Использование машиннообучаемых потенциалов межатомного взаимодействия для изучения свойств кристаллических структур

In the process of modeling multilayer semiconductor nanostructures, it is important to quickly obtain accurate values the characteristics of the structure under consideration. One of these characteristics is the value of the interaction energy of atoms within the structure. The energy value is also important for obtaining other quantities, such as bulk modulus of the structure, shear modulus etc. The paper considers a machine learning based method for obtaining the interaction energy of two atoms. A model built on the basis of the Gaussian Approximation Potential (GAP) is trained on a previously prepared sample and allows predicting the energy values of atom pairs for test data. The values of the coordinates of the interacting atoms, the distance between the atoms, the value of the lattice constant of the structure, an indication of the type of interacting atoms, and also the value describing the environment of the atoms were used as features. The coordinates of the atoms, the distance between the atoms, the lattice constant of the structure, an indication of the type of interacting atoms, the value describing the environment of the atoms were used as features. The computational experiment was carried out with structures of Si, Ge and C. There were estimated the rate of obtaining the energy of interacting atoms and the accuracy of the obtained value. The characteristics of speed and accuracy were compared with the characteristics that were achieved using the many-particle interatomic potential — the Tersoff potential.В процессе моделирования многослойных полупроводниковых наноструктур существенную роль играет быстрое получение точных значений характеристик рассматриваемой структуры. Одной из таких характеристик является значение энергии взаимодействия атомов внутри структуры. Значение энергии важно для получения и других величин, таких как объемный модуль упругости структуры, модуль сдвига и др. В работе рассматриваются способ получения энергии взаимодействия двух атомов, основанный на методах машинного обучения. Модель, построенная на основе машиннообучаемого потенциала GAP (Gaussian Approximation Potential), обучается на заранее подготовленной выборке и позволяет предсказать значения энергии пар атомов для тестовых данных. В качестве признаков использовались значения координат взаимодействующих атомов, расстояние между атомами, значение постоянной решетки структуры, указание на тип взаимодействующих атомов, а также значение, описывающее окружение атомов.  Вычислительный эксперимент проводился с участием однокомпонентных соединений, таких как Si, Ge и С. Оценивались скорость получения энергии взаимодействующих атомов, а также точность полученного значения. Характеристики скорости и точности сравнивались со значениями, полученными с помощью многочастичного потенциала межатомного взаимодействия — потенциала Терсоффа.

Hyperexpression of TLR2 and TLR4 in patients with ischemic stroke in acute period of the disease

Pathogenesis of ischemic stroke  is actively  involved  in the  system  of innate immunity. Under conditions of cerebral  ischemia, a number of biologically  active  substances are  released  that  interact with innate immunity receptors, in particular TLR2  and  TLR4, which  exacerbate inflammation in brain  tissue. Identification of predictor markers  at the level of the innate immunity system may foresee the clinical course of ischemic stroke and ensure timely treatment. Our objective was to study expression of TLR2 and TLR4 receptors in peripheral blood leukocytes  in patients with ischemic stroke in the dynamics of the disease. 27 people  were included in the study. The main  group consisted of patients with ischemic stroke of varying severity (n = 19). Patients of the main  group were divided into two subgroups:  with an NIHSS index value of < 10 (n = 10) and > 10 (n = 9). The control group included healthy  donors  with no history  of acute  and chronic inflammatory diseases (n = 8). Peripheral blood  leukocytes  were used as the  test material. To determine expression  of the TLR2  and TLR4  genes, RT-PCR in real time was used. Surface  expression  of TLRs was determined by flow cytometry. A study of the TLR2 and TLR4 gene expression showed that on the 1st, 3rd  and 7th  day post-stroke, the TLR4 gene expression  in patients was significantly  increased, when compared to the control group (p < 0.01), whereas TLR2 gene expression on the 3rd  day of the disease was not statistically different from the control group. A study of surface expression  of receptors showed that the average TLR2 fluorescence intensity on the patients’ peripheral blood monocytes was significantly  increased on the 1st  and 3rd  day of disease when compared to the control group.  The  surface  expression  of TLR4  on monocytes has a statistically significant  increase  only on day 7. Assessment  of surface expression  of TLRs in subgroups  with different  severity values by NIHSS showed that  patients with a NIHSS index > 10 had a significantly  higher  level of surface of TLR2  expression  over the observation period, while the largest difference in TLR4  expression  in the subgroups  was observed  on the 1st day of the disease (p < 0.05). Patients with ischemic stroke showed an increase  in TLR2 and TLR4 expression at the gene and protein level, compared to healthy  donors. These indices can be considered possible predictors for clinical  prognosis  of ischemic stroke

