Search Results (2,859)

Limited access to quality seed constrains vegetable productivity and food security in Uganda, where informal seed systems remain central to farmers’ access to seed but are inadequately documented and largely unregulated. This study documented vegetable seed production and management practices, identified opportunities and constraints within informal seed systems, and examined the role of community seed banks in strengthening seed security. Using a mixed-method approach, quantitative surveys and key informant interviews were conducted with seed producers, seed traders, and community seed bank leaders across Uganda. Study respondents were predominantly men, with most respondents aged ≥35 years, despite women’s and youth’s primary role in vegetable production. Respondents reported key seed management constraints of seed storage pests, low-quality seeds, inconsistent market supply and price fluctuations, limited capital, and weak regulatory oversight. Seed treatment practices primarily consisted of sun-drying and plant-based pesticides, while seed quality assessment relied largely on experience and visual inspection, using cues such as seed color, size, and cleanliness, with limited use of standardized testing. Given that most vegetable growers obtain seeds through community-based seed channels, strengthening actors’ capacity to produce and supply high-quality seed is essential for sustaining vegetable production, improving farmer incomes, and enhancing food and nutrition security. Full article

Soil erosion on sloping farmland impairs cultivated land quality, food security, and watershed ecological sustainability across China. Vegetation serves as a core erosion buffer, yet how nitrogen–phosphorus (N-P) stoichiometry shapes coordinated maize growth to regulate multi-stage runoff–sediment coupling remains underexplored. This study reveals the complete mechanistic chain linking N-P ratios, crop growth synchrony, and hillslope erosion dynamics via 60 mm·h⁻¹ simulated rainfall experiments at three key summer maize stages, with six N/P gradients (0–3.75) in an eastern China brown soil zone. An N/P ratio of 2 optimized maize biomass, canopy cover, and root soil-binding capacity, yielding the lowest sediment concentrations. Excess nitrogen (N/P = 3.75) triggered spindly, mechanically weak maize growth, elevating runoff volume and sustaining high-variability sediment transport. High-frequency runoff–sediment signals maintained a consistent positive correlation, while mid/low-frequency components decoupled under imbalanced N-P supply. Moderate balanced N-P fertilization (N/P = 1–2) stabilized hillslope hydrological-erosion processes throughout the growing cycle, whereas surplus nitrogen induced asynchronous erosion responses. This research delivers quantitative evidence for coordinated high-yield and erosion-control nutrient management. Full article

Accurately acquiring soil moisture content (SMC) and its spatial distribution is of great significance for water-saving irrigation and sustainable agricultural development in arid regions. However, the complex soil background noise and weak moisture absorption features in the Xinjiang region severely restrict the accuracy and reliability of remote sensing inversion for SMC. To address the challenges of difficult feature capture and low estimation accuracy in soil moisture monitoring, this study utilized GF-5 satellite hyperspectral data and ground-measured SMC data. First, the effects of Fractional-Order Differentiation (FOD) at orders 0–2 (with a 0.2 step size) on spectral moisture response were systematically evaluated. Next, 60 dual-band spectral indices (DBIs) were constructed from full-band combinations under the optimal differentiation orders, and highly correlated indices were selected as candidate features. Finally, three variable screening methods were coupled with three machine learning models to construct nine SMC inversion schemes, and the optimal model combination was employed to map the spatial distribution of SMC in the study area. Results showed that FOD at orders 0.8–1.2 effectively enhanced spectral responses at soil moisture absorption bands, the introduction of DBI concentrated high-correlation band combinations in moisture-sensitive regions, and the optimal scheme (BSS-PLSR) demonstrated good predictive performance and stability. These findings provide data support for precision irrigation decision-making and soil moisture management in arid farmlands. Full article

