Linguistic creativity and discourse profiles of English language children’s novels

Contemporary discourse studies face the necessity to develop the methods of contrastive sub-discourse analysis which apply numeric and comparable data to diversify and describe sub-discourse types. The aim of the research is to propose a method of discourse profiling serving the purpose, and to further test the method in the contrastive study of linguistic creativity in different types of English language childrens novels. The category of linguistic creativity being the leading form of language poesis receives parametric description on all language representation levels (in written form) and provides the discourse values for contrastive analysis. These values are explored in the fragments of non-autobiographic and autobiographic adventure novel sub-discourse types authored by J.C. George, F. Gibson, J.D. Ullman, and G. Durrell (a total amount of 120.000 signs) annotated manually for 52 linguistic creativity parameters on phonological, morphological, word-formation, lexical, syntactic, and graphic levels. The working hypothesis is that the linguistic creativity parametric activity distributions represent the sub-discourse profiles and may serve to contrast sub-discourse types by means of their vectors contingency values. The analysis in individual parameter activity and in parameter groups activity demonstrated significant variance in sub-discourse construal, with autobiographic sub-discourse of G. Durrell manifesting several higher activity values in word-formation (occasional compounding), lexical use (the use of professional language, lexical tropes, allusive names, higher register style) and syntactic use (the use of parallel structures and syntactic intensifiers). In terms of morphological activity, the parameter values tend to be lower (morphological category shifts), the same stands true of some syntactic (the use of elliptical structures) and lexical parameters (the use of lower register types and proper names). The sub-discourse profiles demonstrate several common features, evidently typical of the discourse type itself, and the features differentiating non-autobiographic and autobiographic discourse subtypes. Vector correlation analysis revealed lower correlation values for autobiographic sub-discourse, which proves its specificity and testifies to the discourse profiling method applicability.

Detecting (non)parallel evolution in multidimensional spaces: angles, correlations, and eigenanalysis

Parallelism between evolutionary trajectories in a trait space is often seen as evidence for repeatability of phenotypic evolution, and angles between trajectories play a pivotal role in the analysis of parallelism. However, many biologists have been ignorant on properties of angles in multidimensional spaces, and unsound uses of angles are common in the biological literature. To remedy this situation, this study provides a brief overview on geometric and statistical aspects of angles in multidimensional spaces. Under the null hypothesis that trajectory vectors have no preferred directions, the angle between two independent vectors is concentrated around the right angle, with a more pronounced peak in a higher-dimensional space. This probability distribution is closely related to t- and beta distributions, which can be used for testing the null hypothesis concerning a pair of trajectories. A recently proposed method with eigenanalysis of a vector correlation matrix essentially boils down to the test of no correlation or concentration of multiple vectors, for which a simple test procedure is available in the statistical literature. Concentration of vectors can also be examined by tools of directional statistics such as the Rayleigh test. These frameworks provide biologists with baselines to make statistically justified inferences for (non)parallel evolution.

New Extended Quantitative Local and Global Regularity Index for Single- and Multiframe RC Bridges Based on Modal Vector Correlation

Seismic demand and performance of bridges are highly dependent upon the level of irregularity. Although previous studies have proposed methodologies so as to quantify the irregularity of the bridges in terms of global regularity index, it still remains unclear how to determine the distribution of irregularity along a bridge, as well as to discover the irregularity sources. This research project is intended to develop a quantitative vector regularity criterion for single- and multiframe bridges based on the modified correlation function for spatial locations of scaled mode shapes of deck-alone and whole bridge. The proposed criterion calculates two types of regularity indices, namely, local (LRI) and global regularity indices (GRI). The GRI is a scalar value representing the overall regularity of the entire bridge, whereas the LRI highlights vector irregularity distribution along the bridge. Since the deck discontinuity due to the in-span hinges is one of the leading causes for irregularity, the proposed index has been employed in case of multiframe bridges as well. Furthermore, the current study aims to investigate the correlation between the proposed irregularity indicators and the nonlinear to linear demand ratio. Therefore, the appropriate analysis method can be chosen based on irregularity extent of bridges. Obtained results of the proposed indices reveal that in-span hinge is one of the main parameters affecting the distribution of local irregularity along a bridge. Therefore, multiframe bridges need to be investigated in detail so as to validate the special design requirements recommended by design codes.

