Search Results (5,670)

This paper examines Amitav Ghosh’s Gun Island through a Hindu eco-spiritual framework to explore how ancient cosmological concepts illuminate contemporary environmental crises. Building upon the legend of Bonduki Sadagar and Manasa Devi, Ghosh narrates the rupture of sacred human–nature relationships in both colonial and postcolonial contexts. This study employs a tripartite conceptual lens of karma, dharma, and ecosystem drawn from Hindu philosophy to analyze how the novel frames environmental degradation, human moral failure, and ecological interconnectedness. Karma, as the law of cause and effect, is used to depict the consequences of human exploitation through natural disasters, climate migration, and the collapse of ecosystems. Dharma emerges as a principle advocating ecological responsibility and symbiosis between humans and nonhuman life. This paper argues that Ghosh tactfully intertwines Hindu metaphysics with contemporary ecological science to critique capitalist modernity’s environmental violence. The novel’s depiction of floods, the sinking of Venice, and the global refugee crisis dramatizes karmic consequences, while its evocation of myth–science convergence offers a vision of sacred interdependence. Ultimately, this paper concludes that Gun Island provides an urgent eco-spiritual model for reimagining planetary ethics and responding to the Anthropocene through humility, relationality, and spiritual responsibility. Full article

Miami, Florida, renowned for its cultural richness and coastal beauty, also faces the concerning challenges created by urban heat islands (UHIs). As one of the hottest cities of the United States, Miami is facing escalating temperatures and threatening heat-related vulnerabilities due to urbanization and climate change. Our study addresses the critical issue of mapping and investigating UHIs in complex urban settings. This study leveraged Planet satellite data and Landsat data to conceptualize and develop appropriate mitigation strategies for UHIs in Miami. Utilizing the Planet satellite imagery and Landsat data, we conducted a combined study of land cover and land surface temperature variations within the city. This approach fuses remotely sensed data to identify the UHI hotspots. This study aims for dynamic approaches for UHI mitigation. This includes studying the status of green spaces present in the city, possible expansion of urban green spaces, the propagation of cool roof initiatives, and exploring the recent climatic trend of the city. The research revealed that built-up areas consistently showed higher land surface temperatures while zones with dense vegetation have lower surface temperatures, supporting the role of urban green spaces in surface temperature reduction. This research can also set a robust model for addressing UHIs in other cities facing rapid urbanization and experiencing mounting temperatures each passing year by helping in assessing LST, land cover, and related spectral indices as well. Full article

This article examines how governance structures and procedural timing influence the effectiveness of Territorial Management Instruments (TMIs) in Portugal. Anchored in a comparative analysis of two key legal reforms (Decree-Law No. 380/1999 and Decree-Law No. 80/2015), the study explores the tensions between democratic legitimacy and regulatory complexity. While the 1999 framework emphasized vertical coordination and participatory rights, it often led to procedural rigidity and institutional inertia. Conversely, the 2015 reform promoted digital tools and streamlined processes but introduced new governance gaps, reduced stakeholder diversity, and compressed consultation timelines. Drawing on a qualitative analysis of legal texts, policy documents, and technical documentation, the article introduces the concept of temporal governance, the idea that planning time is not merely a constraint but a governable resource. Through this lens, planning delays are reframed as either pathological (caused by inefficiency and fragmentation) or productive (used strategically to enhance environmental assessment and stakeholder engagement). A new conceptual framework is proposed to classify types of planning time, differentiate delays, and support temporal calibration in governance design. Findings show that effective planning outcomes hinge not only on legal architecture or participatory norms but also on the institutional ability to balance speed with deliberation and strategic foresight with procedural pragmatism. The paper concludes by calling for adaptive governance models that integrate time as a dynamic dimension of spatial planning, with implications for environmental resilience, democratic value, and, above all, institutional trust. Full article

