Search Results (916)

There is ongoing debate about the value of infrastructure systems—energy, water, transport, waste, and communications—and how infrastructure investments should be prioritized to account for social, economic, and environmental wellbeing. The concept of an infrastructure system is inherently linked to interdependencies. Although infrastructure systems differ across countries and cities, they are all closely connected to transport, as movement involves both cost and utility. These systems ultimately exist to serve individuals, who assign value to them. To explore the full spectrum of value creation, which underpins business models, the relationship between individuals and transport infrastructure must be understood. This research tests the hypothesis that integrating economic, environmental, and social value dimensions within a unified business model provides a more comprehensive representation of infrastructure interdependencies than conventional economically focused approaches. Economic value was analyzed using principal component analysis of input–output tables, social value through structured interviews and statistical analysis, and environmental value using secondary data linked to economic demand in the infrastructure context of England, Scotland, Wales, and Northern Ireland. The proposed business model integrates social, economic, and environmental values, giving policymakers a clearer understanding of infrastructure system interactions and supporting more informed investment decisions that maximize societal value. Full article

The growing deployment of distributed renewable generation, storage, electric vehicles, heat pumps, smart buildings, and controllable demand is expanding the flexibility available to local energy systems. Energy communities provide the governance context for collective participation and value creation, while community virtual power plants provide the operational mechanism for aggregating distributed resources and connecting them to local optimisation, flexibility markets, grid services, and resilience functions. This PRISMA-ScR-informed framework development study synthesises the literature from Scopus, Web of Science, and IEEE Xplore to examine how artificial intelligence supports community VPP operation, where agentic AI adds capabilities beyond established optimisation, reinforcement learning, and multi-agent systems, and which design requirements follow governed orchestration. The synthesis shows that current evidence is strongest for component-level forecasting, scheduling, bidding, adaptive control, distributed coordination, and digital-twin validation, whereas integrated agentic orchestration remains an emerging direction. Classical multi-agent systems already provide decentralised representation, communication, negotiation, and coordinated control; the additional role proposed for agentic AI is therefore narrower and concerns context-aware multi-step workflow orchestration, governed tool use, exception handling, grounded explanation, and bounded delegation across existing analytical and control services. The study introduces operational flexibility intelligence as the capability to transform potential distributed flexibility into deployable, authorised, market-, grid-, resilience-, and community-compatible action. It further develops a conceptual layered reference architecture in which agentic orchestration operates through governed tools and interfaces rather than bypassing validated resource controllers. Fairness, comfort, privacy, cybersecurity, resilience, auditability, and human-in-command authority are treated as cross-cutting operational constraints. The architecture defines a design and validation agenda rather than an empirically validated implementation. Full article

The growing demand for personalized experiences in premium beverages has stimulated the development of consumer-centered strategies that allow active participation in product customization beyond traditional sensory evaluation. This study investigated Bougainvillea bract infusions subjected to three postharvest treatments—fresh material (Series A), sun-drying (Series B), and oven-drying at 105 °C (Series C)—as a platform for chromatic co-creation in silver tequila at the point of consumption. Five extract-to-tequila ratios (1:9–3:7, v/v) were characterized using CIELAB colorimetry, UV-Vis spectroscopy, and differential pulse voltammetry (DPV) and subsequently evaluated through sensory analysis with 30 untrained consumers. Postharvest drying generated two distinct chromatic families: fresh bracts produced bluish-red profiles (b* < 0; h° ≈ 273–280°), whereas dried bracts generated orange-red hues (b* > 0; h° ≈ 10–27°). Instrumental analyses revealed corresponding pigment transformations associated with betalain degradation and changes in phenolic composition, providing objective support for the observed visual differences. Sensory evaluation demonstrated that the infused formulations significantly enhanced color and aroma without affecting texture. Rather than identifying a universally preferred formulation, the results revealed complementary consumer preference profiles, highlighting the value of personalization in premium beverage experiences. Overall, this study demonstrates that scientifically characterized botanical infusions can transform color into an interactive consumer attribute, providing an analytically supported platform for chromatic co-creation and experiential consumption in premium tequila. Full article