Depopulation represents one of the most significant development challenges in the rural areas of the Pannonian Plain. This paper examines phenomena observed in the Vojvodina Region that may contribute to mitigating negative demographic trends. The research was initiated by information and narratives identified in the media and subsequently verified through fieldwork. The study is based on the analysis of semi-structured interviews conducted with residents of settlements where the presence of new inhabitants has been identified. Particular attention is paid to the settlement of foreign nationals and returning migrants, the arrival and return of well-known public figures to rural areas, and state support measures aimed at encouraging people to remain in or return to rural settlements. The paper also considers the role of the media in promoting rural areas, as well as the importance of new forms of work that enable greater spatial mobility and facilitate living outside urban centers. The collected data were analyzed using SWOT analysis, which enabled the identification of strengths, weaknesses, opportunities, and threats associated with the presence of new residents in rural areas. The aim of the paper is to examine the contributions of new residents to the sustainable development of rural areas in the Vojvodina Region and to highlight their alignment with the objectives of the 2030 Agenda for Sustainable Development. The significance of the study lies in drawing scholarly attention to these phenomena and emphasizing the need for their continuous monitoring, as they may influence future demographic, economic, social, and spatial transformations of the Vojvodina Region. Full article

To address the rapid flash setting of NaOH-activated slag and promote high-volume utilization of coal-based solid wastes, this study investigated the synergy of fly ash (FA), coal gangue (CG), and gasification slag (GS) in partially replacing granulated blast furnace slag (GBFS) for NaOH activated binders, aiming to mitigate flash setting while preserving mechanical performance. Binary and ternary pastes with up to 90 wt% substitution were evaluated for setting time, fluidity, and compressive strength, supported by quantitative XRD and SEM. The G8F1G1 achieved the optimal balance, extending initial and final setting times from 28 and 32 min to 35 and 43 min, yielding a fluidity of 218 mm, and maintaining a 28-day strength of 48.5 MPa, equivalent to neat GBFS. The FA-GS synergy suppressed crystalline by damping the Ca²⁺ supersaturation peak through FA derived oligomers while providing nucleation sites via fine carbonaceous particles in GS, thereby retaining the amorphous C-A-S-H gel at approximately 77 wt%. This preserved the load-bearing gel network but eliminated early percolating crystalline frameworks, extending workability without strength loss. In contrast, CG acted as an inert diluent, introducing weak interfaces and porosity that severely degraded strength. A critical amorphous threshold near 64 wt% (G6F2G2, amorphous gel) governed the transition to a granular bed. The FA-GS system offers an effective route for high-volume valorization of coal-based solid wastes in sustainable construction materials. Full article

Following the 2021 Montiferru wildfire, one of the largest wildfire events in modern Italian history, assessing the suitability of olive-growing environments for high-quality extra virgin olive oil (EVOO) production is crucial for supporting sustainable agricultural restoration. This study models the spatial distribution and temporal stability of total polyphenol concentration in EVOO (cv. Bosana) across a complex Mediterranean landscape. Olive samples from georeferenced sites were collected during the 2022 (22 samples) and 2023 (37 samples) harvest seasons and processed using a standardized protocol. Spatial modeling was performed via Empirical Bayesian Kriging Regression Prediction (EBKRP), integrating seven bioclimatic and topographic covariates. Cross-validation demonstrated high predictive accuracy with negligible bias (RMSE = 53.3 and 58.8 mg kg⁻¹ for 2022 and 2023, respectively). While single-predictor correlations were weak, multi-variable analysis highlighted a strong interaction between topography and water balance driving phenolic accumulation. The mean prediction map identified regional hotspots approaching600 mg kg⁻¹ of polyphenols content in the obtained olive oils. Spatial overlay analysis successfully delineated “Stable High-Phenolic Core Areas” (>500 mg kg⁻¹ with interannual variation < 100 mg kg⁻¹), filtering out high-altitude marginal zones. This geostatistical approach provides a valuable territorial decision-making tool to support post-fire agricultural reconversion and the valorization of high-quality monovarietal EVOO terroirs. Full article

