Semantic information extraction from images of complex documents

Even though the digital processing of documents is increasingly widespread in industry, printed documents are still largely in use. In order to process electronically the contents of printed documents, information must be extracted from digital images of documents. When dealing with complex documents, in which the contents of different regions and fields can be highly heterogeneous with respect to layout, printing quality and the utilization of fonts and typing standards, the reconstruction of the contents of documents from digital images can be a difficult problem. In the present article we present an efficient solution for this problem, in which the semantic contents of fields in a complex document are extracted from a digital image.

Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Expression of the P2X(2) receptor in different classes of ileum myenteric neurons in the female obese ob/ob mouse

AIM: To examine whether the ob/ob mouse model of obesity is accompanied by enteric nervous system abnormalities such as altered motility. METHODS: The study examined the distribution of the P2X(2) receptor (P2X(2)R) in myenteric neurons of female ob/ob mice. Specifically, we used immunohistochemistry to analyze the co-expression of the P2X(2)R with neuronal nitric oxide synthase (nNOS), choline acetyltransferase (ChAT), and calretinin (CalR) in neurons of the small intestine myenteric plexus in ob/ob and control female mice. In these sections, we used scanning confocal microscopy to analyze the co-localization of these markers as well as the neuronal density (cm(2)) and area profile (mu m(2)) of P2X(2)R-positive neurons. In addition, enteric neurons were labeled using the nicotinamide adenine dinucleotide (NADH) diaphorase method and analyzed with light microscopy as an alternate means by which to analyze neuronal density and area. RESULTS: In the present study, we observed a 29.6% increase in the body weight of the ob/ob animals (OG) compared to the control group (CG). In addition, the average small intestine area was increased by approximately 29.6% in the OG compared to the CG. Immunoreactivity (IR) for the P2X(2)R, nNOS, ChAT and CaIR was detectable in the myenteric plexus, as well as in the smooth muscle, in both groups. This IR appeared to be mainly cytoplasmic and was also associated with the cell membrane of the myenteric plexus neurons, where it outlined the neuronal cell bodies and their processes. P2X(2)R-IR was observed to co-localize 100% with that for nNOS, ChAT and CaIR in neurons of both groups. In the ob/ob group, however, we observed that the neuronal density (neuron/cm(2)) of P2X(2)R-IR cells was increased by 62% compared to CG, while that of NOS-IR and ChAT-IR neurons was reduced by 49% and 57%, respectively, compared to control mice. The neuronal density of CaIR-IR neurons was not different between the groups. Morphometric studies further demonstrated that the cell body profile area (mu m(2)) of nNOS-IR, ChAT-IR and CaIR-IR neurons was increased by 34%, 20% and 55%, respectively, in the OG compared to controls. Staining for NADH diaphorase activity is widely used to detect alterations in the enteric nervous system; however, our qualitative examination of NADH-diaphorase positive neurons in the nnyenteric ganglia revealed an overall similarity between the two groups. CONCLUSION: We demonstrate increases in P2X(2)R expression and alterations in nNOS, ChAT and CaIR IR in ileal myenteric neurons of female ob/ob mice compared to wild-type controls. (c) 2012 Baishideng. All rights reserved.

A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation

The Neotropical evaniid genus Evaniscus Szepligeti currently includes six species. Two new species are described, Evaniscus lansdownei Mullins, sp. n. from Colombia and Brazil and E. rafaeli Kawada, sp. n. from Brazil. Evaniscus sulcigenis Roman, syn. n., is synonymized under E. rufithorax Enderlein. An identification key to species of Evaniscus is provided. Thirty-five parsimony informative morphological characters are analyzed for six ingroup and four outgroup taxa. A topology resulting in a monophyletic Evaniscus is presented with E. tibialis and E. rafaeli as sister to the remaining Evaniscus species. The Hymenoptera Anatomy Ontology and other relevant biomedical ontologies are employed to create semantic phenotype statements in Entity-Quality (EQ) format for species descriptions. This approach is an early effort to formalize species descriptions and to make descriptive data available to other domains.

Semantic Dementia Versus Nonfluent Progressive Aphasia Neuropsychological Characterization and Differentiation

Background: Early progressive nonfluent aphasia (PNFA) may be difficult to differentiate from semantic dementia (SD) in a nonspecialist setting. There are descriptions of the clinical and neuropsychological profiles of patients with PNFA and SD but few systematic comparisons. Method: We compared the performance of groups with SD (n = 27) and PNFA (n = 16) with comparable ages, education, disease duration, and severity of dementia as measured by the Clinical Dementia Rating Scale on a comprehensive neuropsychological battery. Principal components analysis and intergroup comparisons were used. Results: A 5-factor solution accounted for 78.4% of the total variance with good separation of neuropsychological variables. As expected, both groups were anomic with preserved visuospatial function and mental speed. Patients with SD had lower scores on comprehension-based semantic tests and better performance on verbal working memory and phonological processing tasks. The opposite pattern was found in the PNFA group. Conclusions: Neuropsychological tests that examine verbal and nonverbal semantic associations, verbal working memory, and phonological processing are the most helpful for distinguishing between PNFA and SD.