There is a lack of studies comparing PE teachers’ reflections on the role of sport in different regions. Using Kirk’s conceptualization of the role of sport, this qualitative comparative study aimed to explore and compare fifth-grade physical education (PE) teachers’ perceptions and experiences related to PE teaching in Finland and in the Kurdistan region of Iraq (KRI). In-depth interviews were conducted with eight Finnish and six KRI teachers, and the data were analyzed using the NVivo qualitative analysis program. The results showed that the Finnish teachers’ reflections were classified into four themes: joy and competence rather than sport, sport and curriculum, the status of sport in society and prerequisites for physical activities and sport. The KRI teachers’ reflections were also classified into four themes: sport as an aim in PE, the teacher as a model and leader of the sport, sport raising one’s status and PE being not only about sport. The role of sport in PE was recognized by teachers from both regions, although from different perspectives. The Finnish teachers made a clear distinction between PE and sport. The KRI teachers perceived PE and sport almost as one, in the belief that PE primarily teaches pupils about sport and that sport itself is a central goal. Both groups of teachers aimed to enhance their pupils’ well-being and encourage a physically active lifestyle through PE. The KRI teachers believed that engaging students in sports would promote these aims, whereas Finnish teachers saw sport as just one of many components needed to achieve these objectives. The Finnish teachers emphasized the national PE curriculum guiding their work, while the KRI teachers had no standardized PE curriculum in primary school. This comparative study highlights the importance of implementing a well-structured PE curriculum in primary schools in the KRI. Further studies should examine how the implementation of such a curriculum will affect KRI teachers’ teaching and the role of sport in PE. Full article

The rise of algorithm-driven virtual museums presents a philosophical challenge for how cultural meaning is constructed and critiqued in digital curation. Prevailing approaches highlight important but partial aspects: the loss of aura and authenticity in digital reproductions, efforts to maintain semiotic continuity with physical exhibits, optimistic narratives of technological democratisation, and critical technopessimist warnings about commodification and bias. Yet none provides a unified theoretical model of meaning-making under algorithmic curation. This paper proposes a dialectical-semiotic framework to synthesise and transcend these positions. The Dialectical Modelling Nexus (DMN) is a new conceptual structure that views meaning in virtual museums as emerging from the dynamic interplay of original and reproduced contexts, human and algorithmic sign systems, personal interpretation, and ideological framing. Through a critique of prior theories and a synthesis of their insights, the DMN offers a comprehensive model to diagnose how algorithms mediate museum content and to guide critical curatorial practice. The framework illuminates the dialectical tensions at the heart of algorithmic cultural mediation and suggests principles for preserving authentic, multi-layered meaning in the digital museum milieu. Full article

Ontologies are essential tools for representing, organizing, and sharing knowledge across various domains. This study presents a methodology for ontology construction supported by large language models (LLMs), with an initial application in the automotive sector. Specifically, a user preference ontology for adaptive interfaces in autonomous machines was developed using ChatGPT-4o. Based on this case study, the results were generalized into a reusable methodology. The proposed workflow integrates classical ontology engineering methodologies with the generative and analytical capabilities of LLMs. Each phase follows well-established steps: domain definition, term elicitation, class hierarchy construction, property specification, formalization, population, and validation. A key innovation of this approach is the use of a guiding table that translates domain knowledge into structured prompts, ensuring consistency across iterative interactions with the LLM. Human experts play a continuous role throughout the process, refining definitions, resolving ambiguities, and validating outputs. The ontology was evaluated in terms of logical consistency, structural properties, semantic accuracy, and inferential completeness, confirming its correctness and coherence. Additional validation through SPARQL queries demonstrated its reasoning capabilities. This methodology is generalizable to other domains, if domain experts adapt the guiding table to the specific context. Despite the support provided by LLMs, domain expertise remains essential to guarantee conceptual rigor and practical relevance. Full article

This position paper proposes a conceptual framework (CF-BIAI-SXT) for integrating blockchain with AI to enhance ethical governance, transparency, and privacy in high-risk AI applications that ensure societal resilience through the mitigation of sexual exploitation. Sextortion is a growing form of digital sexual exploitation, and the role of AI in its mitigation and the ethical issues that arise provide a good case for this paper. Through a combination of systematic and narrative literature reviews, the paper first explores the ethical shortcomings of existing AI systems in sextortion prevention and assesses the capacity of blockchain operations to mitigate these limitations. It then develops CF-BIAI-SXT, a framework operationalized through BPMN-modeled components and structured into a three-layer implementation strategy composed of technical enablement, governance alignment, and continuous oversight. The framework is then situated within real-world regulatory constraints, including GDPR and the EU AI Act. This position paper concludes that a resilient society needs ethical, privacy-first, and socially resilient digital infrastructures, and integrating two core technologies, such as AI and blockchain, creates a viable pathway towards this desideratum. Mitigating high-risk environments, such as sextortion, may be a fundamental first step in this pathway, with the potential expansion to other forms of online threats. Full article

