Search Results (66,367)

Background/Objectives: Nanostructured biomaterials based on natural polymers have gained increasing attention in pharmaceutics due to their biocompatibility, multifunctionality, and diverse biomedical applications. This novel study aimed to biofabricate chitosan-doped zinc oxide nanocomposites (CS–ZnONCs) using Leucas aspera leaf extract and to evaluate their physicochemical properties and in vitro biomedical performance. Methods: CS–ZnONCs were synthesized using L. aspera leaf extract through a green precipitation approach, and the resulting nanocomposites were characterized by various spectroscopic techniques. The in vitro antioxidant, antibacterial, and anti-inflammatory activities were evaluated, while wound-healing potential was assessed using L929 fibroblast cell migration assays. Results: UV–visible analysis confirmed the formation of CS–ZnONCs, with a characteristic absorption peak at 362 nm, and FTIR spectra indicated the presence of various important functional groups. XRD results demonstrated the crystalline nature of ZnO within the chitosan matrix. Well-dispersed, quasi-spherical nanoparticles with an average size of 44 ± 3.1 nm were identified by HR-TEM, and a positive zeta potential (+9 mV) suggested considerable colloidal stability. CS–ZnONCs showed a high swelling capacity (88 ± 2.75% for 2%) and significant phytocompound release (65.38 ± 2.79% at pH 7.4). The CS–ZnONCs showed significant antioxidant activity (ABTS of 88.19 ± 1.59%), notable antibacterial efficacy against Staphylococcus aureus (18.78 ± 0.98 mm) and Escherichia coli (17.14 ± 0.96 mm), and significant anti-inflammatory activity (82.12 ± 1.47% membrane stabilization). In vitro biocompatibility and wound-healing assays revealed significant cytocompatibility in Vero cells, with 98.75 ± 1.17% cell viability observed, whereas the fibroblast migration assay demonstrated near-complete wound closure (96.55 ± 6.46%). Conclusions: The green-synthesized CS–ZnONCs exhibit favorable physicochemical properties, biocompatibility, and multifunctional biological activities, supporting their potential as a promising sustainable biomaterial nanomedicine for pharmaceutical formulations, wound healing, and regenerative medicine applications. Full article

The soybean pod borer, Leguminivora glycinivorella, is a monophagous pest that threatens soybean production. Its larvae feed concealed within pods, which limits the efficacy of conventional insecticides. Elucidating its chemosensory system is therefore essential for developing green, behavior-based management strategies. Reference-based transcriptomics across multiple tissues of L. glycinivorella identified a comprehensive repertoire of chemosensory genes, including 76 odorant receptors (ORs), 15 gustatory receptors (GRs), 18 ionotropic receptors (IRs), 52 odorant-binding proteins (OBPs), 18 chemosensory proteins (CSPs), and 4 sensory neuron membrane proteins (SNMPs). Sequence and phylogenetic analyses characterized these candidates within the context of known insect chemosensory families. Notably, canonical bitter GRs and specific IR lineages (e.g., IR100/IR85a) were not detected in our dataset, potentially reflecting adaptation to the specialized soybean-feeding habit of this pest. Expression profiling further revealed pronounced sexual and tissue dimorphism: male antennae showed significant enrichment of putative pheromone receptors (PRs) and LglySNMP1, whereas several OBPs and ORs exhibited female-biased expression, suggesting roles in host location and oviposition. Additionally, the high expression of GR43a homologs points to fructose sensing, while the lack of detectable CO₂ receptor components (except LglyGR2) suggests atypical carbon dioxide perception mechanisms. Collectively, this study provides a valuable expression atlas of chemosensory genes in L. glycinivorella and identifies sex-specific candidate genes for future functional validation and behavior-based pest management. Full article

