Demographic policy is one of the key tasks of almost any state at the present time. It correlates with the solution of pressing problems in the economic and social spheres, directly depends on the state of healthcare, education, migration policy and other factors and directly affects the socio-economic development of both individual regions and the country as a whole. Many Russian and foreign researchers believe that demographic indicators very accurately reflect the socio-economic and political situation of the state. The relevance of the study is due to the fact that for the progressive socio-economic development of any country, positive demographic dynamics are necessary. The main sign of the negative demographic situation that has developed in modern Russia and a number of countries, primarily European, is the growing scale of depopulation (population extinction). The purpose of this work was to analyze the existing demographic policy of Russia and compare demographic trends in Russia and other countries. The work uses methods of statistical data analysis, comparison of statistical indicators of fertility, mortality, natural population decline, migration, marriage rates in Russia and the Republic of Srpska, methods of retrospective analysis, research of the institutional environment created by the action of state and national programs “Demography”, “Providing accessible and comfortable housing and public services for citizens of the Russian Federation”, “Strategy of socio-economic development for the period until 2024”, Presidential decrees, etc. Research has shown that despite measures taken to overcome the demographic crisis, Russia’s population continues to decline. According to the Federal State Statistics Service of the Russian Federation (Rosstat), as of 1 January 2023, 146.45 million people lived in Russia. By 1 January 2046, according to a Rosstat forecast published in October 2023 the country’s population will decrease to 138.77 million people. To solve demographic problems in the Russian Federation, a national project “Demography” was developed and approved. The government has allocated more than 3 trillion rubles for its implementation. However, it is not possible to completely overcome the negative trend. The authors proposed a number of economic and ideological measures within the framework of agglomeration, migration, and family support policies that can be used within the framework of socio-economic development strategies and national programs aimed at overcoming the demographic crisis.

Heat stress amplified by climate change causes excessive reductions in labor capacity, work injuries, and socio-economic losses. Yet studies of corresponding impact assessments and adaptation developments are insufficient and incapable of effectively dealing with uncertain information. This gap is caused by the inability to resolve complex channels involving climate change, labor relations, and labor productivity. In this paper, an optimization-based productivity restoration modeling framework is developed to bridge the gap and support decision-makers in making informed adaptation plans. The framework integrates a multiple-climate-model ensemble, an empirical relationship between heat stress and labor capacity, and an inexact system costs model to investigate underlying uncertainties associated with climate and management systems. Optimal and reliable decision alternatives can be obtained by communicating uncertain information into the optimization processes and resolving multiple channels. Results show that the increased heat stress will lead to a potential reduction in labor productivity in China. By solving the objective function of the framework, total system costs to restore the reduction are estimated to be up to 248,700 million dollars under a Representative Concentration Pathway of 2.6 (RCP2.6) and 697,073 million dollars under RCP8.5 for standard employment, while less costs found for non-standard employment. However, non-standard employment tends to restore productivity reduction with the minimum system cost by implementing active measures rather than passive measures due to the low labor costs resulting from ambiguities among employment statuses. The situation could result in more heat-related work injuries because employers in non-standard employment can avoid the obligation of providing a safe working environment. Urgent actions are needed to uphold labor productivity with climate change, especially to ensure that employers from non-standard employment fulfill their statutory obligations.

Accurate prediction of US Treasury bond yields is crucial for investment strategies and economic policymaking. This paper explores the application of advanced machine learning techniques, specifically Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models, in forecasting these yields. By integrating key economic indicators and policy changes, our approach seeks to enhance the precision of yield predictions. Our study demonstrates the superiority of LSTM models over traditional RNNs in capturing the temporal dependencies and complexities inherent in financial data. The inclusion of macroeconomic and policy variables significantly improves the models’ predictive accuracy. This research underscores a pioneering movement for the legacy banking industry to adopt artificial intelligence (AI) in financial market prediction. In addition to considering the conventional economic indicator that drives the fluctuation of the bond market, this paper also optimizes the LSTM to handle situations when rate hike expectations have already been priced-in by market sentiment.

The rapidly growing construction industry often deals with complex and dynamic projects that pose significant safety risks. One of the state-owned companies in Indonesia is engaged in large-scale toll road construction projects with a high incidence of workplace accidents. This study aims to improve safety performance in toll road construction by implementing the Scrum framework. The study uses a System Dynamics approach to model interactions between the Scrum framework, project management, and work safety subsystems. Various scenarios were designed by modifying controlled variables and system structures, including introducing a punishment entity. These scenarios were evaluated based on their impact on reducing incidents and the incident rate over the project period. The results indicate that the combined scenario significantly reduces incidents and incident rates in different conditions. The study also finds a strong relationship between Scrum framework implementation and improved safety performance, demonstrating a reduction in incidents and incident rates by over 50% compared to existing conditions. This research underlines the effectiveness of the Scrum framework in enhancing safety in construction projects.

This paper critically reviews the prevailing generalizations in current research on Generation Z (Gen-Z) travel behavior. While various studies have characterized Gen-Z’s transportation preferences as leaning towards sustainable and technology-integrated modes of transport, this paper argues that the findings are largely based on observations from developed countries and may not accurately reflect behavior in developing countries. This paper is written using a narrative literature study approach. Through a comprehensive literature review, the paper highlights the differences in Gen-Z travel patterns across different geographical regions, emphasizing the need for context-specific analysis. The paper addresses often overlooked factors such as economic limitations, infrastructure challenges, and cultural nuances that shape mobility choices. The aim is to dissect the cohort effect and look at its validity across different socio-economic landscapes through existing literature. As such, the paper provides nuanced insights into the heterogeneity of Gen-Z travel behavior and suggests cautioning against over-generalization, as well as advocating for a more localized approach in transportation policy and planning. The paper also encourages similar research in developing countries to gain a more comprehensive understanding of Gen-Z travel behavior globally.