Search Results (421)

Under the requirements of the EU Nature Restoration Regulation, significant investment in the restoration of marine and coastal ecosystems will be necessary in EU Member States. A certain level of knowledge among the population will be required to ensure authorities have the required social license to pursue marine ecosystem restoration activities, and awareness raising campaigns will likely be a part of the body of actions taking place to support the delivery of the EU Nature Restoration Regulation. This survey assesses the baseline awareness, attitudes and support for marine and coastal restoration amongst the Irish adult population. Relatively low levels of awareness of both restoration initiatives and the regulation are documented, with approximately 15% of respondents aware of restoration activities and 19% aware of the regulation. While distance to the coast isn’t always strongly correlated with awareness and support, connection to the marine—represented by visiting the coast and being concerned about the marine environment—is strongly correlated with these metrics. The results indicate that information campaigns around marine and coastal restoration should attempt to highlight the benefits society receives from the marine and coastal environment and foster a sense of connection with it. Full article

Against the backdrop of rapid urbanization and land development, the degradation of regional ecosystem services and the intensification of ecological risks have become prominent challenges. This study takes the Pinglu Canal Economic Belt—a region characterized by the triple pressures of “large-scale engineering disturbance, karst ecological vulnerability, and port economic agglomeration”—as a case study. Based on remote sensing image data from 2000 to 2020, a landscape ecological risk index was constructed, and regional landscape ecological risk levels were assessed using ArcGIS spatial analysis tools. On this basis, ecological sources were identified by combining the InVEST model with morphological spatial pattern analysis (MSPA),and an ecological resistance surface was constructed by integrating factors such as land use type, elevation, slope, distance to roads, distance to water bodies, and NDVI. Furthermore, the circuit theory method was applied to identify ecological corridors, ecological pinch points, and barrier points, ultimately constructing the ecological security pattern of the Pinglu Canal Economic Belt. The main findings are as follows: (1) Ecological risks were primarily at low to medium levels, with high-risk areas concentrated in the southern coastal region. Over the past two decades, an overall optimization trend was observed, shifting from high risk to lower risk levels. (2) A total of 15 ecological sources (total area 1313.71 km²), 31 ecological corridors (total length 1632.42 km), 39 ecological pinch points, and 15 ecological barrier points were identified, clarifying the key spatial components of the ecological network. (3) Based on spatial analysis results, a zoning governance plan encompassing “ecological protected areas, improvement areas, restoration areas, and critical areas” along with targeted strategies was proposed, providing a scientific basis for ecological risk management and pattern optimization in the Pinglu Canal Economic Belt. Full article

Availability of irrigation water during growing seasons in the Republic of South Africa (RSA) remains a significant concern. Persistent droughts and unpredictable rainfall patterns attributed to climate change, coupled with an increasing population, have exacerbated irrigation water scarcity. Globally, treated wastewater has been utilised as an irrigation water source; however, despite global advances in the usage of treated wastewater, its suitability for irrigation in RSA remains a contentious issue. Considering this uncertainty, this review article aims to unravel the South African scenario on the suitability of treated wastewater for irrigation purposes and highlights the potential environmental impacts and public health risks. The review synthesised literature in the last two decades (2000–present) using Web of Science, ScienceDirect, ResearchGate, and Google Scholar databases. Findings reveal that treated wastewater can serve as a viable irrigation source in the country, enhancing various soil parameters, including nutritional pool, organic carbon, and fertility status. However, elevated levels of salts, heavy metals, and microplastics in treated wastewater resulting from insufficient treatment of wastewater processes may present significant challenges. These contaminants might induce saline conditions and increase heavy metals and microplastics in soil systems and water bodies, thereby posing a threat to public health and potentially causing ecological risks. Based on the reviewed literature, irrigation with treated wastewater should be implemented on a localised and pilot basis. This review aims to influence policy-making decisions regarding wastewater treatment plant structure and management. Stricter monitoring and compliance policies, revision of irrigation water standards to include emerging contaminants such as microplastics, and intensive investment in wastewater treatment plants in the country are recommended. With improved policies, management, and treatment efficiency, treated wastewater can be a dependable, sustainable, and practical irrigation water source in the country with minimal public health risks. Full article

