The article examines the migration of Russians to Türkiye from February 2022 to the end of 2023 and its socioeconomic impact on the host country. The study identifies the sociological profile of Russian relocants: educated and financially secure individuals, who maintain connections with Russia and remain highly engaged in domestic affairs. The analysis is based on statistical data, sociological surveys, and materials from Russian and international media. Particular attention is given to the factors influencing Russians’ decision to move to Türkiye, including its convenient geographical location, favorable climate, and relatively simple and financially accessible legalization process. At the same time, adaptation is hindered by language barriers and employment difficulties for foreigners. The mass influx of Russians in 2022 led to an increase in real estate prices, as well as the cost of goods and services, prompting the Turkish government to introduce countermeasures, such as raising the price of “investment passports” and restricting the number of districts available for residence permits.
Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Maria Barkova, Alexandr Zhukov, Igor Kartsan, Violetta Kuznetsova, Viktor Gedzun, Marina Bondareva; Spacecraft propellant dispenser for space debris disposal. AIP Conf. Proc. 29 March 2024; 3021 (1): 020024. https://doi.org/10.1063/5.0193014 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search
We address the problem of argument detection by investigating discourse and communicative text structure. A formal graph-based structure called communicative discourse tree (CDT) is used. It consists of a discourse tree (DT) with additional labels on edges, which stand for verbs. These verbs represent communicative actions. Discourse trees are based on rhetoric relations, extracted from a text according to Rhetoric Structure Theory. The problem is tackled as a binary classification task, where the positive class corresponds to texts with arguments and the negative class corresponds to texts with no argumentation. The feature engineering for the classification task is conducted, deciding which discourse and communicative features are better associated with argumentation. New Intense Argumentation dataset is built and described. Mixed dataset including different types of argumentation and different text genres is collected. Evaluation on this mixed dataset is provided.
A three-dimensional multifrequency inverse problem of acoustic sounding of a stationary inhomogeneous medium is considered. This nonlinear inverse problem is reduced to solving an auxiliary three-dimensional linear Fredholm integral equation of the first kind. In the analysis of the uniqueness of the solution to the inverse problem, the connection between the integral equation and determining the source in the Helmholtz equation is indicated. The last problem is ambiguously solvable in the general case. Examples of such ambiguity are given. Questions about detailed data (frequencies, sources) ensuring or not the uniqueness of solutions are considered. A speed-efficient algorithm for solving the inverse problem based on Fourier transforms is proposed. This algorithm makes it possible to calculate uniquely an approximate solution by a stable method under data perturbations. The results of numerical experiments on solving a three-dimensional model inverse problem on fairly detailed grids are presented.
