Search Results (24,411)

Essential oils (EOs) are volatile, strongly aromatic bioactive substances extracted from plants, primarily composed of terpenes, terpenoids, phenylpropanoids, and other oxygenated compounds. Owing to their unique chemical structures, EOs exhibit a wide range of biological activities, including antimicrobial, anti-inflammatory, antioxidant, anticancer, neuroprotective, bone-protective, wound-healing, and gut microbiota-modulating effects, highlighting their potential therapeutic value. However, the composition and bioactivity of EOs are influenced by multiple factors and often compromised by improper storage conditions such as temperature and light exposure, leading to the gradual loss of their functional properties. To overcome these limitations, encapsulation technologies have been employed to enhance EO stability, enable sustained and targeted release, and preserve or even improve their bioactive functions. This review summarizes the major constituents of EOs, their physiological activities, therapeutic value, and mechanisms of action. It also discusses their limitations and suitable encapsulation technologies, materials, and carrier systems for stabilization and delivery. Full article

Reflection on sustainable economic models, such as the civil economy, has led to the development of alternative food supply chains grounded in ethical values and practices. From this perspective, the Food Village model was proposed to meet stakeholders’ needs, overcome the limitations of Alternative Food Networks, and scale up. In this study, a Discrete Choice Experiment on hypothetical Food Village participation scenarios was combined with the Portrait Values Questionnaire to analyse preferences for the model’s attributes in relation to personal values. The results indicate that consumers appreciate the ethical and territorial characteristics of Food Village, such as local and organic products and cooperative governance, as long as convenience is guaranteed (product variety, flexible hours). Furthermore, they prefer moderate forms of participation, while excessively burdensome involvement reduces their willingness to participate. Individual values influence preferences: values of “self-transcendence” and conservation are associated with greater willingness, while those of “self-affirmation” correlate with lower adherence to Food Village. This evidence suggests implications for policy and scalability: initiatives like Food Village, if supported by public incentives and flexible participatory schemes, can contribute to more sustainable food systems at scale. Full article

Springs fed by carbonate-fractured/karst aquifers support spring-dependent ecosystems and provide drinking water in the Italian Apennines, where complex hydro-meteorological environments are increasingly affected by prolonged droughts. The aim of this study was to investigate the hydrogeological behavior of two springs (Alzabove and Lupa) on the mountain ridge of Central Italy, using monthly reanalysis datasets to support sustainable water management. The Master Recession Curves based on the 1998–2023 recession periods highlighted a slightly higher average recession coefficient for Lupa (α = −0.0053 days⁻¹) than for Alzabove (α = −0.0020 days⁻¹). The hydrogeological settings of the Lupa recharge area led to a less resilient response to prolonged, extreme droughts as detected via the Standardized Precipitation-Evapotranspiration Index (SPEI) computed at different time scales using ERA-5 Land datasets. The SPEI computed at a 6-month scale (SPEI₆) showed the best correlation with monthly spring discharge, with a 1-month delay time. A parsimonious linear regression model was built using the antecedent monthly spring discharge values and SPEI₆ as independent variables. The best modeling performance was achieved for the Alzabove spring, with some overestimation of spring discharge during extremely dry conditions (e.g., 2002–2003 and 2012), especially for the Lupa spring. The findings are encouraging as they reflect the use of a simple tool developed to support decisions on the sustainable management of springs in mountain environments, although issues related to evapotranspiration underestimation during extreme droughts remain. Full article