This paper presents a theoretical and empirical analysis of how banks apply artificial intelligence (AI) in digital and mobile banking to implement and communicate ESG (Environmental, Social, and Governance) strategies, with particular emphasis on environmental dimensions of sustainable finance. The study adopts a mixed methodological approach combining desk research, encompassing a synthesis of academic studies, industry reports, and European regulatory frameworks on AI and ESG, and case study analysis of selected banks implementing AI-based sustainability solutions. The findings reveal that AI supports ESG strategy implementation primarily through green investment recommendations, carbon footprint analytics, automated sustainability reporting, and ethical communication with clients. AI-driven tools enhance the operational efficiency, transparency, and customer engagement of financial institutions while simultaneously fostering low-carbon financial behaviors. However, the study also highlights ethical and governance challenges related to algorithmic transparency, data bias, and responsible AI oversight. The paper contributes to the growing body of literature on AI-driven digital transformation and sustainable finance by identifying research gaps and outlining future directions for exploring the role of AI in accelerating the transition of the banking sector. Full article

This study proposes a multi-dimensional, fuzzy logic-based decision-making framework to assess airport sustainability performance under uncertainty, addressing a notable gap in the literature. The proposed model integrates the Fuzzy Analytic Hierarchy Process (FAHP) to determine the weights of sustainability criteria and the Intuitionistic Fuzzy COPRAS (IF-COPRAS) method to evaluate airport alternatives. The assessment considers four main sustainability dimensions: environmental, economic, social, and technical/institutional. A case study involving five major airports in Türkiye reveals that environmental and economic indicators play a pivotal role in shaping sustainability performance. While Istanbul Airport (IST) demonstrated the highest performance across all scenarios, a comparison with Airport Carbon Accreditation (ACA) levels indicates that carbon-focused certification alone is insufficient to reflect the full spectrum of sustainability outcomes. This research presents a novel and robust evaluation framework, contributing to the limited body of fuzzy logic-based MCDM applications for airport sustainability in the Turkish context. The findings offer actionable strategic insights for policymakers and airport managers regarding investment prioritization, operational strategy reinforcement, and the alignment of airport development with long-term sustainability goals. The results are validated through rigorous sensitivity analyses, confirming the robustness of the model despite the focused expert panel. Full article

Amid intensifying global climate change and accelerating urbanization, maintaining a balance between carbon emission reduction has become essential for achieving sustainable development. This research investigates the spatiotemporal evolution and driving mechanisms of carbon sequestration services in the ecological development zone of northern Guangdong, China. By integrating Big Geodata technology with the InVEST model, the study quantitatively evaluates both the supply and demand dimensions of carbon sequestration services using land-use, nighttime light, and socioeconomic data. Carbon storage capacities were estimated for different land-use types (including cropland, forest, grassland, water body, built-up land, and undeveloped land), while carbon emissions were spatially distributed based on nighttime light intensity, providing a holistic perspective on the regional carbon budget. The findings indicate significant spatial heterogeneity: the western region exhibits an average carbon sequestration capacity approximately 20% higher than the eastern region, due to extensive forest and grassland coverage, whereas urban areas exhibit higher carbon demand coupled with insufficient supply. Through an analysis of land-use transfer matrices and contribution assessment, land-use transformations, particularly the conversion of ecological land to urban built-up areas, were quantitatively identified as the primary factor disrupting the regional carbon balance. This study proposes actionable territorial spatial planning strategies, such as prioritizing ecological conservation in high-carbon-supply areas and promoting low-carbon urban renewal in high-demand zones, directly derived from the spatial mismatch patterns revealed by the InVEST model outputs. These insights contribute significantly to regional sustainable development practices and global climate governance. Full article