Water conservation is among the most important ecosystem service functions, and its dynamic changes can reflect the health of regional ecosystems. As one of the ten major tributaries of the Yellow River, the Yi–Luo River in Henan Province plays a significant role in maintaining regional ecological health through the ecosystem water conservation functions of its basin. To explore the characteristics of these functions, this study employed ecosystem transfer matrix and water balance methods to analyze the changes in ecosystem types in the basin and the dynamic changes in the corresponding water conservation functions from 2010 to 2020. The results showed that from 2010 to 2020, the dominant ecosystem types were farmland, forestland, and shrubland, and the main transformations between different ecosystem types were from farmland to urban areas and wetland, from grassland to shrubland, and from shrubland to forestland. The water conservation functions of the different ecosystem types varied significantly, with the average water conservation capacities ranked as follows: forestland > wetland > shrubland > grassland > farmland > others > urban areas. Due to the decreased water conservation depths in the forestland and shrubland ecosystems, the overall water conservation depth decreased over the study period. In addition, the water conservation capacities of the farmland, forestland, and shrubland ecosystems were the highest, reaching 12.94 × 10⁸, 12.15 × 10⁸ and 9.73 × 10⁸ tons, respectively, accounting for 34.47%, 32.35%, and 25.91% of the total water conservation capacity, respectively. Overall, water conservation in the study area was high in the south and low in the north, and there was an overall decreasing trend over time. Moreover, the regions with critical and important water conservation functions accounted for the largest proportion (47.2%). The critical and important regions were mainly located in the higher altitudes of Luanchuan County and Lushi county, while the moderate and average regions were primarily located in the plains, and weak regions were distributed mainly in the urban area of Luoyang city. Through analysis of the spatiotemporal changes and degree of importance of water conservation functions in the Yi–Luo River Basin, the key regions for ecological protection and construction were identified. The study results can be used to help enhance ecological security in the Yellow River Basin of Henan Province and play a significant role in promoting the regional economy as well as the health and sustainable development of the ecological environment. Full article

Electrical machine design faces growing constraints from power density, wide operating ranges, thermal and mechanical limits, acoustics, manufacturability, cost, and critical material availability. While finite element and multi-physics simulations remain essential, their direct use in population-based or multi-objective optimization is often computationally prohibitive. AI, spanning surrogate modeling, machine learning, deep learning, physics-informed networks, Bayesian optimization, and emerging generative methods, is increasingly used to accelerate analysis, enlarge design spaces, and support inverse or multi-objective tasks. This review examines AI-assisted electrical machine design from a workflow perspective, distinguishing functional approximation, performance prediction, topology-aware learning, physics-informed modeling, active learning, and robust optimization under uncertainty. It highlights current limitations, including narrow topology coverage, reliance on FEM-generated data, weak extrapolation, limited uncertainty reporting, scarce experimental validation, and insufficient attention to manufacturability and sustainability. A design-readiness framework and minimum reporting checklist are proposed to improve trustworthiness and reusability. The review concludes that AI should serve as a physics-aware, validation-dependent accelerator, complementing, not replacing, electromagnetic expertise, multi-physics simulation, and prototype testing. Full article

Artificial intelligence, digital payments and platform-based services are reshaping the operating conditions of Africa’s informal economy and micro-enterprise sector. While mobile money, digital marketplaces, app-mediated logistics and algorithmic scoring systems are commonly presented as instruments of financial inclusion and enterprise modernisation, their effects on informal traders remain uneven, conditional and under-governed. This systematic review synthesises recent peer-reviewed evidence on AI-mediated digitalisation pathways for informal and micro-enterprises in Africa, with particular attention to mobile money, platform payments, app-based logistics, digital credit, algorithmic management and platform governance. Following PRISMA-informed systematic review procedures, this review analyses 60 peer-reviewed, DOI-bearing articles published between April 2022 and June 2026 through a mechanism–outcome synthesis approach. The final corpus was selected through database searching, duplicate removal, title-and-abstract screening, full-text eligibility assessment, quality appraisal and mechanism–outcome coding. The findings show that digitalisation can expand market access, reduce cash-handling risks, create transaction histories, strengthen customer reach, improve operational continuity and support household resilience. However, the same digital infrastructures may also intensify livelihood vulnerability through opaque scoring, unexplained account freezes, fee shocks, exclusionary verification procedures, algorithmic ranking losses, data extraction and weak dispute-resolution mechanisms. The review therefore argues that informal enterprise digitalisation should not be understood only as a technology adoption issue, but as a socio-technical systems governance challenge. The article contributes a governance-and-risk framework linking local infrastructure, platform and payment design, AI (artificial intelligence) mediation, adoption conditions and livelihood outcomes. It further identifies minimum policy and design protections required for inclusive and resilient participation, including transparent fees, proportionate verification, human appeal channels, explainable restrictions, data-use consent, timely settlement and contingency mechanisms during digital outages or erroneous flags. The review concludes that sustainable digital inclusion for African informal micro-enterprises depends not merely on access to digital tools, but on the fairness, transparency, recoverability and accountability of the systems through which traders participate. Full article