Knowledge translation (KT) involves the co-creation, exchange and dissemination of knowledge to increase evidence-informed public health. Increasingly, there is a demand to strengthen evidence-informed public health, and with this, a need to understand how to support KT efforts within public health systems. Whilst a variety of KT frameworks have been developed, frameworks and studies that provide insight into KT initiatives that operate across the individual, organisational and system levels are lacking. This paper presents the development of a KT framework used by a government-funded sexual health and blood-borne virus capacity-building partnership for research and evaluation in an Australian jurisdiction. The approaches taken and practical insights into operationalising a collaborative approach to KT are described. The process of developing the framework included inputs from the literature, a needs assessment survey, and stakeholder consultation. The final framework is composed of a conceptual model and a suite of KT strategies that reflect the dynamic and complex nature of KT in public health. The framework illustrates the broader influences of KT, key strategies, and guiding principles. Findings have relevance for service providers, researchers and policymakers (including funders) seeking ways to engage in KT at the individual, organisational and system levels. Full article

Sustainable development depends on whether emerging economies can convert foreign direct investment (FDI) into durable, knowledge-based capabilities rather than transient, low-skill employment. This paper asks how FDI catalyzes sustainable human-capital formation and whether multinational enterprises (MNEs) can help build the institutions that underpin a knowledge-economy transition. Using a single-equation instrumental-variables (2SLS) model for human-capital formation, with secondary-school enrolment as the dependent variable over 46 annual observations for Morocco (1975–2020), we find a positive and statistically significant FDI effect (β = 0.0029 per million USD of FDI inflow, p = 0.006), robust in sign and significance across OLS, 2SLS, and Dynamic OLS specifications. The result is consistent with a skill-demand channel through which knowledge-intensive MNEs are associated with higher private and social returns to education and with increased targeted public and private training investment. Sectoral evidence from Morocco’s aerospace and automotive clusters shows enrolment in vocationally oriented program growing 312% between 2005 and 2022, concentrated in curricula co-designed with foreign investors. Communications infrastructure carries a positive and significant coefficient across all four estimators but loses significance once urbanization is added as a control, so we do not treat it as a confirmed independent channel, while public education expenditure carries a negative and significant coefficient that is not stable in sign under Fully Modified OLS, indicating that its independent contribution is not well identified with the present instrument set. We interpret these findings through a sustainability lens, linking the mechanism to Sustainable Development Goals 4 (quality education), 8 (decent work and growth) and 9 (industry, innovation and infrastructure), and we specify three boundary conditions—skill specificity, investor commitment, and state coordination capacity—and argue that the mechanism should be expected to transfer to other developing economies, including in the MENA region and sub-Saharan Africa, only where these conditions co-occur, rather than as a general claim. The study advances the literature on MNE-led institutional co-creation and offers policy guidance for designing FDI strategies that support inclusive, sustainable knowledge-economy development across the MENA region and sub-Saharan Africa. Full article

Forest management strongly influences understory plant communities, yet their responses to management remain context-dependent and scale-sensitive. This review synthesizes current knowledge on understory vegetation in managed forests by combining a bibliometric analysis of global research trends (1986–2025) with a comprehensive qualitative evaluation of empirical studies. The bibliometric assessment identified 726 publications, with a marked increase in output after 2017 and a predominance of research articles within Environmental Sciences, forestry, and biodiversity conservation. Research activity is geographically concentrated in North America and Europe, while other biomes remain comparatively underrepresented. The classical review highlights canopy structure and light availability as primary drivers of understory diversity. Management interventions such as thinning, harvesting, gap creation, and prescribed fire frequently increase local (α) species richness and vegetation cover in the short term by promoting early-seral and light-demanding species. However, these gains are often accompanied by compositional shifts toward ruderal and generalist taxa, reductions in bryophytes and forest specialists, and declines in spatial heterogeneity at broader scales. Consequently, β-diversity and landscape-level distinctiveness may decrease despite stable or elevated plot-level richness. Management intensity, retention of structural legacies (e.g., large trees and deadwood), soil and hydrological conditions, landscape context, and interactions with global change drivers (e.g., nitrogen deposition and climate warming) strongly mediate vegetation responses. Low-to-moderate-intensity systems that maintain structural heterogeneity and approximate natural disturbance regimes appear most effective at balancing production objectives with biodiversity conservation. Understory vegetation responses to forest management reflect trade-offs between short-term richness increases and long-term risks of compositional homogenization and specialist decline. Evaluating biodiversity outcomes therefore requires multi-scale, trait-informed approaches that move beyond species richness alone. This synthesis provides an integrative framework to support evidence-based, biodiversity-oriented forest management in increasingly human-modified landscapes. Full article