Background/Objectives: Body self-image interacts with young adults’ health behaviors in complex ways, yet its role in shaping supplement use is not well defined. This study examined young adults’ body self-image and their use of dietary supplements commonly marketed to enhance physique, fitness, and weight outcomes. Methods: College students (N = 122; 18–28 years) completed the Body Self-Image Questionnaire-Short Form to assess body self-image and answered three dichotomous questions related to general dietary (DS), performance-enhancing (PES), and weight-loss (WLS) supplement use. Student scores were calculated across nine psychological subscale groups and ranked as high, moderate, or low percentile within our study sample. Chi-square analyses examined supplement prevalence in student responses ranked within the highest and lowest tertiles; middle tertile data were excluded as part of the extreme-group design. All responses were included in the logistical regression analysis. Results: Higher scores for the Investment in Ideals and Health-Fitness Evaluation subscales observed significantly higher PES use; both subscales and the male gender were significant predictors of PES use. Higher scores for the Fatness Evaluation, Negative Affect, and Social Dependence subscales observed significantly higher WLS use; Fatness Evaluation and age were significant predictors of WLS use. Subscales were not significantly associated with general supplement use in chi-square or logistical regression analyses. Conclusions: Our findings suggest that internalized appearance ideals, emotional distress, and social approval pressures are linked to weight- and physique-driven supplement behaviors in college students. Targeted, inclusive campus wellness initiatives are needed to address psychological drivers of weight-management practices, including potentially high-risk supplement use. Full article

Characterized by zero-carbon, congestion-free, and high-capacity features, the utilization of metro systems for collaborative passenger-and-freight transport (the metro-based underground logistics system, M-ULS) has been recognized as a favorable alternative to facilitate automated freight transport in future megacities. This article constructs a three-echelon M-ULS network and establishes a multi-objective bilevel programming model, considering the interests of both government investment departments and transport enterprises. The overall goal of the study is to establish a transportation network with the lowest construction cost, lowest operating cost, and highest facility utilization rate, taking into account factors such as population density, transportation conditions, land resources, logistics demand, and metro station location, under given cost parameters and demand conditions. The upper-level model takes government investment as the main body and aims to minimize the total cost, establishing an optimization model for location selection allocation paths with capacity constraints; the lower-level model aims to minimize the generalized cost for freight enterprises by simulating the competition between traditional transportation and the M-ULS mode. In addition, a bi-level programming model solving framework was established, and a multi-stage precise heuristic hybrid algorithm based on adaptive immune clone selection algorithm (AICSA) and improved plant growth simulation algorithm (IPGSA) is designed for the upper-level model. Finally, taking the central urban area of Beijing as an example, four network scales are set up for numerical simulation research to verify the reliability and superiority of the model and algorithm. By analyzing and setting key indicators, an optimal network configuration scheme is proposed, providing a feasible path for cities to improve logistics efficiency and reduce the impact of logistics externalities under limited land resources, further strengthening the strategic role of subway logistics systems in urban sustainable development. Full article

As critical ecosystems, coastal zones necessitate the identification of their ecosystem service values, trade-off/synergy patterns, spatiotemporal evolution, and driving factors to inform scientific decision-making for sustainable ecosystem management. This study selected the coastal zone of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the research region. By incorporating land-use types such as mangroves, tidal flats, and aquaculture areas, we analyzed land-use changes in 1990, 2000, 2010, and 2020. The InVEST model was employed to quantify six key ecosystem services (ESs): annual water yield, urban stormwater retention, urban flood risk mitigation, soil conservation, coastal blue carbon storage, and habitat quality, while spatial correlations among them were examined. Furthermore, Spearman’s rank correlation coefficient was used to assess trade-offs and synergies between ecosystem services, and redundancy analysis (RDA) combined with the geographically and temporally weighted regression (GTWR) model were applied to identify driving factors and their spatial heterogeneity. The results indicate that: (1) Cultivated land, forest land, impervious surfaces, and water bodies exhibited the most significant changes over the 30-year period; (2) Synergies predominated among most ecosystem services, whereas habitat quality showed trade-offs with others; (3) Among natural drivers, the normalized difference vegetation index (NDVI, positive effect) and evapotranspiration were critical factors. The proportion of impervious surfaces served as a key land-use change driver, and the nighttime light index emerged as a primary socioeconomic factor (negative effect). The impacts of drivers on ecosystem services displayed notable spatial heterogeneity. These findings provide scientific support for managing the supply-demand balance of coastal ecosystem services, rational land development, and sustainable development. Full article