Многомасштабное моделирование кластеров точечных дефектов в полупроводниковых структурах

Clusters of point and extended defects, arising in semiconductors as a result of radiation exposure, allow structures to acquire various properties that can be used in the manufacture of new generation devices for nanoelectronics. Numerical simulation of semiconductor materials used to research such processes is a resource-intensive and multifaceted task. To solve it, the multiscale modeling complex was created and the multiscale composition containing instances of basic composition models was set. An algorithm was developed that allows speeding up calculations for systems of large dimensions and accounting for a large number of interacting atoms. The structure of silicon with a complex of point defects was considered as a model. Molecular dynamics simulation was performed using the multiparameter potential of Tersoff. For the calculations, an effective approach to the implementation of parallel computing was presented, and software for parallelizing the computations was used, placed on the hybrid high-performance computing complex of the FRC «Computer Science and Control» of Russian Academy of Science. To implement the parallelized algorithm, the OpenMP standard was used. This approach has significantly reduced the computational complexity of the calculations.It was shown that the developed high-performance software can significantly accelerate molecular dynamics calculations, such as the calculation of divacancy communication energy, due to the parallelization algorithm.Кластеры точечных и протяженных дефектов, возникающие в полупроводниках в результате радиационного воздействия, позволяют структурам приобретать различные свойства, которые могут быть использованы при изготовлении приборов нового поколения для наноэлекроники. Численное моделирование полупроводниковых материалов, применяемое для изучения таких процессов, — это ресурсоемкая и многограная задача. Для ее решения создан комплекс многомасштабного моделирования и задана многомасштабная композиция, содержащая экземпляры базовых моделей-композиций. Разработан алгоритм, позволяющий ускорять расчеты для систем больших размерностей и учета большого количества взаимодействующих атомов. В качестве модели рассмотрена структура кремния с комплексом точечных дефектов. Молекулярно-динамическое моделирование проведено с применением многопараметрического потенциала Терсоффа. Для расчетов представлен эффективный подход к осуществлению параллельных вычислений, и применены программные средства распараллеливания вычислений, размещенные на гибридном высокопроизводительном вычислительном комплексе ФИЦ «Информатика и управление» РАН. Для реализации распараллеленного алгоритма использован стандарт OpenMP. Такой подход позволил значительно снизить вычислительную сложность проводимых расчетов.Показано, что разработанное высокопроизводительное программное обеспечение может значительно ускорить молекулярно-динамические расчеты, в частности, такие как расчет энергии связи дивакансий за счет алгоритма распараллеливания

Collection of microorganisms of ICG SB RAS as a genetic resource for biotechnology

