Search Results (4,584)

A balance between support and independence in guardianship systems is of high concern, especially with those who need help in making decisions. The research presents a novel approach to evaluating voluntary models of guardianship, focusing on the preservation of individual autonomy and examining the underlying decision symmetry in assessing diverse guardianship options. The ultimate solution to the inherent uncertainty and lack of objectivity in expert evaluations is to apply the circular q-rung orthopair fuzzy (Cq-ROF) combined compromise for ideal solution (CoCoFISo) approach, an effective multi-criteria decision-making (MCDM) model that integrates ranking and sorting views using a Cq-ROF framework within a symmetry-oriented analytical perspective. These are five major assessment factors: how well autonomy is preserved, legal and ethical adherence, psychological health, social integration aid, and risk prevention. It explores ten alternative approaches to guardianship, ranging from complete legal guardianship to community-based self-management solutions, and the use of technology as an element of support. The suggested approach can facilitate more sophisticated modelling of expert opinions, rather than relying on simplistic and straightforward distinctions and diverse evaluations. The case study results indicate that the hybrid and supported forms of decision-making could offer opportunities to preserve a high degree of personal autonomy while ensuring safety and compliance. The research gives a coherent, adaptable, and explainable approach to managing ethical and policy-level judgment concerning voluntary guardianship systems. Full article

Background: Caesarean section (CS) is a critical intervention, yet stark inequities in access persist across low- and middle-income countries (LMICs). Over the last decade, governments have introduced policies to eliminate or subsidize user fees; however, the collective impact of these initiatives on utilization, equity, and financial protection has not been fully synthesized. Methods: We conducted a systematic review in line with PRISMA 2020 guidelines. Searches were conducted in PubMed, Dimensions, Google Scholar, Scopus, Web of Science, and government portals for studies published between 1 January 2009 and 30 May 2025. Eligible studies evaluated government-initiated financing reforms, including full user-fee exemptions, partial subsidies, vouchers, insurance schemes, and provider-payment restructuring. Two reviewers independently applied the PICOS criteria, extracted data using a 15-item template, and assessed the study quality. Given heterogeneity, results were synthesized narratively. Results: Thirty-seven studies from 28 LMICs were included. Most (70%) evaluated fee exemptions. Mixed-methods and cross-sectional designs predominated, while only six studies employed interrupted time series designs. Twenty-two evaluations (59%) reported increased CS uptake, ranging from a 1.4-fold rise in Senegal to a threefold increase in Kano State, Nigeria. Similar surges were also observed in non-African contexts such as Iran and Georgia, where reforms included incentives for vaginal delivery or punitive tariffs to curb overuse. Fourteen of 26 fee-exemption studies documented pro-rich or pro-urban drift, while catastrophic expenditure persisted for 12–43% of households, despite the implementation of “free” policies. Median out-of-pocket costs ranged from USD 14 in Burkina Faso to nearly USD 300 in Dakar’s slums. Only one study linked reforms to a reduction in neonatal mortality (a 30% decrease in Mali/Benin), while none demonstrated an impact on maternal mortality. Qualitative evidence highlighted hidden costs, delayed reimbursements, and weak accountability. At the same time, China and Bangladesh demonstrated how demographic reforms or voucher schemes could inadvertently lead to CS overuse or expose gaps in service readiness. Conclusions: Government-led financing reforms consistently increased CS volumes but fell short of ensuring equity, financial protection, or sustained quality. Effective initiatives combined fee removal with investments in surgical capacity, timely reimbursement, and transparent accountability. Future CS policies must integrate real-time monitoring of equity and quality and adopt robust quasi-experimental designs to enable mid-course correction. Full article

Accurate carbon emission estimation across all operational stages of container terminals is essential for advancing low-carbon development in the transportation sector and designing effective emission reduction pathways. This study develops a two-layer carbon accounting framework that integrates vessel berthing–waiting and terminal operations, tailored to the operational characteristics of Shanghai Port container terminals. The Ship Traffic Emission Assessment Model (STEAM) is applied to estimate emissions during berthing, while a bottom-up method is employed for mobile-mode container handling operations. Targeted mitigation strategies—such as shore power adoption, operational optimization, and “oil-to-electricity” or “oil-to-gas” transitions—are evaluated through comparative analysis. Results show that vessels generate substantial emissions during erthing, which can be significantly reduced (by over 60%) through shore power usage. In terminal operations, internal transport trucks have the highest emissions, followed by straddle carriers, container tractors, and forklifts; in stacking, tire cranes dominate emissions. Comprehensive comparisons indicate that “oil-to-electricity” can reduce total emissions by approximately 39%, while “oil-to-gas” can achieve reductions of about 73%. These findings provide technical and policy insights for supporting the green transformation of container terminals under the national dual-carbon strategy. Full article

