The application of optimization algorithms is crucial for analyzing oil and gas company portfolio and supporting decision-making. The paper investigates the process of optimizing a portfolio of oil and gas projects under economic uncertainty. The literature review explores the advantages of applying various optimizers to models that consider the mean and semi-standard deviations of stochastic multi-year cash flows and revenues. The methods and results of three different optimization algorithms are discussed: ranking and cutting algorithms, linear (Simplex) and evolutionary (genetic) algorithms. Functions of several key performance indicators were used to test these algorithms. The results confirmed that multi-objective optimization algorithms that examine various key performance indicators are used for efficient optimization in oil and gas companies. This paper proposes a multi-criteria optimization model for investment portfolios of oil and gas projects. The model considers the specific features of these projects and is based on the Markowitz portfolio theory and methodological recommendations for project assessment. An example of its practical application to oil and gas projects is also provided.

 Public-private partnerships (PPPs) are vital for infrastructure development in developing countries, integrating private efficiency with public oversight. However, PPP models often face risks, particularly in Indonesia’s water sector, due to its unique geographical and regulatory challenges. This study aims to identify and evaluate risk factors specific to drinking water PPP projects in Indonesia. Using a quantitative approach, structured questionnaires were distributed to experts in the sector, and the data was analyzed using a fuzzy evaluation method. Risks were categorized into location, design and construction, financial, operational, revenue, and political. The study emphasizes that effective risk management, including identification, analysis, and mitigation, is essential for project success. It highlights the importance of stakeholder involvement and flexible risk management strategies. Comprehensive and proactive risk management is key to the success of drinking water infrastructure projects. The research suggests that an integrated and collaborative approach among stakeholders can enhance risk management effectiveness. These findings provide valuable insights for policymakers, project managers, investors, and other stakeholders, underscoring the necessity for adaptable regulatory frameworks and robust policy guidelines to improve the sustainability and efficacy of future water-related PPPs.

Weather and climate services are essential tools that help farmers make informed choices, such as choosing appropriate crop varieties. These services depend considerably on the availability of adequate investments in infrastructure related to weather forecasting, which are often provided by the State in most countries. Zimbabwean farmers generally have limited access to modern weather and climate services. While extensive attempts have been made to investigate farmers’ socioeconomic factors that influence access to and use of weather and climate services, comparative political economy analysis of weather and climate service production and use is limited. To address this knowledge gap, this study examines the production, dissemination, and usage of modern seasonal weather services through a political economy analysis perspective. The findings of this study highlight considerable discrepancies in access and use of seasonal weather forecasts between male and female farmers, those who practise African Traditional Religions versus Christians, and the minority group (Ndau tribe) and the majority group (Manyika tribe). This result suggested the presence of social marginalization. For example, minority Ndau members living in remote areas with limited radio signals and a weak mobile network have limited access to modern seasonal weather forecasts, forcing them to rely much more on indigenous weather forecasts. Further, due to unequal power relations, a greater proportion of male farmers participated in agricultural policy formation processes than their female counterparts. To promote inclusive development and implementation, deliberate efforts need to be made by State authorities to incorporate adherents of African traditional religions, members of minority tribes and female farmers in agricultural policymaking processes, including seasonal weather forecast delivery policies. Further, the study suggests the relaxation or elimination of international sanctions on Zimbabwe by the European Union, United Kingdom and the United States of America, given that they are considerably affecting marginalized groups of farmers in their climate change adaptation practices, including the use of modern weather and climate services. The vast majority of these marginalized farmers never benefitted from the land reform programme and were also not responsible for the design and implementation of this programme which triggered these sanctions.

Under the background of engineering education certification, the traditional personnel training model can’t meet the requirements of high-quality personnel training under the new engineering background. Taking Surveying and mapping engineering major of Liaoning Institute of Science and Technology as an example, this paper explores the continuous improvement of the output-oriented talent training model through collaborative education of talents training objectives, curriculum system, practical teaching system, teacher team construction, enterprises and graduates. Over the years, the surveying and mapping engineering major of our school has achieved good results in personnel training. The major actively ADAPTS to the regional development of the local economy, closely connects with the needs of regional talents, and highlights its characteristics in serving the local economy.

The technological development and growth of the telecommunications industry have had a great positive impact on the education, health, and economic sectors, among others. However, they have also increased rivalry between companies in the market to keep and acquire new customers. A lower level of market concentration is related to a higher level of competitiveness among companies in the sector that drives a country’s socioeconomic development. To guarantee and improve the level of competition, it is necessary to monitor the concentration level in the telecommunications market to plan and develop appropriate strategies by governments. With this in mind, the present work aims to analyze the concentration prediction in the telecommunications market through recurrent neural networks and the Herfindahl-Hirschman index. The results show a slight gradual increase in competition in terms of traffic and access, while a more stable concentration level is observed in revenues.