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Krasnoarmeyskaya, Russia

The study retrospectively investigated the percolation characteristics of the perinatal period and during the first year of study at school - especially physical development of 919 first-formers from 17 schools in the city of Kirov. It has been established that the perinatal period pathology exerted different influence on the components of physical development of the children. Late preeclampsia in the history had no effect on anthropometric indices at birth and at the age 1 year, but reduced them at the age 7-8 years. Anemia and placental insufficiency in anamnesis influenced the anthropometric parameters at birth, but was not manifested at the age 1 year and 7-8 years. The value of the circumference of the chest and the Rohrer index, the value of vital capacity, speed of growth processes and harmonious physical development were most vulnerable to the pathologies of the perinatal period and continued up to the age 7-8 years. Among the studied pathologies, late gestosis (reduced anthropometric parameters and affects on the cardiovascular system) and fetoplacental insufficiency (reduced rate of growth processes and harmonious physical development) exerted the most negative influence at the age 7-8 years.

Korotaeva K.N.,Vyatka State Humanities University | Tsirkin V.I.,Kirov State Medical Academy | Vyaznikov V.A.,Kirov Regional Clinical Hospital
Bulletin of Experimental Biology and Medicine | Year: 2012

Experiments on myocardial strips isolated from the right auricular myocardium of patients with heart failure showed that tyrosine, histidine, and tryptophan increased the amplitude of electrically stimulated contractions. The nature of this effect and clinical implications are discussed. © 2012 Springer Science+Business Media, Inc.

Blinov P.D.,Vyatka State Humanities University | Kotelnikov E.V.,Vyatka State Humanities University
Komp'juternaja Lingvistika i Intellektual'nye Tehnologii | Year: 2015

The paper investigates the problem of automatic aspect-based sentiment analysis. Such version is harder to do than general sentiment analysis, but it significantly pushes forward the limits of unstructured text analysis methods. In the beginning previous approaches and works are reviewed. That part also gives data description for train and test collections. In the second part of the article the methods for main subtasks of aspectbased sentiment analysis are described. The method for explicit aspect term extraction relies on the vector space of distributed representations of words. The term polarity detection method is based on use of pointwise mutual information and semantic similarity measure. Results from SentiRuEval workshop for automobiles and restaurants domains are given. Proposed methods achieved good results in several key subtasks. In aspect term polarity detection task and sentiment analysis of whole review on aspect categories methods showed the best result for both domains. In the aspect term categorization task our method was placed at the second position. And for explicit aspect term extraction the first result obtained for the restaurant domain according to partial match evaluation criteria.

Blinov P.D.,Vyatka State Humanities University | Kotelnikov E.V.,Vyatka State Humanities University
Komp'juternaja Lingvistika i Intellektual'nye Tehnologii | Year: 2014

The article is focused on aspect-based sentiment analysis, which is a specific version of the general sentiment analysis task. Its goal is to detect the opinions expressed in the text on the level of significant aspects of the specified entity. An overview of the existing approaches and previous work is presented. The main result of our work is a new method of aspect-based sentiment analysis based on the distributed representations of words. Such representations are obtained by using deep learning algorithms. The method includes the well-known algorithm of training distributed representations of words, two new techniques for constructing the aspect and sentiment lexicons, and an algorithm for calculating aspect scores. Examples of aspect and sentiment terms are given. The vectors of resulting terms are visualized using the t-SNE method. The article presents the results of experiments on a test corpus for three aspects-"food", "interior" and "service", which yield aF1-measure increase of 11 to 16% as compared to the baseline.

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