Epoxy resin (E-51) exhibits excellent adhesion and is widely used in the preparation of functional composite coatings. However, its smooth surface lacking micro/nano composite structures limits its self-cleaning capability and optical properties. Direct incorporation of organic silicone or inorganic fillers often faces severe phase separation and filler agglomeration issues, resulting in defects in coating durability and weather resistance. To address these challenges, this study developed a synergistic modification strategy integrating surface energy modulation with the architectural design of micro/nano-structures. Amino-terminated PDMS undergoes ring-opening addition reactions with epoxy groups in the epoxy resin, while functionalized barium sulfate nanoparticles modified with dual silane coupling agents are incorporated to enhance optical properties. This synergistic approach not only resolved interfacial compatibility but also endowed the PDMS@EP-BaSO₄ coating with outstanding comprehensive properties; the water contact angle increased to 123.5°, demonstrating an easy-to-clean benefit. Visible light reflectance reached 95%, and emissivity rose to 90%. Furthermore, when applied to metal surfaces, the coating exhibited excellent stability against acid–alkali–salt corrosion, extreme temperatures, and ultrasonic agitation. This work provided a novel approach for developing protective coatings that integrated high reflectance, high emissivity, and long-term anti-soiling properties. Full article

Complex structural health monitoring (SHM) systems are rarely installed on typical bridges, likely because of an expected low return on investment; however, low-cost, passive sensors made from a retroreflective sheeting material (RRSM) offer an economical alternative for SHM of typical bridges. Most departments of transportation (DOTs) fabricate and maintain traffic signs made from RRSMs. By using a material familiar to DOTs, the technology transfer from signs to strain sensing is streamlined. This paper focuses on the development of a passive strain sensor made from an RRSM. A standard Type XI fluorescent yellow-green RRSM is tested in tension to establish the relationship between retroreflectivity (RR) and induced strain. Results show RR decreases linearly with increasing strain after an initial plateau of ~1000 × 10⁻⁶ m/m. To function as a strain sensor, the RRSM is pre-strained beyond the plateau. A production sensor is designed to attach to the tension face of a structural element for monitoring. Periodic RR measurements are used to estimate the likely maximum strain change at the sensor location. The sensor has the potential to provide a practical, low-cost, and easily implementable solution to improve the monitoring of typical bridges, enhancing their safety and longevity. Full article

In developing countries, sustainable development strategies are increasingly shifting toward a green economy that integrates economic, social, and environmental dimensions. Despite the growing importance of green economic growth, comparative empirical studies examining its determinants in Turkey and Romania remain limited. This study investigates the dynamic relationships between environmentally sustainable growth, carbon emissions, life expectancy, renewable energy consumption, education, and technological innovation in Turkey and Romania over the period 1980–2023. Using annual time series data, the analysis applies the Augmented Dickey–Fuller and Zivot–Andrews unit root tests to examine stationarity and potential structural breaks. The empirical framework is based on the Autoregressive Distributed Lag (ARDL) bounds testing approach, which allows the estimation of both long-run equilibrium relationships and short-run dynamics. The results provide partial evidence of long-run relationships among the variables. Although the ARDL bounds test results fall within the inconclusive region, the negative and statistically significant error correction terms indicate that deviations from long-run equilibrium are corrected over time. The findings also reveal heterogeneous short-run causal interactions across the two countries, suggesting that the drivers of environmentally sustainable growth differ between Turkey and Romania. Overall, the results highlight the importance of country-specific policy frameworks, institutional structures, and energy transition pathways in promoting green economic growth. Full article

Grapevine trunk diseases, particularly those caused by Neofusicoccum parvum, represent a major threat to vineyard productivity and are increasingly difficult to control with conventional fungicides. Green synthesis of silver nanoparticles (AgNPs) using biocontrol fungi offers a promising alternative, but the factors governing the efficiency and bioactivity of biogenic nanoparticles remain poorly understood. Here, three Trichoderma species (T. harzianum, T. asperellum and T. virens) were evaluated as biological nanofactories for AgNP production. Cell-free fungal filtrates were used to synthesize AgNPs, which were characterized by UV–visible spectrophotometry, Dynamic Light Scattering (DLS) and transmission electron microscopy, while fungal redox metabolism was assessed using DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assays and HPLC profiling of extracellular metabolites. AgNPs were tested against two isolates of N. parvum in vitro. The Trichoderma strains differed markedly in nanoparticle yield, size and antifungal activity, with T. harzianum T0 producing the highest amounts of small, well-dispersed AgNPs that exerted a strong fungistatic effect on N. parvum. Nanoparticle production correlated with antioxidant capacity and the abundance of redox-active metabolites. Integration of these parameters into a Fungal Nanofactory Efficiency Index (FNEI) revealed that nanoparticle bioactivity depends on both dose and biological origin. These results demonstrate that fungal metabolism is a key determinant of biogenic nanoparticle performance and identify Trichoderma as a platform for sustainable nanotechnology-based control of grapevine trunk pathogens. Full article