Rice husk ash (RHA) has emerged as a promising supplementary cementitious material (SCM) for sustainable construction due to its high silica content and potential to reduce the environmental impact of concrete. However, the evolution of RHA research and its transition toward advanced, data-driven material systems remain insufficiently synthesised. This study presents an integrated bibliometric analysis (BA) and systematic literature review (SLR) in which Scopus-indexed publications from 2007 to 2021 establish the historical evolution and structural dynamics of the field, while studies published between 2022 and 2026 are systematically reviewed to capture emerging developments and ensure contemporary relevance. The bibliometric analysis reveals a steady increase in research activity and identifies a shift from experimental material optimisation toward sustainability and computational modelling. When interpreted alongside the systematic review findings, this trend reflects a structured Past–Present–Future evolution of RHA research, from feasibility studies to microstructural optimisation and, more recently, to predictive and data-driven material design. The systematic review confirms that optimally processed RHA, typically at 10–30% cement replacement, enhances compressive strength, durability, and resistance to aggressive environments through improved pozzolanic reactivity and microstructural densification. Recent studies (2022–2026) further demonstrate the integration of machine learning, life-cycle assessment, and digital modelling approaches for performance prediction, mix optimisation, and sustainability evaluation. By linking bibliometric trends with scientific insights, this study identifies key research gaps, including the lack of standardisation in RHA production, limited large-scale validation, and weak integration of experimental and computational approaches, and proposes an integrated five-tier framework, moving from material standardisation through performance validation and computational intelligence to sustainability integration and industrial-policy adoption, to guide future research and implementation. The findings highlight the transition of RHA from a conventional SCM to a component of intelligent, sustainable, and circular construction systems, providing a foundation for future research and industrial application. Full article

Accurately identifying carbon reduction drivers based on regional variability is important for balancing different carbon reduction targets and advancing sustainable development. This paper first defines and quantifies carbon emission reduction capacity. It then combines cluster analysis and spatial modeling to analyze the drivers of carbon emission reduction capacity at different administrative levels. The results show that the mean values of carbon emission reduction capacity for the different plates, in descending order, are Plate II > Plate I > Plate III > Plate IV. The internal spatial relationships within the plates are relatively weak, while the synergies and spillover effects between the plates are more significant. Moreover, economic development has the largest positive impact on carbon emission reduction capacity in Shandong Province. Industrial structure has the largest effect on the carbon emission reduction capacities of Plates I, II, and III, with positive effects in Plates I and III but a negative effect in Plate II, while population size has the largest negative effect on the carbon emission reduction capacity of Plate IV. These findings could provide theoretical references and practical support for governments to formulate regionally differentiated carbon emission reduction policies and promote coordinated carbon emission reduction and high-quality regional development. Full article

Indigenous Knowledge (IK) is the traditional wisdom used to manage and sustain ecosystem services (ES). This review paper presents the integration of ES and IK for sustainable natural resource management and policy in Ethiopia, suggesting that despite increased research in recent years, there is a lack of uptake at the policy and program implementation levels. A total of 75 studies published between 2015 and 2025 were systematically reviewed, covering an 11-year sequential scope following PRISMA 2020 guidelines and including articles from the Web of Science, Scopus, Google Scholar, African Journal Online and Indigenous Knowledge Documentation Centre (IKDC) databases. The findings show that provisioning services dominate the literature (67.4%), followed by regulating (18.3%), cultural (9.2%), and supporting services (5.1%). IK documented across 22 ethnic groups demonstrated important contributions to biodiversity conservation, sustainable agriculture, forest management, and water resource management. However, only 26.8% of the reviewed studies successfully integrated IK into ES frameworks. Policy content analysis tool (PCAT) of 23 national documents showed weak institutional support for IK integration, with an average integration score of only 5.8 out of 20. Major barriers include limited policy implementation, institutional fragmentation, and negative perceptions toward IK. Successful integration cases were strongly associated with community ownership, participatory monitoring, legal recognition, and long-term funding support. This review is important because it systematically shows that IK delivers confirmed environmental and livelihood benefits over this 11-year time frame. It highlights the urgent need for stronger policy frameworks, inclusive governance, and recognition of IK to improve ecosystem conservation and sustainable resource management in Ethiopia. Full article