Environmental conditions have become more unstable; therefore, innovative and eco-friendly methods of food production are urgently required. Most existing hydroponic systems lack the capacity for real-time responses and decision-making based on integrated data, similar to contemporary farms. This document outlines the creation of an advanced hydroponic farming system that utilizes Internet of Things (IoT) sensors and a digital twin (DT) simulator to address these challenges. A completely monitored and continuously assessed hydroponic farming simulator operating on a Raspberry Pi, employing various sensors, data management and processing, and automated environmental regulation. The development of this intelligent hydroponic farming system employs a dual-model machine learning pipeline: one that identifies plant diseases through image analysis, and another that assesses plant nutrient levels based on sensor data. The data from the two models are combined using a cloud-based DT, enabling remote access to the DT and offering closed-loop control for irrigation, nutrient dosing, and management of all environmental factors related to crop growth in a hydroponic setting. This research showcases the capability to develop scalable, data-focused precision agriculture solutions that can adapt to the demands of today’s agricultural environment by combining all elements of IoT sensing, machine learning, and DT simulations into one functional hyperphysical system. Full article

Copper and its alloys are indispensable for electronics, communications, new energy systems, and aerospace engineering due to their exceptional electrical conductivity and mechanical properties. However, the thin cuprous oxide (Cu₂O) layer that naturally forms on copper and its alloys is prone to failure under elevated temperatures and high humidity, particularly in chloride-rich environments, leading to accelerated localized corrosion. While conventional chromate-based passivation has long been the industrial standard for preventing corrosion, its use has been increasingly restricted by global regulations (such as RoHS and REACH) due to its severe toxicity and health risks. To address the conflict between environmental compliance and protective performance, this review systematically evaluates recent advances in environmentally friendly, chromium-free anti-corrosion coatings in the present review. These alternative coatings are critically analyzed and categorized into four mechanistic groups: (i) inorganic conversion coatings (including molybdate, tungstate, rare earth, and phosphate systems); (ii) organic films formed via chemical or physical adsorption (such as organic inhibitors, thiol-based monolayers, and organosilane self-assembled films); (iii) conversion coatings engineered through covalent bonding, coordination chemistry, and microstructural tailoring; and (iv) multifunctional coatings that integrate self-healing capability with high electrical conductivity. Beyond providing a technical summary, this review explored how the swift progression of electronic information technology, new energy infrastructure, and robotics has imposed more exacting, multifunctional demands on copper components. This review provides a strategic roadmap for future research and prioritizes the creation of protection strategies that operate robustly in multi-physics coupling environments—integrating high conductivity, autonomous self-healing, and long-term chemical stability to ensure the reliability of next-generation infrastructure. Full article

Ensuring the sustainability of agriculture-related industries requires not only expanding value added but also maintaining stable value creation and adaptive capacity under changing economic conditions. This study examines the economic and organizational sustainability of China’s agriculture-related industries within global value chains. Using the 2026 release of the OECD Analytical Activities of Multinational Enterprises database and ownership-split inter-country input–output tables for 2011–2023, we construct an ownership-disaggregated value-added accounting framework covering the production, processing, and circulation stages and apply structural decomposition analysis to identify the sources of value-added change and potential weak links. The results show that domestic demand is the principal source of value creation for both domestic-owned and foreign-owned enterprises and became increasingly important over the study period. Final-goods-related value added remains larger than intermediate-goods-related value added, although the latter grows more rapidly, indicating deeper participation in cross-border production networks. Structural exposure varies across stages and periods. Production is strongly supported by domestic demand but exhibits pronounced internal offsetting in some periods; processing becomes a major adjustment node during 2019–2020, while circulation records the clearest contraction in the same period before returning to a more balanced growth structure during 2020–2023. Foreign-owned enterprises, particularly in processing, become increasingly embedded in China’s domestic market and local production structure. Risk exposure is interpreted as structural sensitivity rather than a direct measure of risk probability or expected loss. The findings highlight the importance of domestic demand, diversified input and market linkages, greater stability and adaptability in processing and circulation, and well-governed cross-ownership relationships for sustainable value-chain development. Full article

For millennia, farmers in cassava’s homeland in the neotropics selected varieties suited to their climate, soils, biological environments, management systems, and nutritional needs. These actions were fundamental to the crop’s success as a reliable staple energy source. After the arrival of Europeans in the New World, these varieties spread first to Africa and later to Asia, where they were further selected for local conditions and needs. The founders of the International Center for Tropical Agriculture in Cali, Colombia, recognized the importance of legacy landrace varieties as sources of genetic diversity for breeding to support tropical production systems, improve nutrition, and boost income. One of earliest activities of the new center, beginning in 1969, was to organize the collection of cassava landraces to establish a genetic resource for breeding purposes at the center’s headquarters in the Cauca Valley. We describe the multifaceted understanding about this remarkable heritage through thorough evaluation over a diverse range of environments and the creation of new varieties aimed at adding value across the crop’s diverse agro-ecologies and uses. CIAT breeders, along with a broad coalition of partners, have targeted demands from growers, processors, and consumers throughout the tropics. Latin American germplasm remains the foundational source of novel, high-value traits that differentiate cassava products across markets, underpinning the continued gains in productivity, quality, and end-use performance. Full article

