forces of regional business cycles. Evidence for regional business cycle synchronization is particularly strong for Korea, Malaysia and the Philippines, while Japan shows weak evidence of regional synchronization. On the other hand, Indonesia, Thailand, Singapore and China are decoupling from regional business cycles. The driver of monetary aggregate is the most significant determinant of regional fluctuations of macroeconomic aggregates, whereas oil price and productivity are on average important driving forces of nation-specific fluctuations of real economic activities.

GRAbB: Selective Assembly of Genomic Regions, a New Niche for Genomic Research.

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Balázs Brankovics

2016-06-01

Full Text Available GRAbB (Genomic Region Assembly by Baiting is a new program that is dedicated to assemble specific genomic regions from NGS data. This approach is especially useful when dealing with multi copy regions, such as mitochondrial genome and the rDNA repeat region, parts of the genome that are often neglected or poorly assembled, although they contain interesting information from phylogenetic or epidemiologic perspectives, but also single copy regions can be assembled. The program is capable of targeting multiple regions within a single run. Furthermore, GRAbB can be used to extract specific loci from NGS data, based on homology, like sequences that are used for barcoding. To make the assembly specific, a known part of the region, such as the sequence of a PCR amplicon or a homologous sequence from a related species must be specified. By assembling only the region of interest, the assembly process is computationally much less demanding and may lead to assemblies of better quality. In this study the different applications and functionalities of the program are demonstrated such as: exhaustive assembly (rDNA region and mitochondrial genome, extracting homologous regions or genes (IGS, RPB1, RPB2 and TEF1a, as well as extracting multiple regions within a single run. The program is also compared with MITObim, which is meant for the exhaustive assembly of a single target based on a similar query sequence. GRAbB is shown to be more efficient than MITObim in terms of speed, memory and disk usage. The other functionalities (handling multiple targets simultaneously and extracting homologous regions of the new program are not matched by other programs. The program is available with explanatory documentation at https://github.com/b-brankovics/grabb. GRAbB has been tested on Ubuntu (12.04 and 14.04, Fedora (23, CentOS (7.1.1503 and Mac OS X (10.7. Furthermore, GRAbB is available as a docker repository: brankovics/grabb (https://hub.docker.com/r/brankovics/grabb/.

tagtog: interactive and text-mining-assisted annotation of gene mentions in PLOS full-text articles.

Science.gov (United States)

Cejuela, Juan Miguel; McQuilton, Peter; Ponting, Laura; Marygold, Steven J; Stefancsik, Raymund; Millburn, Gillian H; Rost, Burkhard

2014-01-01

The breadth and depth of biomedical literature are increasing year upon year. To keep abreast of these increases, FlyBase, a database for Drosophila genomic and genetic information, is constantly exploring new ways to mine the published literature to increase the efficiency and accuracy of manual curation and to automate some aspects, such as triaging and entity extraction. Toward this end, we present the 'tagtog' system, a web-based annotation framework that can be used to mark up biological entities (such as genes) and concepts (such as Gene Ontology terms) in full-text articles. tagtog leverages manual user annotation in combination with automatic machine-learned annotation to provide accurate identification of gene symbols and gene names. As part of the BioCreative IV Interactive Annotation Task, FlyBase has used tagtog to identify and extract mentions of Drosophila melanogaster gene symbols and names in full-text biomedical articles from the PLOS stable of journals. We show here the results of three experiments with different sized corpora and assess gene recognition performance and curation speed. We conclude that tagtog-named entity recognition improves with a larger corpus and that tagtog-assisted curation is quicker than manual curation. DATABASE URL: www.tagtog.net, www.flybase.org.

A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts.

Science.gov (United States)

Westergaard, David; Stærfeldt, Hans-Henrik; Tønsberg, Christian; Jensen, Lars Juhl; Brunak, Søren

2018-02-01

Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has mostly been carried out on collections of abstracts, due to their availability. Here we present an analysis of 15 million English scientific full-text articles published during the period 1823-2016. We describe the development in article length and publication sub-topics during these nearly 250 years. We showcase the potential of text mining by extracting published protein-protein, disease-gene, and protein subcellular associations using a named entity recognition system, and quantitatively report on their accuracy using gold standard benchmark data sets. We subsequently compare the findings to corresponding results obtained on 16.5 million abstracts included in MEDLINE and show that text mining of full-text articles consistently outperforms using abstracts only.

