In this paper we describe a methodology that allows researchers to measure empirically, in the form of well-defined indicators, the extent to which economic analysis and evidence is been applied in the enforcement of competition law, using data collected from the decisions of competition authorities. By mapping the value of these indicators to different legal standards, our methodology also allows one to identify the legal standards adopted in the assessment of different conducts that were investigated by the authorities. The policy implications of empirical work in this area are potentially very important, since the extent to which economic analysis is applied in the assessment of anti-competitive conduct by competition authorities may well influence the quality of this assessment (i.e. the quality of enforcing competition law, measured by the extent to which decision-errors and deterrence effects are minimised). Empirical analysis using the indicators can be used to undertake comparative analysis in different countries, to examine the extent to which authorities favour specific legal standards in the assessment of specific conducts and the way in which the judicial review process treats decisions depending on the legal standard used.
S.S. Chern conjectured that the Euler characteristic of every closed affine manifold has to vanish. We present an analog of this conjecture stating that the Euler-Satake characteristic of any compact affine orbifold is equal to zero. We prove that Chern's conjecture is equivalent to its analog for the Euler-Satake characteristic of compact affine orbifolds, and orbifolds may be ineffective. This fact allowed us to extend to orbifolds the known results of B.~Klingler and also results of B.~Kostant and D.~Sullivan on sufficient conditions to fulfill Chern's conjecture. Thus we prove that if an $n$-dimensional compact affine orbifold $\mathcal N$ is complete or if its holonomy group belongs to the special linear group $SL(n,\mathbb R),$ then the Euler-Satake characteristic of $\mathcal N$ has to vanish. An application to pseudo-Riemannian orbifolds is considered. Examples of orbifolds belonging to the investigated class are given. In particular, we construct an example of a compact incomplete affine orbifold with the vanishing Euler characteristic, the holonomy group of which does not belong to $SL(n,\mathbb R).$
This study explores examples of sustainable growth in Chinese and Russian natural gas companies. The topic of sustainable growth has become a priority focus for studies in market development. Company growth encounters many obstacles, and any such study necessitates a multivariate analysis of interrelated financial and non-financial factors. The authors aim to highlight two fundamental issues in this study. The first is the choice of those indicators which characterise company growth. The second is the identification of factors that have a sustainable impact on growth. Additionally, we try to answer the question: “Are the sustainable growth factors of Russian and Chinese gas market companies comparable?”. The primary purpose of this study is to analyse Chinese and Russian gas market companies’ financial growth strategies using the ‘Geniberg Z-matrix’, as well as enhanced Financial Sustainability Indicators System indices by identifying which indicators have a greater influence on the Sustainable Growth Rate. The scientific novelty of this study is related to the process of constructing financial reports with a focus on sustainable factors, and the implementation of a sustainable financial growth matrix to the appropriate information of Chinese and Russian oil and gas companies. Through this approach, a relationship between sustainable growth and energy companies’ financial strategy was confirmed. Chinese and Russian gas companies’ financial growth strategy was analysed by employing the Geniberg-Z matrix as well as enhanced Financial Sustainability Indicators System indices. We found that ROCE, WACC, ROL, and CGDummy influence Chinese gas companies’ sustainable growth rate and recommended the implementation of an FSIS calculation. In the same way, ROCE, ROFA, CR, DOL, ROL influence Russian gas companies’ sustainable growth rate, and we recommend an FSIS calculation. Evaluation results also show that Chinese and Russian gas companies are financially attractive and have stable results, but could improve their financial strategies from a sustainable growth perspective.
The report presents the results of a global study of biomedical clusters. Its goal is to identify and analyse the most successful international practices of promoting biomedical clusters, in which the cooperation of universities, firms and clinics, combined with a developed infrastructure and public support measures led to a significant improvement in the quality of healthcare.
The edition summarises the positive effects of biomedical clusters, describes their global landscape and reveals the key success factors, which are then compared with the features of the Moscow International Medical Cluster activities.
The publication is of practical interest to government officials, entrepreneurs, researchers, clinicians, and other professionals involved in the development of biomedical clusters, and to anyone else interested in healthcare and cluster policies.