QCD factorization for twist-three axial-vector parton quasidistributions

The transverse component of the axial-vector correlation function of quark fields is a natural starting object for lattice calculations of twist-3 nucleon parton distribution functions. In this work we derive the corresponding factorization expression in terms of twist-2 and twist-3 collinear distributions to one-loop accuracy. The results are presented both in position space, as the factorization theorem for Ioffe-time distributions, and in momentum space, for the axial-vector quasi- and pseudodistributions.

Cerebral hemispheres – cerebellum – kidney interaction in patients with acute cerebral ischemia

The nervous system, in particular the autonomic one, is well known to constantly regulate the internal functioning of the body, adapting it to changeable external and internal environmental parameters. In particular, there is a close multiple-vector correlation between the nervous system and the kidneys. The aim of this study was to specify the mechanisms, clinical and paraclinical characteristics of the concomitant lesions of the nervous system and the kidneys in patients with acute stroke. This paper presents the case report of 215 patients, aged 70 ± 8.44, who suffered from ischemic stroke. Among them, we examined 144 women and 71 men. The patients underwent a comprehensive examination, including a detailed clinical and neurological check-up (evaluating the patients’ condition severity with the National Institutes of Health Stroke Scale (NIHSS) and the Barthel index on admission and on the 21st day of the disease), laboratory analysis (electrolyte balance, nitrogen metabolism (on admission and on the 21st day of the disease) and instrumental examination (CT scan of the brain, the follow-up brain magnetic resonance imaging). The statistical methods were used to analyze the data. In the 1st day of the disease, all the surveyed patients with right hemispheric carotid stroke and the overwhelming majority of the patients with left hemispheric carotid stroke and ischemic stroke in the vertebrobasilar system had cerebral renal syndrome, represented by renal concentration-filtration dysfunction, accompanied by the reduced glomerular filtration rate. A reliable relationship was found between the renal concentration and filtration function and the right hemispheric ischemic focus in patients with ischemic stroke, the characteristics are to be specified.

A general index for linear and nonlinear correlations for high dimensional genomic data

Background With the advance of high throughput sequencing, high-dimensional data are generated. Detecting dependence/correlation between these datasets is becoming one of most important issues in multi-dimensional data integration and co-expression network construction. RNA-sequencing data is widely used to construct gene regulatory networks. Such networks could be more accurate when methylation data, copy number aberration data and other types of data are introduced. Consequently, a general index for detecting relationships between high-dimensional data is indispensable. Results We proposed a Kernel-Based RV-coefficient, named KBRV, for testing both linear and nonlinear correlation between two matrices by introducing kernel functions into RV2 (the modified RV-coefficient). Permutation test and other validation methods were used on simulated data to test the significance and rationality of KBRV. In order to demonstrate the advantages of KBRV in constructing gene regulatory networks, we applied this index on real datasets (ovarian cancer datasets and exon-level RNA-Seq data in human myeloid differentiation) to illustrate its superiority over vector correlation. Conclusions We concluded that KBRV is an efficient index for detecting both linear and nonlinear relationships in high dimensional data. The correlation method for high dimensional data has possible applications in the construction of gene regulatory network.

Potential of Using Phase Correlation in Distributed Scatterer InSAR Applied to Built Scenarios

The improved spatial resolution of Synthetic Aperture Radar (SAR) images from newly launched sensors has promoted a more frequent use of distributed scatterer (DS) interferometry (DSI) in urban monitoring, pursuing sufficient and detailed measurements. However, the commonly used statistical methods for homogeneous pixel clustering by exploring amplitude information are firstly, computationally intensive; furthermore, their necessity when applied to high-coherent built scenarios is little discussed in the literature. This paper explores the potential of using phase information for the detection of homogeneous pixels on built surfaces. We propose a simple phase-correlated pixel (PCP) clustering and introduce a coherence-weighted phase link (WPL), i.e., PCPWPL, to pursue a faster processing of interferogram phase denoising. Rather than relying on the statistical tests of amplitude characteristics, we exploit vector correlation in the complex domain to identify PCPs with similar phase observations, thus, avoiding the intensive hypothesis test. A coherence-weighted phase linking is applied for DS phase reconstruction. The estimation of geophysical parameters, e.g., deformation, is completed using an integrated network of persistent scatterers (PS) and DS. Efficiency of the proposed method is fairly illustrated by both synthetic and real data experiments. Pros and cons of the proposed PCPWPL were analyzed with the comparison to a conventional amplitude-based strategy using an X-band CosmoSkyMed dataset. It is demonstrated that the use of phase correlation is sufficient for DS monitoring in built scenarios, with equivalent measurement quantity and cheaper computational cost.