Комплексный анализ социально-экономических последствий вступления Китая, Украины и России в ВТО по различным отраслям экономики позволил выработать рекомендации для наиболее успешной адаптации России к нормам ВТО. Акцент сделан на опыте Китая. Практика его участия в ВТО крайне полезна для России с позиций позитивного влияния на развитие экономики страны, когда с одной стороны, идет расширение промышленного и производственного секторов экономики, продвижение товаров на мировых рынках, а с другой, есть возможность использовать правовые инструменты ВТО для защиты национального внутреннего рынка.
Положительный опыт участия в ВТО Китая несколько контрастирует с приведенным опытом Украины. Оценка многовекторной политики Украины и ее ассоциирование с ЕС позволила сделать вывод о невозможности этой страны идти одновременно по пути и евразийской и европейской интеграции.
Обострившееся в последнее время торгово-экономическое и политическое противоборство России с американскими и европейскими партнерами подталкивает к кардинальному изменению государственной экономической стратегии. Определить направления таких трансформаций поможет постижение как положительного, так и отрицательного опыта продвижения в мировое экономическое пространство давних торговых партнеров России – Китая и Украины.
The dynamics of two-component solitons is studied, analytically and numerically, in the framework of a system of coupled extended nonlinear Schrödinger equations, which incorporate the cross-phase modulation, pseudo-stimulated-Raman-scattering (pseudo-SRS), cross-pseudo-SRS, and spatially inhomogeneous second-order dispersion (SOD). The system models co-propagation of electromagnetic waves with orthogonal polarizations in plasmas. It is shown that the soliton's wavenumber downshift, caused by pseudo-SRS, may be compensated by an upshift, induced by the inhomogeneous SOD, to produce stable stationary two-component solitons. The corresponding approximate analytical solutions for stable solitons are found. Analytical results are well confirmed by their numerical counterparts. Further, the evolution of inputs composed of spatially even and odd components is investigated by means of systematic simulations, which reveal three different outcomes: formation of a breather which keeps opposite parities of the components; splitting into a pair of separating vector solitons; and spreading of the weak odd component into a small-amplitude pedestal with an embedded dark soliton.
Flow variations over time generalize standard network flows by introducing an element of time. In contrast to the classical case of static flows, a flow over time in such a network specifies a flow rate entering an arc for each point in time. In this setting, the capacity of an arc limits the rate of flow into the arc at each point in time. Traditionally, flows over time are computed in time-expanded networks that contain one copy of the original network for each discrete time step. While this method makes available the whole algorithmic toolbox developed for static network flows, its drawback is the enormous size of the time-expanded network. In this paper, we extend the results about the minimum flow problem to network flows (with n nodes and m arcs) in which the time-varying lower bounds can involve both the source and the sink nodes (as in Fathabadi et al.) and also one additional node other than the source and the sink nodes. It is shown that this problem for the set (Formula presented.) of time points can be solved by at most n minimum flow computations, by suitably extending the dynamic minimum flow algorithm and reoptimization techniques. The running time of the presented algorithm is (Formula presented.).
The article concerns the research of functional and linguistic peculiarities of religious discourse in different historical periods. The author considers the religious discourse as a method, consistently reproduced in time and space, of transmitting the complex of meanings of a sacral text with account of the mentality, religious experience and objective reality of people speaking a certain language in a certain phase of history. The contrastive analysis of polyglot sacral texts appearing as a significant part of religious discourse and being a subject of rendering into different languages is worthwhile only when historical, chronological, sociocultural and situative factors which have an impact on the meaning of a sacral text are taken into consideration. Since translators were expected to observe the compulsory rules of rendering the meaning and structure of the source text, translations appeared that distorted the text meaning or did not reproduce it accurately.
В отличие от русской традиции, британские авторы, пишущие для детей и подростков, уделяют большое внимание проблеме толерантности, создавая книги, где ребенок или подросток с особенностями развития выступает в качестве протагониста.
This paper addresses the problem of insufficient performance of statistical classification with the medium-sized database (thousands of classes). Each object is represented as a sequence of independent segments. Each segment is defined as a random sample of independent features with the distribution of multivariate exponential type. To increase the speed of the optimal Kullback-Leibler minimum information discrimination principle, we apply the clustering of the training set and an approximate nearest neighbor search of the input object in a set of cluster medoids. By using the asymptotic properties of the Kullback-Leibler divergence, we propose the maximal likelihood search procedure. In this method the medoid to check is selected from the cluster with the maximal joint density (likelihood) of the distances to the previously checked medoids. Experimental results in image recognition with artificially generated dataset and Essex facial database prove that the proposed approach is much more effective, than an exhaustive search and the known approximate nearest neighbor methods from FLANN and NonMetricSpace libraries.
Comparative statistical properties of Parkinson, Garman-Klass, Roger-Satchell and bridge oscillation estimators are discussed. Point and interval estimations, related with mentioned estimators are considered. The advantages of statistical indicators of the Brownian bridge than the other estimators had been shown. The results allow to conclude that the growth of trend leads to a significant shift of the calculated value for the classical.
We extend the Dixit and Stiglitz set-up by introducing consumer heterogeneity into a general equilibrium model of monopolistic competition. By getting a closedform solution for a symmetric equilibrium, we show how the market outcome depends on the joint distribution of tastes and labor productivities of consumers. In contrast to the traditional framework, the model predicts that the short-run equilibrium price may vary with the number of firms, demonstrating both anti- and procompetitive behavior, which is in accordance with economic intuition and empirical evidence.
In this paper, we consider the problem of insufficient runtime and memory-space complexities of contemporary deep convolutional neural networks in the problem of image recognition. A survey of recent compression methods and efficient neural networks architectures is provided. The experimental study is focused on the visual emotion recognition problem. We compare the computational speed and memory consumption during the training and the inference stages of such methods as the weights matrix decomposition, binarization and hashing in the visual emotion recognition problem. It is experimentally shown that the most efficient recognition is achieved with the full network binarization and matrices decomposition.