Binary Solvent Extraction System and Extraction Time Effects on Phenolic Antioxidants from Kenaf Seeds (Hibiscus cannabinus L. Extracted by a Pulsed Ultrasonic-Assisted Extraction

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Yu Hua Wong

2014-01-01

Full Text Available The aim of this study was to determine the best parameter for extracting phenolic-enriched kenaf (Hibiscus cannabinus L. seeds by a pulsed ultrasonic-assisted extraction. The antioxidant activities of ultrasonic-assisted kenaf seed extracts (KSE were determined by a 2,2-diphenyl-1-picrylhydrazyl (DPPH radical scavenging capacity assay, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS radical scavenging assay, β-carotene bleaching inhibition assay, and ferric reducing antioxidant power (FRAP assay. Total phenolic content (TPC and total flavonoid content (TFC evaluations were carried out to determine the phenolic and flavonoid contents in KSE. The KSE from the best extraction parameter was then subjected to high performance liquid chromatography (HPLC to quantify the phenolic compounds. The optimised extraction condition employed 80% ethanol for 15 min, with the highest values determined for the DPPH, ABTS, and FRAP assay. KSE contained mainly tannic acid (2302.20 mg/100 g extract and sinapic acid (1198.22 mg/100 g extract, which can be used as alternative antioxidants in the food industry.

Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery

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CAO Yungang

2016-10-01

Full Text Available A novel approach for road centerline extraction from high spatial resolution satellite imagery is proposed by fusing both pixel-based and object-based features. Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps. Then, extracted multiple features are utilized in the fusion framework of Dempster-Shafer evidence theory to roughly identify the road network regions. Finally, an automatic noise removing algorithm combined with the tensor voting strategy is presented to accurately extract the road centerline. Experimental results using high-resolution satellite imageries with different scenes and spatial resolutions showed that the proposed approach compared favorably with the traditional methods, particularly in the aspect of eliminating the salt noise and conglutination phenomenon.

Multimedia Information Extraction

CERN Document Server

Maybury, Mark T

2012-01-01

The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance.  While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and vid

The Amber Industry: Development Сhallenges and Combating Amber Trafficking in the Baltic Region

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Volchetskaya Т. S.

2017-12-01

Full Text Available This article considers the current state and prospective development of the amber industry in the Baltic Sea region. The authors identify the main obstacles to the industry’s development in Russia — poor pricing mechanisms for raw amber, an imbalance between supply and demand, a slow pace of technological modernisation, and a delayed introduction of new technologies and processing techniques. The authors identify gaps in the regulatory framework and highlight problems of legal regulation and law enforcement as regards the amber industry. Combating illegal amber extraction and trafficking is a pressing problem in the Kaliningrad region (Russia and other Baltic region states. The article explores theoretical aspects of the legislative policy on combating illegal amber extraction and trafficking. The authors focus on the relevant law enforcement practices and hold that administrative sanctions for unauthorised amber extraction and trade are not fully effective in Russia. The authors stress the need for introducing criminal liability for a repeated offence and outline opportunities for using forensic gemological examination of amber and amber products.

The continuous inhalation of oxygen-15 for assessing regional oxygen extraction in the brain of man

International Nuclear Information System (INIS)

Jones, T.; Chesler, D.A.; Ter-Pogossian, M.M.

1976-01-01

A non-invasive steady-state method for studying the regional accumulation of oxygen in the brain by continuously inhaling oxygen-15 has been investigated. Oxygen respiration by tissue results in the formation of water of metabolism which may be considered as the 'exhaust product' of respiration. In turn the steady-state distribution of this product may be related to that of oxygen utilization. It has been found in monkeys than an appreciable component of the signal, recorded over the head during the inhalation of 15 O 2 , was attributable to the local production of 15 O-labelled water of metabolism. In man the distribution of radioactivity recorded over the head during 15 O 2 inhalation clearly related to active cerebal tissue. Theoretically the respiration product is linearly dependent on the oxygen extraction ratio of the tissue, and at normal cerebal perfusion it is less sensitive to changes in blood flow. At low rates of perfusion a more linear dependence on flow is shown. The dual dependence on blood flow and oxygen extraction limited the interpretation of the cerebal distribution obtained with this technique. Means for obtaining more definitive measurements with this approach are discussed. (author)