AI is currently shaping how people are being entrepreneurial by allowing the establishment of AI-native ventures. The creation of these new types of businesses builds off an infrastructure of data, computing power, and research that typically accompany advanced economies. In contrast, most developing economies are still experiencing institutional and structural barriers that inhibit the formation of new ventures and their subsequent growth. Despite the existence of research that explores some of the ways in which successful ecosystems from developed economies could be applied to developing ecosystems, there is little guidance on how to systematically adapt these successful practices in resource-constrained environments. This research uses a comparative, document-based study design to assess how to benchmark and configure AI-native entrepreneurship ecosystems across heterogeneous institutional environments. Using Switzerland and Jordan as two contrasting analytical cases, we define twelve dimensions of an ecosystem and then create comparative ecosystem profiles using a standardized coding and scoring framework. We combine dimension-level data on talent development, applied research, infrastructure, financing, governance and market access with baseline socio-economic indicators. Our results demonstrate a high level of structural asymmetry between the two ecosystems. Switzerland has a balanced and highly coordinated configuration, whereas there is a strong university anchor and demand for talent in Jordan, but there are also significant weaknesses in terms of infrastructure, financing, and industry linkages. Building from these results, we present the parameter re-weighting and the context-sensitive design model to encourage the emergence of AI-native entrepreneurship in Jordan through coordinated architecture, collaborative experimentation resources and internationalization at an early stage. This article advances both the fields of entrepreneurial ecosystems and digital entrepreneurship by framing AI-native entrepreneurship as a new form of knowledge-intensive venture creation and providing a context-sensitive approach for adapting entrepreneurial ecosystems. The results provide a document-informed basis for policymakers, academic institutions and other ecosystem actors seeking to develop AI-based innovation in resource-constrained economies. Full article

External spaces of buildings represent a type of potential space that can supplement the urban public space system under the background of urban renewal. However, as spaces with ambiguous publicness, their design and layout often need to convey stronger welcoming attitudes to attract citizens’ use. This study aims to explore the expression elements of publicness in external spaces of museum buildings. A mixed method approach, including field observation and measurement, questionnaire surveys (with a total sample size of 277), and statistical analysis, was adopted to explore and reveal the design logic of publicness expression in the layout and form of external spaces of museum buildings. Taking nine museum building external spaces located in Beijing’s core area as empirical cases, this study analyzes the influence of spatial layout on publicness expression from six dimensions: leisure atmosphere and activity diversity, spatial quality and perceived safety, landscape creation and spatial comfort, pedestrian friendliness, spatial identity, and boundary treatment and management measures. The study aims to understand the subtle threshold characteristics between the design of external spaces of museum buildings and the expression of publicness, and to explore the benefits of external spaces of buildings in supplementing the urban public space system. This research is expected to respond to public demands for high quality public spaces and improve the refinement of urban space management and optimization. Full article

The creation of innovative learning environments in courses to provide sustained talent support has long remained a central research concern for high-quality social development. Neglected foundational skills in professional course clusters are often a hidden barrier to higher education for sustainable development (HESD). To close five persistent foundational skill gaps across improper citation (J1), ineffective figure use (J2), poor analysis (J3), irresponsible AI use (J4), and comprehensive application (J5) within the hydraulic engineering course cluster, a four-stage deliberate practice module (5Di-40Pr-5Tr-3Cm) has been embedded into a two-week hydraulic model experiment course, and its learning outcomes are systematically evaluated. A systematic analysis of its achievement levels across neglected foundational skill indicators of J1~J5 at each stage was conducted, stratified by the overall cohort and subgroups (P: objective demand, T: behavior type, G: optimization methods). The key findings include: ① deliberate practice demonstrates better teaching outcomes than lecture-based instruction, which can be evidenced in 2026, when J5’s achievement levels at the 3Cm stage yielded a moderate effect size relative to the 2025 lecture-based condition (d = 0.42); compared with the 2024 no-intervention baseline, the cumulative effect is a obvious increasing trend (d = 1.43); ② In far-transfer subgroup diagnosis, P2 (medium objective demand) shows a rank-order reversal, low at 40Pr but higher at 3Cm, and is identified as the “partial understanding” group and providing a diagnostic anchor for tiered intervention; ③ In near-transfer pathway diagnosis, J5’s low performance in 5Tr (65.35%, below overall mean of 83.09%; CV = 7%) stems from two distinct pathways: a “knowledge-deficit pathway” (max-decay subgroups) and a “processing-load pathway” (subgroups where J1, J2 do not exhibit max decay). In addition, stage-specific thresholds (40Pr: 90%, range 60~99%; 5Tr and 3Cm: 83% ± 3%, range of for 40Pr, mean = 90%, recommended range = 60~99%; for 5Tr, mean = 83% ± 3%, range = 65~96% and 75~90%) provide quantitative benchmarks for targeted intervention. These cumulative findings are intended to advance the evaluation paradigm of engineering practice courses from “total score attainment” toward “structural diagnosis” and align with the competency-oriented philosophy of higher education for sustainable development (HESD). Full article