Accurate prediction of shrimp body weight is critical for optimizing harvest timing, feed management, and stocking density decisions in intensive aquaculture. While prior studies emphasize environmental factors, operational management variables—particularly harvesting metrics—remain understudied. This study quantified the predictive importance of harvesting-related variables using 5 years of industrial-scale operational data from 12 ponds (5479 cleaned records, 34.94% retention rate). We trained seven machine learning models and applied three independent feature importance methods: consensus importance ranking, SHAP explainability analysis, and Pearson correlations. Main findings: Operational variables (days of culture: 2.833 SHAP, stocking density: 1.871, cumulative feed: 1.510) ranked substantially above environmental variables (temperature: 0.123, pH: 0.065, dissolved oxygen: 0.077). Partial harvest frequency showed bimodal clustering, indicating two distinct viable operational strategies. The Weighted Ensemble model achieved the highest performance (R² = 0.829, RMSE = 4.23 g, MAE = 3.12 g). Model stability analysis via 10-fold GroupKFold cross-validation showed that the Artificial Neural Network (ANN) exhibited the tightest confidence bounds (0.708 g width, 27.7% coefficient of variation), indicating exceptional consistency. This is the first study to systematically analyze the importance of harvesting variables using SHAP explainability, revealing that operational management decisions may yield greater returns than marginal environmental control investments. Our findings suggest that operational optimization may be more impactful than environmental fine-tuning in well-managed systems. Full article

Fire incidents pose a significant threat to urban communities. However, the inherent vulnerability of old communities to fire incidents is often overlooked, resulting in a lack of targeted evaluation methods for old community fire resilience (OCFR). Therefore, this study aims to propose a comprehensive evaluation model to systematically measure the level of OCFR. Initially, an evaluation indicator system for the OCFR was developed based on the pressure–state–response (PSR) model and 4M (man, machine, media, management) theory. Subsequently, an integrated evaluation model combining the coefficient of variation (COV) and the fuzzy comprehensive evaluation (FCE) approach was established to ensure objective weighting and reliable assessment. Finally, the Community W in Xuzhou City of China was selected as a typical case, and data from 210 valid resident questionnaires were utilized to evaluate its OCFR and propose targeted improvement strategies. The key findings indicate that the ‘state’ dimension holds the largest weight, with the top-weighted indicators being OCFR210 (firefighting investment development), OCFR211 (disaster prevention education and publicity), and OCFR214 (emergency rescue organization and management). The OCFR score for Community W was 70.256, placing it in the ‘good’ level. Furthermore, sensitivity analysis revealed the robustness of the evaluation model for OCFR. This research not only introduces a novel evaluation model that expands the body of knowledge on fire resilience but also provides practical strategies to mitigate fire risks and enhance fire management in old communities, with the ultimate goal of reducing community fire incidents. Full article

This study evaluated the effects of matrix-dosed protease supplementation on growth performance, nutrient utilization, intestinal morphology, serum biochemistry, carcass traits, and economic return in broiler chickens. A total of 240 Cobb 500 chicks were assigned to six dietary treatments (T0–T5) with four replicates of 10 birds each for 33 days. Protease supplementation, particularly with protease F at 250 g/tonne (T5), significantly increased body weight at day 7 (163.0 ± 1.4 g; p = 0.002) and day 21 (854.0 ± 7.0 g; p = 0.014), and improved the feed conversion ratio at day 33 (1.54 ± 0.01; p = 0.002). Birds in the T5 group consistently exhibited the highest serum total protein (p < 0.001 on Day 21; p = 0.002 on Day 33), albumin (p < 0.001 on both days), and creatinine (p < 0.001 on Day 21; p = 0.006 on Day 33), along with reduced low-density lipoprotein (LDL) levels (p < 0.001 on Day 21; p = 0.002 on Day 33). Intestinal morphology was also enhanced, with villus height increasing to 874.0 ± 1.0 µm at day 21 and 931.0 ± 1.0 µm at day 33, accompanied by greater villus height-to-crypt depth ratios (11.23 ± 0.02 and 12.59 ± 0.01, respectively; p < 0.001). Moreover, apparent ileal digestibility of dry matter, crude protein, metabolizable energy, and amino acids were improved in T5 compared with the control and other treatments. Economic analysis showed the highest profit and return on investment (7.01%) in T5, followed by T4 and T2. These findings indicate that matrix-based protease supplementation enhances growth, nutrient absorption, and gut morphology while delivering substantial economic benefits, making it a cost-effective strategy for improving broiler productivity and profitability in commercial production systems. Full article

