Search Results (358)

This study examines how mothers raising children with disabilities in American Samoa experience the processes of seeking diagnosis, navigating special education, and advocating for services within an insular rural context. American Samoa, an unincorporated U.S. territory located 2600 miles from Hawaiʻi with a population under 50,000, represents a case of what we term insular rurality—a condition in which the structural disadvantages of rurality are intensified by oceanic isolation, territorial governance, and colonial history. Data were collected through three focus groups with fifteen mothers whose children hold a range of disability diagnoses, with a card sort activity at the outset of each session serving as an idiographic anchor to protect individual voice within the group format. Analysis followed Interpretative Phenomenological Analysis adapted for focus groups (IPA-FG), proceeding from line-by-line exploratory noting through Personal Experiential Themes and Group Experiential Themes within each focus group case to cross-case convergence and divergence analysis, interpreted through the Fonofale model of Pacific wellness. Findings reveal two overarching themes: systemic invalidation, in which mothers encountered deficit-based assumptions, stagnant educational goals, and institutional disengagement; and parent peer support as the primary infrastructure, in which mothers became de facto experts, built community-driven solutions, and envisioned more inclusive futures. Technology emerged as a contradictory force—valuable for parent learning but largely ineffective for children’s remote therapy. These findings suggest how workforce shortages and geographic isolation create conditions in which maternal advocacy becomes a systems-level necessity rather than a personal choice. Implications for rural education policy, IDEA implementation in U.S. territories, and culturally grounded family support are discussed. Full article

Despite growing interest in Virtual Labs (VLs), limited research examines the factors influencing educators’ willingness to adopt them through the lens of inquiry-based learning (IBL). This exploratory pilot study evaluates educators’ interaction with the VHEalthLab VLs toolkit, examining their perceptions on usability, pedagogical value, IBL support, and intention to use. The study combines IBL, as a pedagogical lens, with the Technology Acceptance Model (TAM) within a Triple Bottom Line sustainability framework aligned with Sustainable Development Goals 4 and 10. Using an exploratory cross-sectional design with an embedded qualitative component, data were collected from seventy Biology educators across four European countries (Cyprus, Greece, Romania, Spain) through two structured questionnaires. Data analysis included descriptive statistics, Pearson correlations, directed content analysis, and joint display integration. Findings indicate that adoption intention was associated primarily with pedagogical rather than technological factors; IBL alignment showed the strongest association with intention to implement VLs (r = 0.63, p < 0.001), while perceived usefulness was most strongly associated with pedagogical materials (r = 0.65, p < 0.001). Assessment and inclusion functioned as quality criteria rather than factors associated with adoption intention. Educators consistently endorsed VLs as complements to physical laboratories, with their perceptions suggesting potential environmental, economic, and social sustainability implications within a blended model. Full article

