Search Results (23,762)

The controlled-environment cultivation of Capsicum chinense Jacq. is a high-value but input-sensitive system, where optimizing fertilization management practices (FMPs) is essential for maximizing yield and fruit quality. We tested the hypothesis that targeted FMPs—biochar, wood vinegar, and Cropmax—enhance vegetative growth, pigment accumulation, and reproductive performance in three genotypes (‘Carolina Reaper’, ‘Trinidad Scorpion’, and ‘Habanero Chocolate’) under containerized greenhouse conditions. Across biometric, pigment, and yield metrics, biochar–Cropmax combinations produced the strongest responses, increasing plant height by up to 22%, leaf number by 51%, and chlorophyll content index by 36% over controls. Yield gains were substantial: ‘Trinidad Scorpion’ reached 301.79 g plant⁻¹ (+46%), ‘Habanero Chocolate’ 142.58 g (+32%), and ‘Carolina Reaper’ showed marked improvement in mean fruit mass (5.58 g). Biochar also elevated dry matter content to 10.31% and soluble solids to 8.35 °Brix. These results demonstrate that integrating biochar-based FMPs can significantly intensify C. chinense greenhouse production while aligning with sustainable horticultural objectives. Full article

This study aimed to quantitatively evaluate the potential health effects of exposure to major air pollutants inside newly manufactured automobiles and to develop a grading system for automobile indoor air quality based on this assessment. To achieve this, the concentrations of 28 air pollutants were measured in five different automobile models. Among these, 18 substances were selected for health risk assessment based on the availability of acute and chronic toxicity data and the requirement that each substance had been detected at least once under one or more of the automobile test modes (AM, PM, and DM). Acute hazard quotients (HQ_acute), chronic non-carcinogenic hazard quotients (HQ), and excess lifetime cancer risks (ECR) were subsequently calculated. The results of acute and chronic health risk assessments showed significant variation depending on the automobile test mode, and some automobiles exceeded health-based reference values for certain pollutants. Based on these findings, this study developed a 10-level grading system for automobile indoor air quality by comprehensively integrating pollutant-specific health risk levels and exceedances of the recommended limits outlined in Ministry of Land, Infrastructure, and Transport’s “Indoor Air Quality Guidelines for Newly Manufactured Automobiles.” The grading scale ranges from Grade 1 (Excellent) to Grade 10 (Hazardous), reflecting both acute and chronic health risks as well as legal standards, thereby improving upon conventional concentration-based management approaches. The proposed grading system enables a quantitative interpretation of automobile indoor air quality from a health-based perspective and is expected to be applicable in various fields, including automobile manufacturers’ air quality control, consumer information disclosure, and policy development. Full article

This article presents the results of a rockfall analysis conducted for the limestone walls of a former quarry that is now used as an urban park. The performed simulations (2D statistical analysis using Rigid Body Impact Mechanics—RBIM and Discrete Element Modelling—DEM) enabled the determination of the maximum displacement range during the ballistic phase and the maximum rebound height at the slope base, which facilitated the delineation of a safe land-use zone. A hazard zone was also identified, within which public access must be strictly prohibited due to the risk posed by flying debris. Based on slope stability assessments (safety factor values and rockfall trajectories), recommendations were formulated for slope reinforcement measures and appropriate management actions for designated sections to ensure safe operation of the site. Three mitigation strategies were proposed: (1) no protective measures, (2) no structural reinforcements but with installation of a rockfall barrier, and (3) full-scale stabilisation to allow unrestricted access to the quarry walls. The first option—leaving slopes unsecured with only designated safety buffers—is not recommended. Full article