Anchored in the strategic framework of Vision 2030, the research departs from anecdotal or survey-based approaches by exclusively leveraging publicly available, auditable data from national ministries, international university rankings, and scholarly publication databases. An original Integrated Green Transformation Framework (IGTF) is operationalized through fixed-effects regression modeling, longitudinal policy document analysis, and cross-sectional benchmarking of sustainability performance indicators across twelve Saudi universities. The findings demonstrate a statistically significant and temporally coherent association between national green policy milestones, such as the Saudi Green Initiative and the National Renewable Energy Program 2018, and measurable improvements in university-level sustainability strategies, operational efficiency, and research output. The average share of renewable energy utilization across sampled institutions increased from 2.1 percent in 2016 to 18.7 percent in 2023, representing substantial progress yet remaining below the Vision 2030 national target of 50%, while per-student water consumption declined by 34 percent over the same period. Scholarly publications in green economy domains rose by 638 percent, with a strong positive correlation (r = 0.76, p < 0.001) between research intensity and curriculum integration of sustainability content. Despite these advances, persistent disparities exist in resource allocation and implementation depth, particularly between historically endowed universities and newer regional institutions, highlighting a “sustainability divide” that requires targeted policy intervention. Full article

This study investigates the hydrodynamic responses and energy harvesting performance of a hemispherical point-absorber wave energy converter (WEC) in uniform current. A frequency-domain Rankine source method (RSM) is developed to rigorously account for current-modified free-surface conditions, and an approximate free-surface Green-function method (AFSGM) is implemented to assess practical applicability under weak-current assumptions. The numerical settings for body, free-surface, and radiation-boundary discretizations are determined through convergence tests. Model validation is performed by comparing motion responses against published benchmark results under both zero-current and current conditions. The effects of current and motion constraints are examined for surge–heave free and heave-only cases. Results show that current can amplify the heave response and that surge freedom enhances heave motion through coupling effects, leading to increasing discrepancies between RSM and AFSGM as current strengthens. For heave-only motion, AFSGM provides practically acceptable predictions within |Fr| ≤ 0.045, while noticeable differences appear near resonance beyond this range, for which RSM is recommended. Energy harvesting is evaluated using a linear PTO damping model, revealing that current alters the capture width ratio (CWR) and shifts the optimal PTO damping and frequency, indicating the necessity of considering current in performance assessment and PTO design. Full article

Salmonella enterica serotype Mbandaka has emerged as a significant foodborne pathogen in poultry, posing increasing public health risks through its zoonotic transmission from poultry sources to humans, yet critical gaps remain in understanding its transmission inter-host transmission and antimicrobial resistance (AMR) mechanisms within the poultry industry. In this study, we addressed these knowledge gaps by conducting a comprehensive genomic analysis of 1813 S. Mbandaka genomes, including genotyping, phylogenetic reconstruction, and pangenome analysis. The results revealed that S. Mbandaka exhibits a global distribution pattern, with sequence type 413 (ST413) representing the dominant lineage. Phylogenetic analysis revealed frequent close genomic relatedness between human and poultry-derived strains (SNP ≤ 10), suggesting poultry as a potential major zoonotic reservoir for human S. Mbandaka infection. Furthermore, close genetic relationship was also detected among the human-derived strains, suggesting the potential community spread. In addition, genomic analysis indicated an increase over time in the number of antimicrobial resistance genes (ARGs) detected per genome, frequently associated with plasmids and insertion sequences (ISs). Notably, the ARGs significantly enriched in Chinese strains were primarily associated with the Col(pHAD28) plasmid. Comparative analysis demonstrated that the ARG profiles of S. Mbandaka were similar to those of other Salmonella serovars, suggesting the potential for cross-species transmission. In conclusion, these findings represent a large-scale retrospective genomic analysis of publicly available whole-genome sequences and elucidate the transmission dynamics and AMR mechanisms of S. Mbandaka in poultry, providing insights into its risks to poultry production and public health while guiding the development of targeted prevention strategies for the poultry sector. Full article

