Search Results (53)

The spread of infectious diseases is inherently linked to human social behavior, characterized by complexity, diversity, and openness. Intelligent agents in computer science provide a powerful framework for capturing such dynamics, enabling complex epidemic patterns to emerge from simple local rules. These agents exhibit self-organization, adaptability, and self-optimization, making them well suited for individual-level modeling. Agent-based models (ABMs) have shown promising results in epidemic simulation and policy evaluation. However, current implementations often suffer from simplistic behavioral assumptions and rigid interaction mechanisms, limiting their realism and flexibility. This paper first reviews the current landscape of epidemic modeling approaches. It then analyzes the underlying mechanisms of advanced intelligent agents, highlighting their modeling capabilities. The study focuses on four key advantages of intelligent agent-based modeling and elaborates on three critical roles these agents play in evaluating and optimizing intervention strategies. Full article

Technological developments and the integration of social media into journalistic practices have transformed the media landscape, changing how information is gathered, produced, and shared. This evolution poses challenges, including the lack of clear guidelines and practical tools for ensuring the quality of digital news content. To address these issues, IQJournalism, an intelligent quality prediction advisor, was developed. This paper outlines the methodology for the development of IQJournalism, a platform that leverages advanced AI technologies to process Greek news articles and provide real-time editing recommendations on various dimensions, including language quality, subjectivity level, emotionality, entertainment, and social media engagement. First, a qualitative study was conducted through semi-structured, in-depth interviews with 20 experts, academic researchers and media professionals to identify indicators of perceived quality in journalism. These insights were then transformed into measurable features, which served as training data for explainable machine learning-based models for quality categorization and prediction. Finally, the IQJournalism platform was designed following a user-centered iterative process that included prototyping, testing, and redesigning. The innovative approach aims to serve as a valuable tool for improving journalistic quality, contributing to more reliable and engaging online news content. Importantly, the platform is not limited to the journalistic sector, but can also be used to optimize content in various areas, such as marketing, political, and strategic communication, supporting editors seeking to improve the quality and impact of their writing. Full article

In the evolving landscape of China’s capital markets, the integration of Environmental, Social, and Governance (ESG) considerations has become increasingly crucial for investors and decision-makers. Traditional financial performance metrics often fall short in capturing the multidimensional and long-term impacts of ESG factors. This study introduces a novel computational framework that combines domain-adapted pre-trained language models with structured financial regression analysis, aiming to empirically assess the correlation between ESG disclosures and long-term financial performance. This approach allows for the simultaneous processing of both structured and unstructured ESG data, using graph-based modeling and reinforcement learning to guide sustainability aligned policy optimization. Our empirical results show that firms with consistent and well-structured ESG strategies exhibit significantly superior long-term financial outcomes compared to those with weak or inconsistent ESG engagement. This study not only confirms the value of ESG engagement in enhancing financial resilience but also offers practical recommendations for investors, regulators, and corporate decision-makers, emphasizing consistent disclosure, sector-aligned ESG investment, and proactive adaptation to policy shifts. Full article

This research aims to assess the current landscape of digital communication practices among PDO and PGI agricultural products in Southern European countries—Italy, Spain, France, Greece, and Portugal—which together account for 75% of Europe’s GI-registered agri-food products. By analyzing the GI View portal and conducting desk research to assess the presence of producer groups and the promotion of their products across digital platforms, this study offers insights into how these products are marketed online. It combines an overview of digital presence across multiple platforms with a content analysis of Facebook posts. The findings reveal that, although digital tools—especially websites and social media—are increasingly used by GI producer groups, their potential remains underexploited. Most groups maintain some digital presence, yet the strategies are inconsistent and e-commerce remains underused. Despite being inherently linked to environmental and social sustainability, these attributes are rarely communicated—particularly on Facebook. This social media channel is the most used platform among GI producer groups; however, its use is poorly optimized with an irregular posting frequency. This study recommends investments in capacity building, integrated branding approaches, and the strategic inclusion of the inherent value of GI products in digital narratives to enhance their visibility, differentiation, and sustainability communication. Full article

