Search Results (290)

In agriculture, the use of fructans has gained relevance due to their ability to improve plant immunity and resistance to pathogens. However, many studies use high-purity fructans, which makes their application more expensive. In this work, the efficacy of two agave fructans, one food grade from Agave tequilana Weber var. Azul (FT) and the other obtained by semi-craft extraction from A. cupreata (FC) were evaluated in comparison with reagent-grade inulin from dahlia tubers. The effectiveness of their defense response against Phytophthora capsici infection in tomato (Solanum lycopersicum L.) was analyzed by evaluating defense mechanisms, including lignin deposition, hydrogen peroxide (H₂O₂) accumulation, and β-1,3-glucanase and peroxidase activity. The results indicated that foliar application of both fructans showed protection against infection, reducing disease incidence and severity. FT fructans at lower concentration (0.5 g/L) showed the highest protection, followed by FC, while dahlia inulin showed lower effectiveness. An early and progressive accumulation of H₂O₂ was observed in fructan-treated plants, in contrast to the late increase in untreated infected plants. Also, peroxidase activity was higher in the fructan treatments, suggesting a more efficient defense response. Although lignin deposition was not directly correlated with protection against P. capsici, fructans showed potential as resistance inducers. Given their low cost, easy extraction, and zero environmental impact, agave fructans represent a viable alternative for crop protection in sustainable agricultural systems. This study opens the door to their validation in the field and their application in other economically important crops, contributing to biological control strategies with less dependence on agrochemicals. Full article

The development of the Great Wall National Cultural Park has unleashed the potential for integrating cultural and tourism development along the Great Wall. However, ICH along the Great Wall, a key part of its cultural identity, suffers from low recognition and a mismatch between protection and development efforts. This study analyzes provincial-level and above ICH along Hebei’s Great Wall using geospatial tools and the Geographical Detector model to explore distribution patterns and influencing factors, while Geographically Weighted Regression is utilized to reveal spatial heterogeneity. It tests two hypotheses: (H1) ICH shows a clustered pattern; (H2) economic factors have a greater impact than cultural and natural factors. Key findings show: (1) ICH distribution is numerically balanced north–south but spatially uneven, with dense clusters in the south and scattered patterns in the north. (2) ICH and crafts cluster significantly, while dramatic balladry spreads evenly, and other categories are random. (3) Average annual temperature and precipitation have the greatest impact on ICH distribution, with the factors ranked as: natural > cultural > economic. Multidimensional interactions show significant enhancement effects. (4) Influencing factors vary spatially. Population density, transport, temperature, and traditional villages are positively related to ICH. Elevation, precipitation, tourism, and cultural institutions show mixed effects across regions. These insights support targeted ICH conservation and sustainable development in the Great Wall cultural corridor. Full article

This study presents a breakthrough in sustainable injection molding by uniquely combining a backpropagation neural network (BPNN) with particle swarm optimization (PSO) to overcome traditional optimization challenges. The BPNN’s exceptional ability to learn complex nonlinear relationships between six key process parameters (including melt temperature and holding pressure) and product quality is amplified by PSO’s intelligent search capability, which efficiently navigates the high-dimensional parameter space. Together, this hybrid approach achieves what neither method could accomplish alone: the BPNN accurately models the intricate process-quality relationships, while PSO rapidly converges on optimal parameter sets that simultaneously meet strict quality targets (66–70 g weight, 3–5 mm thickness) and minimize energy consumption. The significance of this integration is demonstrated through three key outcomes: First, the BPNN-PSO combination reduced optimization time by 40% compared to traditional trial-and-error methods. Second, it achieved remarkable prediction accuracy (RMSE 0.8229 for thickness, 1.5123 for weight) that surpassed standalone BPNN implementations. Third, the method’s efficiency enabled SMEs to achieve CAE-level precision without expensive software, reducing setup costs by approximately 25%. Experimental validation confirmed that the optimized parameters decreased energy use by 28% and material waste by 35% while consistently producing parts within specifications. This research provides manufacturers with a practical, scalable solution that transforms injection molding from an experience-dependent craft to a data-driven science. The BPNN-PSO framework not only delivers superior technical results but does so in a way that is accessible to resource-constrained manufacturers, marking a significant step toward sustainable, intelligent production systems. For SMEs, this framework offers a practical pathway to achieve both economic and environmental sustainability, reducing reliance on resource-intensive CAE tools while cutting production costs by an estimated 22% through waste and energy savings. The study provides a replicable blueprint for implementing data-driven sustainability in injection molding operations without compromising product quality or operational efficiency. Full article