The rise of common institutional ownership has a profound impact on corporate environmental policies, and the business environment in which the enterprises operate can significantly affect the decisions of institutional investors. This study evaluates the effect of common institutional ownership on corporate environmental responsibility disclosure (CERD) practices in Chinese manufacturing firms from the performance feedback perspective. Utilizing a sample period spanning from 2008 to 2021, the study indicates several key findings. Firstly, the presence of common institutional ownership is demonstrated to enhance the level of CERD in these firms, especially soft information on environmental responsibility. Secondly, this positive effect is amplified when positive performance expectation gaps exist. Mechanism tests reveal that under the dual pressures of common institutional investor exit threats and a negative expected performance gap, firms tend to lower their level of CERD. Conversely, synergistic effects effectively promote this disclosure. Furthermore, analysis of the impact pathway demonstrates that under such conditions, common institutional ownership exerts pressure to reduce both monetary and non-monetary private benefits accruing to management, thereby leading to optimized CERD. In addition, heterogeneity analysis indicates a more significant effect of common institutional ownership on CERD enhancement in private enterprises compared to their state-owned counterparts, particularly when positive performance expectation gaps are present. Full article

The integration of emerging technologies is reshaping the teaching skills required in the 21st century, yet little evidence exists on how contextualized training supports rural teachers in adopting active methodologies and critically incorporating AI into entrepreneurship education. This study evaluated the impact of a 40-h professional development program implemented in Educational District 15D01 in the Ecuadorian Amazon. Thirty-nine secondary school teachers participated (mean age = 43.1 years); 36% lacked prior entrepreneurship training, and 44% had not recently mentored student projects. A sequential explanatory mixed-methods design was employed. The quantitative phase employed a 22-item questionnaire that addressed four dimensions: entrepreneurial knowledge, competencies, methodological strategies, and AI integration. Significant pre–post improvements were found (p < 0.001), with large effects for knowledge (d = 1.43), methodologies (d = 1.39), and AI integration (d = 1.30), and a moderate effect for competences (d = 0.66). The qualitative phase analyzed 312 open-ended responses, highlighting greater openness to innovation, enhanced teacher agency, and favorable perceptions of AI as a resource for ideation, prototyping, and evaluation. Overall, the findings suggest that situated, contextually aligned training can strengthen digital equity policies, foster pedagogical innovation, and empower educators in underserved rural communities, contributing to sustainable pathways for teacher professional development. Full article

As cattle are criticized for contributing to environmental problems by emitting pollutants, it is expected that environmental regulations on livestock will be strengthened. This will lead to an increase in the costs and benefits associated with these regulations. This paper develops a model that clearly shows the effects of environmental regulations on the production costs for cattle-breeding farmers and the changes in social welfare, as well as environmental benefits. The benefits associated with the regulation are measured by evaluating reductions in both greenhouse gas (GHG) and ammonia emissions. These benefits are then compared to the reduction in social welfare. According to the analysis, the reduction in social welfare, in terms of consumer and producer surplus, outweighs the environmental benefits. These results suggest that, in designing environmental regulations, policy measures are needed to alleviate producers’ economic burdens and minimize reductions in social welfare through byproduct utilization and technical support. Furthermore, this study contributes to laying the institutional foundation for the sustainable development of the livestock industry and the reduction in management costs associated with manure treatment. Full article

The rapid advancement of kinetic pursuit technologies has significantly increased the difficulty of evasion for high-speed UAVs (HSUAVs), particularly in scenarios where two collaboratively operating pursuers approach from the same direction with optimized initial space intervals. This paper begins by deriving an optimal initial space interval to enhance cooperative pursuit effectiveness and introduces an evasion difficulty classification framework, thereby providing a structured approach for evaluating and optimizing evasion strategies. Based on this, an intelligent maneuver evasion strategy using semantic classification progressive learning with twin delayed deep deterministic policy gradient (SCPL-TD3) is proposed to address the challenging scenarios identified through the analysis. Training efficiency is enhanced by the proposed SCPL-TD3 algorithm through the employment of progressive learning to dynamically adjust training complexity and the integration of semantic classification to guide the learning process via meaningful state-action pattern recognition. Built upon the twin delayed deep deterministic policy gradient framework, the algorithm further enhances both stability and efficiency in complex environments. A specially designed reward function is incorporated to balance evasion performance with mission constraints, ensuring the fulfillment of HSUAV’s operational objectives. Simulation results demonstrate that the proposed approach significantly improves training stability and evasion effectiveness, achieving a 97.04% success rate and a 7.10–14.85% improvement in decision-making speed. Full article

