Search Results (5,346)

Road infrastructure underpins Nigeria’s economic competitiveness, yet Public–Private Partnership (PPP) performance is constrained not by inadequate legislation but by persistent weaknesses in enforcement and governance. Transparency deficits across procurement, design management, certification, and toll-revenue reporting have produced chronic delays, cost overruns, and declining public trust. This study offers the first empirical investigation of blockchain–Building Information Modelling (BIM) integration as a transparency-enhancing mechanism within Nigeria’s PPP road sector, focusing on Lagos State. Using a qualitative design, ten semi-structured interviews with stakeholders across the PPP lifecycle were thematically analysed to diagnose systemic governance weaknesses and assess the contextual feasibility of digital innovations. Findings reveal entrenched opacity rooted in weak enforcement, discretionary decision-making, and informal communication practices—including biased bidder evaluations, undocumented design alterations, manipulated certifications, and toll-revenue inconsistencies. While respondents recognised BIM’s potential to centralise project information and blockchain’s capacity for immutable records and smart-contract automation, they consistently emphasised that technological benefits cannot be realised absent credible institutional foundations. The study advances an original theoretical contribution: the Codify–Condition–Capacitate framework, which explains the institutional preconditions under which digital governance tools can improve transparency. This framework argues that effectiveness depends on: codifying digital standards and legal recognition; conditioning enforcement mechanisms to reduce discretionary authority; and capacitating institutions through targeted training and phased pilots. The research generates significant practical implications for policymakers in Nigeria and comparable developing contexts seeking institution-aligned digital transformation. Methodological rigour was ensured through purposive sampling, thematic saturation assessment, and documented analytical trails. Full article

With the rapid development of the Internet of Things (IOT), 5G, and modern power systems, demand-side loads are becoming increasingly observable and remotely controllable, which enables demand-side flexibility to participate more actively in grid dispatch and emergency support. Under extreme rainstorm conditions, however, component failure risk rises and the availability and dispatchability of demand-side flexibility can change rapidly. This paper proposes a risk-aware emergency regulation framework that translates rainstorm information into actionable multi-load aggregation decisions for urban power systems. First, demand-side resources are quantified using four response attributes, including response speed, response capacity, maximum response duration, and response reliability, to enable a consistent characterization of heterogeneous flexibility. Second, a backpropagation (BP) neural network is trained on long-term real-world meteorological observations and corresponding reliability outcomes to estimate regional- or line-level fault probabilities from four rainstorm drivers: wind speed, rainfall intensity, lightning warning level, and ambient temperature. The inferred probabilities are mapped onto the IEEE 30-bus benchmark to identify high-risk areas or lines and define spatial priorities for emergency response. Third, guided by these risk signals, a two-level coordination model is formulated for a load aggregator (LA) to schedule building air conditioning loads, distributed photovoltaics, and electric vehicles through incentive-based participation, and the resulting optimization problem is solved using an adaptive genetic algorithm. Case studies verify that the proposed strategy can coordinate heterogeneous resources to meet emergency regulation requirements and improve the aggregator–user economic trade-off compared with single-resource participation. The proposed method provides a practical pathway for risk-informed emergency regulation under rainstorm conditions. Full article

