Asia Pacific Academy of Science Pte. Ltd.
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Geographical indications in Indian agriculture products: A pathway to sustainability and social development
Full text linkGeographical Indications (GIs) are one of the important types of Intellectual Property Rights (IPRs) that are based on the geographical region. In light of this, the geographical region is vital for innovation to develop the regional economy and significant to understanding innovative performance in the particular region. With this context, the objectives of the paper are 1) to assess GIs products and sketch the historical development of GI in India; 2) to explore the scenario of agriculture products registered under the GIs; and 3) to address challenges of GIs during registration. Furthermore, the study is based on secondary data obtained from the Geographical Indication Registry of India. Findings: The study shows that the number of agricultural product registrations has increased in the last few years. This increase may be attributed to the new IPR policy regime and heightened public awareness
Receptivity of flow in a square lid driven cavity to implicit numerical excitations for high-fidelity HPC
Full text linkThis study aims to investigate the effects of implicit numerical excitation on the receptivity of flow inside a square lid-driven cavity (LDC) leading to bifurcation and instability for a fixed (257 × 257) grid with different temporal resolutions via the solution of the Navier-Stokes equation. Computational results have been provided showing the flow dynamics of the LDC problem as explained with a time series at a representative point near the top corner of the cavity at (0.95, 0.95) for supercritical Reynolds numbers with respect to the bifurcation phenomenon by lowering the time step. As the accuracy of numerical methods plays a vital role in capturing the dynamics at different Reynolds numbers, this vortex-dominated flow is explained for bifurcation and instability. We propose this as a benchmark problem for the direct numerical simulation (DNS) and for machine learning (ML) of fluid flow that will lead to efficient ML algorithms and an understanding of flow receptivity, instability, and transition by DNS
Some applications of partial differential equations in medical image processing
Full text linkThe second-order nonlinear diffusion parabolic partial differential equations models have been widely applied in image restoration. However, the numerical results in the literature treat only the case without source term. In this paper, we have developed a general calculation code which is based in a consistent explicit approximation finite difference method scheme. Furthermore, the paper provides satisfying answers with a nonlinear source term relying on the image solution and its gradient. Numerical experiments are presented to show the robustness of the cases with source term to obtain better results in image denoising restoration using measures as Peak Signal-to-Noise Ratio (PSNR) and SNR of filtering and noisy image
Corporate carbon disclosure: Methods, motivations, and impacts
Full text linkIn the context of the global shift toward a low-carbon economy, carbon disclosure has emerged as a crucial tool for facilitating the low-carbon transition of firms and addressing climate change. As a result, it has become an increasingly prominent focus in academic research and policy making. This paper reviews the existing literature on carbon disclosure, examining the methods, standards, motivations, and impacts associated with current research in this area. Based on this analysis, the paper identifies key gaps in the existing literature and suggests directions for future research, aiming to contribute to the advancement of theoretical understanding and provide a valuable reference for future studies
Research on the impact of ESG performance on the investment efficiency of enterprises
Full text linkSince the twenty-first century, the severity of the climate and environmental issues has continued to climb; how to achieve harmony between man and nature has become an unavoidable issue in the post-industrial era; in order to scientifically assess the sustainable development potential of enterprises, relevant departments and organizations have jointly constructed an ESG evaluation system, making it a hot spot of market concern. The research on ESG and corporate investment efficiency is still insufficient and mostly focuses on the impact of single ESG factors. Based on this, this paper innovatively starts from the global ESG perspective. It takes the data of China’s A-share listed companies from 2018 to 2022 as the research object, aiming at deeply exploring the actual impact of ESG performance on investment efficiency. At the same time, this paper analyzes the difference of this effect under the variables of corporate nature, industry characteristics, and market attention. The study results show that ESG performance significantly optimizes firms’ investment efficiency, and the inhibition effect on overinvestment is particularly significant. With the deepening of the research, it can be found that the positive impact of ESG performance on investment efficiency in the more heavily polluted industries is smaller than that of lightly polluted enterprises. This paper provides recommendations for government departments, third-party ESG rating agencies, and relevant enterprises based on the above research results. These recommendations are expected to promote the improvement of the ESG rating system, improve investment efficiency, and help the administration establish a more comprehensive ESG ecosystem
Metaverse in Smart Cities: Transforming Urban Life and Governance
No full textThe integration of metaverse technologies within Smart Cities (SCs) is transforming urban governance and citizen engagement. Despite the increasing academic and industry interest, research on the practical applications of the metaverse in SCs remains fragmented. This study addresses this gap through a systematic literature review on how metaverse-driven solutions impact economic transformation, governance, mobility, sustainability, and social interactions in urban environments. Motivated by the growing demand for immersive, data-driven, and participatory SC solutions, this research applies Giffinger’s SC model to evaluate metaverse integration across key SC dimensions. The study synthesizes findings from existing applications and case studies, such as Metaverse Seoul, Dubai’s Metaverse Strategy, Virtual Helsinki, and Tampere’s CitiVerse initiative, to illustrate the diverse ways in which cities are leveraging metaverse technologies. These applications demonstrate the metaverse’s potential in digital governance, Artificial Intelligence (AI)-driven urban planning, e-participation, transportation optimization, and climate resilience strategies. This research contributes to the field by providing a comprehensive framework for understanding the benefits and challenges of metaverse-driven SC models. The findings suggest that while metaverse adoption in SCs presents significant advantages in efficiency, participation, and innovation, it also entails challenges related to technological accessibility, governance frameworks, and security measures that must be addressed for broad uptake. The study’s impact extends to policymakers, urban planners, and technology developers by offering strategic insights for responsible and inclusive metaverse adoption. Ultimately, this study provides a structured roadmap for integrating metaverse technologies into smart urban ecosystems, ensuring their long-term viability, accessibility, and effectiveness in shaping the cities of the future. 
