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With the acceleration of technological development and the digital transformation of economies, the impact of intellectual property on economic growth will increase. The article shows that the forms and means of legal protection and use of intellectual property will evolve in line with the opportunities that will be provided by the infrastructure (production, fixation, management, tracking and protection of intellectual property rights) in this area. In Russia, the "digitalization" of legal protection and use of intellectual property rights will make it possible to form public-private platforms for rights management, which will create additional opportunities for authors to effectively manage their rights. This will attract investors to the non-raw-material sector of the economy and may become an important driver for the development of the digital economy in the country as a whole.

AbstractWe consider a simple long short-term memory (LSTM) neural network extension of the Poisson Lee-Carter model, with a particular focus on different procedures for how to use training data efficiently, combined with ensembling to stabilise the predictive performance. We compare the standard approach of withholding the last fraction of observations for validation, with two other approaches: sampling a fraction of observations randomly in time; and splitting the population into two parts by sampling individual life histories. We provide empirical and theoretical support for using these alternative approaches. Furthermore, to improve the stability of long-term predictions, we consider boosted versions of the Poisson Lee-Carter LSTM. In the numerical illustrations it is seen that even in situations where mortality rates are essentially log-linear as a function of calendar time, the boosted model does not perform significantly worse than a simple random walk with drift, and when non-linearities are present the predictive performance is improved. Moreover, boosting allows us to obtain reasonable model calibrations based on as few data points as 20 years.

As urbanization continues and more people move into cities and urban areas, pressure on available land for new constructions will continue to increase. This situation constitutes an incentive to review the need for interior space and uses of existing buildings. A great deal can be gained from using existing buildings more efficiently instead of constructing new ones: Reduced resource usage during construction (investments, natural resources, and energy), operation, and maintenance ; more activity per square meter of buildings creates a greater basis for public transport and other services ; more intensive use of buildings creates a more vibrant city without building on virgin land. The aim of this paper is to initiate a discussion regarding how digitalization can affect the demand and supply of interior space in existing buildings and elaborate on how policy can support more resource-efficient uses of space. New activity-based resource measurements intended for use in buildings are proposed, and several principles that have the potential to decrease environmental impact through more efficient usage of space are outlined. Based on these ideas for encouraging the flexible use of building spaces that are facilitated by digitalization and the new measurement approaches, a four-step principle for construction is proposed: The first step is to reduce the demand for space, the second is to intensify usage of existing space, the third is to reconstruct and adapt existing buildings to current needs, and the fourth is to construct new buildings. Urging political, municipal, construction, and real-estate decision makers to contemplate this principle, particularly in view of the new conditions that digitalization entails, will lead to more sustainable construction and, in the long term, a sustainable built environment.