Search results for: N. Volkova
5 Psychological Consultation of Married Couples at Various Stages of Formation of the Young Family
Authors: Gulden Aykinbaeva, Assem Umirzakova, Assel Makhadiyeva
Abstract:
The problem of studying of young married couples in connection with a change of social institute of a family and marriage is represented very actual for family consultation, considering a family role in the development of modern society. Results of numerous researchs say that one of difficult in formation and stabilization of a matrimony is the period of a young family. This period is characterized by various processes of integration, adaptation and emotional compatibility of spouses. The young family in it the period endures the first standard crisis which postpones a print for the further development of the family scenario. Emergence new, earlier not existing, systems of values render a huge value on the process of formation of a young family and each of spouses separately. Possibly to solve the set family tasks at the development of the uniform system of the family relations in which socially mature persons capable to consider a family as the creativity of each other act as subjects. Due to the research objective in work the following techniques were used: a questionnaire of satisfaction with V. V. Stolin's marriage and A. N. Volkova's technique directed on detection of coherence of family values and role installations in a married couple, and also content – the analysis. Development of an internal basis of a family on mutual clearing of values is important during the work with married couples. 'The mature view' of the partner in the marriage union provides coherence between the expected and real behavior of the partner that is important for the realization of the purposes of adaptation in a family. For research of communication of the data obtained by means of A. N. Volkova's techniques, V. V. Stolina and content – the analysis, the correlation analysis, with the application of the criterion of Spirmen was used. The analysis of results of the conducted research allowed us to determine the number of consistent patterns: 1. Nature of change of satisfaction with marriage at spouses testifies that the matrimonial relations undergo high-quality changes at different stages of formation of a young family. 2. The matrimonial relations in the course of their development, formation and functioning in young marriage undergo considerable changes on psychological, social and psychological and insignificant — at the psychophysiological and sociocultural levels. The material received by us allows to plan ways of further detailed researches of the development of the matrimonial relations not only in the young marriage but also at further stages of development of a matrimony. We believe that the results received in this research can be almost applied at creation of algorithms of selection of marriage partners, at diagnostics of character and the maintenance of matrimonial disharmonies, at the forecast of stability of marriage and a family.Keywords: married couples, formation of the young family, psychological consultation, matrimony
Procedia PDF Downloads 3964 Inverted Umbrella-type Chiral Non-coplanar Ferrimagnetic Structure in Co(NO₃)₂
Authors: O. Maximova, I. L. Danilovich, E. B. Deeva, K. Y. Bukhteev, A. A. Vorobyova, I. V. Morozov, O. S. Volkova, E. A. Zvereva, I. V. Solovyev, S. A. Nikolaev, D. Phuyal, M. Abdel-Hafiez, Y. C. Wang, J. Y. Lin, J. M. Chen, D. I. Gorbunov, K. Puzniak, B. Lake, A. N. Vasiliev
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The low-dimensional magnetic systems tend to reveal exotic spin liquid ground states or form peculiar types of long-range order. Among systems of vivid interest are those characterized by the triangular motif in two dimensions. The realization of either ordered or disordered ground state in a triangular, honeycomb, or kagome lattices is are dictated by the competition of exchange interactions, also being sensitive to anisotropy and the spin value of magnetic ions. While the low-spin Heisenberg systems may arrive at a spin liquid long-range entangled quantum state with emergent gauge structures, the high-spin Ising systems may establish the rigid non-collinear structures. This study presents the case of chiral non-coplanar inverted umbrella-type ferrimagnet formed in cobalt nitrate Co(NO₃)₂ below TKeywords: chiral magnetic structures, low dimensional magnetic systems, umbrella-type ferrimagnets, chiral non-coplanar magnetic structures
Procedia PDF Downloads 1253 Short-Range and Long-Range Ferrimagnetic Order in Fe(Te₁.₅Se₀.₅)O₅Cl
Authors: E. S. Kozlyakova, A. A. Eliseev, A. V. Moskin, A. Y. Akhrorov, P. S. Berdonosov, V. A. Dolgikh, K. N. Denisova, P. Lemmens, B. Rahaman, S. Das, T. Saha-Dasgupta, A. N. Vasiliev, O. S. Volkova