Internal Mammary Arterial Injury from Lead Extraction: A Clinically Subtle yet Important Complication of Implantable Device Removal

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Cesar Cruz

2011-01-01

Full Text Available Percutaneous implantable device extraction has increased in recent years and is associated with small but significant risk. Arteriovenous fistula formation is an uncommon complication of this procedure. We report two cases where lead extraction was complicated by an arteriovenous fistula between the left internal mammary artery and the left brachiocephalic vein. In both cases, the patients were asymptomatic and the presence of a continuous murmur in the left subclavicular region led to the appropriate diagnosis. These were successfully treated with coil embolization. Auscultation around prior extraction sites should be routinely done to aid in the diagnosis of this potentially harmful complication.

Object Extraction in Cluttered Environments via a P300-Based IFCE

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Xiaoqian Mao

2017-01-01

Full Text Available One of the fundamental issues for robot navigation is to extract an object of interest from an image. The biggest challenges for extracting objects of interest are how to use a machine to model the objects in which a human is interested and extract them quickly and reliably under varying illumination conditions. This article develops a novel method for segmenting an object of interest in a cluttered environment by combining a P300-based brain computer interface (BCI and an improved fuzzy color extractor (IFCE. The induced P300 potential identifies the corresponding region of interest and obtains the target of interest for the IFCE. The classification results not only represent the human mind but also deliver the associated seed pixel and fuzzy parameters to extract the specific objects in which the human is interested. Then, the IFCE is used to extract the corresponding objects. The results show that the IFCE delivers better performance than the BP network or the traditional FCE. The use of a P300-based IFCE provides a reliable solution for assisting a computer in identifying an object of interest within images taken under varying illumination intensities.

Source of spill ripple in the RF-KO slow-extraction method with FM and AM

International Nuclear Information System (INIS)

Noda, K.; Furukawa, T.; Shibuya, S.; Muramatsu, M.; Uesugi, T.; Kanazawa, M.; Torikoshi, M.; Takada, E.; Yamada, S.

2002-01-01

The RF-knockout (RF-KO) slow-extraction method with frequency modulation (FM) and amplitude modulation (AM) has brought high-accuracy irradiation to the treatment of a cancer tumor moving with respiration, because of a quick response to beam start/stop. However, a beam spill extracted from a synchrotron ring through RF-KO slow-extraction has a huge ripple with a frequency of around 1 kHz related to the FM. The spill ripple will disturb the lateral dose distribution in the beam scanning methods. Thus, the source of the spill ripple has been investigated through experiments and simulations. There are two tune regions for the extraction process through the RF-KO method: the extraction region and the diffusion region. The particles in the extraction region can be extracted due to amplitude growth through the transverse RF field, only when its frequency matches with the tune in the extraction region. For a large chromaticity, however, the particles in the extraction region can be extracted through the synchrotron oscillation, even when the frequency does not match with the tune in the extraction region. Thus, the spill structure during one period of the FM strongly depends on the horizontal chromaticity. They are repeated with the repetition frequency of the FM, which is the very source of the spill ripple in the RF-KO method

A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts

Science.gov (United States)

Westergaard, David; Stærfeldt, Hans-Henrik

2018-01-01

Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has mostly been carried out on collections of abstracts, due to their availability. Here we present an analysis of 15 million English scientific full-text articles published during the period 1823–2016. We describe the development in article length and publication sub-topics during these nearly 250 years. We showcase the potential of text mining by extracting published protein–protein, disease–gene, and protein subcellular associations using a named entity recognition system, and quantitatively report on their accuracy using gold standard benchmark data sets. We subsequently compare the findings to corresponding results obtained on 16.5 million abstracts included in MEDLINE and show that text mining of full-text articles consistently outperforms using abstracts only. PMID:29447159

