Search Results (2,450)

This study employs a comparative fuzzy-set qualitative comparative analysis (fsQCA) to examine the combined effects of traditional factors and green patents on innovation performance in Chinese listed agricultural enterprises, offering insights into sustainability in agriculture through innovation. By analyzing 84 valid cases from 107 agricultural companies, we conduct two fsQCA analyses to compare innovation pathways with and without green patents as a conditional factor. The first analysis investigates the impacts of five factors—firm size, executives’ educational background, return on net assets, ownership concentration, and government subsidies—on non-green innovation performance, identifying four distinct pathways: executive-dispersed, employee-financed, executive-centralized, and executive-profitable. In the second analysis, green patents are introduced as an independent variable. The overall solution coverage remains stable, but the configurational landscape shifts, with two original pathways persisting and two new pathways emerging—both involving green patents. The findings suggest that the impact of green patents on innovation is condition-dependent rather than universally beneficial. Green patents amplify innovation performance only when supported by strong managerial education, financial stability, and policy incentives, particularly in the executive green synergy pathway, where raw coverage reaches 0.41, underscoring their role as a conditional multiplier in sustainable innovation. These results provide theoretical and empirical evidence for balancing economic benefits with environmental responsibility in agricultural enterprises and emphasize the need for targeted policy subsidies, enhanced managerial education, and optimized shareholder structures to drive sustainable innovation. Full article

Natural plant products have been used for cancer treatment since ancient times and continue to play a vital role in modern anticancer drug development. However, only a small fraction of identified medicinal plants has been thoroughly investigated, particularly for their effects on cellular pathways in lung and colorectal cancers, two under-researched cancers with poor prognostic outcomes (lung cancers). This review focuses on the lung and colorectal cancer signaling pathways modulated by bioactive compounds from eleven traditional medicinal plants: Curcuma longa, Astragalus membranaceus, Glycyrrhiza glabra, Althaea officinalis, Echinacea purpurea, Sanguinaria canadensis, Codonopsis pilosula, Hydrastis canadensis, Lobelia inflata, Scutellaria baicalensis, and Zingiber officinale. These plants were selected based on their documented use in traditional medicine and modern clinical practice. Selection criteria involved cross-referencing herbs identified in a scoping review of traditional cancer treatments and findings from an international survey on herbal medicine currently used for lung and colorectal cancer management by our research group and the availability of existing literature on their anticancer properties. The review identifies several isolated phytoconstituents from these plants that exhibit anticancer properties by modulating key signaling pathways such as PI3K/Akt/mTOR, RAS/RAF/MAPK, Wnt/β-catenin, and TGF-β in vitro. Notable constituents include sanguinarine, berberine, hydrastine, lobeline, curcumin, gingerol, shogaol, caffeic acid, echinacoside, cichoric acid, glycyrrhizin, 18-β-glycyrrhetinic acid, astragaloside IV, lobetyolin, licochalcone A, baicalein, baicalin, wogonin, and glycyrol. Curcumin and baicalin show preclinical effectiveness but face bioavailability challenges, which may be overcome by combining them with piperine or using oral extracts to enhance gut microbiome conversion, integrating traditional knowledge with modern strategies for improved outcomes. Furthermore, herbal extracts from Echinacea, Glycyrrhiza, and Codonopsis, identified in traditional knowledge, are currently in clinical trials. Notably, curcumin and baicalin also modulate miRNA pathways, highlighting a promising intersection of modern science and traditional medicine. Thus, the development of anticancer therapeutics continues to benefit from the synergy of traditional knowledge, scientific innovation, and technological advancements. Full article