In this article, we present a novel reinforcement learning-based framework in the discrete cosine transform to achieve better image steganography. First, the input image is divided into several blocks to extract semantic and structural features, evaluating their suitability for data embedding. Second, the Proximal Policy Optimization algorithm (PPO) is introduced in the block selection process to learn adaptive embedding policies, which effectively balances image fidelity and steganographic security. Moreover, the Deep Q-network (DQN) is used for adaptively adjusting the weights of the peak signal-to-noise ratio, structural similarity index, and detection accuracy in the reward formulation. Experimental results on the BOSSBase dataset confirm the superiority of our framework, achieving both lower detection rates and higher visual quality across a range of embedding payloads, particularly under low-bpp conditions. Full article

As governments increasingly explore digital financial instruments to diversify funding channels and expand citizen participation, Thailand’s G-Token represents an early attempt to integrate blockchain technology into sovereign debt issuance. This study examines its potential implications through a multi-dimensional risk and governance framework, situating the analysis within both domestic regulatory structures and international benchmarks. The evaluation considers macroeconomic effects—such as potential shifts in monetary policy transmission, bank disintermediation risks, and systemic liquidity impacts—alongside micro-level concerns involving investor protection, market integrity, and financial literacy. Using comparative analysis with the European Union, Singapore, and United States regulatory approaches, the paper identifies critical gaps in legal classification, oversight maturity, and structural safeguards. Findings indicate that while Thailand’s design—particularly its separation from payment systems—supports monetary coherence, its ad hoc legal integration, reliance on administrative investor protections, and early-stage market infrastructure pose vulnerabilities if adoption scales. The study concludes that achieving long-term viability will require explicit statutory authorization, enhanced disclosure and governance standards, strengthened interagency oversight, and inclusive market access strategies. These insights provide a structured basis for emerging economies seeking to adopt government-backed tokenized instruments without undermining financial stability or public trust. Full article

The COVID-19 pandemic caused the world to pause temporarily on an almost planetary scale. The creation and diffusion of knowledge about environmental planning and public health are now almost taken for granted. However, such processes were rather different in pre-pandemic times. It took a substantial dose of labor and resources to generate the information needed to produce useful and usable knowledge, and especially to make it available to others in a timely and effective way. As automobility has come to occupy center stage in the lives of an increasing number of suburbanized dwellers, it has taken multiple energy and public health crises, bold leadership, and the real threat of climate change to create the conditions needed to bolster sustainable Non-Motorized Transportation (NMT) as a complement to cleaner and more convenient mass transit options in cities. How does knowledge about sustainable NMT get created? How are sustainable NMT innovations diffused? How can technological and societal transitions to more sustainable realities be nurtured and augmented? This article utilizes a longitudinal and integrated knowledge creation and diffusion model with a Participatory Planning Process to analyze the adoption of measures aimed at reducing the negative consequences of too much automobility and encouraging higher levels of walking, cycling, and mass transportation. The research methods comprised autoethnographic, qualitative, and policy evaluation techniques. The study makes use of the means and ends matrix to discuss cases from five distinct realms: personal, academic, institutional, volunteering NGO, and private sector. The key findings and lessons learned promote scenarios of managed degrowth and sustainable urban transitions. Full article

This study investigates the development and application of the GDELT (Global Database of Events, Language, and Tone) news database. Through experiments, we conducted a quantitative statistical analysis of the GDELT event database to evaluate its practical characteristics. The results indicate that although the database achieves comprehensive coverage across all countries and regions and includes most major global media outlets, the accuracy rate of its key fields is only approximately 55%, with a data redundancy as high as 20%. Based on these findings, while the GDELT data demonstrates good coverage and data integrity, data correction and deduplication are recommended before its use in research contexts and industrial applications. Subsequently, a survey of the existing literature reveals that current studies using GDELT primarily focused on event-related metrics, such as event quantity, tone, and GoldsteinScale, for application in international relations analysis, crisis event prediction, policy effectiveness testing, and public opinion impact analysis. Nevertheless, news constitutes a fundamental channel of information dissemination in media networks, and the propagation of news events through these networks represents a critical area of study for information recommendation, public opinion guidance, and crisis intervention. Existing research has employed the Event, GKG, and Mentions tables to construct cross-national news flow network models. However, the informational correlations across different data table fields have not been fully leveraged in preliminary data selection, leading to substantial computational overhead. To advance research in this field, this study employs chained list queries on the Event and Mentions tables within GDELT. Using social network analysis, we constructed a media co-occurrence network of event reports, through which core hubs and associative relationships within the event dissemination network are identified. Full article