In recent years, artificial intelligence (AI) has been increasingly used in criminal justice systems across the world. To achieve objectives set out through Sustainable Development Goals (SDGs), adoption of technology is inevitable and undeniable. The press release dated 25 February 2025 from India’s Ministry of Law and Justice, quoting Prime Minister of India Narendra Modi to make a “justice system that will be fully future-ready”, confirmed that the Indian law enforcement agencies are integrating AI into policing and law enforcement to enhance crime detection, criminal investigation, etc. It is intended to enhance their capabilities in solving criminal cases and delivering justice speedily and more efficiently. However, the usage of AI tools in such contexts presents a double-edged sword, as evidenced by their application in a number of cases across the world like Christopher Gatlin, Nijeer Parks, the Harm Assessment Risk Tool (HART), and in India during the 2020 Delhi riots cases. As reported by the Washington Post, in Christopher Gatlin’s case it was found that the police arrested him on the basis of the facial recognition programme matching his face with the captured video footage. He spent 17 months in jail before his release by the court, observing that the police failed to conduct fair investigation. A similar incident was reported by NJ.com and CNN Business. In the investigations following the 2020 Delhi riots, Delhi Police effected over 1900 arrests in 758 riot-related cases, relying predominantly on AI-driven facial recognition matches. Subsequent court scrutiny in decided cases raised questions about reliability, leading to widespread acquittals and discharges of the accused in 82% of decided cases as of early 2025. In certain cases, AI-driven solutions have failed, leading to criminal prosecutions of innocent people based on AI-generated evidence. This study examines the reliability, validity, and ethics of AI technology in the criminal justice system in India’s unique socio-legal and political environment. The researchers analyse three interrelated axes. First, a comprehensive review of the international algorithmic policing literature to identify successes and failures. In addition, cases of AI-assisted investigations during the Delhi riots show how facial recognition systems and other AI techniques were used for inquiry. Finally, stakeholders’ perspectives, including a preliminary survey of 27 legal experts showing strong consensus on classifying AI-FRT outputs strictly as corroborative evidence and highlighting BSA insufficiencies for addressing opacity and explainability, help identify practical, procedural, and normative fault lines. Researchers noted that while AI has the potential to revolutionise resource-constrained investigative agencies, its unquestioning and uncritical adoption risks amplify pre-existing biases, undermine presumptions of innocence, and shift the burden of refuting algorithmic inference onto the accused. Independent algorithmic audits, transparent documentation of error rates and confidence thresholds, statutory guidelines on AI tool use and admissibility, and sustained capacity-building throughout the justice delivery chain are needed to integrate it into the Indian criminal justice system. Without such measures, the very tools designed and introduced to enhance accuracy threaten to undermine the fundamental norms of the criminal justice system such as fairness and due process. This fills a gap in doctrinal analysis of AI-specific evidentiary admissibility in non-Western contexts like India. This study aims to propose policy reforms, enhance judicial discourse, and promote a more circumspect trajectory for AI adoption in Indian law enforcement by mapping the potential and risks of algorithmic evidence in a non-Western legal order. Full article

This study explores the interaction mechanisms between population and environment systems within the context of high-quality development (HQD), providing empirical insights for developing countries navigating rapid urbanization. The existing literature often focuses on regional macro-averages, which may obscure internal spatial structural heterogeneity and the phenomenon of bottleneck shifts within urban agglomerations (UAs). Focusing on six typical UAs in China from 2011 to 2023, we constructed a multi-dimensional evaluation system and utilized an optimal parameters-based geographical detector (OPGD) and an obstacle degree model (ODM) to decode the spatiotemporal evolution of these systems. The results demonstrate that: (1) Both population and environment subsystems have improved steadily. Ecological carrying capacity has increased significantly, and the primary systemic constraint has transitioned from the “environmental bottom line” to the “population dividend,” with several super/mega cities converging toward a synchronous development interval. (2) The modified coupling coordination degree (MCCD) exhibits an overall upward trend. While eastern UAs demonstrate core-driven synergistic evolution, central and western UAs face risks of a “single-core siphon effect” and “peripheral hollowing-out,” leading to pronounced spatial polarization. (3) The OPGD analysis reveals that the driving efficiency of large-scale traditional infrastructure investment has experienced a marginal decline, whereas economic fundamentals and technological innovation have emerged as core drivers for non-linear enhancement. (4) The ODM confirms that traditional environmental pressures have been substantially alleviated. The core constraints have transitioned to the population and economic dimensions, with labor productivity and science and technology (S&T) expenditure identified as the primary obstacles. Aligning with the United Nations Sustainable Development Goals (SDGs), our findings may suggest that policy focus should shift from physical spatial expansion toward “soft connectivity” based on institutional and technological spillovers. We recommend establishing cross-regional coordination mechanisms to mitigate the siphon effects of core cities and transitioning policy priorities from ecological defense to high-quality population development. Full article

This study assesses how a country’s digitalization impacts sustainability indicators as measured by unmonitored environmental, social and governance (ESG) risks, which serve as a proxy for the development of financial technology (FinTech). The study employs a cross-country approach using data for up to 163 countries, going beyond the firm-level focus of previous studies. The DiGiX Digitalization Index and the ICT Development Index are used to measure digital maturity, while pillar-level indicators and Sustainalytics ESG country risk scores are used to assess ESG indicators. With evidence of nonlinear, threshold-type effects at higher levels of digital maturity, the regression results suggest a strong negative correlation between digital maturity and ESG risk. Different country typologies are further identified using unsupervised cluster analysis, which reveals a continuous digital and ESG gradient in environmental, social and governance aspects. The analysis proves digital maturity serves as a systemic enabler of ESG risk management by strengthening data availability, governance capacity and policy enforcement. These findings provide policy-related guidance for coordinating digitalization strategies in line with the Sustainable Development Goals. Full article