Yeast biosensors represent a promising biotechnological innovation for ensuring the safety and quality of fermented beverages such as beer, wine, and kombucha. These biosensors employ genetically engineered yeast strains to detect specific contaminants, spoilage organisms, or hazardous compounds during fermentation or the final product. By integrating synthetic biology tools, researchers have developed yeast strains that can sense and respond to the presence of heavy metals (e.g., lead or arsenic), mycotoxins, ethanol levels, or unwanted microbial metabolites. When a target compound is detected, the biosensor yeast activates a reporter system, such as fluorescence, color change, or electrical signal, providing a rapid, visible, and cost-effective means of monitoring safety parameters. These biosensors offer several advantages: they can operate in real time, are relatively low-cost compared to conventional chemical analysis methods, and can be integrated directly into the fermentation system. Furthermore, as Saccharomyces cerevisiae is generally recognized as safe (GRAS), its use as a sensing platform aligns well with existing practices in beverage production. Yeast biosensors are being investigated for the early detection of contamination by spoilage microbes, such as Brettanomyces and lactic acid bacteria. These contaminants can alter the flavor profile and shorten the product’s shelf life. By providing timely feedback, these biosensor systems allow producers to intervene early, thereby reducing waste and enhancing consumer safety. In this work, we review the development and application of yeast-based biosensors as potential safeguards in fermented beverage production, with the overarching goal of contributing to the manufacture of safer and higher-quality products. Nevertheless, despite their substantial conceptual promise and encouraging experimental results, yeast biosensors remain confined mainly to laboratory-scale studies. A clear gap persists between their demonstrated potential and widespread industrial implementation, underscoring the need for further research focused on robustness, scalability, and regulatory integration. Full article

Promoting the value realization of ecological products is a central issue in practicing the concept that “lucid waters and lush mountains are invaluable assets.” This is particularly urgent for alpine regions, which are vital ecological security barriers but face stringent developmental constraints. This study takes Golog Tibetan Autonomous Prefecture in Qinghai Province as a case study. It establishes a Gross Ecosystem Product (GEP) accounting framework tailored to the characteristics of alpine ecosystems and conducts continuous empirical accounting for the period 2020–2023. The findings reveal that: (i) The total GEP of Golog is immense (reaching 655.586 billion yuan in 2023) but exhibits significant dynamic non-stationarity driven by climatic fluctuations, with a coefficient of variation as high as 11.48%. (ii) The value structure of the GEP is highly unbalanced, with regulatory services contributing over 97.6%. Water conservation and biodiversity protection are the two pillars, highlighting its role as a supplier of public ecological products and the predicament of market failure. (iii) The spatial distribution of GEP is highly heterogeneous. Maduo County, comprising 34% of the prefecture’s land area, contributes 48% of its total GEP, with its value per unit area being 1.68 times that of Gande County, revealing the spatial agglomeration of key ecosystem services. To address the dynamic, structural, and spatial constraints identified by these quantitative features, this paper proposes synergistic realization pathways centered on “monetizing regulatory services,” “precision policy regulation,” and “capacity and institution building”. The aim is to overcome the systemic bottlenecks—“difficulties in measurement, trading, coarse compensation, and weak incentives”—in alpine ecological functional zones. This provides a systematic theoretical and practical solution for fostering a virtuous cycle between ecological conservation and regional sustainable development. Full article

Amid China’s “Manufacturing Power” push, full-chain digital restructuring in the Guangdong–Hong Kong–Macao Greater Bay Area remains hampered by mismatches among technology, organization, and environment. We therefore explored how shop floor actors perceive and shape this Technology–Organization–Environment (TOE) interplay. Semi-structured interviews with frontline operators, maintainers, and supply chain staff from GBA manufacturers were inductively coded, yielding 36 concepts, 10 categories, and 3 core TOE aggregates that were woven into a grounded model. The analysis shows that industrial internet platforms and smart equipment only create value when matched by flexible shop floor structures, cross-department data protocols, and skilled teams; otherwise, data silos, simulation–production deviations, and “buy-but-not-build” procurement stall adoption. Market pressure for customized, short-lead-time products and divergent municipal pilot policies further intensify the TOE balancing act, particularly for SMEs with weak absorptive capacity. By revealing a grassroots “technology-driven → organization-adapted → environment-adjusted” spiral that is moderated by frontline feedback, the study extends the TOE framework to micro-level, regional innovation theory and offers policy–practice levers for differentiated, cross-city manufacturing upgrading. Full article

