Asia Pacific Academy of Science Pte. Ltd.
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Generating minimal topologies from κ-neighborhoods and primals
Full text linkThis manuscript presents innovative rough approximation operators based on an abstract structure called “minimal topology”. This approach offers greater flexibility than traditional topological frameworks by removing the conventional closure requirements for unions and intersections inherent in standard topology, thereby expanding its applicability. We construct eight types of minimal topologies using Nκ-neighborhood systems and the concept of primals. The relationships between these topologies are examined, with a focus on identifying conditions under which they are equivalent. New rough-set models are derived from these minimal topologies, and key properties of their lower and upper approximations are established. Additionally, we apply these approximations to classify subset regions and compute their accuracy measures
Competency-driven decision making in data-centric offshoring: A fuzzy analytical hierarchy approach
Full text linkThis research addresses a gap in offshore outsourcing studies by examining service providers’ competencies in Big Data Analytics as a Service (BDAaaS), Business Process Outsourcing (BPO), and Artificial Intelligence as a Service (AIaaS). The accelerating evolution of AI and data-centric industries necessitates this research to elucidate the essential competencies for achieving excellence in these domains. To overcome subjectivity in evaluating qualitative attributes, the fuzzy Analytic Hierarchy Process (AHP) is employed to assess the significance of service provider capabilities. The findings reveal variations in the importance of provider capabilities across BDAaaS, BPO, and AIaaS sectors. These results align with the strategic goals of many Indian IT outsourcing firms. By highlighting the differing competency requirements in these emerging cloud-based services, the study contributes valuable insights for service providers looking to enhance their competitive position in the global market. This research provides a foundation for future studies on provider competencies in the evolving landscape of data-driven cloud services
Decision-making models under conditions of uncertainty of formation, description and intellectual analysis of complex data files
Full text linkResearch objective: to prove the feasibility of forming a problem-oriented array under complex conditions of uncertainty by using different options for modeling decision-making and selecting the optimal model. Formation, description, and intellectual analysis of a complex data set, which is an example of a problem-oriented library-museum-archival-information array on nobelistics, are carried out under conditions of uncertainty due to the ambiguity of attribution of each element to this array. The possibility of modeling decision-making in these conditions is shown, the best of which is the optimal formation, description, and intellectual analysis of a complex array of problem-oriented data. A typical information situation is used for modeling when the decision-making body has knowledge of the a priori probability distribution on the state elements of the data array. For each of the seven variants of information situations, a set of criteria for making optimal decisions is selected; each criterion is mathematically described. The real functioning subject-oriented library-museum-archive-information data array on nobelistics of the International Nobel Information Center, consisting of the Nobel Scientific Library, the Museum of the Nobel Family and Nobel Prize Laureates, the Archive of the Nobel Family and Nobel Prize Laureates, and electronic databases on nobelistics, was used
Metafusion: hybrid ML-based object recognition and GPU rendering for real-time 3D metaverse visualization
No full textThe metaverse, as a shared virtual collective space, holds unparalleled promise for engaging 3D experiences through augmented reality (AR) and virtual reality (VR). Despite notable progress, there still exists a void in the proper visualization of intricate data and environments in real-time. This article suggests a novel approach utilizing AR/VR technologies to enhance 3D visualization in the metaverse. Through the integration of real-time processing of data, multi-layered virtual environments, and advanced rendering methods, the envisioned system increases interaction, immersion, and scalability. The computational model relies on hybrid algorithms that integrate machine learning-based object recognition and GPU-based rendering efficiency. This work introduces a new hybrid method for improving real-time 3D visualization in Metaverse through the integration of machine learning (ML)-based object identification and GPU-based rendering. The system uses the identified importance of objects to dynamically adjust the level of detail (LOD) of individual objects in the scene to optimize rendering quality and computational performance. The major system components are an object recognition module that classifies and ranks objects in real-time and a GPU rendering pipeline that dynamically scales the rendering detail according to the priority of the objects. The algorithm tries to achieve the trade-off between high visual quality and system performance by using deep learning for precise object detection and GPU parallelism for efficient rendering. Experimental outcomes illustrate that the introduced system realizes considerable enhancements in rendering speed, interaction latency, and visual quality compared to common AR/VR rendering methods. The results confirm the prospects of fusing AI and graphics to develop more effective and visually sophisticated virtual environments