Genetic knowledge of microorganisms plays a critical role in the creation of new biotechnologies, since the effectiveness of any biotechnology is determined by the particular qualities of the structurally functional organization of molecular-genetic systems and their components used for the production of targeted products. Collections of microbial cultures play a decisive role in mobilizing biological resources and make it possible to form a solid base for genetic, molecular biological and biotechnological research. The aim of this work was to assess the key molecular-genetic and phenotypic characteristics of strains of the collection of microorganisms created in the “FRC Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences” as a genetic resource for biotechnology. Thirty strains of microorganisms of the collection were isolated by employees of the FRC ICG SB RAS from extreme natural ecosystems, the key molecular-genetic and phenotypic characteristics were described using modern methods of molecular biology and mass-spectrometry. DNA isolation and the sequencing of 16S rRNA gene sequences were performed. The strains of the collection were characterized by morphological, physiological, moleculargenetic and mass-spectrometric characteristics. The particular qualities of growing of strains on different substrates have been established, the study of cell morphology has been carried out. The physiological characteristics of the strains of the collection have been established: the attitude to oxygen, the type of nutrition, the range of temperature and pH, the attitude to NaCl and others. Different resistance of strains to antibiotics has been established. The creation of personal mass spectra of protein profiles of the studied strains of the collection was carried out. The resulting DNA sequences of the strains are deposited in the GenBank. The chemotaxonomic characteristics of strains have been determined. The biotechnological properties of the strains were assessed, the amount of metabolites (ethanol, lactic and acetic acids) in the culture liquid was determined. The value of the collection of microorganisms of the FRC ICG SB RAS as a genetic resource for biotechnology and bioengineering is determined not only by the species diversity of its strains, but also by a wide range of their area isolation and by the depth of their characterization using the widest arsenal of both classical and modern methods (including methods of genomics, proteomics, transcriptomics and bioinformatics)

ВЕДЕНИЕ БЕРЕМЕННОСТИ, РОДОВ И ПОСЛЕРОДОВОГО ПЕРИОДА У ПАЦИЕНТКИ С ЛЕКАРСТВЕННО-УСТОЙЧИВЫМ, ДЕСТРУКТИВНЫМ ТУБЕРКУЛЕЗОМ ЛЕГКИХ ПОСЛЕ ЭТАПНОГО ХИРУРГИЧЕСКОГО ЛЕЧЕНИЯ

The article describes a clinical case of the successful management of pregnancy, delivery and post-natal period in the female patient with fibrous cavernous tuberculosis with extensive drug resistance and multiple thoracic surgeries in the past. This clinical case demonstrates that it is possible for a mother with the advanced form of tuberculosis to give birth to a healthy mature newborn.Представлено клиническое наблюдение успешного ведения беременности, родов и послеродового периода у пациентки с фиброзно-кавернозным туберкулезом с широкой лекарственной устойчивостью возбудителя и многократными торакальными операциями в анамнезе. Показана возможность рождения здорового доношенного ребенка у матери с тяжелой формой туберкулеза

Rates of credit obligations compliance on IFRS financial statement as a factor of financial stability

For the purposes of effective management of economic activity of the entities of insufficiently own accounting information. For objective assessment of a financial and economic provision of the entity it is necessary to pass from separate accounting data to certain valuable ratios of major factors – to financial performance or financial ratios. Calculation and interpretation of their values the integral and essentially necessary part of a financial analysis, especially it is important if the company has credit liabilities. Conditions of credit agreements often include accomplishment of credit covenants which represent restrictions for activities and a financial position of the company in addition to timely settlement of percent and a body of the credit and provide to lessors a certain level of safety from bankruptcy of the debtor. The article considers the covenants and financial covenants definitions; the main financial covenants containing in credit agreements between large banks and borrowers; data on structure of a credit portfolio and financial debt of NLMK as at June 30, 2016; the main financial covenants containing in credit agreements of the companies of NLMK Group; definitions and formulas of calculation of financial rates based on the IFRS financial statement; calculation of covenants on the example of IFRS consolidated financial statements of NLMK; subtleties of calculation of financial rates; the main differences of financial rates calculation based on the financial statements prepared on the different principles; conclusion about stability and a financial condition of NLMK by the results received during calculation financial covenants as at end of the first half of the year 2016

MANAGEMENT OF PREGNANCY, DELIVERY AND POST-NATAL PERIOD IN THE PATIENT WITH DRUG RESISTANT DESTRUCTIVE PULMONARY TUBERCULOSIS AFTER SEVERAL SURGERIES

The article describes a clinical case of the successful management of pregnancy, delivery and post-natal period in the female patient with fibrous cavernous tuberculosis with extensive drug resistance and multiple thoracic surgeries in the past. This clinical case demonstrates that it is possible for a mother with the advanced form of tuberculosis to give birth to a healthy mature newborn