Despite the climate crisis, a significant barrier to sustainability is limitations to the current accounting and reporting system. These deficiencies, mean the global financial system continues to invest trillions of dollars annually in environmentally sub-optimal projects. To catalyze the economic transition away from fossil-fuel and plastic configurations to more sustainable ones, sustainability accounting and reporting (SAR) is imperative. However, theoretical contention, pragmatic concerns, and costs stoke strong resistance to SAR. The research used ablative thematic analysis to apply hermeneutic phenomenology. First, it scanned the backdrop to the SAR problem and identified a corpus of recent literature from key associated institutions. The initial interpretation of the texts disentangled SAR’s conflicting threads and generated three themes of ‘climate crisis’ and ‘conservative’ or more ‘radical’ SAR reform paradigms. Iteratively harnessing these thematic lenses, the investigation re-examined the SAR literature corpus. The textual ‘dialogue’ generated understanding of the fragmented SAR responses to the climate crisis. Accordingly, the research reformulated its first theme to ‘dystopic climate crisis fragmentation’ and refined the other themes to take account of materiality and the split between Anglo-Saxon (IFRS, SSAB) or global (UN) and continental European accounting institutions (EU, GRI). Conservatives retain a single materiality investor-focus and concede only incremental standard improvements. Radicals seek to implement double materiality with a broader spectrum of stakeholders in mind. Both approaches have theoretical as well as pragmatic advantages and disadvantages, so the SAR contention rumbles on. Whilst the standard-setting landscape is evolving, disagreements remain. Its roots of contention are philosophical and pragmatic. Philosophically, radicals strive to temper libertarian anarcho-capitalist proclivities and broaden firm responsibility. Pragmatically, social, or environmental externalities are problematic to assign or measure. Given vested interests in the destructive status quo, it would be naïve to expect a harmonious SAR Ithaca to emerge anytime soon. Yet the challenges impel an intensification of SAR dialogue and concrete actions. Rather than a scientifically nomothetic contribution, the paper provides a qualitative, artful interpretation of a complex, contentious but crucial field. Full article

Today, urbanisation and environmental changes are increasingly influencing the social and biological landscape of our planet. This systematic review aims to assess the relationship between urban–architectural and socioeconomic factors and vector concentrations in the urban environment. Following the Preferred Reporting Methodology for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the PubMed, Scopus, and Cochrane libraries were screened for studies conducted in urban contexts and those involving only arboviruses and potential exposure to arboviral vectors in urban environments, published from the beginning to 22 April 2025. Out of a total of 171 identified studies, 132 were selected for further analysis. Of these, 14 studies were eligible. The included studies reported different ways of measuring vector density and different considerations of the urban–architectural or socio-demographic factors related to it. The studies were set in different urban contexts: Asia, Central and South America, Africa and Oceania. Among the vector species, Aedes aegypti was the most analysed, often with Aedes albopictus. Socioeconomic status emerges as a determining factor. Low-income areas experience higher mosquito densities due to overcrowding, sub-optimal infrastructure, and environmental neglect. This review highlights the importance of implementing a standardised and effective global approach in urban health planning. Full article

Urban flooding is a growing concern, particularly in coastal lowland cities where climate change exacerbates hazards through rising sea levels and intense rainfall. Traditional flood defenses like fluvial polders often exacerbate urban fragmentation and maintenance costs if poorly integrated into planning. This study proposes a multifunctional assessment design framework to evaluate polder design effectiveness considering both the hydraulic and social–environmental dimensions, emphasizing blue–green infrastructure (BGI) for flood control, leisure, and landscape integration. Three design scenarios for Rio de Janeiro’s Jardim Maravilha neighborhood were modeled hydrodynamically: S1 (dike near urban areas, pump-dependent) and S2/S3 (dikes along the riverbank, gravity-driven). Results show S2/S3 outperformed S1 in storage capacity (2.7× larger volume), freeboard resilience (0.42–0.43 m vs. 0.25 m), and urban integration (floodable parks accessible to communities), though S1 had faster reservoir emptying. Under climate change, all scenarios sustained functionality, but S1’s freeboard reduced by 86%, nearing its limit. The framework’s standardized scoring system balanced quantitative and qualitative criteria, revealing trade-offs between hydraulic efficiency and urban adaptability. The optimized S3 design, incorporating external storage and dredging, achieved the best compromise. This approach aids decision-making by systematically evaluating resilience, operational feasibility, and long-term climate adaptation, supporting sustainable flood infrastructure in coastal cities. Full article

Traditional villages, as repositories of cultural heritage and natural landscapes, have gained increasing prominence in the tourism industry. However, balancing authenticity preservation with visitor satisfaction remains a critical challenge. This study employs a combined Analytic Hierarchy Process (AHP)–Scenic Beauty Estimation (SBE) approach under the theoretical framework of 4E theory (Entertainment, Education, Aesthetics, and Escapism) to comprehensively evaluate visitor satisfaction in traditional village tourism landscapes. Eight nationally designated tourism-oriented traditional villages in Anhua County, China were selected as case studies. Findings from the AHP analysis reveal that aesthetic and escapism experiences are the most influential dimensions in shaping visitor satisfaction, while entertainment and educational experiences, though secondary, remain integral to a well-rounded tourism framework. The SBE evaluation corroborates these results, highlighting that seasonal characteristics, stress relief, and cultural landscape diversity significantly enhance visitor experiences. Conversely, deficiencies were observed in social interactivity, satisfaction with educational experiences, and fulfillment of aesthetic needs, indicating areas for improvement. A strong positive correlation between AHP and SBE scores (Pearson correlation coefficient = 0.867, p < 0.01) underscores the alignment between expert-driven evaluations and visitor perceptions. These insights suggest that integrating expert-based hierarchical analysis with empirical visitor assessments provides a more robust and multidimensional framework for sustainable tourism management. Recommendations include enhancing social interactivity, optimizing educational components, enriching aesthetic experiences, and ensuring the preservation of vernacular landscapes to foster sustainable, experience-driven rural tourism development. Full article