Urinary lithiasis in pediatrics
Full text linkRenal lithiasis is an infrequent entity in childhood and its incidence is increasing in developed countries. It affects white individuals more than African-Americans in a 4:1 ratio, with male predominance. There are geographical, racial and genetic factors involved in its pathogenesis, which also depends on physicochemical factors (renal elimination of water and solutes, urinary pH, balance between factors that stimulate/inhibit crystallization), anatomical alterations, infections and socioeconomic changes; which over time have produced changes in dietary habits, which have modified the frequency, chemical composition and location of calculi. Despite its rarity, lithiasis should be considered in order to avoid irreversible renal damage. The availability of less aggressive therapy has reduced surgical indications to 5%, opening new perspectives in the treatment of urolithiasis in childhood
Unequal access to drinking water in the city of Doba (Chad): An urban political ecology perspective
Full text linkWithin the context of climate change and other environmental stressors, water scarcity has become a major concern in urban areas of the Sahel region of Africa. Water is an important resource and its scarcity which is exacerbated by socio-economic inequalities has created unequal power relations and conflicts. From this guiding premise, this work seeks to examine challenges in ensuring effective drinking water supply and how they have reshaped relations in urban areas using the case of Doba. A mixed methods approach was employed and includes documentary research, a questionnaire survey with 120 purposively selected households, 11 in-depth interviews and a collection of water samples for quality analysis. Data collected was analyzed qualitatively and quantitatively while water quality analyses were conducted at the Sarh laboratory. Under the lens of the Urban Political Ecology (UPE) approach, results revealed that households drink water from boreholes (31%), open wells (48%), springs (8%) and pipe born water (20%). The physicochemical analysis showed an iron level of 0.24 mg/L in tap water and the turbidity rate of 48.20 Nephelometric Turbidity Units (NTU) in well water while bacteriological analysis gives a total aerobic chlorine level of 100 CFU/100 ml in all the waters sources analyzed. These inequalities results from poor state of infrastructure, climate change and socio-economic differences at the level of households. This has resulted to conflicts between the state water supplying institutions and dwellers and between dwellers themselves over water sources. This work has a policy implication as the provision of drinking water requires concerted efforts between all stakeholders
Evaluating plastic bag levies: A systematic review of behavioural, regulatory, and normative pathways
No full textSingle-use plastic bags remain a critical contributor to plastic pollution, with ecological impacts ranging from terrestrial litter to marine ecosystem degradation. In response, governments worldwide have introduced financial disincentives, regulatory restrictions, and educational campaigns to curb their consumption. However, the relative effectiveness and sustainability of these interventions remain contested. This systematic review followed PRISMA 2020 guidelines. A comprehensive search was conducted in the Web of Science Core Collection using the Boolean string (“levies” OR “charge”) AND (“single-use plastic” OR “plastic bag”), yielding 2445 records. After applying filters for publication year (2007–2025), article type, and English language, 10,496 records were screened. A total of 136 full-text articles were assessed for eligibility, 16 met the inclusion criteria. Findings revealed that economic instruments, particularly levies and charges, consistently produced the most substantial reductions in plastic bag consumption. Regulatory and campaign-based approaches improved awareness but lacked durability unless coupled with financial disincentives. Educational and social-norm interventions reinforced pro-environmental behaviours, amplifying compliance and long-term sustainability when integrated with levies. Overall, multi-layered strategies combining economic, regulatory, and cultural levers were the most effective. Economic instruments are necessary but not sufficient on their own. Integrated approaches by pairing charges with enforcement, education, and social-norm reinforcement to offer the greatest potential to reduce plastic bag use and align with global sustainability goals.
