Search Results (5,795)

During the critical period of agricultural green transformation, clarifying the evolutionary logic of farmers’ green production behavior under a multi-stakeholder framework provides significant insights for implementing “Dual Carbon” goals, establishing long-term mechanisms for high-quality agricultural development, and resolving deep-seated contradictions in agricultural non-point source pollution. Based on the social co-governance and public participation framework, this paper constructs a tripartite evolutionary game model involving government departments, farmer groups, and the general public, grounded in cost–benefit analysis, social governance friction, and evolutionary game theory. Through simulation, the study explores the equilibrium states and the specific impacts of varying parameter values on stable points. The findings reveal that: (1) The “interest price scissors” (benefit disparity) between green and conventional production is the key determinant of farmers’ strategic equilibrium. Once this structural contradiction is resolved, green production becomes the optimal strategy. (2) Farmers are highly sensitive to marginal cost–benefit fluctuations, leading to a sequential behavioral cascade: farmers retreat first, followed by the government, and finally the public. (3) Public participation cost is the pivotal variable for activating the co-governance mechanism, and the application of digital governance tools determines the time required to reach equilibrium. (4) A “Success Paradox” exists in government regulation; incentive mechanisms must be adjusted promptly after initial success. (5) Integrated policy combinations outperform single instruments; breaking the “locked-in” state requires a policy shock of sufficient intensity. This research offers a theoretical basis and policy enlightenment for optimizing the social co-governance landscape and promoting sustainable agricultural modernization. Full article

This study maps the global scholarly landscape on digital parenting and children’s digital device use through bibliometric analysis of 628 Scopus articles (2010–2025). Using PRISMA-guided screening and science-mapping visualisations (VOSviewer and CiteSpace), the review identifies publication growth, influential sources, intellectual structures, and thematic clusters shaping the field. The mapped knowledge structure is dominated by health and media-effects traditions, with major research fronts centred on parental mediation, screen-time outcomes, online safety, and digital wellbeing. Crucially, the analysis shows that parenting perspectives remain weakly represented within this global corpus, with limited engagement with faith-based concepts that could shape mediation practices and moral reasoning in households. This underrepresentation contributes to a Western-centric evidence base, indicating a need for Islamically situated digital parenting research that integrates developmental concerns with ethics and culturally grounded mediation strategies. The study concludes by proposing a focused research agenda to strengthen theory building and empirical work in family contexts. Full article

Decision-making is a central activity in agile software engineering (SE), yet research on how decisions are made and supported in agile contexts remains fragmented across models, methods, roles, and lifecycle stages. While prior studies have examined isolated aspects such as prioritization or planning, a comprehensive synthesis of decision-making as a phenomenon in agile SE is lacking. This systematic literature review addresses this gap by consolidating and structuring existing research on agile decision-making and to identify dominant patterns, gaps, and future research directions. A systematic search was conducted in IEEE Xplore, ACM Digital Library, Scopus, and Web of Science, complemented by backward and forward snowballing, covering publications from 2014 to 2024. In total, 42 studies were included and analyzed using a structured coding scheme covering decision models, methods, actors, lifecycle contexts, and research methodologies. The results reveal a strong concentration of analytical and hybrid decision-making models in planning and requirements activities, while decision-making in coding, testing, and operations remains underexplored. Software developers are the most frequently studied decision-making actors, whereas managers are mainly discussed as external stakeholders rather than active decision-makers within agile workflows. The main contributions of this study are the following: a structured synthesis of agile decision-making research over multiple analytical dimensions, the identification of key research gaps in lifecycle coverage and actor perspectives, and the proposal of a coherent nomenclature for decision-making in agile SE. These contributions provide a foundation for future empirical studies and support the development of more comprehensive theories of decision-making in agile software engineering organizations. Full article

Disinformation, amplified by digital platforms and algorithmic distribution systems, represents a growing challenge for media trust, public health communication, and societal stability. This narrative literature review examines disinformation through an integrative psychosocial perspective, focusing on how patterns of exposure interact with individual vulnerability factors—including education, political beliefs, social identity, personality traits, and emotional responses to uncertainty—to influence the processing and acceptance of misleading information. The review synthesises interdisciplinary evidence on how algorithmic amplification and emotionally salient content increase susceptibility to disinformation and shape risk perception, health-related decision-making, and preventive behaviours. Findings indicate that repeated exposure to false or misleading information reinforces perceived credibility through familiarity effects, contributes to declining trust in institutional sources, and intensifies social and political polarisation. Disinformation is therefore conceptualised not only as an informational problem but also as a psychosocial process affecting emotional regulation, cognitive evaluation, and collective responses to crises, particularly in public health contexts. The analysis further highlights a recursive feedback loop in which reduced media trust increases vulnerability to subsequent disinformation, with broader implications for democratic participation and social cohesion. Mitigation strategies discussed include media literacy initiatives, critical thinking education, platform governance, regulatory approaches, and interventions targeting psychosocial drivers of susceptibility. Full article