Polyethylene is the most used plastic in the world, and over 90% of this plastic is ultimately disposed of in landfills or released into the environment, leading to severe ecological implications. In this research, the technoeconomic feasibility of upcycling low-density polyethylene (LDPE) to produce ethylene is studied. The catalytic conversion of LDPE to ethylene is considered in microwave heating mode and Joule heating mode. Experimental data is obtained under conditions where most of the upcycled products are in the gas phase. A flowsheet is developed that produces industrial quantities of ethylene for both heating modes. A technoeconomic analysis and a life cycle analysis are conducted and compared with the traditional ethane cracking process for producing ethylene. Simulation results indicate that the upcycling system exhibits a lower capital expenditure and a comparable operating expenditure relative to conventional ethane steam cracking while generating additional valuable co-products, such as propylene and aromatic hydrocarbons, leading to a higher net present value potential. Sensitivity analyses reveal that the electricity price has the most significant impact on both the net present value and levelized cost of production, followed by the low-density polyethylene feedstock cost. Life-cycle assessment reveals a substantial reduction in greenhouse-gas emissions in the upcycled process compared to the fossil-based ethane steam-cracking route, primarily due to the use of renewable electricity, the lower reaction temperature that reduces utility demand, and the use of plastic waste as the feedstock. Overall, the proposed process demonstrates strong potential for the sustainable production of ethylene from waste LDPE. Full article

Universities must prepare future professionals with critical thinking skills to effectively address complex social and environmental challenges. In engineering degrees, while technical competences are strongly developed, the acquisition of ethical and social skills remains challenging within the framework of traditional subjects. This paper explores how the integration of the Sustainable Development Goals (SDGs), following a competence-based educational model, can contribute to the development of ethical, social, and sustainability-related competences in an engineering degree. A set of activities, exercises, and tasks grounded in real professional contexts was designed to encourage students to explore sustainable solutions to social and environmental problems, supported by experiential learning and visible thinking routines. These activities were coherently aligned through interdisciplinary coordination among professors teaching in the degree. The results indicate that the proposed approach was positively received by both professors and students, who valued its contribution to personal and professional development. Students demonstrated enhanced critical thinking and greater awareness of the social and environmental implications of engineering decisions. This work aims to support and inspire educators seeking to integrate SDGs into their teaching by offering a feasible, transferable, and easy-to-implement framework for embedding ethical, social and sustainability-related competences in engineering teaching. Full article

With the increasing prominence of sustainable consumption and the rising influence of Generation Z in the fashion market, secondhand fashion e-commerce platforms have become essential carriers of green fashion. Although AI-assisted recommendation mechanisms are widely embedded in these platforms, their psychological and behavioral effects on users’ continuous use and social engagement remain insufficiently examined. To address this gap, this study incorporates the Stimulus–Organism–Response (SOR) framework to investigate the psychological reaction pathways and behavioral intentions of Generation Z users within Human-AI Collaboration-enabled green e-commerce environments. Three AI-driven service stimuli—Human-AI Collaborative Recommendation Perception, AI Interaction Transparency, and Perceived Personalization—were conceptualized as stimulus variables; Psychological Immersion, Emotional Triggering, Cognitive Engagement, and Platform Trust were modeled as organism variables; and Continuous Use Intention and Social Sharing Intention served as behavioral response variables. Based on 498 valid samples analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results demonstrate strong empirical support for all proposed hypotheses. Specifically, AI-driven stimuli significantly and positively influence psychological responses, which subsequently strengthen users’ continuous usage and social sharing intentions. This research provides theoretical insights for developing Human-AI Collaboration-enabled service systems that balance efficiency and emotional resonance on green e-commerce platforms, and offers practical implications for promoting sustainable fashion values among younger consumers. Full article

