Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Tokamak TCABR: Acquisition system, data analysis, and remote participation using MDSplus

Each plasma physics laboratory has a proprietary scheme to control and data acquisition system. Usually, it is different from one laboratory to another. It means that each laboratory has its own way to control the experiment and retrieving data from the database. Fusion research relies to a great extent on international collaboration and this private system makes it difficult to follow the work remotely. The TCABR data analysis and acquisition system has been upgraded to support a joint research programme using remote participation technologies. The choice of MDSplus (Model Driven System plus) is proved by the fact that it is widely utilized, and the scientists from different institutions may use the same system in different experiments in different tokamaks without the need to know how each system treats its acquisition system and data analysis. Another important point is the fact that the MDSplus has a library system that allows communication between different types of language (JAVA, Fortran, C, C++, Python) and programs such as MATLAB, IDL, OCTAVE. In the case of tokamak TCABR interfaces (object of this paper) between the system already in use and MDSplus were developed, instead of using the MDSplus at all stages, from the control, and data acquisition to the data analysis. This was done in the way to preserve a complex system already in operation and otherwise it would take a long time to migrate. This implementation also allows add new components using the MDSplus fully at all stages. (c) 2012 Elsevier B.V. All rights reserved.

Investigation of auditory processing disorder and language impairment using the speech-evoked auditory brainstem response

This study investigated whether there are differences in the Speech-Evoked Auditory Brainstem Response among children with Typical Development (TD), (Central) Auditory Processing Disorder (C) APD, and Language Impairment (LI). The speech-evoked Auditory Brainstem Response was tested in 57 children (ages 6-12). The children were placed into three groups: TD (n = 18), (C)APD (n = 18) and LI (n = 21). Speech-evoked ABR were elicited using the five-formant syllable/da/. Three dimensions were defined for analysis, including timing, harmonics, and pitch. A comparative analysis of the responses between the typical development children and children with (C)APD and LI revealed abnormal encoding of the speech acoustic features that are characteristics of speech perception in children with (C)APD and LI, although the two groups differed in their abnormalities. While the children with (C)APD might had a greater difficulty distinguishing stimuli based on timing cues, the children with LI had the additional difficulty of distinguishing speech harmonics, which are important to the identification of speech sounds. These data suggested that an inefficient representation of crucial components of speech sounds may contribute to the difficulties with language processing found in children with LI. Furthermore, these findings may indicate that the neural processes mediated by the auditory brainstem differ among children with auditory processing and speech-language disorders. (C) 2012 Elsevier B.V. All rights reserved.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

Polymorphous low-grade adenocarcinoma: an analysis of epidemiological studies and hints for pathologists

Abstract Background This study is an analysis of the prevalence of polymorphous low grade adenocarcinoma (PLGA) in epidemiological surveys of salivary tumors published in the English language from 1992 to 2012. Methods These surveys included studies from different researchers, countries and continents. The 57 surveys for which it was possible to calculate the percentage of PLGAs among all malignant minor salivary gland tumors (MMSGT) were included in this review. Results The statistical analyses show significant differences in the PLGA percentage by time period, country and continent in the studies included in this review. The percentage of PLGAs among MMSGTs varied among the studies, ranging from 0.0% to 46.8%. PLGA rates have varied over the period studied and have most recently increased. The frequency of reported PLGA cases also varied from 0.0% to 24.8% by the country in which the MMSGT studies were performed. The PLGA percentages also varied significantly by continent, with frequencies ranging from 3.9% in Asia to 20.0% in Oceania Conclusion Based on these results, we concluded that although the accuracy of PLGA diagnoses has improved, they remain a challenge for pathologists. To facilitate PLGA diagnoses, we have therefore made some suggestions for pathologists regarding tumors composed of single-layer strands of cells that form all of the histological patterns present in the tumor, consistency of the cytological appearance and uniformly positive CK7, vimentin and S100 immunohistochemistry, which indicate a single PLGA phenotype. Virtual slide The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1059098656858324