Demand for mental health support has exerted unprecedented pressure on statutory services. Innovative solutions such as Green or Nature-Based Social Prescribing (NBSP) programmes may help address unmet need, improve access to personalised treatment, and support the sustainable delivery of primary services within a prevention model of population health. We piloted an innovative health economics-informed Social Return on Investment (SROI) analysis and forecast of a ‘Making Well’ therapeutic craft and horticulture programme for mental health between October 2021 and March 2022. Quantitative and qualitative outcome data were collected from participants with mild-to-moderate mental health conditions at baseline and nine-weeks follow-up using a range of validated measures, including the Short Warwick–Edinburgh Mental Well-being Scale, ICEpop CAPability measure for Adults (ICECAP-A), General Self-Efficacy Scale (GSES), and a bespoke Client Service Receipt Inventory (CSRI). The acceptability and feasibility of these measures were explored. Results indicate that the Making Well programme generated well-being-related social value in the range of British Pound Sterling (GBP) GBP 3.30 to GBP 4.70 for every GBP 1 invested. Our initial pilot forecast suggests that the programme has the potential to generate GBP 5.40 to GBP 7.70 for every GBP 1 invested as the programme is developed and delivered over a 12-month period. Despite the small sample size and lack of a control group, our results contribute to the evidence-base for the effectiveness and social return on investment of NBSP as a therapeutic intervention for improving health and well-being and provides an example of the use of health economic well-being outcome measures such as ICECAP-A and CSRIs in social value analysis. Combining SROI evaluation and forecast methodologies with validated quantitative outcome measures used in the field of health economics can provide valuable social cost–benefit evidence to decision-makers. Full article

The relationship between ecosystem services (ESs) and human well-being (HWB) is a central issue of sustainable development. However, current research often relies on qualitative frameworks or indicator-based assessments, limiting a comprehensive understanding of the relationship between natural environment and human acquisition, which still needs to be strengthened. As an element transferred in the natural–society coupling system, carbon can assist in characterizing the dynamic interactions within coupled human–natural systems. Carbon, as a fundamental element transferred across ecological and social spheres, offers a powerful lens to characterize these linkages. This study develops and applies a novel analytical framework that integrates carbon flow as a unifying metric to quantitatively assess the spatiotemporal dynamics of the land use and land cover change (LUCC)–ESs–HWB nexus in Guizhou Province, China, from 2000 to 2020. The results show that: (1) Ecosystem services in Guizhou showed distinct trends from 2000 to 2020: supporting and regulating services declined and then recovered, and provisioning services steadily increased, while cultural services remained stable but varied across cities. (2) Human well-being generally improved over time, with health remaining stable and the HSI rising across most cities, although security levels fluctuated and remained low in some areas. (3) The contribution of ecosystem services to human well-being peaked in 2010–2015, followed by declines in central and northern regions, while southern and western areas maintained or improved their levels. (4) Supporting and regulating services were positively correlated with HWB security, while cultural services showed mixed effects, with strong synergies between culture and health in cities like Liupanshui and Qiandongnan. Overall, this study quantified the coupled dynamics between ecosystem services and human well-being through a carbon flow framework, which not only offers a unified metric for cross-dimensional analysis but also reduces subjective bias in evaluation. This integrated approach provides critical insights for crafting spatially explicit land management policies in Guizhou and offers a replicable methodology for exploring sustainable development pathways in other ecologically fragile karst regions worldwide. Compared with conventional ecosystem service frameworks, the carbon flow approach provides a process-based, dynamic mediator that quantifies biogeochemical linkages in LUCC–ESs–HWB systems, which is particularly important in fragile karst regions. However, we acknowledge that further empirical comparison with traditional ESs metrics could strengthen the framework’s generalizability. Full article