Academic Activities Transaction Extraction Based on Deep Belief Network

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Xiangqian Wang

2017-01-01

Full Text Available Extracting information about academic activity transactions from unstructured documents is a key problem in the analysis of academic behaviors of researchers. The academic activities transaction includes five elements: person, activities, objects, attributes, and time phrases. The traditional method of information extraction is to extract shallow text features and then to recognize advanced features from text with supervision. Since the information processing of different levels is completed in steps, the error generated from various steps will be accumulated and affect the accuracy of final results. However, because Deep Belief Network (DBN model has the ability to automatically unsupervise learning of the advanced features from shallow text features, the model is employed to extract the academic activities transaction. In addition, we use character-based feature to describe the raw features of named entities of academic activity, so as to improve the accuracy of named entity recognition. In this paper, the accuracy of the academic activities extraction is compared by using character-based feature vector and word-based feature vector to express the text features, respectively, and with the traditional text information extraction based on Conditional Random Fields. The results show that DBN model is more effective for the extraction of academic activities transaction information.

A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts

DEFF Research Database (Denmark)

Westergaard, David; Stærfeldt, Hans Henrik; Tønsberg, Christian

2018-01-01

Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has mostly been carried out on collections of abstracts, due to their availability. Here we present an analysis of 15...... subcellular associations using a named entity recognition system, and quantitatively report on their accuracy using gold standard benchmark data sets. We subsequently compare the findings to corresponding results obtained on 16.5 million abstracts included in MEDLINE and show that text mining of full...... million English scientific full-text articles published during the period 1823-2016. We describe the development in article length and publication sub-topics during these nearly 250 years. We showcase the potential of text mining by extracting published protein-protein, disease-gene, and protein...

AUTOMATIC SHAPE-BASED TARGET EXTRACTION FOR CLOSE-RANGE PHOTOGRAMMETRY

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X. Guo

2016-06-01

Full Text Available In order to perform precise identification and location of artificial coded targets in natural scenes, a novel design of circle-based coded target and the corresponding coarse-fine extraction algorithm are presented. The designed target separates the target box and coding box totally and owns an advantage of rotation invariance. Based on the original target, templates are prepared by three geometric transformations and are used as the input of shape-based template matching. Finally, region growing and parity check methods are used to extract the coded targets as final results. No human involvement is required except for the preparation of templates and adjustment of thresholds in the beginning, which is conducive to the automation of close-range photogrammetry. The experimental results show that the proposed recognition method for the designed coded target is robust and accurate.

Regional Studies Program. Extraction of North Dakota lignite: environmental and reclamation issues

Energy Technology Data Exchange (ETDEWEB)

LaFevers, J.R.; Johnson, D.O.; Dvorak, A.J.

1976-12-01

This study, sponsored by the U.S. Energy Research and Development Administration, addresses the environmental implications of extraction of coal in North Dakota. These implications are supported by details of the geologic and historical background of the area of focus, the lignite resources in the Fort Union coalfield portion. The particular concentration is on the four-county area of Mercer, Dunn, McLean, and Oliver where substantial coal reserves exist and a potential gasification plant site has been identified. The purposes of this extensive study are to identify the land use and environmental problems and issues associated with extraction; to provide a base of information for assessing the impacts of various levels of extraction; to examine the economics and feasibility of reclamation; and to identify research that needs to be undertaken to evaluate and to improve reclamation practices. The study also includes a description of the physical and chemical soil characteristics and hydrological and climatic factors entailed in extraction, revegetation, and reclamation procedures.

Essential Oils Extracted Using Microwave-Assisted Hydrodistillation from Aerial Parts of Eleven Artemisia Species: Chemical Compositions and Diversities in Different Geographical Regions of Iran

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Majid Mohammadhosseini

2017-03-01

Full Text Available This study aimed to assess the chemical compositions of essential oils (EOs extracted through microwave-assisted hydrodistillation from aerial parts of 11 Artemisia species growing wild in different regions in Northern, Eastern, Western, and Central parts of Iran. The EOs were subsequently analyzed via GC and GC-MS. The percentage yields of the EOs varied over the range of 0.21-0.50 (w/w%. On the basis of these characterizations and spectral assignments, natural compounds including camphor, 1,8-cineole, camphene, α-pinene, β-pinene, β-thujone, and sabinene were the most abundant and frequent constituents among all studied chemical profiles. Accordingly, oxygenated monoterpenes, monoterpene hydrocarbons, and non-terpene hydrocarbons were the dominant groups of natural compounds in the chemical profiles of 13, 4, and 2 samples, respectively. Moreover, five chemotypes were identified using statistical analyses: camphene, α-pinene and β-pinene; 1,8-cineole; camphore and 1,8-cineole; camphore and camphore and β-thujone.