With growing community awareness of greenhouse gas emissions and their environmental consequences, distributed rooftop photovoltaic (PV) systems have emerged as a sustainable energy alternative in residential settings. However, the high penetration of these systems without effective operational strategies poses significant challenges for local distribution grids. Specifically, the estimation of surplus energy production from these systems, closely linked to complex outdoor weather conditions and seasonal fluctuations, often lacks an accurate forecasting approach to effectively capture the temporal dynamics of system output during peak periods. In response, this study proposes a recurrent neural network (RNN)- based forecasting framework to predict rooftop PV surplus in the context of micro-residential communities over time horizons not exceeding 48 h. The framework includes standard RNN, long short-term memory (LSTM), bidirectional LSTM (BiLSTM), and gated recurrent unit (GRU) networks. In this context, the study employed estimated surplus energy datasets from six single-family detached houses, along with weather-related variables and seasonal patterns, to evaluate the framework’s effectiveness. Results demonstrated the significant effectiveness of all framework models in forecasting surplus energy across seasonal scenarios, with low MAPE values of up to 3.02% and 3.59% over 24-h and 48-h horizons, respectively. Simultaneously, BiLSTM models consistently demonstrated a higher capacity to capture surplus energy fluctuations during peak periods than their counterparts. Overall, the developed data-driven framework demonstrates potential to enable short-term smart energy scheduling in micro-residential communities, supporting electric vehicle charging from single-family detached houses through efficient rooftop PV systems. It also provides decision-making insights for evaluating renewable energy contributions in the residential sector. Full article

Fuel moisture content (FMC) estimation is essential for wildfire danger assessment and fire behavior modeling. This study quantifies the value of integrating satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP and the Advanced Baseline Imager (ABI) aboard GOES-16 with High-Resolution Rapid Refresh (HRRR) numerical weather prediction data for hourly 10 h dead FMC estimation across the continental United States. We leverage the complementary characteristics of each system: VIIRS provides enhanced spatial resolution (375–750 m), while ABI contributes high temporal frequency observations (hourly). Using XGBoost machine learning models trained on 2020–2021 data, we systematically evaluate performance improvements stemming from incorporating satellite retrievals individually and in combination with HRRR meteorological variables through eight experimental configurations. Results demonstrate that while both satellite systems individually enhance prediction accuracy beyond HRRR-only models, their combination provides substantially greater improvements: 27% RMSE and MAE reduction and 46.7% increase in explained variance (R${}^2$) relative to HRRR baseline performance. Comprehensive seasonal analysis reveals consistent satellite data contributions across all seasons, with stable median performance throughout the year. Diurnal analysis across the complete 24 h cycle shows sustained improvements during all hours, not only during satellite overpass times, indicating effective integration of temporal information. Spatial analysis reveals improvements in western fire-prone regions where afternoon overpass timing aligns with peak fire danger conditions. Feature importance analysis using multiple explainable AI methods demonstrates that HRRR meteorological variables provide the fundamental physical framework for prediction, while satellite observations contribute fine-scale refinements that improve moisture estimates. The VIIRS lag-hour predictor successfully maintains observational value up to 72 h after acquisition, enabling flexible operational implementation. This research demonstrates the first systematic comparison of VIIRS versus ABI contributions to dead FMC estimation and establishes a framework for hourly, satellite-enhanced FMC products that support more accurate fire danger assessment and enhanced situational awareness for wildfire management operations. Full article

In recent years, the application of augmented reality digital technology in brands has transformed the way consumers interact with brands. This study focuses on the impact of augmented reality (AR) technology on consumption behavior and brand communication related to intangible cultural heritage products, integrating the TAM and UTAUT2 theories to construct a research model. This study employed a time–location sampling method, utilizing SPSS and AMOS software for data analysis based on valid questionnaires completed by 305 AR-experiencing consumers in Changsha City, Hunan Province. Results indicate that the presence and novelty of AR technology significantly and positively influence consumers’ attitudes toward using AR technology, which in turn affects their purchase intent, social media sharing behavior, and brand attitudes. The study confirms that emotional factors and consumer perceptions play a guiding and decisive role in the new consumption reality enabled by AR technology. These research findings have practical significance and value for ICH brand building and AR marketing, demonstrating that AR is an effective means to enhance the visibility and influence of the ICH brand. They inject new vitality into promoting more sustainable ICH protection and popularization, as well as the development of the digital creative industry. Full article