Occupational Health and Safety (OHS) in educational settings is a vital responsibility that is often inconsistently implemented. There is a need for research to bridge the gap between policy and practice. This study employed a cross-sectional mixed-methods design in six schools in the capital city of Indonesia to identify key implementation barriers, strategies, and compliance levels in OHS. Data were collected from 217 teachers using a structured KPAP (Knowledge, Attitudes, Perceptions, Practices) survey and from an additional 38 teachers via Focus Group Discussions (FGDs). Quantitatively, teachers showed highly positive attitudes (99.4% viewing OHS as a professional duty) and generally positive perceptions but implementation practices were sub-optimal (e.g., low participation in drills and PPE usage), showing a gap between awareness and action. Qualitatively, the main barriers identified were a lack of specific OHS regulation or guidance for schools, limited resources/infrastructure, and the perception of OHS as a low priority. Management strategies focused on external collaboration and ongoing in-school initiatives. In conclusion, a significant gap exists between OHS awareness and its integration into school management, highlighting the urgent need for strengthened governance, comprehensive policies, and sustained capacity-building to ensure a proactive, safe, and sustainable school environment for staff and students. Full article

The incorporation of Artificial Intelligence (AI) into medical services in Saudi Arabia offers a substantial opportunity. Despite the increasing integration of AI techniques such as machine learning, natural language processing, and predictive analytics, there persists an issue in the thorough comprehension of their applications, advantages, and issues within the Saudi healthcare framework. This study aims to perform a thorough systematic literature review (SLR) to assess the current status of AI in Saudi healthcare, determine its alignment with Vision 2030, and suggest practical recommendations for future research and policy. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, 699 studies were initially obtained from electronic databases, with 24 studies selected after the application of established inclusion and exclusion criteria. The results indicated that AI has been effectively utilised in disease prediction, diagnosis, therapy optimisation, patient monitoring, and resource allocation, resulting in notable advancements in diagnostic accuracy, operational efficiency, and patient outcomes. Nonetheless, limitations to adoption, such as ethical issues, legislative complexities, data protection issues, and shortages in worker skills, were also recognised. This review emphasises the necessity for strong ethical frameworks, regulatory control, and capacity-building efforts to guarantee the responsible and fair implementation of AI in healthcare. Recommendations encompass the creation of national AI ethics and governance frameworks, investment in AI education and training initiatives, and the formulation of modular AI solutions to guarantee scalability and cost-effectiveness. This breakthrough enables Saudi Arabia to realise its Vision 2030 objectives, establishing the Kingdom as a global leader in AI-driven healthcare innovation. Full article

Dual Carbon Goals are driving transformation in China’s power system, where increased renewable energy penetration is accompanied by heightened fluctuations on the generation and load sides. Energy storage and microgrid coordination have emerged as key solutions. However, existing research faces the challenge of balancing microgrid operations, energy storage services, and the alignment of user demand with stakeholder interests. This paper establishes a tripartite collaborative optimization framework to balance multi-stakeholder interests and enhance system efficiency, assuming fixed energy storage capacity. Centering on a principal-agent game between microgrid operators and consumer aggregators, energy storage service providers are integrated into this dynamic. Microgrid operators set 24-h electricity and heat pricing while adhering to tariff constraints, prompting consumer aggregators to adjust energy consumption and storage strategies accordingly. The KKT conditional method is employed to solve the model, deriving optimal user energy consumption strategies at the lower level while solving marginal pricing equilibrium relationships at the upper level, balancing accuracy with information privacy. The creative contribution of this article lies in the first construction of a tripartite collaborative optimization architecture in which energy storage service providers are embedded in a game of ownership and subordination. It proposes a dynamic coupling mechanism between pricing power, energy consumption decision-making, and energy storage configuration under fixed energy storage capacity constraints, achieving a balance of interests among multiple parties. By building a case study using MATLAB (R2022b), we compare operation costs, benefits, and absorption rates across different scenarios to validate the framework’s effectiveness and provide a reference for engineering applications. Full article

