Области применения нейротехнологий в реальном секторе экономики
Neurotechnologies are used in various areas of the real economy. The article analyzes the solutions of companies in the field of neurotechnology to identify the main areas of commercial application of such solutions. The classification of these solutions is given for such areas of application as assessment and development of skills using neurotechnology, neuromarketing, neurocontrol, neuroeducation, neuroentertainment, neuromedicine and neuroresearch. The article also provides cases and justification for the use of neurotechnologies to solve various problems of business, the end user and the government. Key problems in implementing solutions using neurotechnologies and ways to solve them are described. Some tools used in solutions with the use of neurotechnology are indicated, as well as the classification of these tools into impact and reading tools, as well as tools for working with signals of the peripheral and central nervous system.
The article gives an overview of influence of stock market discrimination on market value of companies in China. There are two types of shares on Chinese stock market: class A shares, which are available for domestic investors, and class B shares, which are available for foreign investors. Such market structure is not a unique Chinese market's feature. It is also used in such countries as Finland, Singapore, Switzerland, Thailand, etc. What differs Chinese market from markets with similar structure is the fact that class B shares are traded with substantial discount to class A shares. Such a situation is explained by such factors informational asymmetry between domestic and foreign investors; different liquidity of different classes of shares; diversification effect, connected with investment in Chinese stock market; size of companies; ratio of amounts of shares of different classes; stock exchange where company's shares are traded.
Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.
We consider a linear optimal control model for the marketing of seasonal products which are produced by the same firm and sold by retailers in different market segments. The horizon is divided in two consecutive non-intersecting intervals, called production and selling periods, respectively. The production period state variables are the inventory levels and two kinds of goodwills (consumers' and retailers' goodwill, respectively) while the selling period state variables are the sales levels and the two kinds of goodwiIls. ln the production interval there are three kinds of controls: on production, quality and advertising, while in the selling one the controls are on communication via advertisirng; promotion addressed to consumers and incentives given to retailers. We consider the case of several kinds of communications. The optimal control problem is transformed into an equivalent nonlinear programming problem.
Handwriting is an advanced motor skill and one of the key developments in human culture. Here we show that handwriting can be decoded—offline and online—from electromyographic (EMG) signals recorded from multiple hand and forearm muscles. We convert EMGs into continuous handwriting traces and into discretely decoded font characters. For this purpose, we use Wiener and Kalman filters, and machine learning algorithms. Our approach is applicable to clinical neural prostheses for restoration of dexterous hand movements, and to medical diagnostics of neural disorders that affect handwriting. We also propose that handwriting could be decoded from cortical activity, such as the activity recorded with electrocorticography (ECoG).
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.