Safflower (Carthamus tinctorius L.) is increasingly attracting the attention of Mediterranean farmers due to its broad environmental adaptability and low input requirements. Although still relatively underexplored, this species holds remarkable potential as a source of natural dyes and bioactive phytochemicals with recognized health-promoting and phytotherapeutic properties. In this study, the effects of genotype and sowing time on safflower’s productive and qualitative traits were investigated by testing six genotypes and two sowing times (autumn and spring) in an open-field trial conducted in central Tuscany. The Pieve genotype achieved the highest floret dry yield per head, number of heads per plant, and total floret yield per plant, whereas the Montola 2000 genotype was distinguished by its elevated polyphenol concentration and pronounced antioxidant activity. Autumn sowing resulted in higher yields of bioactive pigments, including carthamin and yellow quinochalcones, alongside greater total phenolic content and antioxidant capacity. Conversely, spring sowing appeared to limit pigment biosynthesis, likely due to environmental stressors such as elevated temperature and excessive light exposure. Overall, these findings highlight the strong influence of genotype and sowing time on the accumulation of health-beneficial compounds in safflower. By optimizing these factors, safflower can be strategically valorized as a multipurpose crop in the Mediterranean region, combining economic and environmental sustainability with the production of natural compounds of high nutraceutical and phytotherapeutic value. Full article

With the acceleration of industrialization, the problems of water resource pollution and shortage caused by oil spills and industrial wastewater discharge have become increasingly severe, posing a major threat to ecological sustainable development. Therefore, efficient oil–water separation technology has become a key breakthrough to alleviate this crisis. In this study, Janus membranes with asymmetric wettability were prepared by layer-by-layer electrospinning. The influence of the thickness ratio between the hydrophobic layer and the hydrophilic layer on the mechanical properties, separation flux, and oil–water mixture efficiency of the Janus membranes was examined, and an optimized membrane configuration was determined: the optimal thickness ratio between hydrophobic and hydrophilic layers was 4:6. Under these conditions, the fracture stress of the fiber membranes reached 99% MPa, the fracture strain was 55.63 ± 4.77%, the separation flux values were 1888.22 and 1042.66 L m⁻² h⁻¹ for the oil–water mixture and water-in-oil emulsion, respectively, with the separation efficiencies all exceeding 99%. After 50 cycles of separation for two different oil-in-water emulsions, the separation flux and separation efficiency of the optimal sample remained relatively stable, demonstrating strong practicability. In general, the Janus fiber membranes met the expected requirements, laying a good foundation for future applications in oil–water separation, floating oil collection in water, and other fields. Full article

This paper analyzes the functional feasibility and strategic value of hybrid hydrogen storage and photovoltaic (PV) energy systems at isolated areas, specifically at Egypt’s Shalateen station. The paper is significant as it formulates a solution to the energy independence coupled with economic feasibility issue in regions where the basic energy infrastructure is non-existent or limited. Through the integration of a portfolio of advanced optimization algorithms—Differential Evolution (DE), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Multi-Objective Genetic Algorithm (MOGA), Pattern Search, Sequential Quadratic Programming (SQP), and Simulated Annealing—the paper evaluates the performance of two scenarios. The first evaluates the PV system in the absence of hydrogen production to demonstrate how system parameters are optimized by Pattern Search and PSO to achieve a minimum Cost of Energy (COE) of 0.544 USD/kWh. The second extends the system to include hydrogen production, which becomes important to ensure energy continuity during solar irradiation-free months like those during winter months. In this scenario, the same methods of optimization enhance the COE to 0.317 USD/kWh, signifying the economic value of integrating hydrogen storage. The findings underscore the central role played by hybrid renewable energy systems in ensuring high resilience and sustainability of supplies in far-flung districts, where continued enhancement by means of optimization is needed to realize maximum environmental and technological gains. The paper offers a futuristic model towards sustainable, dependable energy solutions key to the energy independence of the future in such challenging environments. Full article