Screening for carbohydrate-binding proteins in extracts of Uruguayan plants

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Plá A.

2003-01-01

Full Text Available The presence of carbohydrate-binding proteins, namely lectins, ß-galactosidases and amylases, was determined in aqueous extracts of plants collected in Uruguay. Twenty-six extracts were prepared from 15 Uruguayan plants belonging to 12 Phanerogam families. Among them, 18 extracts caused hemagglutination (HAG that was inhibited by mono- and disaccharides in 13 cases, indicating the presence of lectins. The other 8 extracts did not cause any HAG with the four systems used to detect HAG activity (rabbit and mouse red cells, trypsin-treated rabbit and mouse red cells. For the extracts prepared from Solanum commersonii, HAG activity and HAG inhibition were similar for those prepared from tubers, leaves and fruits, with the chitocompounds being responsible for all the inhibitions. Purification of the S. commersonii tuber lectin was carried out by affinity chromatography on asialofetuin-Sepharose, and SDS-PAGE under reducing conditions gave a single band of Mr of approximately 80 kDa. The monomer N-acetylglucosamine did not inhibit HAG induced by the purified lectin, but chitobiose inhibited HAG at 24 mM and chitotriose inhibited it at 1 mM. ß-Galactosidase activity was detected in leaves and stems of Cayaponia martiana, and in seeds from Datura ferox. Only traces of amylase activity were detected in some of the extracts analyzed. The present screening increases knowledge about the occurrence of carbohydrate-binding proteins present in regional plants.

Extraction protocols for orthodontic treatment: A retrospective study

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Vaishnevi N Thirunavukkarasu

2016-01-01

Full Text Available Background and Objectives: Various extraction protocols have been followed for successful orthodontic treatment. The purpose of this study was to evaluate the extraction protocols in patients who had previously undergone orthodontic treatment and also who had reported for continuing orthodontic treatment from other clinics. Materials and Methods: One hundred thirty eight patients who registered for orthodontic treatment at the Faculty of Dentistry were divided into 10 extraction protocols based on the Orthodontic treatment protocol given by Janson et al. and were evaluated for statistical significance. Results: The descriptive statistics of the study revealed a total of 40 (29% patients in protocol 1, 43 (31.2% in protocol 2, 18 (13% in protocol 3, 16 (11.6% in protocol 5, and 12 (8.7% in Type 3 category of protocol 9. The Type 3 category in protocol 9 was statistically significant compared to other studies. Midline shift and collapse of the arch form were noticed in these individuals. Conclusion: Extraction of permanent teeth such as canine and lateral incisors without rational reasons could have devastating consequences on the entire occlusion. The percentage of cases wherein extraction of permanent teeth in the crowded region was adopted as a treatment option instead of orthodontic treatment is still prevalent in dental practice. The shortage of orthodontists in Malaysia, the long waiting period, and lack of subjective need for orthodontic treatment at an earlier age group were the reasons for the patient's to choose extraction of the mal-aligned teeth such as the maxillary canine or maxillary lateral incisors.

The text of the Agreement establishing the Asian Regional Co-operative Project on Medical and Biological Applications of Nuclear Techniques

International Nuclear Information System (INIS)

1987-04-01

The full text of the Agreement establishing the Asian Regional Co-operative Project on Medical and Biological Applications of Nuclear Techniques between the Agency and Member States is reproduced. The Agreement entered into force on 20 May 1986 after the Governments of Japan, Bangladesh and the Philippines had notified the Agency of their acceptance of the Agreement

Extraction and Quantitative HPLC Analysis of Coumarin in Hydroalcoholic Extracts of Mikania glomerata Spreng: ("guaco" Leaves

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Celeghini Renata M. S.