Background/Objectives: Single-parent families represent a growing and particularly vulnerable family structure within community and primary health care contexts. These families often experience cumulative burdens related to caregiving overload, socioeconomic constraints, social isolation, and fragmented support networks, which directly affect health and well-being. This integrative review aimed to synthesize and critically analyse direct and conceptually transferable evidence relevant to Family Health Nursing interventions supporting single-parent families in community and primary health care contexts, identify existing knowledge gaps, and inform the development of a relational empowerment model. Methods: An integrative literature review was conducted following PRISMA 2020 guidelines. A comprehensive search was performed across three electronic databases (PubMed, CINAHL, and Scopus) covering publications from 2020 to 2025. Inclusion criteria comprised peer-reviewed empirical studies and reviews addressing nursing or health interventions relevant to single-parent families in community or primary health care contexts. Data were extracted and synthesized thematically, with attention to theoretical frameworks, intervention characteristics, and reported outcomes. Results: Twenty-nine studies met the inclusion criteria. The synthesis revealed four main thematic domains: (1) caregiving burden and psychosocial vulnerability, (2) access to and coordination of community-based resources, (3) nurse–family relational processes, and (4) empowerment-oriented nursing interventions. Theoretical underpinnings frequently included family systems perspectives, the Calgary Family Assessment and Intervention Models, and empowerment-oriented frameworks. Conclusions: Nursing interventions for single-parent families in community health settings should prioritise relational empowerment approaches that acknowledge family diversity, contextual vulnerability, and dynamic caregiving demands. The proposed relational empowerment model offers a practice-informed framework to guide Family Health Nursing interventions, education, and policy development, supporting more responsive and equitable care for single-parent families. Full article

This study examines how institutional investors allocate trading across the earnings announcement cycle and whether industry trading concentration strengthens that activity. The analysis is motivated by two complementary ideas: public disclosures can increase the value of investors’ prior information, and even sophisticated investors face costly information processing. These perspectives imply that institutional trading need not be concentrated only before disclosure and may be strongest after earnings announcements, when investors combine newly released public information with prior firm- and industry-specific signals. Using daily institutional trading data from Ancerno, we find that institutional net trading is positively related to earnings surprises before, during, and after earnings announcements, with the strongest relation occurring in the post-announcement period. We also document a clear asymmetry: trading is strongly related to positive earnings surprises across all three stages, whereas trading related to negative earnings surprises is concentrated mainly after disclosure. In addition, industry trading concentration strengthens the relation between institutional trading and earnings news across the announcement cycle, especially for positive surprises. These findings provide an integrated view of institutional information processing around a major recurring disclosure event, show that the timing of institutional trading is informative about how earnings news is incorporated into prices, and support the view that industry specialization is linked to stronger earnings-related trading. Full article

Adaptive reuse of industrial heritage from a tourism perspective presents a complex design challenge requiring a balance between heritage preservation, functional innovation, and diverse stakeholder expectations. However, current practices often face issues such as ambiguous demand interpretation and a disconnect between design generation and systematic evaluation. Addressing these limitations, this paper proposes and illustrates a human–machine collaborative design paradigm that integrates generative AI into a closed-loop process of “demand analysis–intelligent generation–comprehensive evaluation.” The method first employs Kansei Engineering and the KANO model to qualitatively extract and quantitatively prioritise heterogeneous user needs, translating subjective perceptions into structured design constraints and optimisation objectives. Next, these needs are encoded as text prompts to drive targeted spatial exploration by the generative AI tool Nano Banana AI. Finally, the TOPSIS method is applied for multi-criteria performance evaluation and solution selection. A case study of Shanghai Libo Brewery suggests that this paradigm can enhance design efficiency and show potential to outperform traditional methods across dimensions such as historical preservation, public accessibility, ecological integration, social inclusivity, and formal innovation. The research offers a quantifiable and systematically documented intelligent design methodology for industrial heritage renewal, while acknowledging the exploratory nature of the generative phase. Furthermore, it provides a visitor-demand-driven innovation pathway for developing industrial heritage tourism destinations, thereby potentially enhancing cultural experiences and tourism appeal at heritage sites. This research illustrates a move from an experience-driven paradigm toward a data- and value-driven approach, contributing theoretical methodologies to the intersection of cultural tourism and artificial intelligence. Full article