Semantic Equivalence of the Brazilian Portuguese version of the "Body Change Inventory"

With the increase in research on the components of Body Image, validated instruments are needed to evaluate its dimensions. The Body Change Inventory (BCI) assesses strategies used to alter body size among adolescents. The scope of this study was to describe the translation and evaluation for semantic equivalence of the BCI in the Portuguese language. The process involved the steps of (1) translation of the questionnaire to the Portuguese language; (2) back-translation to English; (3) evaluation of semantic equivalence; and (4) assessment of comprehension by professional experts and the target population. The six subscales of the instrument were translated into the Portuguese language. Language adaptations were made to render the instrument suitable for the Brazilian reality. The questions were interpreted as easily understandable by both experts and young people. The Body Change Inventory has been translated and adapted into Portuguese. Evaluation of the operational, measurement and functional equivalence are still needed.

Local inflammatory events induced by Bothrops atrox snake venom and the release of distinct classes of inflammatory mediators

Bothrops atrox is responsible for most accidents involving snakes in the Brazilian Amazon and its venom induces serious systemic and local effects. The local effects are not neutralized effectively by commercial antivenoms, resulting in serious sequelae in individuals bitten by this species. This study investigates the local inflammatory events induced in mice by B. atrox venom (Bay), such as vascular permeability, leukocyte influx and the release of important inflammatory mediators such as cytokines, eicosanoids and the chemokine CCL-2, at the injection site. The effect of Bay on cyclooxygenase (COX-1 and COX-2) expression was also investigated. The results showed that intraperitoneal (i.p.) injection of BaV promoted a rapid and significant increase in vascular permeability, which reached a peak 1 h after venom administration. Furthermore, BaV caused leukocyte infiltration into the peritoneal cavity between 1 and 8 h after i.p. injection, with mononuclear leukocytes (MNs) predominating in the first 4 h, and polymorphonuclear leukocytes (PMNs) in the last 4 h. Increased protein expression of COX-2, but not of COX-1, was detected in leukocytes recruited in the first and fourth hours after injection of BaV. The venom caused the release of eicosanoids PGD(2), PGE(2), TXA(2) and LTB4, cytokines TNF-alpha, IL-6, IL-10 and IL-12p70, but not IFN-gamma, and chemokine CCL-2 at different times. The results show that Bay is able to induce an early increase in vascular permeability and a leukocyte influx to the injection site consisting mainly of MNs initially and PMNs during the later stages. These phenomena are associated with the production of cytokines, the chemokine CCL-2 and eicosanoids derived from COX-1 and COX-2. (c) 2012 Elsevier Ltd. All rights reserved.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Molecular Characterization and Physical Mapping of Two Classes of 5S rDNA in the Genomes of Gymnotus sylvius and G. inaequilabiatus (Gymnotiformes, Gymnotidae)

The nucleotide sequences of the 5S rRNA multigene family and their distribution across the karyotypes in 2 species of Gymnotiformes, genus Gymnotus (G. sylvius and G. inaequilabiatus) were investigated by means of fluorescence in situ hybridization (FISH). The results showed the existence of 2 distinct classes of 5S rDNA sequences in both species: class I and class II. A high conservative pattern of the codifying region of the 5S rRNA gene was identified, contrasting with significant alterations detected in the nontranscribed spacer (NTS). The presence of TATA-like sequences along the NTS of both species was an expected occurrence, since such sequences have been associated with the regulation of the gene expression. FISH using 5S rDNA class I and class II probes revealed that both gene classes were collocated in the same chromosome pair in the genome of G. sylvius, while in that of G. inaequilabiatus, class II appeared more disperse than class I. Copyright (C) 2012 S. Karger AG, Basel

Sleep length, working hours and socio-demographic variables are associated with time attending evening classes among working college students

It is the aim of the present study to assess factors associated with time spent in class among working college students. Eighty-two working students from 21 to 26 years old participated in this study. They were enrolled in an evening course of the University of Sao Paulo, Brazil. Participants answered a questionnaire on living and working conditions. During seven consecutive days, they wore an actigraph, filled out daily activity diaries (including time spent in classes) and the Karolinska Sleepiness Scale every three hours from waking until bedtime. Linear regression analyses were performed in order to assess the variables associated with time spent in classes. The results showed that gender, sleep length, excessive sleepiness, alcoholic beverage consumption (during workdays) and working hours were associated factors with time spent in class. Thus, those who spent less time in class were males, slept longer hours, reported excessive sleepiness on Saturdays, worked longer hours, and reported alcohol consumption. The combined effects of long work hours (>40 h/week) and reduced sleep length may affect lifestyles and academic performance. Future studies should aim to look at adverse health effects induced by reduced sleep duration, even among working students who spent more time attending evening classes.

Lexical-semantic processing in the semantic priming paradigm in aphasic patients

There is evidence that the explicit lexical-semantic processing deficits which characterize aphasia may be observed in the absence of implicit semantic impairment. The aim of this article was to critically review the international literature on lexical-semantic processing in aphasia, as tested through the semantic priming paradigm. Specifically, this review focused on aphasia and lexical-semantic processing, the methodological strengths and weaknesses of the semantic paradigms used, and recent evidence from neuroimaging studies on lexical-semantic processing. Furthermore, evidence on dissociations between implicit and explicit lexical-semantic processing reported in the literature will be discussed and interpreted by referring to functional neuroimaging evidence from healthy populations. There is evidence that semantic priming effects can be found both in fluent and in non-fluent aphasias, and that these effects are related to an extensive network which includes the temporal lobe, the pre-frontal cortex, the left frontal gyrus, the left temporal gyrus and the cingulated cortex.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.