2001-01-01

Full Text Available Methods for preparation of hydroalcoholic extracts of "guaco" (Mikania glomerata Spreng. leaves were compared: maceration, maceration under sonication, infusion and supercritical fluid extraction. Evaluation of these methods showed that maceration under sonication had the best results, when considering the ratio extraction yield/extraction time. A high performance liquid chromatography (HPLC procedure for the determination of coumarin in these hydroalcoholic extracts of "guaco" leaves is described. The HPLC method is shown to be sensitive and reproducible.

Chemical and Antimicrobial Profiling of Propolis from Different Regions within Libya.

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Weam Siheri

Full Text Available Extracts from twelve samples of propolis collected from different regions of Libya were tested for their activity against Trypanosoma brucei, Leishmania donovani, Plasmodium falciparum, Crithidia fasciculata and Mycobacterium marinum and the cytotoxicity of the extracts was tested against mammalian cells. All the extracts were active to some degree against all of the protozoa and the mycobacterium, exhibiting a range of EC50 values between 1.65 and 53.6 μg/ml. The toxicity against mammalian cell lines was only moderate; the most active extract against the protozoan species, P2, displayed an IC50 value of 53.2 μg/ml. The extracts were profiled by using liquid chromatography coupled to high resolution mass spectrometry. The data sets were extracted using m/z Mine and the accurate masses of the features extracted were searched against the Dictionary of Natural Products (DNP. A principal component analysis (PCA model was constructed which, in combination with hierarchical cluster analysis (HCA, divided the samples into five groups. The outlying groups had different sets of dominant compounds in the extracts, which could be characterised by their elemental composition. Orthogonal partial least squares (OPLS analysis was used to link the activity of each extract against the different micro-organisms to particular components in the extracts.

Extraction, fatty acid profile and antioxidant activity of sesame extract (Sesamum Indicum L.

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R. H. R. Carvalho

2012-06-01

Full Text Available This article carried out the extraction of sesame oil by using three extraction techniques: supercritical fluid extraction (SFE, Soxhlet and sequential extraction. The SFE was performed using supercritical carbon dioxide (SC-CO2 as solvent and ethanol as cosolvent. Tests were performed at 20 MPa, 35ºC and a flow rate of 2.5 g CO2/min with a total extraction time of 210 minutes. The Soxhlet extraction was performed for 8 hours, using petroleum ether and ethanol as solvents, until the exhaustion of the oil contained in the seeds. The sequential extraction used ethyl ether, ethanol and water as solvents. The Soxhlet extraction was the most effective (58.93%, while the SFE technique obtained 26.47% as the best result. The antioxidant activity (AA was determined by the β-carotene/linoleic acid system, with good oxidation inhibition percentages (29.32-83.49% for all the extracts. The main fatty acids (FA in sesame oil were oleic and linoleic acids.

Regional myocardial extraction of a radioiodinated branched chain fatty acid during right ventricular pressure overload due to acute pulmonary hypertension

International Nuclear Information System (INIS)

Hurford, W.; Lowenstein, E.; Zapol, W.; Barlai-Kovach, M.; Livni, E.; Elmaleh, D.R.; Strauss, H.W.

1985-01-01

To determine whether branched chain fatty acid extraction is reduced during right ventricular (RV) dysfunction due to acute pulmonary artery hypertension, studies were done in 6 anesthetized dogs. Regional branched chain fatty acid extraction was measured by comparing the myocardial uptake of I-125 labeled 15-[p-(iodophenyl)]-3-methylpentadecanoic acid (I-PDA) to myocardial blood flow. Acute pulmonary hypertension was induced by incremental intravenous injection of 100 micron diameter glass beads into six pentobarbital anesthetized, mechanically ventilated dogs. Myocardial blood flow was measured by radiolabeled microspheres both under baseline conditions and during pulmonary hypertension. Mean RV pressure rose from 12 +- 2 (mean +- SEM) to 30 +-3mmHg resulting in a 225 +- 16% increase in RV stroke work. RV ejection fraction, as assessed by gated blood pool scans fell from 39 +- 2 to 18 +- 2%. Left ventricular (LV) pressures, stroke work and ejection fraction were unchanged. Myocardial blood flow increased 132 + 59% in the RV free wall and 67 +- 22% in the RV septum. LV blood flow was unchanged. Despite increased RV work and myocardial blood flow, no differences were noted in the branched chain fatty acid extraction ratios among LV or RV free walls or septum. The authors conclude that early RV dysfunction associated with pulmonary artery hypertension is not due to inadequate myocardial blood flow or branched chain fatty acid extraction