Smart shipping and achieving net-zero emissions have become pressing priorities in maritime transport, yet limited research has integrated sustainable shipping development with green finance decision-making. To address this gap, this study applies the AHP–RDEMATEL–TOPSIS approach to analyze the interrelationships and relative importance of key sustainability factors and to identify optimal green financing instruments. Incorporating ESG dimensions, the research conducted a survey of large international exporters in Taiwan and senior managers of shipping companies. The results reveal that green infrastructure is the most critical factor for container shipping lines, while energy efficiency and renewable energy technologies are dominant for bulk carriers and shippers. Corporate reputation and image emerge as primary factors impacted across all three groups. In financing decisions, green bonds are most suitable for container lines, whereas green equities are best suited for bulk carriers. This study bridges the theoretical gap between sustainability assessment and finance, providing practical guidance for shipping companies’ financial departments seeking to align decarbonization goals with effective green financing solutions. Ultimately, the primary contribution of this study lies in establishing an empirically validated, multi-criteria decision support framework that empowers maritime stakeholders to systematically optimize their green investment portfolios amid the global transition towards net-zero emissions. Full article

This research synthesizes a more than a decade of empirical and conceptual research on Industry 4.0 technologies with circular economy ecosystem in the European context. The shifting from linear to circular economy requires adoption of I4.0 technologies in particular Artificial Intelligence (AI), Internet of Things (IoT), and Virtual Reality (VR). Yet current scholarship on circular economy ecosystems (CEE) remains theoretically fragmented. To address this gap, we conducted a systematic literature review (SLR) of 94 peer-reviewed journal articles (2010–2025) using the Web of Science (WoS) database following the PRISMA protocol by deploying theories, contexts, methods (TCM) framework and thematic analysis. We developed a comprehensive framework based on addressing key barriers e.g., diverse expectations of stakeholders, resistance to change, sustainable leadership challenges, lack of digitally enabled-capabilities and institutional pressure with the help of important enablers such as AI capabilities, collaboration with stakeholders, frugal innovation and supportive government policies. Our findings contribute to the emerging discourse on how combining digital technologies with circular economy practices can support the development of low emission manufacturing systems, in line with current zero-emission policy goals in the European Union. This review contributes fragmented literature by highlighting theoretical, contextual and methodological gaps as previously disparate perspectives to help align and move research forward. This research contributes to SDG 9- “Industry, innovation and infrastructure” and SDG 12 “Responsible Consumption and Production”. Full article

Cosmic-Ray Neutron Sensing (CRNS) has become a standard method for non-invasive soil moisture monitoring at the field scale. With most CRNS sensors being derivatives from scientific nuclear equipment, the development of instruments based on alternative neutron detection technologies is a major development goal for CRNS. We present a modular instrument family based on boron-10-lined proportional counters, specifically designed for long-term autonomous field operation. The system is controlled by a data logger supporting various telemetry options and external SDI-12 environmental sensors, while the frontend electronics use pulse-height and pulse-length information to suppress non-neutron background and electronic noise. Our results show high energy efficiency, with the latest generation close to 50 mW, allowing solar-powered operation even in challenging environments. The performance of the instruments is validated within long-term field deployments in different settings, showing that boron-10-based systems provide a scalable, low-power and cost-efficient alternative for the next generation of CRNS monitoring networks. Full article