The manuscript explores the valorization of forest logging residues, collected during forest management operations between summer 2023 and spring 2025 in mixed deciduous and coniferous forests, as a raw material for producing valuable bioactive products. These products offer a sustainable alternative to synthetic pesticides and fertilizers. Seven batches of biomass, comprising understory trees and branches from deciduous (mainly aspen, birch, and grey alder) and coniferous (mainly Scots pine) species, were collected during different seasons, crushed, and extracted using an ethanol–water solution. The yield of hydrophilic extracts containing proanthocyanidins (PACs) ranged from 18 to 25% per dry biomass. The highest PACs concentration (42% of extract dry mass) was found in small branches with a high bark content. The extracts and PACs at concentrations of 6.25‒12.50 mg mL⁻¹ showed fungicidal activity against several pathogenic fungi, including Botrytis cinerea Pers., Mycosphaerella sp. Johanson, Heterobasidion annosum (Fr.) Bref., and Heterobasidion parviporum Niemelä & Korhonen. Residual biomass after extraction, enriched with sea buckthorn berry pomace and a siliceous complex, was characterized and evaluated for its impact on the growth of Scots pine seedlings and selected agricultural crops. Results from forest and agricultural field trials in 2023–2025 confirmed a positive effect of the fertilizer on crop yield and quality at a low application rate (40 kg ha⁻¹ per crop). Fertilizer increased the yield of radish, dill, potatoes, and wheat by up to 44% (highest for potatoes and dill) compared to the reference, confirming its agronomic value. Full article

Financial time-series data often exhibit statistically significant skewness and heavy tails, and numerous flexible distributions have been proposed to model them. In the context of the Log-linear Realized GARCH model with Skew-t (ST) distributions, our objective is to explore how the choice of prior distributions in the Adaptive Random Walk Metropolis method and initial parameter values in the Generalized Reduced Gradient (GRG) Solver method affect ST parameter and log-likelihood estimates. An empirical study was conducted using the FTSE 100 index to evaluate model performance. We provide a comprehensive step-by-step tutorial demonstrating how to perform estimation and sensitivity analysis using data tables in Microsoft Excel. Among seven ST distributions—namely, the asymmetric, epsilon, exponentiated half-logistic, Hansen, Jones–Faddy, Mittnik–Paolella, and Rosco–Jones–Pewsey distributions—Hansen’s ST distribution is found to be superior. This study also applied the GRG method to estimate new approaches, including Realized Real-Time GARCH, Realized ASHARV, and GARCH@CARR models. An empirical study showed that the GARCH@CARR model with the feedback effect provides the best goodness of fit. Out-of-sample forecasting evaluations further confirm the predictive dominance of models incorporating real-time information, particularly Realized Real-Time GARCH for volatility forecasting and Realized ASHARV for 1% VaR estimation. The findings offer actionable insights for portfolio managers and risk analysts, particularly in improving volatility forecasts and tail-risk assessments during market crises, thereby enhancing risk-adjusted returns and regulatory compliance. Although the GRG method is sensitive to initial values, its presence in the spreadsheet method can be a powerful and promising tool in working with probability density functions that have explicit forms and are unimodal, high-dimensional, and complex, without the need for programming experience. Full article

Urban economic development together with the concentration of population acts as a major stimulus for changes in land-use configurations, thereby reshaping local ecosystems and influencing habitat quality. Conducting a rigorous evaluation of the temporal–spatial dynamics and the mechanisms underlying these changes is crucial for refining spatial management strategies, improving urban livability, and steering cities toward sustainable pathways. In this research, we established a comprehensive analytical framework that integrates the PLUS model, the InVEST model, and the GeoDetector model to examine shifts in land-use patterns and habitat quality in Busan Metropolitan City during 1988–2019 to pinpoint the principal influencing factors and to project possible trajectories for 2029–2049 under multiple climate change scenarios. The key findings can be summarized as follows: (1) during the last thirty years, the city’s land-use structure underwent substantial transformation, with forested areas and built-up zones becoming the primary categories, indicating continuous urban encroachment and the reduction in ecological land; (2) the average habitat quality dropped by 18.23%, displaying a distinct spatial gradient from low values in plains and coastal areas to higher values in mountainous and inland zones; (3) results from the GeoDetector revealed that variations in land-use type and NDVI exerted the greatest influence on habitat quality differences, reflecting the combined impacts of environmental conditions and socio-economic pressures; (4) scenario projections show that the SSP1-2.6 pathway supports ecological land growth and leads to a notable improvement in habitat quality, while SSP5-8.5 causes ongoing deterioration driven by the expansion of construction land. The SSP2-4.5 pathway demonstrates a relatively moderate pattern, balancing urban development needs with ecological preservation and thus is more consistent with the long-term sustainability objectives of Busan. This study provides a robust scientific basis for understanding historical and projected changes in land cover and habitat quality in Busan and offers theoretical guidance for optimizing land-use structures, strengthening ecological protection, and fostering sustainable development in Busan and other coastal mountainous cities. Full article