Axiom A diffeomorphisms of closed 2-manifold of genus p⩾2 whose nonwandering set contains a perfect spaciously situated one-dimensional attractor are considered. It is shown that such diffeomorphisms are topologically semiconjugate to a pseudo-Anosov homeomorphism with the same induced automorphism of fundamental group. The main result of this paper is as follows. Two diffeomorphisms from the given class are topologically conjugate on perfect spaciously situated attractors if and only if the corresponding homotopic pseudo-Anosov homeomorphisms are topologically conjugate by means of a homeomorphism that maps a certain subset of one pseudo-Anosov homeomorphism onto a subset of the other.
Recurrent neural networks have proved to be an effective method for statistical language modeling. However, in practice their memory and run-time complexity are usually too large to be implemented in real-time offline mobile applications. In this paper we consider several compression techniques for recurrent neural networks including Long–Short Term Memory models. We make particular attention to the high-dimensional output problem caused by the very large vocabulary size. We focus on effective compression methods in the context of their exploitation on devices: pruning, quantization, and matrix decomposition approaches (low-rank factorization and tensor train decomposition, in particular). For each model we investigate the trade-off between its size, suitability for fast inference and perplexity. We propose a general pipeline for applying the most suitable methods to compress recurrent neural networks for language modeling. It has been shown in the experimental study with the Penn Treebank (PTB) dataset that the most efficient results in terms of speed and compression–perplexity balance are obtained by matrix decomposition techniques.
The universal mechanism of modulation instability (MI) has been discovered first for the Nonlinear Schr¨odinger equation (NLS) and is well studied in the frame of the higher order NLS equations. Recent studies demonstrated by pure existence theorems that also the higher order Korteweg-de Vries (KdV) equations might possess the MI. In this Letter we present explicit form of the conditions for the MI to appear in the KdV-family of equations of the general form ut + sup ux + uxxx =0 where s = ±1 with p > 0 being an arbitrary integer.
Value co-creation is a new notion in contemporary business practice, which is now also becoming one of the key marketing concepts. The success of the value co-creation strategy is based on the DART (dialogue, access, risk-benefits and transparency) concept which is emerging as the basis for interaction between the consumer and the firm. Still, the lack of a formalized approach towards the representation of the DART mechanism remains an issue. Thus, the purpose of the present paper is to describe a formal approach based on DEMO methodology tools as an attempt aimed at value co-creation process modelling.
In recent year’s science and technology policy in Russian Federation experienced a burst of initiatives aimed on fostering innovation-based economic development. One of policy instrument deployed by the government is promotion of regional innovation clusters including innovation clusters in biotechnology. Development of the biotechnology sector in Russian Federation is grounded in significant science and technology legacy of Soviet era. The purpose of the study is to evaluate level of development of support infrastructure in regional biotechnology clusters in Russian Federation. This is an exploratory study is based on a case-study design involved semi-structured survey of 54 participants of a Russian biotechnology cluster. The paper revealed an immature nature of the support infrastructure which inhibits innovation in biotechnology companies. Based on the findings paper offers a conceptual framework of organising regional biotechnology cluster under conditions of severe market failure in support infrastructure. Although paper focuses on regional clusters in Russia, the implications of the study have significance to scholars in better understanding the nature of biotechnology development in Russia. The developed framework could be utilised by policymakers in regions with underdeveloped market conditions.
This paper is focused on the automatic extraction of persons and their attributes (gender, year of born) from album of photos and videos. A two-stage approach is proposed in which, firstly, the convolutional neural network simultaneously predicts age/gender from all photos and additionally extracts facial representations suitable for face identification. Here the MobileNet is modified and is preliminarily trained to perform face recognition in order to additionally recognize age and gender. The age is estimated as the expected value of top predictions in the neural network. In the second stage of the proposed approach, extracted faces are grouped using hierarchical agglomerative clustering techniques. The birth year and gender of a person in each cluster are estimated using aggregation of predictions for individual photos. The proposed approach is implemented in an Android mobile application. It is experimentally demonstrated that the quality of facial clustering for the developed network is competitive with the state-of-the-art results achieved by deep neural networks, though implementation of the proposed approach is much computationally cheaper. Moreover, this approach is characterized by more accurate age/gender recognition when compared to the publicly available models.