This paper explores the integration of ecological sustainability, human-centered design, and advanced computational techniques, with a particular focus on the use of Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNNs), and Deep Recurrent Neural Networks (DRNNs) in urban landscape planning and rural landscape restoration. DRNNs, an advanced extension of traditional RNNs, are specifically designed to capture complex temporal dependencies in sequential data through deeper network architectures. These models are particularly effective in identifying intricate patterns in time-series data, making them well-suited for dynamic processes in landscape planning and ecological analysis. The study highlights the significance of applying ecological principles to urban design, aiming to create spaces that are not only visually appealing but also environmentally harmonious and socially inclusive. Additionally, the research investigates the role of installation art in public urban spaces, emphasizing its potential to foster community interaction, raise environmental awareness, and promote sustainability. By integrating data-driven approaches, such as LSTM-based lithology identification and DRNN-based ecological forecasting, the paper illustrates how advanced algorithms can optimize landscape features, predict ecological trends, and guide more informed planning decisions. Ultimately, this research underscores the need for a holistic and sustainable approach in urban landscape design that balances environmental, social, and technological dimensions, ensuring a harmonious coexistence between people and their environments. Full article

Influence maximization (IM) is a pivotal challenge in social network analysis, which aims to identify a subset of key nodes that can maximize the information spread across networks. Traditional methods often sacrifice solution accuracy for spreading efficiency, while meta-heuristic approaches face limitations in escaping local optima and balancing exploration and exploitation. To address such challenges, this paper introduces a landscape-aware discrete particle swarm optimization (LA-DPSO) to solve the IM problem. The proposed algorithm employs a population partitioning strategy based on a fitness distance correlation index to enhance population diversity. For the two partitioned subpopulations, a global evolutionary mechanism and a variable neighborhood search mechanism are designed to make a symmetrical balance between the exploration and exploitation. The fitness landscape entropy is introduced to detect the local optima and prevent the population from premature convergence during the evolution. Experiments conducted on six real-world social networks demonstrate that the proposed LA-DPSO achieves an average performance improvement of 16% compared to state-of-the-art methods while exhibiting excellent scalability across diverse network types. Full article

In the face of rapid progress in heritage preservation and cultural tourism integration, landscape planning in historic cities is pivotal to showcasing regional identities and disseminating cultural value. However, the complexity of cultural characteristic identification and the imbalance in planning often restrict the progress of urban development. Additionally, existing studies predominantly rely on subjective methods and focus on a single cultural attribute, highlighting the urgent need for research on diversified cultural perception. Using Jingdezhen, a renowned historic cultural city, as an example, this study introduces a multi-label deep learning approach to examine cultural perceptions in tourism heritage landscapes. Leveraging social media big data and an optimized ResNet-50 model, a framework encompassing artifacts, production, folk, and living culture was constructed and integrated with ArcGIS spatial analysis and diversity indices. The results show: (1) The multi-label classification model achieves 92.35% accuracy, validating its potential; (2) Heritage landscapes exhibit a “material-dominated, intangible-weak” structure, with artifacts culture as the main component; (3) Cultural perception intensity is unevenly distributed, with core areas demonstrating higher recognition and diversity; (4) Diversity indices suggest that comprehensive venues display stronger cultural balance, whereas specialized ones reveal marked cultural singularity, indicating a need for improved integration across sites. This research expands the use of multi-label deep learning in tourism heritage studies and offers practical guidance for global heritage sites tackling mass tourism. Full article

In the digital age, the rapid proliferation of misinformation and disinformation poses a critical challenge to societal trust and the integrity of public discourse. This study presents a comprehensive machine learning framework for fake news detection, integrating advanced natural language processing techniques and deep learning architectures. We rigorously evaluate a diverse set of detection models across multiple content types, including social media posts, news articles, and user-generated comments. Our approach systematically compares traditional machine learning classifiers (Naïve Bayes, SVMs, Random Forest) with state-of-the-art deep learning models, such as CNNs, LSTMs, and BERT, while incorporating optimized vectorization techniques, including TF-IDF, Word2Vec, and contextual embeddings. Through extensive experimentation across multiple datasets, our results demonstrate that BERT-based models consistently achieve superior performance, significantly improving detection accuracy in complex misinformation scenarios. Furthermore, we extend the evaluation beyond conventional accuracy metrics by incorporating the Matthews Correlation Coefficient (MCC) and Receiver Operating Characteristic–Area Under the Curve (ROC–AUC), ensuring a robust and interpretable assessment of model efficacy. Beyond technical advancements, we explore the ethical implications of automated misinformation detection, addressing concerns related to censorship, algorithmic bias, and the trade-off between content moderation and freedom of expression. This research not only advances the methodological landscape of fake news detection but also contributes to the broader discourse on safeguarding democratic values, media integrity, and responsible AI deployment in digital environments. Full article