AGRICULTURAL USES OF SEAWEEDS EXTRACTS

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Monica Popescu

2013-12-01

Full Text Available Marine bioactive substances extracted from seaweed are currently used in food, animal feed, as a raw material in the industry and have therapeutic applications. Most of the products based on marine algae are extracted from Brown algae Ascophyllum nodosum. The use of extracts of seaweed in agriculture is beneficial because the amount of chemical fertilizers and obtaining organic yield.

Extraction and Biochemical Characterization of Sulphated Glycosaminoglycans from Chicken Keel Cartilage

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Humaira Majeed Khan1, Muhammad Ashraf2, Abu Saeed Hashmi3, Mansur-ud-Din Ahmad4 and Aftab Ahmad Anjum5

2013-11-01

Full Text Available The present study was conducted to explore the potential and cheaper source of major and abundantly found sulphated glycosaminoglycans (GAGs in chicken keel cartilage. Chicken is comparatively readily accessible to all the communities of Pakistan and its cartilages are the rich source of sulphated GAGs. The GAGs were extracted from prewashed and ground keel cartilages (n=3 of chicken using 3 M MgCl2, dialyzed, digested with papain, precipitated with three volumes of ethanol, and finally lyophilized to dry powder. The dry products were used for proximate analysis (carbohydrates 65.49±0.10, crude protein 12.82±0.26, ash 11.12±.56, moisture 9.88±0.32 and fat 0.69±0.14%. Dimethylmethylene blue binding (DMMB assay was performed to determine the quantity of total GAGs in each group of product and protein contents were estimated by Bradford method. Identification of extracted samples of GAGs was performed with FTIR spectrometer using KBr disc and purity of the samples was determined by SDS-PAGE. Quantity of total GAGs in extracted samples was 70.77±2.27% and estimated amount of protein was 4.64±0.29%. FTIR spectra of standard and samples of CS showed identical and characteristic peaks in finger print region. Finger print region revealed the presence of C-O-S, S=O, -COO, -C-C, R-SO2–R, -CONH2 and R-SO2-NH2 molecules. SDS-PAGE analysis revealed the presence of 77.8 and 50.5 kDa proteins in all extracted samples of GAGs. It can be concluded that chicken keel cartilage is the potential and cheap source of GAGs. Analysis by SDS-PAGE revealed that most of the non-collagen protein can be removed by three volumes of solvent extraction and FTIR is an advance technique for identification of GAGs in mid infrared region (400-4000 cm-1.

Phytochemical investigation and antimicrobial activity of leaves extract of Vernonia auriculifera Hiern.

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Bekele Albejo

2015-12-01

Full Text Available Context: The genus Vernonia is one of the largest groups in the family Compositae constituting more than 500 species distributed widely in tropical and sub-tropical regions of Africa, Asia, and America. Traditionally the genus is used for the treatment of schistosomiasis, amoebic dysentery, gastrointestinal problems, malaria, venereal diseases, wounds, hepatitis, and diabetes. Vernonia auriculifera Hiern is used for healing wounds as ointment around the injured areas. Aims: To investigate the phytochemical constituents and evaluate antimicrobial activity of leaves extract of Vernonia auriculifera Hiern. Methods: Phytochemical screening tests were conducted to identify the class of compounds present in the leaves extracts of V. auriculifera. Silica gel column chromatographic technique was applied to separate the constituents of the extracts. Various spectroscopic techniques (IR, 1H NMR, 13C NMR, DEPT-135, COSY, gHSQC, and gHMBC were applied to determine the structures of isolated compounds. Results: Phytochemical screening of the methanol leaf extract revealed the presence of tannins, flavonoids, terpenoids, saponins and absence of anthraquinones, steroids, and alkaloids. Silica gel column chromatography of the methanol leaves extract yielded one compound. The hexane, chloroform, methanol and water extracts were tested against Staphylococcus aureus. The methanol and water extracts showed promising growth suppression at minimum inhibitory concentration of 200 mg/mL. Conclusions: The polar extracts of the leaves of Vernonia auriculifera Hiern possess antimicrobial activity.