With over 180 million tons produced annually and a global market exceeding 500 billion dollars, beer is one of the most widely consumed beverages in the world, thanks to its broad variety of styles, traditions, ingredients, and brewing techniques. However, behind this widespread popularity lies a potentially impactful production chain, whose environmental impacts remain underexplored, particularly within the craft segment. This research evaluates the sustainability of a hemp-based craft beer produced in the Lazio region (Italy) using an integrated approach that combines life cycle assessment with environmental impact monetization. The results indicate that the main impacts in beer production are related to global warming potential (0.916 kg CO₂ eq/L), terrestrial ecotoxicity (0.404 kg 1.4-DCB eq/L), land use (0.841 m²a crop eq/L), and fossil resource scarcity (0.211 kg oil eq/L), primarily due to malt production and hop transportation. Packaging analysis revealed that including environmental costs, aluminum cans may add an additional environmental cost of €0.80–1.60 per unit, while glass bottles, despite their weight, incur a lower additional cost. For a beer priced at €3.50, this would translate to a real cost of €4.30–5.10, reflecting a 22–45% increase. Improving sustainability in the brewing sector requires strategic actions, such as careful supplier selection and appropriate packaging choices. Overall, sustainability in brewing emerges as a balance between production needs, distribution impacts, and systemic decisions. Full article

Mining activities in Pakistan’s mineral-rich provinces threaten freshwater security through groundwater depletion, contamination, and flood-induced pollution. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework integrating governance, social, environmental, and technical (GSET) dimensions to holistically assess mining-induced water hazards across Balochistan, Khyber Pakhtunkhwa, and Punjab. Using GIS-based spatial risk mapping with multi-layer hydrological modeling, we combine computational analysis and participatory validation to identify vulnerability hotspots and prioritize high-risk mines. Community workshops involving women water collectors, indigenous leaders, and local experts enhanced map accuracy by translating indigenous knowledge into spatially referenced mitigation plans and integrating gender-sensitive metrics to address gendered water access disparities. Key findings reveal severe groundwater depletion, acid mine drainage, and gendered burdens near Saindak and Cherat mines. Multi-sectoral engagements secured corporate commitments for water stewardship and policy advances in inclusive governance. The framework employs four priority-ranked risk categories (Governance-Economic 15%, Social-Community 30%, Environmental 40%, Technical-Geological 15%) derived via local stakeholder collaboration, enabling context-specific interventions. Despite data limitations, the GIS-driven methodology provides a scalable model for regions facing socio-environmental vulnerabilities. The results demonstrate how community participation directly shaped village-level water management alongside GSET analysis to craft equitable risk reduction strategies. Spatially explicit risk maps guided infrastructure upgrades and zoning regulations, advancing SDG 6 and 13 progress in Pakistan. This work underscores the value of inclusive, weighted frameworks for sustainable mining–water nexus management in Pakistan and analogous contexts. Full article

This study explores the marketing potential of artisanal agri-food products in Ukraine by examining their structural, regional, and consumer dimensions. Amid growing interest in sustainable and locally rooted food systems, the research addresses how artisanal production can evolve from informal crafts to market-recognized value. This study is based on an analysis of official statistical data and an analysis of registered artisanal food producers in specific areas in Ukraine. It emphasizes the role of household-based agriculture in securing raw materials, the impact of cultural–tourism infrastructure on product visibility, and the benefits of self-sufficiency in raw material sourcing for product differentiation. The findings reveal that regions with stronger household production and cultural engagement demonstrate higher activity in the artisanal food sector. This study concludes that artisanal food production offers a viable pathway for regional development, rural resilience, and the strengthening of local food identity. Full article