This study provides a comprehensive overview of emerging contaminants in water resources. It includes a global perspective with specific insights from Portugal. Following PRISMA 2020 guidelines, peer-reviewed studies published between 2020 and 2025 were critically assessed to identify patterns of contamination, monitoring gaps and technological readiness levels. Results indicate frequently detected emerging contaminants including pesticides, antibiotics and antidepressants in surface water, groundwater and wastewater systems. Advanced analytical methods, particularly liquid chromatography coupled with high-resolution mass spectrometry, stands out as the main detection technique, allowing the identification of trace levels of contaminants. These techniques also support the identification of pollution patterns associated with agriculture, urban and industrial effluents. However, significant asymmetries persist between international and Portuguese research. Particularly evident in systematic monitoring networks and integrated risk assessment approaches. Conventional water/wastewater treatment plants show limited removal efficiency, while advanced oxidation processes, adsorption technologies and microalgae-based systems demonstrate promising but variable performance depending on scale and operational maturity. The findings highlight gaps between scientific advances and regulatory implementation, emphasizing the need for strengthened monitoring frameworks and technology scale-up strategies. They also call for improved integration between science, governance, and sustainability policies to ensure resilient water resource management in line with the Sustainable Development Goals. Full article

The commissioning of private suppliers to conduct technological research and development (R&D) has become a central instrument for the public sector to promote technological innovation in public goods. However, information asymmetry and goal divergence between public principals and suppliers create moral hazard problems that can undermine innovation efficiency. Purely output-based incentive contracts are often insufficient to curb suppliers’ opportunistic behavior, especially when R&D outputs are uncertain and difficult to measure ex ante. This raises the need to complement incentive contracts with supervision mechanisms and to jointly optimize the structure of incentives and monitoring efforts. Building on principal–agent theory, this paper develops an incentive model that explicitly incorporates both supervision intensity and regulatory difficulty and analyzes how these factors shape suppliers’ R&D efforts and the public sector’s benefit levels. The results show, first, that appropriately designed supervision can increase suppliers’ willingness to invest in R&D and thereby help to strengthen the effectiveness of incentives. Second, incentive contracts need to be adjusted in line with supervision intensity: by reallocating rewards based on both observed outputs and supervision results, the public principal can induce higher effort levels. Third, as regulatory difficulty rises, the marginal effectiveness of supervision changes; under high regulatory difficulty, excessive supervision may even weaken incentive effects, implying that supervision intensity should be kept within a moderate range. Fourth, there exists an interior level of supervision intensity that balances monitoring costs against incentive benefits and thus maximizes the principal’s overall expected payoff. Viewed from a system engineering perspective, commissioned public goods R&D constitutes a complex multi-actor system subject to external disturbances in which incentive and supervision mechanisms operate as joint control structures regulating system behavior. The findings provide analytical support and policy-relevant insights for designing and calibrating supervision and incentive mechanisms in technological innovation projects for public goods. Full article

Food systems are currently challenged by a difficult balance: they rely heavily on natural resources while simultaneously generating significant volumes of waste, all under increasing pressure to decarbonize operations and close material loops. In this context, this study proposes strategic pillars for circular practices in the food industry, with an emphasis on the transformation of waste and by-products into high value-added resources through bio-based processes supported by biorefineries, in line with the Sustainable Development Goals (SDGs). To underpin this proposal, a PRISMA-guided content analysis of the literature published between 2019 and 2024 (Scopus) identified 30 recurrent CE elements. These elements were systematized into five strategic pillars: valorization of residues and by-products; digitalization of the food supply chain; sustainable education and stakeholder engagement; strategic partnerships for circular business; and regenerative practices based on renewable resources. Together, these pillars point to practical pathways, including the reuse of residues to produce functional ingredients and nutraceuticals, the creation of innovative, sustainable packaging, the generation of renewable energy from biomass, the strengthening of local supply networks, and the use of digital technologies to enhance traceability and transparency. By integrating and organizing fragmented evidence, the proposed framework delivers effective guidance to food industry actors, helping overcome economic and operational barriers to circular practices while supporting collaboration with local partners and research institutions. In doing so, it additionally contributes to advancing key SDGs, particularly SDGs 2, 7, 9, 12, 13, and 17. Full article

