This article presents a comprehensive analysis and strategic framework for enhancing social welfare in Kazakhstan through the adoption of international social security standards. This article aims to formulate scientific and practical recommendations for enhancing the legal framework governing Kazakhstan’s social security system. It posits that integrating international social protection standards is pivotal for refining national legislation and charting future developmental courses. Employing a novel methodology, this study analyzes key documents from the International Labour Organization (ILO), the United Nations, the Commonwealth of Independent States (CIS), and the Eurasian Economic Union (EAEU). It also examines efforts to assimilate these international norms into Kazakhstan’s social security laws. The investigation reveals a stagnation in the evolution of the nation’s social sector, marked by a dearth of innovative ideas and initiatives to elevate the subpar social security standards. The adoption of international social standards emerges as a catalyst for rejuvenating the national social sphere, aiming to elevate the Kazakhstani social protection system to meet global benchmarks. This research outlines the pathways for Kazakhstan’s ratification of and accession to key social protection instruments and offers expert recommendations to support this endeavor. The conclusions and recommendations developed are poised for application in legislative reforms, aiming to amend and enhance existing laws to foster a more robust and inclusive social security framework. The findings suggest that the adoption of international social security standards not only contributes to the improvement of individual lives but also fosters social cohesion and economic stability. The article concludes with tailored recommendations for Kazakhstan, highlighting the role of stakeholder engagement, phased implementation, and continuous evaluation in the successful integration of global social security norms. This research contributes to the ongoing discourse on social security reform, offering a valuable perspective for scholars, policymakers, and practitioners involved in social welfare enhancement efforts in Kazakhstan and similar contexts.

Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.

This study updates Pereira and Pereira by revisiting the macroeconomic and budgetary effects of infrastructure investment in Portugal using a dataset from the Portuguese Ministry of the Economy covering 1980–2019, thereby capturing a period of austerity and decreased investment in the 2010s. A vector-autoregressive approach re-estimates the elasticity and marginal product of twelve infrastructure types on private investment, employment, and output. The most significant long-term accumulated effects on output accrue from investments in airports, ports, health, highways, water, and railroads. In contrast, those in municipal roads, electricity and gas, and refineries are statistically insignificant. All statistically significant infrastructure investments pay for themselves over time through additional tax revenues. Compared to the previous study, highways, water, and ports have more than doubled their estimated marginal products due to a significant increase in relative scarcity over the last decade. In addition, our analysis reveals an important shift in the impacts of infrastructure investment, now producing more substantial immediate effects but weaker long-term impacts. This change offers policymakers a powerful tool for short-term economic stimulus and is particularly useful in addressing immediate economic challenges.

This study investigates the relationship between hydrological processes, watershed management, and road infrastructure resilience, focusing on the impact of flooding on roads intersecting with streams in River Nile State, Sudan. Situated between 16.5° N to 18.5° N latitude and 33° E to 34° E longitude, this region faces significant flooding challenges that threaten its ecological and economic stability. Using precise Digital Elevation Models (DEMs) and advanced hydrological modeling, the research aims to identify optimal flood mitigation solutions, such as overpass bridges. The study quantifies the total road length in the area at 3572.279 km, with stream orders distributed as follows: First Order at 2276.79 km (50.7%), Second Order at 521.48 km (11.6%), Third Order at 331.26 km (7.4%), and Fourth Order at 1359.92 km (30.3%). Approximately 27% (12 out of 45) of the identified road flooding points were situated within third- and fourth-order streams, mainly along the Atbara-Shendi Road and near Al-Abidiya and Merowe. Blockages varied in distance, with the longest at 256 m in Al-Abidiya, and included additional measurements of 88, 49, 112, 106, 66, 500, and 142 m. Some locations experienced partial flood damage despite having water culverts at 7 of these points, indicating possible design flaws or insufficient hydrological analysis during construction. The findings suggest that enhanced scrutiny, potentially using high-resolution DEMs, is essential for better vulnerability assessment and management. The study proposes tailored solutions to protect infrastructure, promoting sustainability and environmental stewardship.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

The reduction of biodiversity and the decline in wildlife populations are urgent environmental issues with devasting consequences for ecosystems and human health. As a result, the protection of wildlife and biodiversity has emerged as one of humanity's greatest goals, not only for protecting and maintaining human health but also for environmental, economic, and social well-being. In recent years, people have become increasingly aware of the importance and effectiveness of wildlife conservation efforts alongside environmental protection measures, sustainable agricultural practices and non-harmful production procedures and services. This study describes the development and implementation of a labeling scheme for wildlife and biodiversity protection for products or services. The label is designed to encourage the adoption of sustainable and environmentally friendly production methods and services that will contribute to biodiversity conservation and the harmonic coexistence of human-wildlife. Moreover, using a case study approach, the research presents an innovative information system designed to streamline the label-awarding process, ensuring transparency and efficiency. The established system evaluates the sustainability practices and measures implemented by businesses, with a focus on honey production in this case. Additionally, the study explores the broader social implications of the label, particularly its potential to engage consumers and promote awareness of biodiversity conservation.