An Environmental Impact Assessment (EIA) is a legal obligation in Bangladesh for projects with substantial environmental and socio-economic impacts. Over time, Bangladesh has established sound policies, rules, and a growing workforce to support the EIA process. However, two key issues persist: the effectiveness of EIA reports and weak implementation of Environmental Management Plans (EMPs). In practice, implementing agencies often prioritize physical progress over environmental safeguards, treating the EIA as merely a clearance formality for Planning Commission approval. Regulatory bodies, such as the Department of Environment and the Planning Commission, frequently neglect the substantive review of EIA reports, focusing on checklist requirements rather than rigorous environmental scrutiny. This procedural mindset undermines the role of EIA as a strategic planning and decision-making tool. This study examines each step of the EIA process, from report preparation to EMP implementation, highlighting gaps that require sustainable improvements. A mixed-method approach was employed to evaluate the quality of the EIA process, with particular attention to its methodological rigor, accuracy of impact assessment, challenges in public participation, and the effectiveness of the proposed EMPs and their implementation. The recommendations presented in this study aim to enhance the efficiency of the EIA process and promote its application in similar contexts across developing countries. Full article

Sustainable hydrogen policy and national strategy documents are rich in qualitative information whose systematic evaluation still relies largely on subjective SWOT frameworks. This study proposes a reproducible hybrid methodology that couples expert-supervised Natural Language Processing (NLP) with a stochastic techno-economic model of the Levelized Cost of Hydrogen (LCOH) to convert policy discourse into quantitative, evidence-based recommendations. TF-IDF vectorization, K-Means clustering, Shannon entropy and Correspondence Analysis (CA) are applied to a manually annotated corpus of 107 sentences drawn from Türkiye’s national hydrogen strategy documents (Cohen’s κ = 0.81, substantial agreement). CA positions Regulation/Legislation and Financing near the Weakness quadrant, Renewable Resource Potential in the Strength quadrant, and Export/Demand Risk near Opportunity—revealing structural bottlenecks that challenge the sustainable energy transition. These qualitative findings are subjected to a quantitative consistency check via a Monte Carlo simulation (N = 10,000 iterations) propagating joint uncertainty in CAPEX, electricity price, electrolyzer efficiency, annual operating hours, discount rate and plant lifetime. The deterministic 2025 LCOH baseline of 4.89 €/kg H₂ carries a P10–P90 interval of [3.95; 5.92] €/kg. Global Sobol sensitivity analysis identifies electricity price as the dominant driver (S₁ ≈ 0.52), suggesting that financing is discursively surfaced by the textual layer. Under business-as-usual technological learning, the probability of reaching a globally competitive LCOH (≤2 €/kg H₂) by 2050 is only 17.8%; a stylized proactive policy intervention (carbon pricing + subsidies) raises this probability to 78.4%. The framework is adaptable to other countries and languages (though the current implementation is Turkish-specific), providing a scalable, open methodology for evidence-based sustainable clean energy planning. Full article

This study provides a stakeholder-based assessment of the drivers, barriers, and strategic priorities shaping energy efficiency (EE) adoption across Egypt’s private sector, focusing on the industry, buildings, and transport sectors. Drawing on 17 semi-structured interviews with stakeholders from government, industry, finance, academia, and development organizations, the study identifies the main factors influencing EE implementation. The findings show that sustainability objectives, particularly carbon reduction commitments and compliance with environmental regulations, alongside donor-funded grants and green finance instruments, are the primary drivers of EE uptake. However, progress remains constrained by institutional and financial barriers, including weak enforcement mechanisms, fragmented governance, limited policy coordination, high upfront costs, restricted access to finance, inflexible banking conditions, and the absence of a domestic EE finance market. Technical and awareness-related challenges further hinder implementation. While gender-related barriers were generally perceived as limited, the analysis revealed underlying disparities in women’s leadership and decision-making roles. Financial barriers represented the largest share across all sectors, while institutional barriers ranked second. The absence of enforcement mechanisms was the most significant individual constraint, cited by 13 out of 17 respondents, followed by limited access to finance (10 out of 17) and high upfront costs (9 out of 17). The study highlights the need for stronger regulatory frameworks, clearer institutional mandates, accessible financing mechanisms, and the integration of gender perspectives to accelerate EE adoption and support Egypt’s sustainable energy transition. Full article