The study is aimed at determining the factors influencing the trade credits dynamics for twenty three firms registered on the Macedonian Stock Exchange, as well as at checking for crisis effects from 2011 to 2015. The study includes a review of the literature on commercial credit factors; elaborately analyzed descriptive statistics of the collected data and dependent variable variance; tests for unobservable effects and their functional form; evaluation of panel regression and interpretation of the results. The authors have proved that net trade credits for these firms depends mainly on the growth potential of lagging firms and their vulnerability, and the crisis effects are significant only for the latter factor. Moreover, the overall efficiency of firms' assets and their ability to convert income into cash does not have a significant impact in the crisis and post-crisis periods. The growth opportunities and profitability demonstrate a negative impact, meaning that growing and more profitable firms on average tend to expand and receive more trade credits than counterparties. Profitability has a significant impact on trade credit and the effect is seen during the first year after the crisis. Thus, the dynamics of trade credits of registered Macedonian firms is largely determined by the internal factors of a firm, and not by the external macroeconomic situation. Therefore, better financial management is suggested to improve the trade credit policy. One of the directions for further research is the evaluation of the autoregressive component of the trade credit dynamics, as well as including spatial effects in the regression equation.
The problem of computing the width of simplices generated by the convex hull of their integer vertices is considered. An FPT algorithm, in which the parameter is the maximum absolute value of the rank minors of the matrix consisting from the simplex vertices, is presented.
Realism- and geopolitics-inspired rhetoric was common currency in Russian foreign policy discourse throughout the 1990s. This led some commentators to adopt realism and geopolitics - realism’s more nationalist and strategic counterpart - as conceptual lenses for understanding Russian foreign policy. As a result, Russian foreign policy of the 2010s is still considered predominantly geopolitics-driven despite the fact that geopolitical vocabulary has virtually disappeared from foreign policy discourse while a desire to carve out spheres of influence have been officially pronounced utterly anachronistic and inappropriate, a “thing of the past”. Thus, a more nuanced interpretation views the rise of geopolitics in Russian post-Soviet foreign policy discourse as an attempt to tap into the symbolic and rhetorical power of geopolitics in order to reduce ontological insecurity brought about by the end of the Cold War. The chapter, therefore, advances a theoretical claim about the relevance of the constructivist and poststructuralist literature and very limited relevance of realism for understanding the twists and turns of Russian post-Soviet foreign policy. Methodologically, the chapter argues that an exploration of state identity rooted in the ontological security argument will benefit from employing discourse analysis. Empirically, the present study provides substantiation of the theoretical claim that the concept of hegemony captures well the historical trajectory of Russia’s relations with its ‘significant other’- Europe/the EU/the West – and provides important insights into the sources of Russia’s ontological insecurity in the 21st century.
In this paper, we studied the phonetic approach for voice processing. A method for automatic recognition of speech signals, in which each quasistationary segment is associated with a fuzzy set of phonemes, was developed. We proposed the operation of the probabilistic triangular norm for fuzzy sets corresponding to the input frame and the nearest reference phoneme. The developed method was experimentally shown to allow a 1.5–5% reduction in the probability of erroneous recognition in comparison with known analogues.
Three Lagrangian invariants are shown to exist for flows in the equatorial region in the β - plane approximation.
They extend the Cauchy invariants to a non-rotating fluid. The relationship between these generalized invariants
and the results following from Kelvin's and Ertel's theorems is ascertained. Explicit expressions of the invariants
for equatorially trapped waves and equatorial Gerstner waves are presented.
We describe the class of graphs whose each subgraph has the next property: The maximal number of disjoint 4-paths is equal to the minimal cardinality of sets of vertices such that every 4-path in the subgraph contains at least one of these vertices. We completely describe the set of minimal forbidden subgraphs for this class. Moreover, we present an alternative description of the class based on the operations of edge subdivision applied to bipartite multigraphs and the addition of so-called pendant subgraphs, isomorphic to triangles and stars.
The issue of rogue wave lifetimes is addressed in this study, which helps to detail the general picture of this dangerous oceanic phenomenon. The direct numerical simulations of irregular wave ensembles are performed to obtain the complete accurate data on the rogue wave occurrence and evolution. Purely collinear wave systems, moderately crested, and short-crested sea states have been simulated by means of the high-order spectral method for the potential Euler equations. As rogue waves are transient and poorly reflect the physical eects, we join instant abnormally high waves in close locations and close time moments to new objects, rogue events, which helps to retrieve the abnormal occurrences more stably and more consistently from the physical point of view. The rogue event lifetime probability distributions are calculated based on the simulated wave data. They show the distinctive dierence between rough sea states with small directional bandwidth on one part, and small-amplitude sea states and short-crested states on the other part. The former support long-living rogue wave patterns (the corresponding probability distributions have heavy tails), though the latter possess exponential probability distributions of rogue event lifetimes and generally produce much shorter rogue wave events.