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Considerable attention has been paid recently to FeTe₂O₅Cl due to reduced dimensionality and frustration in the magnetic subsystem, succession of phase transitions, and multiferroicity. The efforts to grow its selenite sibling resulted in mixed halide compound, Fe(Te₁.₅Se₀.₅)O₅Cl, which was found crystallizing in a new structural type and possessing properties drastically different from those of a parent system. Hereby we report the studies of magnetization M and specific heat Cₚ, combined with Raman spectroscopy and density functional theory calculations in Fe(Te₁.₅Se₀.₅)O₅Cl. Its magnetic subsystem features weakly coupled Fe³⁺ - Fe³⁺ dimers showing the regime of short-range correlations at TM ~ 70 K and long-range order at TN = 22 K. In a magnetically ordered state, sizable spin-orbital interactions lead to a small canting of Fe³⁺ moments. The density functional theory calculations of leading exchange interactions were found in agreement with measurements of thermodynamic properties and Raman spectroscopy. Besides, because of the relatively large magnetic moment of the Fe³⁺ ion, we found that magnetic dipole-dipole interactions contribute significantly to experimentally observed orientation of magnetization easy axis in ac-plane. As a conclusion, we suggest a model of magnetic subsystem in magnetically ordered state of Fe(Te₁.₅Se₀.₅)O₅Cl based on a model of interacting dimers.Keywords: dipole-dipole interactions, low dimensional magnetism, selenite, spin canting
Procedia PDF Downloads 1672 Prednisone and Its Active Metabolite Prednisolone Attenuate Lipid Accumulation in Macrophages
Authors: H. Jeries, N. Volkova, C. G. Iglesias, M. Najjar, M. Rosenblat, M. Aviram, T. Hayek
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Background: Synthetic forms of glucocorticoids (e.g., prednisone, prednisolone) are anti-inflammatory drugs which are widely used in clinical practice. The role of glucocorticoids (GCs) in cardiovascular diseases including atherosclerosis is highly controversial, and their impact on macrophage foam cell formation is still unknown. Our aim was to investigate the effects of prednisone or its active metabolite, prednisolone, on macrophage oxidative stress and lipid metabolism using in-vivo, ex-vivo and in-vitro systems. Methods: The in-vivo study included C57BL/6 mice which were intraperitoneally injected with prednisone or prednisolone (5mg/kg) for 4 weeks, followed by lipid metabolism analyses in the mice aorta, and in peritoneal macrophages (MPM). In the ex-vivo study, we analyzed the effect of serum samples obtained from 9 healthy volunteers before or after treatment with oral prednisone (20mg for 5 days), on J774A.1 macrophage atherogenicity. In-vitro studies were conducted using J774A.1 macrophages, human monocyte derived macrophages (HMDM) and fibroblasts. Cells were incubated with increasing concentrations (0-200 ng/ml) of prednisone or prednisolone, followed by determination of cellular oxidative status, triglyceride and cholesterol metabolism. Results: Prednisone or prednisolone treatment resulted in a significant reduction in triglycerides and mainly in cholesterol cellular accumulation in MPM or in J774A.1 macrophages incubated with human serum. Similar resulted were noted in HMDM or in J774A.1 macrophages which were directly incubated with the GCs. These effects were associated with GCs inhibitory effect on triglycerides and cholesterol biosynthesis rates, throughout downregulation of diacylglycerol acyltransferase1 (DGAT1) expression, and of the sterol regulatory element binding protein (SREBP2) and HMGCR expression, respectively. In parallel to prednisone or prednisolone induced reduction in macrophage triglyceride content, paraoxonase 2 (PON2) expression was significantly upregulated. GCs-induced reduction of cellular triglyceride and cholesterol mass was mediated by the GCs receptors on macrophages since the GCs receptor antagonist (RU 486) abolished these effects. In fibroblasts, unlike macrophages, prednisone or prednisolone showed no anti-atherogenic effects. Conclusions: Prednisone or prednisolone are anti-atherogenic since they protected macrophages from lipid accumulation and foam cell formation.Keywords: atherosclerosis, cholesterol, foam cell, macrophage, prednisone, prednisolone, triglycerides
Procedia PDF Downloads 1461 Decoding Kinematic Characteristics of Finger Movement from Electrocorticography Using Classical Methods and Deep Convolutional Neural Networks
Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi
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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex
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