Journal of Sustainable Development and Green Technology

The cement sector is a linchpin of global infrastructure and is also one of the world’s most significant industrial sources of CO2 emissions, accounting for about 7-8% of anthropogenic emissions. The proper prediction of cementgenerated emissions is thus essential for designing mitigation strategies, planning industrial transitions, and evaluating progress toward carbon-neutrality goals. This paper proposes a new time-series forecasting model that combines Neural Ordinary Differential Equations (NODE) with the Football Optimization Algorithm (FbOA) to enable automated, data-driven hyperparameter optimization. The performance of NODE is compared with Seq2Seq and ConvLSTM models for global CO2 emis-sions from cement production in baseline settings, and subsequently metaheuristically optimized using FbOA, PSO, MVO, WOA, and GA. The baseline experiments demonstrate that NODE, with an MSE of 0.00745, RMSE of 0.0863, MAE of 0.0515, and high levels of agreement (NSE = 0.91, WI = 0.905), outperforms both Seq2Seq and ConvLSTM. Upon hyperparameter optimization, the FbOA + NODE combination achieves significant performance improvement, with MSE of 3.95×10−7 , RMSE of 6.28×10−3 , and MAE of 3.42 × 10−4 , r = 0.977, R2 = 0.973, NSE = 0.975 and WI = 0.98. Competing optimizers (PSO, MVO, WOA, GA) also improve NODE’s performance, and across all important metrics, they are consistently below FbOA. The findings indicate that integrating NODE and FbOA yields an accurate, stable, and computationally inexpensive model for predicting cement-associated CO2 emissions, offering a potential avenue for data-driven climate and industrial planning.

This study investigates the systemic barriers hindering regional economic integration and their implications for broader regional growth. Focusing on qualitative analysis of policy reports, trade data, and regional agreements, it identifies key challenges such as political instability, security concerns, inadequate infrastructure, restrictive trade policies, and weak financial systems that limit effective integration and regional development. The research highlights how insecurity and governance issues deter foreign investment and trade partnerships, while underdeveloped transport and energy networks obstruct connectivity among neighbouring countries. Furthermore, complex trade regulations and limited access to international finance restrict economic cooperation and growth potential. The findings underscore the critical importance of promoting political stability, simplifying trade regulations, and strengthening financial systems to enhance regional integration. Collaborative efforts in infrastructure development and transit facilitation, coupled with international support for institutional reforms, are essential to overcoming these barriers. Such measures will not only facilitate seamless economic integration but also contribute to sustainable regional growth and stability.

The study examines Uzbekistan’s economic development and the implementation of green economy principles from 2017 to 2024. During this period, the country achieved notable progress in economic diversification, the adoption of renewable energy sources, and ensuring environmental sustainability. Nevertheless, challenges such as waste management and the efficient use of water resources remain pressing issues that require future attention and resolution.

This article explores the transformative role of e-commerce in reshaping the global market landscape. Through an in-depth examination of digital trade, supply chain realignment, consumer behavior, and global economic integration, the study assesses how the development of e-commerce has transcended traditional market boundaries and redefined competition, pricing, and logistics. It evaluates the influence of technological infrastructure, regulatory frameworks, and international cooperation in driving the growth of e-commerce and highlights key challenges, including data security, digital inequality, and market volatility. The article concludes with a critical outlook on the structural shifts e-commerce introduces to the global market conjuncture and its implications for the future of trade and economic policy.

This article analyzes the investment attractiveness of various countries by developing ranking systems and econometric models. These models, based on key economic indicators, evaluate countries' investment potential and provide forecasted values for the Global Innovation Index (GII). Using a weighted scoring method, we rank countries according to their investment attractiveness. The study further constructs an econometric model to explore the relationship between investment factors and innovation development, highlighting key areas for policy improvement.