Background/Objectives: Patient and public involvement (PPI) in the design, conduct, and dissemination of pragmatic trials may make trial results more relevant and meaningful. The nature of PPI in paediatric pragmatic trials has been poorly characterized in the literature. This study examined the prevalence and nature of PPI in paediatric pragmatic trials and lessons learned from researchers’ experiences. Methods: For this mixed methods study, we conducted an online survey and semi-structured interviews with corresponding authors of published paediatric pragmatic trials, identified using an online search filter in MEDLINE. Descriptive statistics and qualitative thematic analysis were used to analyse the data. Results: PPI was reported by 71/127 (56%) survey respondents. Reported impacts of PPI in the survey included the following: more feasible interventions (71%), higher-quality research (57%), improved recruitment and retention (57%), and increased applicability of research findings (57%). Both survey and interview participants identified that insufficient resources, time, and training for relationship development were challenges to PPI in paediatric trials. Three themes were identified from the semi-structured interview data (recruitment and engagement, sustaining PPI relationships, and PPI value added). Conclusions: PPI aligns with the purpose and intended impact of pragmatic trials, and paediatric researchers perceive that PPI leads to increased research relevance, quality, and dissemination. There is, however, a need for institutional and funding bodies to invest in PPI partnership, including offering support for researchers and providing opportunities for children, youth, and parents as PPI partners. Full article

This perspective advances a psychoanalytic—embodiment account of the “libido of generativity” (LoG)—future-oriented reorganization of erotic desire that links embodied arousal with caregiving, legacy, and shared projects. We define LoG along four axes (direction of investment: dyad↔triad; temporal horizon: immediacy↔future; outcome modalities: procreative, creative–sublimative, community-forming; affective regulation: shame/guilt↔pride/gratitude). Integrating interoception, body ownership/agency, and self-compassion with reproductive mentalizing, we specify three proximal levers—embodiment, affect regulation, and representation—through which sexual mindfulness can recalibrate bodily salience, blunt shame-based self-objectification, and expand triadic representations (self–partner–child/symbolic offspring). We then translate these mechanisms into a brief, practice-ready relationship guidance (RG) curriculum (6–8 sessions) combining somatic mindfulness, compassion micro-practices, reproductive-mentalizing dialogs, communication skills, and generative rituals. We articulate falsifiable propositions (e.g., mindfulness → ↑couple satisfaction via ↓body-image self-consciousness and ↑reproductive mentalizing) and a sex/gender-attentive reporting plan (SAGER). Primary outcomes include sexual functioning/satisfaction and couple satisfaction/communication; secondary mechanistic endpoints index interoceptive accuracy/awareness (including heartbeat-evoked potentials), self-compassion, and reproductive mentalizing. By aligning contemplative practices with couple-skills training and equity-focused implementation, the LoG framework offers a testable bridge from psychoanalytic theory and embodiment science to measurable improvements in sexual health and couple well-being. Full article

The increasing rate of land use change, particularly deforestation and agricultural expansion, has intensified soil degradation, leading to reduced sediment retention and accelerated soil erosion. This study aims to analyze soil erosion and sediment retention in the Lam Phra Phloeng (LPP) watershed, Thailand, using a coupled modelling approach integrating the Revised Universal Soil Loss Equation (RUSLE) and the Sediment Delivery Ratio (SDR) model from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) suite. Six land use classes (forest, cropland, rangeland, flooded vegetation, built-up areas, and water bodies) were identified using Sentinel-2 MSI satellite data, with a Random Forest (RF) classification algorithm achieving an overall accuracy of 91.3% (Kappa coefficient = 0.89). The results indicate that forested areas exhibit the highest sediment retention, whereas croplands and rangelands experience the most significant soil loss due to erosion. The RUSLE model estimated an average annual soil loss ranging between 50 and 90 tons/ha/year, with the highest erosion rates observed in agricultural lands with steep slopes and minimal vegetation cover. The InVEST SDR model further corroborates these findings, showing that sediment retention is predominantly concentrated in densely vegetated areas, reinforcing the crucial role of natural forests in preventing soil displacement. This complementary modelling approach identifies priority areas for soil conservation practices. This study is the first study to integrate the RUSLE and InVEST models for the Lam Phra Phloeng watershed, providing a coupled assessment of erosion risk and sediment retention capacity and offering a novel and transferable framework for watershed-scale conservation planning and soil management in tropical monsoonal environments. Full article