EVALUATION OF THE MICROCLIMATE DURING OLIVE OIL EXTRACTION OPERATIONS INSIDE OLIVE MILLS

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Vittorio Panaro

2007-06-01

Full Text Available Some oil mills, among the most representative in the Puglia Region in terms of quality and productivity have been considered, and the temperature and humidity of the environment and the sensations of temperature felt by the workers were registered inside them during the process of oil extraction. Subsequently, a numerical code in MATLAB language was created, able to calculate the PMV and PPD and a study was carried out of the conditions of global comfort in the environment during the oil extraction process. The results of the surveys carried out in the mills show the importance of microclimate risk analysis in these workplaces, since the instrumental surveys and the calculations have shown that climatic conditions are not comfortable in the olive storage bays. On the other hand, the data from the oil extraction areas shows an acceptable condition of thermal well-being.

Image segmentation-based robust feature extraction for color image watermarking

Science.gov (United States)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Supercritical CO2 extraction of raw propolis and its dry ethanolic extract

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L. C. Paviani

2012-06-01

Full Text Available Three types of propolis extract were prepared and analyzed with respect to their global extraction yields and with respect to the concentration of the following markers: 3,5-diprenyl-4-hydroxycinnamic acid; 3-prenyl-4-hydroxycinnamic acid; 4-hydroxycinnamic acid and 4-methoxy-3,5,7-trihydroxyflavone. The extract EEP (ethanolic extract of propolis was obtained by the conventional method from raw propolis using ethanol as solvent. The extracts (SFE were obtained by supercritical solvent extraction from the raw propolis using supercritical carbon dioxide (sc-CO2, with and without the addition of ethanol as a co-solvent. The fractionated supercritical extracts (FSCE were obtained by fractionation (extract and raffinate of the dry EEP with sc-CO2. EEP yields of 39.5% were obtained and maximum global extraction yields were 7.3% for SFE with no co-solvent, 51% for SFE with 15% ethanol and 18% for the FSCE extract fraction. The concentrations of the markers in the different extracts differed as a function of the operational parameters, indicating that the addition of co-solvent and the selectivity of sc-CO2 could be manipulated so as to obtain extracts with the yields and concentrations of interest.

A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features

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LEI Xiaoqi

2016-02-01

Full Text Available Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds(semi-automatic extraction,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features,is proposed in this paper.Firstly,the image is segmented,and then the linear and curve roads are obtained by using several object shape features,so the method that just only extract linear roads are rectified.Secondly,the step of road extraction is carried out based on the region growth,the road seeds are automatic selected and the road network is extracted.Finally,the extracted roads are regulated by combining the edge information.In experiments,the images that including the better gray uniform of road and the worse illuminated of road surface were chosen,and the results prove that the method of this study is promising.

Extraction and characterization of galactomannan extracted from Prosopis juliflora seeds

International Nuclear Information System (INIS)

Rodrigues, Delane da C.; Cunha, Arcelina P.; Oliveira, Williara Q. de; Gallao, Maria Izabel; Azeredo, Henriette M. C de

2015-01-01

Different seeds are rich in polysaccharides, which are widely used in research and in industry. The objective was to extract galactomannan from mesquite seeds (Prosopis juliflora) and evaluate their chemical properties for future application in edible films. To test the feasibility of using the polysaccharide, the yield was obtained and the material analyzed by Thermal Analysis (TGA-Thermogravimetric Analysis and Calorimetry Differential Scanning-DSC), Spectroscopy Infrared Region Fourier Transform (FTIR) and Nuclear Magnetic Resonance (NMR). According to the results, the galactomannan was equivalent with the polysaccharides extracted from other sources except for the low yield (6.6%). (author)

In situ genomic DNA extraction for PCR analysis of regions of interest in four plant species and one filamentous fungi