Environmental, social, and governance (ESG) information is increasingly vital in driving capital markets to promote sustainable development. However, significant barriers remain in effectively transforming ESG information into intelligence that supports investor decision-making. Drawing upon information chain theory and intelligence transformation theory, this study constructs an ESG intelligence transformation model tailored for investor decision-making, aiming to address relevant challenges within China’s unique capital market environment. Through a mixed deductive-inductive content analysis of analyst reports issued by Chinese securities firms, this study identifies underlying issues in current ESG information utilization: excessive focus on social dimensions at the expense of integrated consideration of environmental and governance issues; inadequate conversion of environmental and governance data into decision-relevant information; and incomplete pathways for transforming ESG knowledge into intelligence supporting investment decisions. These constraints significantly undermine the potential of ESG information to guide sustainable investment strategies and support green economic transformation. To bridge these gaps, this study proposes an integrated multi-stakeholder optimization strategy encompassing: enhanced disclosure standards by regulators; greater corporate emphasis on environmental and governance disclosures; more sophisticated assessment techniques by rating agencies; and optimized information channels between corporations and investors by financial institutions. This study provides a theoretical foundation and practical pathways for enhancing the quality and utility of ESG information, contributing to sustainable finance research. Full article

Urban flood resilience is an important indicator for measuring a city’s capacity to respond to and recover from flood disasters. However, existing assessments often lack a long-term hydrological baseline. This study establishes the historical water system of Yuan Dadu (1267–1368 CE) as a control scenario to benchmark the flood resilience of modern Beijing. By integrating a historical geographic reconstruction with a hydrological–hydrodynamic simulation and the fuzzy analytic hierarchy process (FAHP), the research quantifies structural differences in resilience profiles between the nature-adapted historical system and the modern engineering-dominated system. The results indicate that Yuan Dadu’s urban flood resilience index (UFRI) is 3.44 and modern Beijing’s is 3.28. Despite modern Beijing’s significant advantage in drainage facility density (0.61 km/km²) and emergency management, the system exhibits a functional substitution failure, where gray infrastructure has failed to fully compensate for a 26% reduction in the unit area storage capacity (from 6.4 to 4.7 × 10⁴ m³/km²) and a 48.4% decline in the water system structural complexity. The findings indicate that, in rapidly urbanized cities on alluvial plains with high impervious coverage, expanding drainage networks alone may be insufficient to offset losses in a natural hydraulic buffering capacity. Accordingly, planning strategies are proposed that integrate distributed micro-storage and restore topological connectivity to recreate system-level hydraulic buffering functions. Full article

Urban riverfronts, as integral components of the urban built environment, serve as essential blue–green infrastructure that offers restorative opportunities to residents in high-density areas. However, the mechanisms through which specific spatial qualities influence well-being outcomes remain underexplored. Guided by Attention Restoration Theory (ART) and Stress Recovery Theory (SRT), this study investigates the associations among spatial perception, perceived restorativeness, environmental sensitivity, and subjective well-being along the Yangtze Riverfront in Nanjing, China. A cross-sectional survey (N = 551) was conducted across six riverfront segments, using a 96-item questionnaire to assess five spatial perception dimensions, four restorativeness dimensions, and four well-being dimensions. Structural equation modeling (SEM) results indicate that spatial perception is positively associated with perceived restorativeness (β = 0.320, p < 0.001), with aesthetic perception demonstrating the strongest relative contribution (β = 0.265). Perceived restorativeness, in turn, significantly contributes to well-being (β = 0.540, p < 0.001), partially mediating the relationship between spatial perception and well-being (indirect effect (β = 0.173; 41.69% of total effect). Notably, environmental sensitivity moderated the spatial–restorative link (β = 0.799, p < 0.001), with restorative benefits being significantly amplified for individuals with higher sensitivity. These findings highlight aesthetics, accessibility, and perceived safety as priority targets for urban design. This study offers actionable insights for optimizing riverfront landscapes as vital urban health resources. Full article