Post-earthquake fires often cause more severe losses than the earthquakes themselves, highlighting the critical role of water distribution networks (WDNs) in mitigating fire risks. This study proposed an improved assessment framework for the post-earthquake firefighting functionality of WDNs. This framework integrates a WDN firefighting simulation model into a cloud model-based assessment method. By combining seismic damage and firefighting scenarios, the simulation model derives sample values of the functional indexes through Monte Carlo simulations. These indexes integrate the spatiotemporal characteristics of the firefighting flow and pressure deficiencies to assess a WDN’s capability to control fire and address fire hazards across three dimensions: average, severe, and prolonged severe deficiencies. The cloud model-based assessment method integrates the sample values of functional indexes with expert opinions, enabling qualitative and quantitative assessments under stochastic–fuzzy conditions. An illustrative study validated the efficacy of this method. The flow- and pressure-based indexes elucidated functionality degradation owing to excessive firefighting flow and the diminished supply capacity of a WDN, respectively. The spatiotemporal characteristics of severe flow and pressure deficiencies demonstrated the capability of firefighting resources to manage concurrent fires while ensuring a sustained water supply to fire sites. This method addressed the limitations of traditional quantitative and qualitative assessment approaches, resulting in more reliable outcomes. Full article

The present conceptual paper proposes a purpose-driven experiential marketing framework for film-induced destinations, integrating sustainability and emotional engagement into destination management. The model under discussion comprises five interconnected dimensions, namely integrated experience, branding, people, emotional touchpoints and processes. These are articulated through purpose-driven marketing principles and aligned with selected Global Reporting Initiative (GRI) indicators. This approach positions sustainability as an inherent component of value creation rather than an external policy layer. The framework under discussion was developed through an interdisciplinary literature review and is illustrated through insights from an exploratory case study of Monsanto, a rural Portuguese village recently featured in HBO’s House of the Dragon. Semi-structured interviews were conducted with a purposive sample of local stakeholders, including tourists, residents, entrepreneurs and institutional representatives. These interviews were analysed thematically to provide indicative evidence of the framework’s relevance and potential applicability. The findings suggest that emotional engagement, co-creation and territorial authenticity play a central role in shaping memorable film-related tourism experiences that are consistent with destination purpose and stakeholder well-being. The study also emphasises the strategic importance of storytelling, audiovisual narratives and collaborative governance in the strengthening of place identity and the support of sustainable differentiation. Despite its exploratory nature, the framework provides practical guidance for destination management organisations (DMOs), cultural programmers and creative industry actors. The article concludes by identifying avenues for future research, including cross-regional application, digital experimentation and the quantitative assessment of experiential dimensions. Full article

Salinization is a growing global problem, particularly in arid and semi-arid areas, where salt concentration interferes with the soil structure, altering natural cycling, decreasing agricultural outputs, and threatening food security. Although many soil amendments have been studied, there is still a limited understanding of their interaction with soil after mixture application and the geochemical processes and long-term sustainability that govern their effects. To address this knowledge gap, this review elucidated the effectiveness and sustainability of soil amendments, biochar, humic substances, and mineral additives in restoring saline and sodic soils of arid and semi-arid region to explore the geochemical processes that underlie their impact. A systematic search of 174 peer-reviewed studies was conducted across multiple databases (Web of Science, Google Scholar, and Scopus) using relevant keywords and the findings were converted into quantitative values to evaluate the effects of biochar, gypsum, zeolite, and humic substances on key soil properties. Biochar significantly improved cation exchange capacity, nutrient retention, microbial activity, and water retention by enhancing soil porosity and capillarity, thereby increasing plant-available water. Gypsum improved phosphorus availability, while zeolite facilitated the removal of sodium and supported microbial activity. Humic substances enhanced soil porosity, water retention, and aggregate stability. When applied together, these amendments improved soil health by regulating salinity, enhancing nutrient cycling, while also stabilizing soil conditions and ensuring long-term sustainability through improved geochemical balance and reduced environmental impacts. The findings highlight the critical role of multi-functional amendments in promoting climate-resilient agriculture and long-term soil health restoration in saline-degraded regions. Further research and field implementation are crucial to optimize their effectiveness and ensure sustainable soil management across diverse agricultural environments. Full article