Global climate change has emerged as a critical challenge for human society in the 21st century. As hubs of population and economic activity, urban and rural areas are increasingly exposed to complex and compounded disaster risks. To systematically evaluate the role of educational intervention in climate adaptability capacity building, this study employs a case study approach, focusing on the “Climate Change Adaptation Education and Teaching Alliance Program” launched in Taiwan in 2014. Through a comprehensive analysis of its institutional structure, curriculum, alliance network, and practical activities, the study explores the effectiveness of educational innovation in cultivating climate resilience talent. The study found that the program, through interdisciplinary collaboration and a practice-oriented teaching model, successfully integrated climate adaptability content into 57 courses, training a total of 2487 students. Project-based learning (PBL) and workshops significantly improved students’ systems thinking and practical abilities, and many of its findings were adopted by local governments. Based on these empirical results, the study proposes that urban and rural planning education should be promoted in the following ways: first, updating teaching materials to reflect regional climate characteristics and local needs; second, enhancing curriculum design by introducing core courses such as climate-resilient planning and promoting interdisciplinary collaboration; third, enriching hands-on learning through real project cases and participatory workshops; and fourth, deepening integration between education and practice by establishing multi-stakeholder partnerships supported by dedicated funding and digital platforms. Through such an innovative educational framework, we can prepare a new generation of professionals capable of supporting global sustainable development in the face of climate change. This study provides a replicable model of practice for education policymakers worldwide, particularly in promoting the integration of climate resilience education in developing countries, which can help accelerate the achievement of UN Sustainable Development Goals (SDG11) and foster interdisciplinary collaboration to address the global climate crisis. Full article

The capacity of the United Kingdom (UK) to prosecute technology-enabled financial and economic crime (FEC) is increasingly shaped by the Collingridge dilemma. Even though the dilemma was broadly conceptualized in technology governance, its application to prosecutorial and enforcement practice, evidentiary standards, and criminal liability attribution represents uncharted scholarly territory. Through socio-legal mixed methods combining doctrinal analysis, case studies, and comparative analysis, the paper shows how the dilemma’s two horns or pillars (i.e., early epistemic uncertainty and late institutional inertia) manifest in criminal law and regulatory contexts. The paper finds that just like the European Union and United States, the UK criminal enforcement ecosystem exhibits both horns across cryptocurrency, algorithmic trading, artificial intelligence (AI), and fintech domains. By integrating supplementary theories such as responsive regulation, precautionary principles and technological momentum, the study advances a socio-legal framework that explains enforcement inertia and doctrinal gaps in liability attribution for emerging technologies. The paper demonstrates how epistemic uncertainty and institutional entrenchment shape enforcement outcomes and proposes adaptive strategies for anticipatory governance including technology-literate capacity building, anticipatory legal reform, and data-driven public-private coordination. These recommendations balance ex-ante legal clarity (reducing uncertainty) with ex-post enforcement agility (overcoming entrenchment) to provide a normative framework for navigating the Collingridge dilemma in FEC prosecution. Full article

Forest certification in developing countries faces significant challenges due to weak institutions, limited market incentives, and complex trade conditions. This study investigates the status and key constraints of the Myanmar forest certification sector through a survey of 180 stakeholders from government organizations, NGOs, INGOs, third-party certification bodies, and private plantation owners, complemented by quantitative analysis and qualitative interviews. The results indicate a moderate level of familiarity with the Myanmar forest certification standard and high awareness of the Myanmar Forest Certification Committee; however, progress remains slow due to limited transparency, poor institutional coordination, financial and technical constraints, and insufficient stakeholder involvement. Non-compliances issues identified during pilot audits were primarily related to incomplete documentation, unclear land tenure, and weaknesses in environmental assessment. Geopolitical factors continue to limit Myanmar’s participation in certified timber markets and weaken efforts to improve traceability. Experiences from Indonesia, Malaysia, and Vietnam highlight that developing credible national certification systems requires time, clear legal frameworks, and strong cooperation among stakeholders. Strengthening institutional capacity, improving transparency, and aligning national standards with international forest governance frameworks are essential for Myanmar to build trust, achieve sustainable forest management, and regain market access. Full article