This paper proposes an innovative research algorithm “measurement—pattern—driving force—synergy” that determines the eco-efficiency of 83 Russian federal subjects (2000–2019) using the Slacks-Based Measure (SBM) model with non-desired outputs (incorporating comprehensive input indicators such as water resources and electricity input, and dual non-desired outputs of waste gas and wastewater). Combined with hot spot analysis, a gravity center model, and panel Tobit regression, we reveal the temporal-spatial evolution and driving mechanisms of eco-efficiency in resource-based economies. The research finds that the overall eco-efficiency of Russia is at a medium level and shows a dynamic correlation with the economic development stage. In the early stage of the period under review, there was a high degree of synergy, but the efficiency declined during the period of rapid economic growth. Later, it rebounded somewhat in tie with technological progress. Spatially, it presents a special pattern of low efficiency in the western European industrialized regions and high efficiency in the Arctic and Far East peripheral regions, reflecting the spatial heterogeneity of resource-dependent economies and the survival-constrained efficiency feature. The analysis of influencing factors indicates that per capita GDP has a significant positive driving effect on eco-efficiency, but the expansion of residents’ consumption, the improvement of education level and the dependence on foreign trade all have inhibitory effects, highlighting the path dependence of the current growth model on the structure of resource consumption. The research suggests that Russia should implement differentiated spatial governance in the future, promote the green transformation of consumption and trade structures, and strengthen the ecological orientation of the education and scientific research system to achieve a fundamental transformation of regional sustainable development from survival constraints to innovation-driven. Full article

The energy system is transforming in clean, low-carbon, safe, and efficient directions. As a key carrier of energy consumption, the operation optimization of the integrated energy system (IES) in industrial parks has become an important lever for facilitating energy transformation. This paper focuses on the modeling of the operation optimization of the IES, pays attention to the impact of electricity–carbon–green certificate coordination, and studies the operation optimization of the IES considering hydrogen energy utilization. Firstly, the topological structure of IES is analyzed, and a model of the integrated energy system in industrial parks covering multiple energy links, such as electricity, heat, and gas, is constructed. Hydrogen energy conversion units such as electrolyzers, fuel cells, and methane reactors are introduced. Secondly, the impact of electricity, carbon, and green certificate markets on the operation of IES is analyzed, and a green certificate-carbon trading integration mechanism is designed, along with the establishment of a corresponding market trading model. Then, with the system’s energy purchase and sale costs, electricity curtailment costs, carbon market transaction costs, green certificate transaction revenues, and equipment operation and maintenance costs as the core, an IES daily optimization scheduling model is constructed to minimize the overall cost. Finally, the feasibility of the model constructed in this paper is verified through a case study in the industrial park in the north of Dezhou, Shandong Province, and the result shows that the cost of IES is 15,013.7 yuan under the optimal operation schedule. The utilization rate of new power energy reaches 89.6%, and the 2.135 green certificates are converted into the carbon market. Meanwhile, comparative analysis across multiple scenarios and sensitivity analysis of single factors are conducted to discuss the necessity and effectiveness of the factors considered in this paper, providing a decision-making basis and inspiration for managers to carry out IES operation scheduling. Full article

This paper constructs and estimates a novel two-sector Dynamic Stochastic General Equilibrium (DSGE) model to analyze the macroeconomics of Kazakhstan’s dual-energy structure, where a large fossil fuel sector coexists with an emerging renewable segment. The model’s key innovation is its integration of an endogenous, depletable oil stock and a dual-inflation Taylor-type rule, which together capture the specific transmission channels between hydrocarbon dependence and green investment. By differentiating between oil-driven and core inflation, the framework quantifies how oil price volatility transmits monetary conditions to the renewable sector. Bayesian estimation, using sectoral data from national accounts, reveals a pronounced asymmetry: oil stock/discovery dynamics and oil revenue fluctuations dominate macroeconomic volatility, while the renewable sector exhibits stable output but remains vulnerable to oil-driven monetary tightening transmitted mainly through indirect channels. The results indicate that Kazakhstan’s ongoing energy transition offers a stabilizing diversification benefit in principle but remains structurally constrained by macroeconomic dynamics and fiscal patterns anchored to hydrocarbon conditions. These findings provide a quantitative basis for designing transition policies that mitigate cross-sector spillovers and support effective diversification in resource-dependent economies. Full article