This article critically examines De Cero a Siempre (DCAS), a cross-sectoral policy established in Colombia in 2016 to provide coordinated and comprehensive early childhood development services. The policy aims to promote optimal conditions for children from pregnancy to six years of age by addressing their nutritional, health, educational, and social needs while fostering participation and citizenship. Designed with a differential approach, the DCAS integrates and adapts services considering gender, culture, income, ethnicity, displacement, and disability. This study evaluates the DCAS policy through the human rights approach. First, we examine the conceptual definitions Second, we identify specific programs and services Third, we assess the implementation and effectiveness of these services using the official System for Monitoring the Comprehensive Development of Early Childhood. The findings reveal a strong policy framework that values human dignity and equity but highlights critical gaps in coverage, particularly in rural areas, due to geographical and social challenges. The current landscape of disability services reveals significant systemic limitations in addressing individualized developmental needs. Our comprehensive analysis exposes critical challenges in designing comprehensive intervention strategies for CWDDs. The article concludes with recommendations to enhance policy implementation and improve service delivery, ensuring equitable access for all children. Full article

This study explores visitor perceptions and behaviors regarding sustainable tourism in Brighton, focusing on the economic, environmental, and social dimensions of sustainability across key tourism sectors, including Destination Management Organizations (DMOs), Tour Operators (TOs) and Travel Agencies (TAs), and accommodation and transportation sectors. Using the Statistical Framework for Measuring the Sustainability of Tourism this study identifies critical areas for improvement and proposes a comprehensive model to enhance the sustainability and resilience of the city’s tourism supply chain. The findings reveal that certain stakeholders in the tourism supply chain are highly regarded for their community engagement and sustainability efforts, while others are seen as needing more focus on social responsibility and community engagement. Some areas show significant gaps in environmental sustainability, while others excel in economic performance but lack integration of environmental and social considerations. The final model integrates targeted approaches to address sustainability gaps across Statistical Framework for Measuring Sustainability of Tourism (SF-MST) scales. It emphasizes the need for community-focused initiatives and effective visitor management to enhance social and environmental sustainability. Economic aspects are addressed through partnerships aimed at promoting sustainable transport and implementing green certification practices. Additionally, the model highlights the importance of inclusive economic programs and transparency to strengthen the social and economic dimensions of sustainability. The integrated model advocates for a holistic, optimized tourism supply chain management approach, ensuring sustainable practices across all sectors. This research contributes actionable insights for policy and destination management, promoting a balanced approach to economic growth, environmental preservation, and community well-being in Brighton’s tourism landscape Full article

This study establishes and refines a social-landscape ecological security pattern that integrates the demand and supply of ecosystem services, providing a substantial foundation for the ecological restoration of territorial spaces. This foundation is crucial for enhancing the effectiveness of “social–ecological” systems in achieving sustainable development. Jilin Province, serving as a national ecological security buffer and experiencing rapid economic growth, exhibits a significant spatial imbalance between social and economic progress and ecological conservation. The balance of ecosystem service demand and supply is pivotal in this context, making Jilin Province an ideal study area. We employed a multifaceted approach, including MSPA, the InVEST model, landscape connectivity assessment, circuit theory, and ecological network integrity evaluation, to elucidate the spatial disparities between the demand and supply of ecosystem services. We then developed and optimized social and landscape ecological security patterns to meet human demands and safeguard ecological integrity, thereby promoting the sustainable development of “social–ecological” systems. The key findings are as follows: (1) The supply of ecosystem services shows a clear spatial gradient, with lower values in the west and higher in the east, while demand is concentrated in the central region with lower values in the east and west, indicating a pronounced spatial mismatch in Jilin Province. (2) The landscape ecological security pattern includes 18 barrier points, 33 pinch points, 166 ecological corridors, and 101 ecological sources. (3) The social–ecological security pattern comprises 119 demand sources and 150 supply–demand corridors. (4) The study introduces 14 supply–demand nodes and 47 optimization corridors, proposing zoning schemes for the eastern core protection area, the central ecological demand area, and the western core restoration area. Additionally, recommendations are concerning the optimization of the “social–ecological” system pattern. This research advances the theoretical understanding of “social–ecological” system development in Jilin Province and offers insights for more harmonized development strategies. Full article