In the context of economic globalization, effective cooperation and information sharing are critical for enhancing the efficiency and competitiveness of supply chains. Fresh agricultural product supply chains face distinctive challenges arising from high perishability, rapid demand fluctuations, and information asymmetry among supply chain members. This study develops an analytical framework comprising the following three conceptually connected but independently calibrated modules: an EOQ cost module, a comparative profit module, and a two-period, two-task dynamic principal–agent module. The modules are connected through the common economic logic of value creation, value distribution, and incentive design, rather than through a one-to-one numerical mapping. Using operational and financial information from the Erli River Crab supply chain in Panshan County, the EOQ and comparative profit models are independently calibrated at different decision scales to evaluate the benchmark economic effects of information-sharing-enabled coordination. The EOQ analysis uses annual aggregate operational quantities, whereas the comparative profit analysis uses a normalized transaction-demand scale; therefore, their numerical quantity magnitudes are not intended for direct one-to-one comparison. Within the EOQ module, information-sharing-enabled coordination reduces total relevant supply chain cost by 8.41% relative to the farmer-led decentralized benchmark and by 60.75% relative to the retailer-led decentralized benchmark. The difference arises because the farmer-led batch quantity is closer to the coordinated optimum, whereas the retailer-led order quantity is substantially smaller, implying a higher modeled frequency of upstream setup activities and a larger setup-cost component under the benchmark parameterization. These results capture the joint effect of full information availability and coordinated batch optimization under two alternative decentralized decision regimes. Within the comparative profit module, over the benchmark wholesale-price interval, the coordinated full-information-sharing benchmark increases total supply chain profit by 1.38–2.30% relative to the decentralized no-information-sharing benchmark. Under the unchanged-wholesale-price comparison, the farmer’s profit increases by 13.21–17.65%, whereas the retailer’s profit decreases by 1.74–3.11%. These results identify positive aggregate value creation and an asymmetric initial allocation under the linear-demand and unchanged-wholesale-price benchmark. This asymmetric allocation is benchmark-specific rather than an unavoidable consequence of information-sharing-enabled coordination, because a negotiated transfer or wholesale-price adjustment can redistribute the additional surplus. The extended analysis derives a participation-compatible transfer interval within which both the farmer and the retailer are weakly better off than under decentralized decision-making. Within the dynamic principal–agent module, a case-motivated illustrative simulation using standardized benchmark parameters shows that more informative intertemporal performance signals strengthen the optimal second-period incentive coefficient, whereas greater risk exposure limits the appropriate intensity of performance-based compensation. Continuation–payoff and ratchet-like effects jointly shape first-period information-sharing effort. Together, the three modules show how information-sharing-enabled coordination affects operational efficiency, surplus allocation, and intertemporal incentives. Full article

Belt conveyors are essential systems for the continuous transport of various materials in many sectors and applications, including heavy industry or mining, which are characterized by demanding environmental and operational conditions. Our research is focused on the development of the system based on magnetic sensors for the detection of ferromagnetic objects. These detection systems are designed to prevent damage to conveyor belts and the downstream vehicles, machines, and processing equipment involved in material transport and processing. By detecting hazardous foreign objects, they help avoid belt damage or tearing, thereby reducing operational disruptions and the associated maintenance and repair costs. Our study confirmed that in addition to the development of the hardware and software solutions, it is also necessary to develop methods for the processing and evaluation of the data recorded by the detection system, as the data represent a valuable source of information not only for the operational workers but also for the managers and are very helpful in the creation of the sustainable transportation system. The article describes an innovative application of the Weibull distribution for the operational enhancement of the system and its comparison to the conventionally used histograms. In addition to that, the utilization possibilities of the obtained statistical data to evaluate the belt conveyor loading for a better planning of the process, to monitor the work of the operational or other employees’ quality of the supported material, or to reveal failures of the detection system or even of the belt conveyor are overviewed and discussed. Full article