Indonesia has identified clean hydrogen as one of the strategic initiatives for its energy transition, recognizing its potential as an energy carrier that can support the achievement of net zero emissions. To deepen the understanding of this emerging technology, this study assesses the readiness of green hydrogen development in Indonesia through a multi-stakeholder perspective combined with a technology readiness evaluation and insights from global developments. Based on stakeholder interviews across government, industry, academia, and energy institutions, this analysis identifies key enabling conditions and barriers for hydrogen deployment in the Indonesian context. This analysis indicates that the readiness level of green hydrogen technology in Indonesia has reached approximately technology readiness level (TRL) 5–TRL 6, suggesting that most initiatives remain at the pilot and demonstration stages. In addition, seven key factors influencing green hydrogen adoption were identified: infrastructure and technology, policy and regulation, finance, application sectors, public acceptance, standardization, and private sector participation. These results provide policy-relevant insights for accelerating hydrogen development and highlight priority areas for advancing Indonesia’s transition toward a low-carbon energy system. Full article

The rapidly growing concern over the hazardous impact of phthalates on the environment and public health has led to a critical need for alternative and environmentally friendly plastics. Plasticizers developed from natural materials represent one possible solution. This paper explores four types of renewable feedstocks (sorbitol/polyols, glycerin, cardanol from cashew nutshell liquid, and limonene from citrus peels) as sources for developing alternative plasticizer systems. Key areas explored include the type of feedstock utilized, the methods used for extracting or processing the feedstocks, the nature of the chemical modification processes (e.g., esterification, epoxidation, etherification, or reactive grafting) applied to generate the respective plasticizers, and the resultant physical and mechanical properties. The performance of each plasticizer system in polymers such as PVC, PLA, and polysaccharide-based bioplastics is evaluated, alongside the compatibility with biological tissues, toxicological properties, biodegradability, and chemical migration into food simulants. The feasibility of each family of plasticizers is also assessed from an economic perspective, including availability of the feedstocks, economies of scale associated with large-volume production, and competitive pricing relative to established petroleum-derived plasticizers. Overall, sorbitol/polyol and glycerin derivative families have reached a level of maturity that provides a good balance of processability, food-contact safety, and biodegradability. Cardanol-based systems provide an attractive option where aromatic functional groups and combined plasticization–stabilization effects are needed. Limonene-derived plasticizer systems appear promising for use in PLA, but their broader utility may be limited by volatility, strong odors, and susceptibility to oxidation. Common issues identified across all four families include chemical migration into food products, regulatory approval, and the need for detailed life-cycle assessments. Full article

Background: The Democratic Republic of the Congo accounts for approximately 12–13% of the global malaria burden. While international guidelines oppose the use of Artemisia annua infusions due to risks of sub-therapeutic dosing and resistance selection, the plant remains widely used in resource-limited regions. This study evaluates the clinical acceptability and perceptions of healthcare providers regarding the integration of Artemisia annua tea into formal malaria control in the Maniema province. Methods: A cross-sectional survey was conducted among 337 healthcare professionals in the Kalima health district using the KoboCollect digital platform. Multivariate logistic regression was employed to identify the primary socio-professional determinants of clinical acceptability. Results: The overall clinical acceptability of Artemisia annua integration was 81.0%, with 82.8% of providers perceiving the preparation as effective. Rural residency was the strongest predictor of adherence (AOR = 6.847; p = 0.003), reflecting a pragmatic response to frequent ACT stockouts and high treatment costs. Despite high acceptability, 49.0% of providers identified the lack of clinical evidence as a major barrier, and 91.4% demanded formal training on standardized dosage and biological mechanisms. Conclusions: A significant “policy–practice gap” exists between international guidelines and field realities in the DRC. Healthcare providers demonstrate high readiness for integration but emphasize the absolute necessity of galenic standardization to mitigate resistance risks. To address these concerns, a complementary genomic investigation is currently underway in the same study area, comparing PfKelch13 mutation prevalence among Artemisia tea users versus ACT-treated patients. This molecular surveillance will provide essential evidence to define safety parameters for future phytopharmaceutical integration. Full article

The sustainability of information poses an ever-greater challenge in the digital age, particularly within local media ecosystems, where access to technology does not necessarily lead to informed participation or stronger ties with institutions. In contexts such as Ecuador, persistent inequalities shape the way people access, use and trust information, reinforcing complex forms of the digital divide. This study analyses how the sustainability of information is reflected in media consumption patterns and levels of institutional engagement within a regional context. Based on a survey of 1784 people in the province of Imbabura, the study applies a combined approach using cluster analysis and random forest models to identify distinct audience profiles. The results reveal four distinct groups, demonstrating that the intensity and diversity of media use are more relevant than mere digital access. High levels of digital use do not guarantee greater institutional engagement; instead, hybrid patterns emerge that combine traditional, digital and institutional media in different ways. The findings show that digital access alone is not sufficient to ensure information sustainability or the formation of institutional opinion. From a public policy perspective, universities and public institutions should promote digital literacy, build trust and design more targeted communication strategies to reduce information inequalities and foster informed participation. Full article