This study investigated the key determinants of entrepreneurship in Ambato, Ecuador, through the application of predictive statistical models. The primary objective was to identify critical variables that influence the success and sustainability of entrepreneurial ventures in the region. A quantitative research design was employed, utilizing multivariate statistical techniques, including decision trees, random forest, and Principal Component Analysis (PCA). Data were collected through structured surveys administered to local entrepreneurs, addressing variables including demographics, education, initial investment, and business operations. The analysis revealed that factors such as geographic location, the entrepreneur’s educational attainment, business tenure, and operational characteristics have a significant influence on entrepreneurial viability. On the basis of these findings, the study proposes a predictive model to assist both policymakers and entrepreneurs in evaluating and enhancing business development strategies. The insights gained offer practical implications: entrepreneurs can refine their strategies for greater effectiveness, while local authorities can craft supportive policies, such as training programs and improved access to financing. The study highlights the importance of entrepreneurship education and targeted support for underdeveloped areas, thereby contributing to broader economic inclusion and enhanced employment opportunities in the region. Full article

This article examines the impact of a new technical assistance (TA) and recognition program (BetterBev) on Massachusetts craft breweries’ adoption of pollution prevention/sustainability practices. The authors explore the following questions: How do technical assistance and recognition address the key barriers and promote P2/sustainability adoption? What are the outcomes and impacts of the implemented P2 practices? What specific P2/sustainability practices are most likely and least likely to be adopted by craft breweries receiving TA, and why? This study is based on 29 craft breweries in Massachusetts, U.S. Data was collected between November 2022 and March 2025 and included site visits; interviews with owners, founders, and head brewers; online research; and assessments of eight impact categories. This study found that providing TA was highly effective in encouraging participants to adopt new P2/sustainability practices (the 29 participants adopted 60 new P2/sustainability practices over two years). The TA helped overcome the main sustainability barriers for craft breweries—the lack of resources, time, and knowledge about available opportunities. MA breweries adopted most of their P2 practices in energy and CO₂ reduction, and the least in water and wastewater reduction. This study confirmed the importance of environmental information as a powerful driver for adopting P2/sustainability actions. Future initiatives should consider a train-the-trainer approach for scaling up P2/sustainability practices, where early adopters share their knowledge and experience with peers. Full article

The widespread deployment of service robots in industries such as hospitality has significantly transformed service delivery, influencing not only customers but also employees. This study examines the multi-dimensional impact of service robots on hotel employees, focusing on their attitudes, emotional responses, and willingness to collaborate, as shaped by perceived benefits (service reliability, process efficiency, and job crafting) and risks (inefficiency, insufficient intelligence, and privacy concerns). Data were collected from 471 hotel employees in South Korea with experience working alongside service robots, and Hayes’ Process Macro Model 4 was employed for hypothesis testing. The findings reveal that perceived benefits positively influence employees’ attitudes, emotions, and willingness to collaborate, while perceived risks exert a negative impact. Furthermore, attitudes and emotional responses mediate these relationships. These findings provide theoretical and practical insights for managers, policymakers, and service robot manufacturers to address employee concerns, improve human–robot collaboration, and promote sustainable technological integration within the service industry. Full article

The sustainable preservation of archeological heritage located in rural and coastal regions requires more than technical interventions; it necessitates the awareness and active participation of local communities. However, community involvement in heritage management in such areas remains limited. This study aims to analyze the levels of cultural heritage awareness, conservation tendencies, and tourism-related expectations among local residents and visitors in the Magarsus Archeological Area, located in the Karataş district on the eastern Mediterranean coast of Turkey. The study was conducted in three phases: a literature review, field observations, and a structured survey conducted between June and August 2022 with 510 participants (280 local residents and 230 domestic visitors from surrounding provinces). The data were analyzed using SPSS 25.0 through descriptive statistical methods, complemented by cross-tabulation and chi-square analysis to identify patterns across demographic variables. The survey results not only reflect general perceptions about heritage and tourism but also offer critical insights into how the rural and coastal character of the site shapes conservation attitudes and tourism behavior. The findings reveal nuanced perceptions, including strong symbolic appreciation for heritage and general openness to tourism, alongside concerns about cultural and environmental risks. While the local community prioritizes the potential for economic benefit, many participants also emphasized the importance of safeguarding local traditions, crafts, and culinary heritage. Nevertheless, concerns were expressed regarding the risks posed by uncontrolled tourism, including environmental degradation, erosion of cultural identity, and the commodification of heritage values. Based on these insights, the study introduces a governance approach built upon three interlinked pillars: community-based participation, environmental sustainability, and tourism practices aligned with cultural values. The proposed approach aims to support the inclusive and sustainable management of Magarsus and other rural and coastal archeological landscapes with similar characteristics. Full article