The Western and Central Pacific Ocean (WCPO), the key global purse seine fishing ground for skipjack tuna (Katsuwonus pelamis), sees frequent ENSO events. These events drastically alter marine ecosystems and fishery resource patterns, complicating fisheries management—given skipjack tuna’s high mobility and sensitivity to marine environmental changes. To address this, the study proposes an improved spatial prediction framework that incorporates the MGWR model to capture environmental changes. The spatial regression results generated by the MGWR model are incorporated as the mean-field input for the BME model. Additionally, the interannual standard deviation of skipjack tuna resources is fed into the BME model as a measure of spatial uncertainty. The results indicate that the mean field and uncertainty field exhibit a strong correlation, with an R² of 0.54, an RMSE of 583.32, an MAE of 377.22, and an ME of 334.77. Compared to the single prediction models BME and MGWR, the MGWR-BME integrated framework has improved R² by 12%, 30%, and 13% in the 2021–2023 predictions, respectively. Additionally, its prediction performance for distinguishing El Niño, La Niña, and normal years has significantly improved, with R² increasing from 0.6 to 0.67 in 2021, from 0.34 to 0.62 in 2022, and from 0.30 to 0.40 in 2023. According to the evaluation results based on Kernel Density Estimation (KDE) curves, the model performs well in fitting low values but shows weaker performance in fitting high values. By applying this approach, we have clarified the multiscale driving mechanisms through which marine environmental heterogeneity affects the distribution of skipjack tuna under ENSO conditions. This insight enables fishery managers to more accurately predict the dynamic changes in skipjack tuna fishing grounds under different climatic scenarios, thereby providing a reliable scientific basis for formulating rational fishing quotas, optimizing fishing operation layouts, and implementing targeted conservation measures—ultimately contributing to the balanced development of fishery resource utilization and ecological protection. Full article

Agricultural productivity is closely linked to the spatial variability of soil physical properties. However, high variability makes it difficult to implement effective management strategies, and the constant expansion of eucalyptus plantations in certain areas alters the soil’s physical properties. This study conducted a geostatistical analysis of the physical properties of a soil in Sogamoso, Boyacá (Colombia), which contains areas with different management practices and vegetation cover, among which the presence of Eucalyptus globulus stands out. Ninety-seven points were sampled in an area of 29.1 ha, with multiple land uses. The data were analyzed using descriptive statistics and geostatistical analysis, which determined the semivariogram parameters, the degree of spatial dependence, and the best-fitting interpolation model for mapping. A correlation analysis between variables was also performed. Analysis of variance showed no significant differences among vegetation covers (dense forest, grass-crop mosaic, weedy grassland, and crop mosaic), indicating structural homogeneity. The hydraulic conductivity (K_sat) had the highest coefficient of variation (CV), at 141.9%, while particle density had the lowest CV, at 9.25%. K_sat (exponential model, range = 207 m) and porosity (spherical model, range = 98 m) showed a strong spatial dependence. K_sat was lower in areas with eucalyptus (0.01 to 0.2 m day⁻¹), attributed to hydrophobicity induced by organic compounds emitted by these plantations. Soil moisture contents showed lower values in areas with eucalyptus, corroborating their high water consumption. Soil aggregates were lower when eucalyptus plantations were on slopes greater than 15%. Porosity showed an inverse correlation with apparent density (r² = −0.86). Full article