Root exudates are key mediators of plant–soil–microbe interactions, shaping rhizosphere dynamics and influencing agroecosystem resilience. Comprising diverse primary and secondary metabolites, these compounds are actively secreted through specific transport pathways and are modulated by intrinsic plant traits and environmental conditions. Root exudates serve as chemical signals that recruit and structure microbial communities, facilitating nutrient mobilization, microbial feedbacks, and the regulation of plant growth and stress responses. By modulating soil chemical, physical, and biological properties, exudates contribute to carbon cycling, soil health, and the maintenance of ecosystem services. Moreover, they play multifunctional roles in enhancing plant tolerance to abiotic and biotic stresses, while also mediating interactions with neighboring plants. This review provides a holistic perspective on root exudation, encompassing their mechanisms and drivers, roles in rhizosphere ecology and plant stress adaptation, and methodological advances, while highlighting opportunities to harness these processes for resilient, productive, and sustainable agroecosystems. Full article

The increasing proliferation of new energy vehicles and autonomous vehicles has led to the formation of mixed traffic flows characterized by diverse driving behaviors, posing new challenges for intersection signal control. To address this issue, this study proposes a multi-class customer feedback queuing network (MCFFQN) model that incorporates state-dependent road capacity and congestion propagation mechanisms to accurately capture the stochastic and dynamic nature of mixed traffic flows. An evaluation framework for intersection performance is established based on key indicators such as vehicle delay, the energy consumption of new energy vehicles, and the fuel consumption and emissions of conventional vehicles. A recursive solution algorithm is developed and validated through simulations under various traffic demand scenarios. Building on this model, a signal timing optimization model aimed at minimizing total costs—including delay and environmental impacts—is formulated and solved using the Mesh Adaptive Direct Search (MADS) algorithm. A case study demonstrates that the optimized signal timing scheme significantly enhances intersection performance, reducing vehicle delay, energy consumption, fuel consumption, and emissions by over 20%. The proposed methodology provides a theoretical foundation for sustainable traffic management under mixed traffic conditions. Full article

This paper draws on a capacity-building initiative by the researcher to prepare the parents of nine selectively mute (SM) children to take the lead in their child’s change process towards, gradually and in tiny steps, starting to speak in more situations and to more people. Egan’s skilled helper model is used as a framework in the parent guidance group. Focus group interviews in the parent group make up the data set for the project, along with the parents’ written answers to questions arising from Egan’s skilled helper model between meetings. Content analysis is used to analyse the data. A common theme among the families is how to find the right balance between supporting and challenging the SM child in communication with others. How to promote greater independence in parent–child relationships is the main question from the project. Full article

This paper addresses the problem of imbalance between coastal and inland areas and recognises the reuse of abandoned buildings as an evolutionary regeneration strategy which, through specific interventions linked by a system of routes for tourism and sport, can gradually trigger sustainable development on a regional scale. It presents research conducted in recent years on behalf of local administrations and continued in national and European projects. The reference context is the Abruzzo region, where coastal, hilly and mountainous areas are a short distance apart and include both densely built-up and populated urban centres and small depopulated towns surrounded by landscapes of high environmental value. The objective is to define, through the responsible use of built resources, viable and sustainable strategies for regeneration and rebalancing oriented towards the concept of transformative resilience. The methodology adopted is divided into phases and includes both theoretical developments and case study applications according to an approach that networks building restoration and reuse interventions in the region. The key results consist of defining a reuse logic that considers the regional territory as a whole, linking different resources, functions and environments. This logic, which envisages the organisation of new functions on a regional scale, emphasises the capacity of building reuse to produce positive effects on the territory and trigger socio-economic development dynamics. This research forms part of the experience underlying a project of significant national interest (PRIN 2022 TRIALs), which will provide guidelines for activating the transformative resilience capacities of inland areas of central Italy. Full article