Visitor perceptions of over tourism: Text-mining insights from Seoul and Bali
Full text linkThis study examines the impact of overtourism on visitor experiences in Bali, Indonesia, and Seoul, South Korea, by analyzing online user-generated reviews from popular tourist locations. The selected sites in Seoul include Myeongdong Shopping Street, Bukchon Hanok Village, and Hongdae Street, while Bali’s sites comprise Penglipuran Village, Kuta Beach, and Seminyak. A total of 1080 reviews per city (360 per location) were collected to ensure a robust and balanced dataset for comparative analysis. To extract visitor perceptions related to congestion, crowding, and other overtourism indicators, reviews were sourced using Outscraper.com, a web-based data extraction tool. A keyword-based filtering approach was applied, focusing on terms such as “noisy,” “traffic,” and “tourist” to identify relevant reviews that reflect visitor concerns about overcrowding and its associated effects. To maintain objectivity and representativeness, 360 reviews per location were randomly selected from the filtered dataset, ensuring a balanced sample of visitor opinions across both urban and island-based tourism destinations. By applying text-mining techniques, this study uncovers key themes and sentiment patterns that define visitor experiences in over-touristed areas. The findings offer valuable insights for tourism stakeholders seeking to mitigate the negative effects of overtourism while improving destination sustainability and visitor satisfaction
Decoding digital complexity: Reconciling the sustainability innovation dichotomy in tourism competition through share value relational capital frameworks
Full text linkThis pioneering study presents a comprehensive examination of the intricate interrelationships between digital transformation, sustainable supply chain strategy (SSCS), share value relational capital (SVRC), frugal innovation (FI), ambidexterity (AMB), and sustainable competitive advantage (SCA) within contemporary tourism organizations. Employing a structural equation modeling approach, the research investigates the causal relationships among these constructs across Indonesia’s primary tourism destinations. The study reveals distinct strategic pathways through which organizations can enhance their sustainable competitive positioning, with share value relational capital emerging as a critical mediating mechanism. The findings underscore the importance of digital transformation and sustainable supply chain strategies in cultivating strong stakeholder relationships, which in turn facilitate the development of frugal innovation capabilities and ambidextrous practices, ultimately contributing to sustainable competitive advantage. The research offers valuable theoretical and managerial implications, extending the application of the resource-based view and the technology-organization-environment framework to the tourism industry. However, the study’s limitations, such as its focus on the Indonesian context and the cross-sectional nature of the data, present opportunities for future research to further expand and refine the understanding of these complex phenomena. By addressing these limitations and exploring new research directions, scholars can continue to advance knowledge of these critical issues and provide valuable insights for tourism organizations seeking to enhance their competitive position in an increasingly dynamic and challenging market environment
Parallelism, traveling waves and modular biodiversity interfaces in non-stationary ecosystems
Full text linkThe present paper treats mainly two questions, namely the mathematical characterization of the notion of biodiversity of a border interface between two adjacent ecosystems, and the role of human interference in the physical reality of interacting multi-species systems. Mathematically, the techniques of reaction-diffusion modeling, Turing’s notion of flow matrices and Verhulst logistic growth dynamics are introduced, in order to model the complex interactions in a fractal, non-stationary ecosystem. A new key approach is the combined use of flow matrices and Verhulst growth dynamics with Laplace transforms. However, these findings so far remain theoretical, not in the least because of the widespread interference of human activities with ecological developments, both planned and unplanned. When comparing mathematical models and the actual physical dynamics of ecosystems, parallel trends as well as species-specific, unique deviations are conspicuous. Especially the latter remain hard to predict, indicating the limited value of mathematical predictions for the actual biodiversity trends in the field. Moreover, in a specific case study from the Netherlands related to the ecology of game mammals and a top-predator (the Wolf), it appears that not only contemporary ecological management operations, but also the contingency of measures from a historical past (exceeding 200 years) play a significant role in understanding the human interference factor in nature (designated as the Anthropocene factor)
Inherit variability characterization considering piezocone test data: Application to bauxite tailings
Full text linkVariability characterization is a key component in the reliability assessment of geotechnical systems, particularly in scenarios involving tailings deposits, where spatial heterogeneity can critically impact design safety. Despite advances in modeling spatial randomness, many reported cases still rely on theoretical assumptions to define appropriate statistical characterizations—such as theoretical probability density functions (PDFs) and correlation structures—which may misrepresent site-specific conditions. To bridge this gap, piezocone penetration tests (CPTu) stand out as promising tools for providing continuous measurements along a vertical profile that can be used to define statistical behavior and avoid bias. This paper presents a spatial variability characterization of a bauxite tailings deposit based on mechanical parameters derived from CPTu data. The study includes basic statistical analysis—mean (μ), standard deviation (s), coefficient of variation (CV)—alongside a comparison with theoretical PDFs. Subsequently, spatial correlation is evaluated through covariance analysis and estimation of the vertical scale of fluctuation (δ), using a dedicated subroutine that fits theoretical autocorrelation models (TAMs). The deposit is classified as highly variable according to the IcRW index. The normal and Weibull PDFs best represent the data distributions. The vertical scales of fluctuation vary significantly: 0.01 m to 4.43 m for cone resistance (qc), 0.01 m to 4.36 m for sleeve friction (fs), and 0.01 m to 5.00 m for pore water pressure (u2). These findings offer valuable input for probabilistic stability and serviceability analyses, contributing to safer and more informed geotechnical designs involving mine tailings