Long-distance water conveyance systems require controlled filling after initial operation or maintenance. This process is complex and challenging to manage accurately. It involves transient two-phase flow with rapid velocity and pressure changes, which can risk pipeline damage. Studying the filling process is thus essential to ensure the safe and efficient operation of the system. Combining a specific engineering case, this work investigates gas–liquid two-phase flow in tunnel sections during filling. We employ a coupled Volume of Fluid (VOF) multiphase model and a Realizable k-ε turbulence model for our simulations. Hydraulic parameters (flow patterns, pressure, velocity) are analyzed using the results. Key findings indicate that higher filling flow rates destabilize the process. Gas retention behavior in low-pressure caverns varies, and gas–liquid eruptions occur at shaft water surfaces. Increased flow rates also intensify phase–pattern transitions, elevate peak pressure and velocity values, and amplify pressure pulsations and velocity fluctuations. Furthermore, faster gas transport in low-pressure caverns triggers flow instability, compromising exhaust efficiency. Full article

The effectiveness of industrial heritage conservation relies on the collaborative efforts of multiple stakeholders. However, existing research lacks systematic exploration of stakeholders’ perception of heritage value and the pathways through which such perception translates into conservation behaviors. This study takes the Shaanxi section of the Baocheng Railway, a typical linear industrial heritage, as a case study. Based on the “Cognitive Appraisal Theory of Emotions” (CATE) theory, it examines the mechanism between heritage value perception, place identity, and heritage responsibility behavior. Through structural equation modeling (SEM) analysis of 414 questionnaire responses, the study finds that heritage value perception of the Baocheng Railway’s Shaanxi section not only significantly positively influences stakeholders’ place identity but also directly promotes the formation of heritage responsibility behavior. Among these, the perception of social value has the most pronounced impact on place identity and responsibility behavior. Furthermore, place identity plays a key mediating role between value perception and responsibility behavior. This study introduces the CATE theory into industrial heritage research, revealing the mechanism of behavior generation from the path of “cognition → emotion → behavior”. By focusing on linear industrial heritage sites, it broadens the scope of heritage research and highlights the central role of social value perception in driving conservation intentions and behaviors. The study further enriches research on heritage responsibility behavior, and the proposed theoretical model and findings can provide theoretical references for the management and conservation of industrial heritage. Full article

White clover (Trifolium repens L.) is known for its ability to fix nitrogen biologically, its high nutritional value, and its adaptability to livestock systems. However, excessive fertilization with synthetic nitrogen alters its symbiosis with Rhizobium and reduces the protein content of the forage. The objective of this study was to evaluate the interaction between nitrogen fertilization (0 and 60 kg N ha⁻¹), cutting time, and post-cutting evaluation on the morphology, yield, and nutritional composition of white clover. A completely randomized block experimental design with three factors, distributed in three blocks, was used. Within each block, three replicates of each treatment were assigned (six interactions), giving a total of 54 experimental units. The data were analyzed using a three-way analysis of variance and Tukey’s multiple comparison test. Exponential models and generalized additive models (GAMs) were applied to the morphology and yield data to identify the best fit. The treatment with 60 kg N ha⁻¹ and cutting at 30 days showed significant increases in plant height (47.42%), fresh weight (59.61%), dry weight (98.41%), and leaf width (27.55%) compared to the control. It also produced the highest protein content (28.44%) compared to the other treatments with fertilization, without negatively affecting digestibility. The GAMs best fit most morphological and yield parameters (except leaf height and width). All fertilized treatments had higher fresh and dry weight yields. In conclusion, applying 60 kg N ha⁻¹ after cutting at 30 days, followed by harvesting between 54 and 60 days, improved both the quality and yield of white clover, which favored sustainable pasture management and reduced excessive nitrogen use. Full article

Waste glass recycling generates waste streams such as fine glass fraction, waste ceramics containing fine glass, and waste polyethylene plastics. All of the aforementioned streams contain contaminants of organic and inorganic origin that are difficult to remove. This research was conducted to determine technological processes aimed at achieving a circular economy (CE) in the recycling of waste glass. Foam glass was made from the fine-grained, multicolored fraction of contaminated glass, an effective method for recycling glass waste at a low cost. A frothing system based on manganese oxide (MnO₂) and silicon carbide (SiC) was proposed, and an optimum weight ratio of MnO₂/SiC equal to 1.0 was determined. The possibility of controlling the process to achieve the desired foam glass densities was demonstrated. Statistical analysis was used to determine the effect of the MnO₂/SiC ratio and MnO₂ content on the density of the resulting foam glass products. Waste ceramics contaminated with different-colored glass were transformed into ceramic–glass granules. The characteristic temperature curve of the technological process was determined. The metal content in water extracts from ceramic–glass granules and pH value indicate their potential use for alkalizing areas degraded by industry and agriculture. Waste polyethylene-based plastics were converted into polyethylene waxes by thermal treatment carried out in two temperature ranges: low temperature (155–175 °C) and high temperature (optimum in 395 °C). The melting temperature range of the obtained waxes (95–105 °C) and their FTIR spectral characteristics indicate the potential application of these materials in the plastics and rubber industries. The integrated management of all material streams generated in the glass recycling process allowed for the development of a CE model for the glass recycling plant. Full article