Urban flooding presents a growing challenge amid rapid urbanization, climate variability, and fragmented governance. Although simulation and risk assessment tools have advanced considerably, their integration into urban planning remains limited. This study utilized a comprehensive bibliometric analysis of 1293 articles from the Scopus database, selected through a PRISMA-guided workflow, to examine the temporal, structural, and conceptual evolution of simulation, flood risk, and planning in urban flood research from 1980 to 2025. The findings reveal a thematic progression from engineering-centric approaches to broader discourses on resilience, adaptation, and systemic risk. However, disciplinary fragmentation persists, with technical modeling, infrastructure planning, and governance still weakly connected. Despite a shared vocabulary around climate risk and resilience, practical integration into decision-making frameworks remains underdeveloped. The study highlights the need for more cohesive research-practice linkages and calls for frameworks that better align simulation outputs with urban planning imperatives. Full article

This article investigates the political cost of poverty in democracies marked by deep social divisions. We develop a probabilistic voting model that incorporates clientelism as a strategic tool employed by elite political parties to secure electoral support from non-elite voters. Unlike models based on ideological proximity, our framework conceptualizes party competition as structured by the socioeconomic composition of their constituencies. We demonstrate that in contexts of high inequality and widespread poverty, elite parties face structural incentives to deploy clientelistic strategies rather than universalistic policy agendas. Our model predicts that clientelistic expenditures by elite parties increase proportionally with both inequality (GINI index) and poverty levels, rendering clientelism a rational and cost-effective mechanism of political control. Empirical evidence from a cross-national panel (2013–2019) confirms the theoretical predictions: an increase of the 1 percent in the GINI index increase a 1.3 percent in the clientelism, even after accounting for endogeneity and dynamic effects. These findings suggest that in divided democracies, poverty is not merely a condition to be alleviated, but a political resource that elites strategically exploit. Consequently, clientelism persists not as a cultural residue or institutional failure, but as a rational response to inequality-driven constraints within democratic competition. Full article

Species have different strategies for implantation and placentation. Much can be learned about general molecular and cellular biology through the examination and comparison of these differences. To varying degrees, implantation in all species includes alterations in epithelial polarity, the transformation of the endometrial stroma, the differentiation of the trophoblast, cell-to-cell and tissue-to-tissue signaling through hormones, cytokines, and extracellular vesicles, and the alteration of the maternal immune system. This review focuses on implantation in pigs, sheep, and cows. These species share with mice/rats and humans/primates the key events of early embryonic development, pregnancy recognition, and the establishment of functional placentation. However, there are differences between the pregnancies of livestock and other species that make livestock unique biomedical models for the study of pregnancy and cell biology in general. Pig, sheep, and cow conceptuses (embryo/fetus and associated placental membranes) elongate prior to implantation, displaying central implantation, extended periods of conceptus attachment to the uterus, and epitheliochorial (pigs) and synepitheliochorial (sheep and cows) placentation. This review will discuss what is understood about how the trophoblast and extraembryonic endoderm of pig, sheep, and cow conceptuses elongate, and how a major goal of current in vitro models is to achieve conceptus elongation. It will then examine the adhesion cascade for conceptus implantation that initiates early placental development in pigs, sheep, and cows. Finally, it will conclude with a brief overview of early placental development in pigs, sheep, and cows, with a listing of some important “omics” studies that have been published. Full article

This narrative inquiry explores a vibrant classroom knowledge community in a Chinese normal university. By examining the teacher’s interactions, we analyze the community’s development through three perspectives: (1) the author’s narrative of the course outline, (2) the teacher’s narrative of classroom culture, and (3) students’ narratives of their growth. The author presents a student-centered model and seven steps for enacting the course, outlining the environment for cultivating the knowledge community. The teacher’s narrative reveals clues to his success, emphasizing his use of storytelling to foster the community and share educational ideas. Students’ narratives reflect their growth, validating the classroom as a safe space for development and language learning. The significance of this research is that the classroom knowledge community consisted of the teacher, his undergraduate students, and his post-graduates. The three layers existed because of this unrestrained character, devoid of conflicts of interest, created a safe place for students’ development. This research study adds to the literature on how knowledge communities form in school contexts. It focuses on a particular space and time and involves multiple layers of participants, which is prerequisite to the conceptualization of classroom knowledge community. This research has important implications for college language education. Full article

Reproductive efficiency is a critical determinant of productivity and profitability in sheep farming. Traditional selection methods have largely relied on phenotypic traits and historical reproductive records, which are often limited by subjectivity and delayed feedback. Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. This review synthesizes the current research on AI-powered behavioral monitoring tools and proposes a conceptual model, ReproBehaviorNet, that maps age- and sex-specific behaviors to biological processes and AI applications, supporting real-time decision-making in both intensive and semi-intensive systems. The integration of accelerometers, GPS systems, and computer vision models enables continuous, non-invasive monitoring, leading to earlier detection of reproductive events and greater breeding precision. However, the implementation of such technologies also presents challenges, including the need for high-quality data, a costly infrastructure, and technical expertise that may limit access for small-scale producers. Despite these barriers, AI-assisted behavioral phenotyping has the potential to improve genetic progress, animal welfare, and sustainability. Interdisciplinary collaboration and responsible innovation are essential to ensure the equitable and effective adoption of these technologies in diverse farming contexts. Full article