 
The impact of climate change on agriculture and economic growth in Cameroon
Full text linkThe agricultural sector is both one of the key sectors of the Cameroonian economy and the one most influenced by the climate. As indicated in the fifth report of the Intergovernmental Panel on Climate Change, the increase in the concentration of greenhouse gases in the atmosphere, the rise in temperature, changes in rainfall patterns, changes in cloud cover, etc., will continue to change. But how does climate change affect agricultural activities and influence economic growth in Cameroon? The aim of this article is to analyze the impact of climate change on agricultural production and on economic growth in Cameroon over the period 1990–2020. To achieve this objective, a stochastic production function model developed by Just and Pope was used. We also used CO2 emissions as a proxy for climate change. The results obtained clearly show that the increase in CO2 emissions has a negative impact on agricultural production and on economic growth
Quantile regression analysis of economic indicators’ impact on employment across G7 countries
Full text linkThis study investigates the intricate relationship between pivotal economic indicators and employment outcomes across various quantiles of the employment distribution within G7 nations, with the objective of elucidating the heterogeneous impacts of these factors on employment. Employing quantile regression analysis, the research assesses the effects of GDP growth, Foreign Direct Investment (FDI), inflation, interest rates, Research and Development (R&D), and trade on employment at distinct quantiles (0.05, 0.25, 0.50, 0.75, and 0.90) of the employment spectrum. This methodological approach allows for a deeper understanding of how these economic determinants exert differential influences across both high-wage and low-wage sectors. The findings reveal that GDP, FDI, and R&D significantly stimulate job creation, especially within high-employment sectors, whereas the effects of inflation and interest rates are more nuanced, benefiting low-employment sectors in some instances but adversely impacting high-employment sectors due to rising costs and reduced investment. Unemployment consistently diminishes job opportunities across all employment quantiles, with its most pronounced effects felt in low-employment sectors. This study makes a novel contribution to the existing literature by utilizing quantile regression to provide a more granular understanding of how economic variables influence labor market outcomes across diverse segments. It underscores the necessity for targeted economic policies designed to address the specific needs of both high- and low-employment sectors, offering critical insights for policymakers aiming to cultivate inclusive and resilient labor markets
Liquiritigenin attenuates myocardial ischemia-reperfusion injury by activating the Nrf2/HO-1 pathway
No full textBackground: The Nrf2/HO-1 signaling pathway is a critical antioxidative stress and cytoprotective pathway, and oxidative stress plays a significant role in myocardial ischemia-reperfusion injury (MIRI). Liquiritigenin, a flavonoid compound derived from licorice, is hypothesized to alleviate MIRI, though its specific mechanism remains unclear. Methods: Following a 15-min pretreatment with liquiritigenin, animals underwent myocardial ischemia-reperfusion injury induction comprising 30-min coronary occlusion and 2-h reperfusion. Continuous cardiac monitoring incorporated both electrocardiography (ECG) and ventricular pressure dynamics, specifically tracking systolic pressure (LVSP), end-diastolic pressure (LVEDP), and ventricular contractility indices (±dp/dtmax). Post-experimental biospecimen analysis included: Myocardial injury evaluation: Serum quantification of lactate dehydrogenase and CK-MB isoenzyme levels. Redox status assessment: Measurement of antioxidant enzyme activities (SOD, GSH) and lipid peroxidation biomarker MDA concentration Histopathological damage: Evaluated via hematoxylin-eosin (HE) staining. Apoptosis: Detected by TUNEL assay. Protein expression: Western blot analysis of Nrf2/HO-1 pathway components (Nrf2, Keap1, HO-1). Conclusion: Liquiritigenin exerts cardioprotective effects against MIRI by activating the Nrf2/HO-1 signaling pathway, thereby attenuating post-reperfusion oxidative stress. This study elucidates the central role of Nrf2/HO-1 pathway interactions in MIRI and identifies liquiritigenin as a potential therapeutic candidate for targeting this pathway