This paper presents an experimental evaluation of the connectivity reliability of a LoRaWAN (Long Range Wide Area Network), deployed in a rural area of Mozambique, focusing on the influence of distance and relative altitude between end nodes and the gateway. The absence of telecommunications and power infrastructure in the study region provided a realistic and challenging scenario to assess LoRaWAN’s feasibility as a low-cost, low-power solution for remote sensing in disconnected environments. Field trials were conducted using an Arduino-based node (with 2 dBi antenna) powered by a 2200 mAh power bank, with no GPS or cellular support. Data were collected at four georeferenced points along a 1 km path, capturing Received Signal Strength Indicator (RSSI), Signal-to-Noise Ratio (SNR), and Packet Delivery Rate (PDR). Results confirmed that both distance and terrain elevation strongly affect performance, with significantly degraded metrics when the end nodes were located at lower altitudes relative to the gateway. Despite operational constraints, such as the need for manual firmware resets and lack of real-time monitoring, the network consistently achieved PDR above 89% and remained operational autonomously for over 24 h. The study highlights the effectiveness of installing gateways on natural elevations to improve coverage and demonstrates that even with basic hardware, LoRaWAN (Low Power Wide Area Network), is a viable and scalable option for rural connectivity. These findings offer valuable empirical evidence to promote national digital inclusion policies and future LPWAN deployments. Full article

Financial institutions, researchers, and policymakers are taking steps to promote financial inclusion, a crucial aspect for social and economic development. This study explores the extent of financial inclusion (FI) in Zimbabwe’s commercial banks. This study employed a mixed-methods approach. A relationship mapping was conducted on the bank customers’ survey, and a thematic analysis was performed on bank executives to evaluate bank challenges and strategies. The findings confirmed positive strides towards achieving financial inclusion. Gaps in financial inclusion were identified in the high rate of people using informal channels and the limited policies in creating a conducive environment for financial inclusion. The study contributes to the ongoing debate by the World Bank in support of financial inclusion as an effective solution for countries like Zimbabwe, which is experiencing a severe macro crisis. The study adds to the emerging financial inclusion literature, proposing solutions to reduce financial exclusion in developing economies. Based on the study findings, policymakers should create a conducive environment for commercial banks and consumers of financial products and services in Zimbabwe. Full article

Background/Objectives: Hepatitis B virus (HBV) remains a persistent challenge for transfusion safety. Although testing for hepatitis B surface antigen (HBsAg) and nucleic acid testing (NAT) reduces transmission risk, antibodies to hepatitis B core antigen (anti-HBc) and antibodies to hepatitis B surface antigen (anti-HBs) provide additional insight into past infection and vaccine-induced immunity. We aimed to determine their seroprevalence among blood donors in southern Croatia and assess associations with age, occupation, and time since vaccination. Methods: This cross-sectional study was conducted between February and November 2024 at two regional transfusion centers in southern Croatia. A total of 1008 voluntary blood donors, all HBsAg- and NAT-negative, were tested for anti-HBc and anti-HBs using chemiluminescent microparticle immunoassay. Demographic and vaccination data were collected through verified medical records. Results: Anti-HBc was detected in 0.5% of donors, exclusively among the unvaccinated. Protective anti-HBs levels were found in 38.1% overall and 70.6% of vaccinated donors, with significant declines by age and more than 15 years post-vaccination (p = 0.024). Healthcare workers showed higher seroprotection than non-healthcare donors (67.0% vs. 35.1%; p < 0.001), although one-third still lacked protective levels. Conclusions: HBV exposure was rare, but waning vaccine-induced immunity was evident, with protective anti-HBs levels in 70.6% of vaccinated donors, declining with age and time since vaccination. These findings highlight the need for periodic monitoring of anti-HBs and targeted booster strategies, especially in older and occupationally exposed groups. HBsAg and NAT provide a high level of transfusion safety, while the role of routine anti-HBc testing in this low-endemic context should be carefully evaluated in view of its potential benefits and drawbacks. Donor-based surveillance is a valuable tool for evaluating long-term vaccine effectiveness and guiding public health policy. Full article

The sustainable development of society requires the incorporation of environmental, social, and governance (ESG) principles. While ESG assessments are widely used in corporate settings, their application in healthcare settings, such as hospitals, remains underexplored. This study aimed to develop a comprehensive evaluation framework integrating ESG and digital transformation (DX) with traditional hospital efficiency and effectiveness assessments. Using open data, financial reports, and hospital website scraping, we applied a slack-based model (SBM) of data envelopment analysis (DEA) and super-efficiency SBM-DEA to calculate sustainability scores across four dimensions: overall sustainability, efficiency, effectiveness, and ESG/DX performance. Results showed that all three components—efficiency, effectiveness, and ESG/DX—were positively associated with overall sustainability. However, ESG/DX performance negatively impacted profitability in smaller hospitals, and improved effectiveness in rehabilitation hospitals was linked to higher operational costs. These findings suggest that while ESG and DX contribute to long-term sustainability, their short-term financial burden may challenge certain hospital types. The proposed index provides valuable insights for hospital management and policy development, aiming to advance ESG and DX initiatives in healthcare. Full article