Introduction: Assessing the quality of patient care within healthcare systems remains a multifaceted challenge due to varying definitions of “quality” and the complexity of care delivery structures worldwide. Patient-centeredness, institutional responsiveness, and contextual adaptability are increasingly recognized as core pillars in quality assessment. Objective: This narrative literature review aims to explore conceptual models and practical frameworks for evaluating healthcare quality, emphasizing tools that integrate technical, functional, and emotional dimensions and proposing a comprehensive model adaptable to diverse health system contexts. Methodology: A systematic literature search was conducted in the PubMed, Scopus, and Cochrane Library databases, covering the years 2000 to 2024. Studies were selected based on relevance to quality assessment models, patient satisfaction, accreditation, and strategic improvement methodologies. The review followed a thematic synthesis approach, integrating structural, process-based, and outcome-driven perspectives. Results: Core frameworks such as Donabedian’s model and balancing measures were reviewed alongside evaluation tools like the Dutch Consumer Quality Index, SERVQUAL, and Importance–Performance Analysis (IPA). These models revealed significant gaps between patient expectations and actual service delivery, especially in functional and emotional quality dimensions. This review also identified limitations related to contextual generalizability and bias. A novel integrative model is proposed, emphasizing the dynamic interaction between institutional structure, clinical processes, and patient experience. Conclusions: High-quality healthcare demands a multidimensional approach. Integrating conceptual frameworks with context-sensitive strategies enables healthcare systems to align technical performance with patient-centered outcomes. The proposed model offers a foundation for future empirical validation, particularly in resource-limited or hybrid settings. Full article

This study explores how artificial intelligence (AI) technologies can be theoretically integrated into literature curriculum development, using the works of Anton Chekhov and Lu Xun as illustrative case texts. The aim is to reduce barriers to language and cultural understanding in literature education and increase the efficiency and accessibility of cross-cultural teaching. We used natural language processing (NLP) techniques to analyze textual features, such as readability index, lexical density, and syntactic complexity, of AI-generated and human-translated “The Chameleon” and “A Madman’s Diary”. Teaching cases from universities in China, Russia, and Kazakhstan are reviewed to assess the emerging practice of AI-supported literature teaching. The proposed theoretical framework draws on hermeneutics, posthumanism, and cognitive load theories. The results of the data-driven analysis suggest that AI-assisted translation tends to simplify sentence structure and improve surface readability. While anecdotal classroom observations highlight the role of AI in initial comprehension, deeper literary interpretation still relies on teacher guidance and critical human engagement. This study introduces a conceptual “AI Literature Teaching Model” that positions AI as a cognitive and cultural mediator and outlines directions for future empirical validation. Full article

Artisanal and small-scale gold mining (ASGM) in Burkina Faso increasingly relies on cyanide, intensifying concerns about environmental contamination and human exposure. This study assessed free cyanide levels in water and soil across three ASGM sites—Zougnazagmiline, Guido, and Galgouli. Water samples (surface and groundwater) and topsoil (0–20 cm) were analyzed using the pyridine–pyrazolone method. Data were statistically and spatially processed using SPSS version 29.0 and the Google Earth Engine in conjunction with QGIS version 3.34, respectively. A site conceptual model (SCM) was also developed, based on the literature review, field observations, and validation by multidisciplinary experts in public health, toxicology, ecotoxicology, environmental engineering, and the mining sector, through a semi-structured survey. The results showed that 9.26% of the water samples exceeded the WHO guideline (0.07 mg/L), with peaks of 1.084 mg/L in Guido and 2.42 mg/L in Galgouli. At Zougnazagmiline, the water type differences were significant (F = 64.13; p < 0.001), unlike the other sites. In the soil, 29.36% of the samples exceeded 0.5 mg/kg, with concentrations reaching 9.79 mg/kg in Galgouli. A spatial analysis revealed pollution concentrated near the mining areas but spreading to residential and agricultural zones. The validated SCM integrates pollution sources, transport mechanisms, exposure routes, and vulnerable populations, offering a structured tool for environmental monitoring and health risk assessment in cyanide-impacted mining regions. Full article