This paper proposes a real-time energy management strategy for low-voltage microgrids that combines short-horizon forecasting with a rule-based supervisory controller to coordinate battery energy storage usage and reactive power support provided by flexible alternating current transmission technologies. The central contribution is the forecast-informed, joint orchestration of active charging and reactive power dispatch to regulate voltage and preserve stability under large photovoltaic variability and uncertain electric vehicle demand. The work also introduces a resilience response index that quantifies performance under external disturbances, forecasting delays, and increasing levels of electric-vehicle integration. Validation is carried out through time-domain numerical simulations in MATLAB/Simulink using realistic solar irradiance and electric vehicle charging profiles. The results show that the coordinated strategy reduces voltage deviation events, maintains stable operation across a wide range of scenarios, and enables electric vehicle charging to be supplied predominantly by renewable generation. Sensitivity analysis further indicates that support from flexible alternating current devices becomes particularly decisive at high charging demand and in the presence of forecasting latency, underscoring the practical value of the proposed approach for distribution-level microgrids. Full article

Wetlands are natural ecosystems of great ecological and economic value. They provide undeniable ecosystem services that contribute to promoting sustainable development. Exposed to different pressures, these limnic ecosystems are particularly vulnerable to climate change. Thus, assessing wetland vulnerability is of utmost importance. Based on a systematic selection of relevant peer-reviewed studies, this paper helps to develop a general vision of the methods used to assess wetland vulnerability in different contexts, emphasizing the use of advanced computational approaches. Hence, an overview of different cases of wetlands all across the five continents and of different types of habitats is presented. Whether the wetland is permanently or seasonally flooded, coastal, or tropical, this study enables the analysis of diverse, already established vulnerability evaluation index systems. Some of these indices were computed using geographic information systems (GISs), artificial intelligence (AI), machine learning (ML), spatial principal component analysis (SPCA) and driver–pressure–state–impact–response (DPSIR) as evaluation models. Indeed, given the adoption of different methods, diverse models, and analytical approaches under different scenarios, the vulnerability assessment process should be seen as an iterative rather than a definitive process. An accurate wetland vulnerability assessment is essential for ensuring the sustainability of wetland ecosystems and for informing effective conservation and management strategies. Full article

Tourist flow prediction plays a crucial role in enhancing the efficiency of scenic area management, optimizing resource allocation, and promoting the sustainable development of the tourism industry. To improve the accuracy and real-time performance of tourist flow prediction, we propose a BP model based on a hybrid genetic algorithm (GA) and ant colony optimization algorithm (ACO), called the GA-ACO-BP model. First, we comprehensively considered multiple key factors related to tourist flow, including historical tourist flow data (such as tourist flow from yesterday, the previous day, and the same period last year), holiday types, climate comfort, and search popularity index on online map platforms. Second, to address the tendency of the BP model to get easily stuck in local optima, we introduce the GA, which has excellent global search capabilities. Finally, to further improve local convergence speed, we further introduce the ACO algorithm. The experimental results based on tourist flow data from the Elephant Trunk Hill Scenic Area in Guilin indicate that the GA-AC*O-BP model achieves optimal values for key tourist flow prediction metrics such as MAPE, RMSE, MAE, and R², compared to commonly used prediction models. These values are 4.09%, 426.34, 258.80, and 0.98795, respectively. Compared to the initial BP neural network, the improved GA-ACO-BP model reduced error metrics such as MAPE, RMSE, and MAE by 1.12%, 244.04, and 122.91, respectively, and increased the R² metric by 1.85%. Full article