Because of the continuous interest in ferrocene chemistry, there is a sustained demand for various ferrocenic building blocks, especially small molecules with useful chemical functional groups, sometimes containing multiple groups. Our interest in ferrocene ketoesters (ω-ferrocenyl-ω-ketoesters) was motivated by the synthesis of esters and subsequently alcohols of ferrociphenols. However, from a bibliographic survey, only one publication dated from 1964 reports the two-step synthesis (six-step synthesis from ferrocene) of methyl 2-ferrocenyl-2-oxoacetate, the simplest member of this family of compounds, with no further developments since. We hypothesized that a simpler method might exist, such as the Friedel–Crafts method. By focusing on our experiments to use aluminum trichloride as the catalyst, we managed to achieve the synthesis of FcCOCOOMe in a single step, albeit with a very low yield, regardless of reaction time, temperature, amount of aluminum chloride and reagents concentration. Nevertheless, considering the time saved, simplicity, and the use of less hazardous and less expensive reagents, this method offers certain advantages for synthesizing this building block. Full article

This study presents a novel approach for the detection and severity assessment of pest-induced damage in maize plants, focusing on the Zyginidia pullula pest. A newly developed dataset is utilized, where maize plant images are initially classified into two primary categories: healthy and infected. Subsequently, infected samples are categorized into three distinct severity levels: low, medium, and high. Both traditional and deep learning-based feature extraction techniques are employed to achieve this. Specifically, hand-crafted feature extraction methods, including Gabor filters, Gray Level Co-occurrence Matrix, and Hue-Saturation-Value color space, are combined with CNN-based models such as ResNet-50, DenseNet-201, and EfficientNet-B2. The maize images undergo preprocessing and segmentation using Contrast Limited Adaptive Histogram Equalization and U2Net, respectively. Extracted features are then fused and subjected to Principal Component Analysis for dimensionality reduction. The classification task is performed using Support Vector Machines, Random Forest, and Artificial Neural Networks, ensuring robust and accurate detection. The experimental results demonstrate that the proposed hybrid approach outperforms individual feature extraction methods, achieving a classification accuracy of up to 92.55%. Furthermore, integrating multiple feature representations significantly enhances the model’s ability to differentiate between varying levels of pest damage. Unlike previous studies that primarily focus on plant disease detection, this research uniquely addresses the quantification of pest-induced damage, offering a valuable tool for precision agriculture. The findings of this study contribute to the development of automated, scalable, and efficient pest monitoring systems, which are crucial for minimizing yield losses and improving agricultural sustainability. Full article

The brewing sector is under increasing pressure to implement sustainable practices, particularly by integrating agro-industrial waste into its value chains. This study explores the potential of mango (Mangifera indica L.) residues as functional and sustainable ingredients within Brazil’s craft beer industry. A qualitative and exploratory methodology was employed, based on a literature review and political, economic, social, and technological (PEST) and strengths, weaknesses, opportunities, and threats (SWOT) analyses, to assess both the external and internal factors influencing the reuse of mango waste. The results highlight the environmental advantages and opportunities for value creation, especially in alignment with circular economy principles. Moreover, growing consumer interest in innovative and sustainable products presents an opportunity for market differentiation. Nonetheless, barriers such as limited infrastructure, cost-related challenges, regulatory constraints, and logistical limitations remain. By bridging sustainability, innovation, and waste minimization, this research offers strategic insights for stakeholders aiming to develop more resilient and responsible production chains. The valorization of mango waste contributes meaningfully to the Sustainable Development Goals—particularly SDGs 8, 9, and 12. Full article