Against the backdrop of China’s “dual carbon” goals and rising global uncertainties, new energy technology innovation plays a critical role in advancing low-carbon transitions and ensuring energy security. However, existing studies mainly focus on single policy instruments, with limited attention to the causal effects of comprehensive, location-based policies. This study treats the establishment of National Green Industrial Parks (GIPs) as a quasi-natural experiment and employs a multi-period difference-in-differences (DID) approach based on panel data from 289 Chinese cities over 2008–2023. The results show that GIPs significantly increase local new energy innovation by approximately 19.1%, and this effect remains robust across multiple tests. Mechanism analysis indicates that fiscal support, green innovation, and industrial agglomeration are the main driving channels. Heterogeneity analysis further reveals stronger effects in the biomass (ρ = 0.243, p < 0.01) and wind energy (ρ = 0.179, p < 0.01) sectors, as well as in cities located southeast of the Hu Huanyong Line, with higher fiscal expenditure, and in non-resource-based cities. These findings provide empirical evidence for optimizing industrial park policies and promoting energy transition through localized policy diffusion. Full article

This paper investigates blockchain applications in the EU’s energy sector, particularly its integration into Internet of Things (IoT)-enabled smart grid systems. The study begins by mapping current EU regulations and incentives for smart energy solutions and reviews emerging smart grid technologies across Europe. The goal is to develop an Innovative Success Framework by analyzing European case studies, aiming to guide energy managers with practical strategies for improving smart grid efficiency. Key findings underscore the role of blockchain in ensuring secure, transparent energy transactions, addressing data security, energy distribution, and decentralized markets. Detailed case studies reveal common success factors: strong regulations, robust technology, and stakeholder engagement. The resulting framework aids energy managers in navigating smart grid complexities, promoting sustainable development through efficient, resilient, and low-carbon energy infrastructures. This research enriches discussions on smart energy, offering policymakers and industry professionals a tool to harness blockchain for advancing sustainable and secure energy systems in line with long-term EU development goals. Full article

Lean production philosophy and sustainability approach have become a critical framework for efficiency improvement, waste reduction, and promoting sustainable manufacturing practices. In the age of artificial intelligence (AI), there is a synergy, which has now found new dimensions, data-driven decision-making, predictive analytics, and operational agility. AI technologies promise to transform industrial processes by converging lean production and sustainability principles, a synergy explored in this paper. AI APIs enable the use of AI to improve resource utilization, reduce environmental pressure, and maintain economic growth inherent to all business sectors while also fostering social accountability. In this study, a robust regression model is employed to study the role of AI in moderating the lean practices and sustainability outcomes relationship, using a sample of 528 manufacturing firms. The results show that the contribution of AI technologies to economic, ecological, and social sustainability is effectively multiplied by that of lean production. This research offers a framework to help practitioners and policymakers optimize production systems in line with Sustainable Development Goals. Finally, the study delivers actionable recommendations for navigating skill gaps and cybersecurity risks that were identified. In sum, this paper contributes to the rapidly emerging conversation by providing empirical evidence on AI’s moderating role in the lean–sustainability relationship and offering a strategic framework for practitioners. Full article

The maritime industry is under increased challenges of balancing operational effectiveness and environmental responsibility. This study examines the application of intelligent agents as a technology that can align these two goals in the triple-bottom-line model that involves social responsibility, environmental footprint, and economic sustainability. An agent architecture taxonomy is outlined and adapted to the maritime industry, distinguishing between reactive, deliberative, hybrid, and multi-agent systems (MAS). The application of these architectures is analysed throughout the maritime domain. In the ship-centric environment, the analysis highlights the role of agents in autonomous navigation, energy-efficient meteorological routing, and predictive maintenance. The analysis in the port and supply-chain domain demonstrates a shift towards decentralized asset orchestration and logistic coordination rather than centralized control. The paper outlines certain barriers to widespread adoption, namely the reality gap of simulation-based training and the lack of transparency in deep-learning models (“black box” problem). The paper concludes by outlining a future research agenda proposing a use of explainable artificial intelligence (XAI), high-fidelity simulation-to-real transfer, and communication protocol standardization to continue the trend of developing strong autonomous capabilities in sustainable maritime logistics. Full article