Under the evolving modern power system, user-side load structures and consumption behaviors are becoming increasingly diversified, while grid–load interactions are growing more frequent. These changes pose new challenges for load characteristic analysis amid the energy transition. The advancement of metering automation has generated massive power consumption data, offering rich insights for load modeling and applications. This paper presents a comprehensive review of intelligent analysis and applications of load characteristics in new power systems. It begins by outlining a systematic framework for load analysis and summarizing relevant public datasets. Then, it synthesizes existing research from three perspectives: load feature analysis and user profiling, interactive aggregation behaviors under market mechanisms, and practical applications. Finally, this paper discusses platform development practices for big data and highlights future research challenges and directions. Full article

Vanishing point detection is a fundamental step in computer vision that allows 3D scene understanding and autonomous navigation. Classical techniques have significant challenges when trying to understand scenes that are heavily cluttered and images containing multiple perspective cues, leading to poor or unreliable vanishing point determination. We present a Dual RANSAC with Rescue Midpoint-based Multi-Trend Vanishing Point Detection framework, which targets the simultaneous detection and fine-tuning of multiple, globally consistent vanishing points. The proposed framework introduces a novel Midpoint-based Multi-Trend Random Sample Consensus formulation that operates on line segment midpoints to infer dominant directional groups, thereby eliminating noisy or unstable midpoints and stabilizing subsequent vanishing point inference. The main novelty lies in using line segment midpoints to model the orientation variation as a linear regression in the midpoint–orientation space, which helps reduce sensitivity to endpoint instability. Candidate vanishing points are prioritized through inlier-based confidence ranking and subsequently optimized via an MSAC-based arbiter to resolve hypothesis conflicts and minimize geometric error. We evaluate our work against state-of-the-art techniques such as J-Linkage and Conditional Sample Consensus, over two of the current challenging public datasets that comprise the York Urban Dataset and the Toulouse Vanishing Point Dataset. The results show that the proposed framework achieves a recall of up to 95% and an image success rate of almost 84%, outperforming both J-Linkage and Conditional Sample Consensus, especially under tighter angular thresholds. This demonstrates the ability of the proposed framework to provide enhanced stability and localization accuracy. Full article

Maritime traffic complexity (MTC) is a term that has gained increased importance in the last decade in the maritime safety domain. It is a concept for understanding navigational safety and operational challenges in congested maritime environments. Although research interest in MTC has grown, it is a concept that remains fragmented, with various interpretations of definitions, indicators, and modeling approaches present in the literature. This study presents a comprehensive literature review and bibliometric analysis to synthesize the current state of research on MTC as a scientific construct and clarify its conceptual foundations from an analytical perspective. In accordance with PRISMA guidelines and systematic literature review (SLR) methodology, relevant studies were identified and screened across major scientific databases. A detailed analysis was conducted on 40 scientific publications. The findings indicate that most existing MTC models rely mainly on Automatic Identification System (AIS) data and corresponding derived metrics. MTC is primarily assessed through geometric vessel–vessel interactions, relative motion parameters, and collision-risk indicators. Bibliometric analysis demonstrates a rapid increase in scientific interest in this topic since 2015, with research concentrated in several leading journals. The study identifies a significant methodological limitation in current frameworks, which often overlook the heterogeneity of marine traffic, environmental conditions, vessel reliability, and human factors. Therefore, this study highlights the need for a more comprehensive MTC evaluation framework that incorporates operational, geographical constraint-based, environmental, and behavioral variables alongside traditional AIS-based metrics. Full article

The rapid growth of scientific publications in sport science has intensified competition for publication and increased the importance of methodological rigor, transparent reporting, and effective scientific communication. Despite the availability of general guidance on scientific writing, recommendations specifically tailored to the context of sport science publishing remain fragmented. The aim of this narrative review was to synthesize methodological, conceptual, and editorial perspectives in order to identify the key factors that influence the quality and publishability of sport science research. The review examines major dimensions of research quality, including theoretical grounding, methodological rigor, statistical inference, open science practices, and the structure of scientific manuscripts. In addition, common weaknesses that frequently lead to manuscript rejection, such as limited scientific contribution, methodological flaws, statistical misinterpretation, and inadequate scientific writing, are discussed. Building on this synthesis, the article proposes an integrated conceptual framework that conceptualizes publishable sport science research as a progressive process moving from conceptual foundations to methodological and analytical rigor, research transparency, and effective scientific communication. The framework, presented as a funnel, illustrates how these interconnected dimensions ultimately contribute to two complementary outcomes: the advancement of scientific knowledge and the practical application of research findings in sport contexts. By providing a structured overview of these elements, the proposed framework aims to support researchers in designing more rigorous studies, improving manuscript quality, and strengthening the impact of sport science research. Full article