Background/Objectives: Cancer remains one of the leading causes of mortality worldwide. Despite significant advancements in treatment strategies and drug development, survival rates remain low and the adverse effects of conventional therapies severely impact patients’ quality of life. This study evaluates the therapeutic potential of plant-derived extracts in hepatocellular carcinoma treatment, with a focus on minimizing side effects while enhancing efficacy. Methods: This research investigates the in vitro synergistic effect of silver bio-nanoparticles synthesized from Clematis vitalba, Melissa officinalis, and Taraxacum officinale extracts (Clematis vitalbae extractum—CVE, Melissae extractum—ME, Taraxaci extractum—TE) in combination with liver cancer drugs, sunitinib (SNTB) and imatinib (IMTB), on HepG2 (human hepatocellular carcinoma) and HUVEC (human umbilical vein endothelial) cell lines. The silver nanoparticles (AgNPs) were characterized using UV-Vis spectroscopy, dynamic light scattering (DLS), zeta potential analysis, and scanning electron microscopy (SEM). The antitumor effects were evaluated through cell viability assays after 24 and 48 h of exposure, with additional cytotoxicity tests on HUVEC cells. Results: Results indicated that Melissa officinalis-derived silver nanoparticles (ME AgNPs) and Clematis vitalba extract with silver nanoparticles (CVE AgNPs) significantly reduced HepG2 cell viability. Their efficacy improved when combined with conventional therapies (SNTB + ME AgNPs 1:1 vs. SNTB: 20.01% vs. 25.73%, p = 0.002; IMTB + ME AgNPs 1:1 vs. IMTB: 17.80% vs. 18.08%, p = 0.036; SNTB + CVE AgNPs 1:1 vs. SNTB: 18.73% vs. 25.73%, p = 0.000; SNTB + CVE AgNPs 1:2 vs. SNTB: 26.62% vs. 41.00%, p = 0.018; IMTB + CVE AgNPs 1:1 vs. IMTB: 12.99% vs. 18.08%, p = 0.001). Taraxacum extract exhibited similar cytotoxicity to its nanoparticle formulation but did not exceed the efficacy of the extract alone at 24 h. Selectivity index assessments confirmed that AgNPs-based formulations significantly improve cytotoxicity and selectivity to HepG2 cells. Among the tested extracts, CVE demonstrated the strongest antitumor effect, enhancing the efficacy of synthetic drugs (CI < 1). SNTB + TE AgNPs (5% EtOH) also demonstrated consistent synergy at high doses, while SNTB + CVE AgNPs provided broad-range synergy, making it suitable for dose-escalation strategies. Conclusions: These findings underscore the potential of nanoparticle-based formulations in combination therapies with targeted kinase inhibitors such as sunitinib and imatinib. Future research should focus on in vivo validation and clinical trials to confirm these findings. Full article

Studying the spatiotemporal trends and influencing factors of vegetation coverage is essential for assessing ecological quality and monitoring regional ecosystem dynamics. The existing research on vegetation coverage variations and their driving factors predominantly focused on inland ecologically vulnerable regions, while coastal areas received relatively little attention. However, coastal regions, with their unique geographical, ecological, and anthropogenic activity characteristics, may exhibit distinct vegetation distribution patterns and driving mechanisms. To address this research gap, we selected Shandong Province (SDP), a representative coastal province in China with significant natural and socioeconomic heterogeneity, as our study area. To investigate the coastal–inland differentiation of vegetation dynamics and its underlying mechanisms, SDP was stratified into four geographic sub-regions: coastal, eastern, central, and western. Fractional vegetation cover (FVC) derived from MOD13A3 v061 NDVI data served as the key indicator, integrated with multi-source datasets (2000–2023) encompassing climatic, topographic, and socioeconomic variables. We analyzed the spatiotemporal characteristics of vegetation coverage and their dominant driving factors across these geographic sub-regions. The results indicated that (1) the FVC in SDP displayed a complex spatiotemporal heterogeneity, with a notable coastal–inland gradient where FVC decreased from the inland towards the coast. (2) The influence of various factors on FVC significantly varied across the sub-regions, with socioeconomic factors dominating vegetation dynamics. However, socioeconomic factors displayed an east–west polarity, i.e., their explanatory power intensified westward while resurging in coastal zones. (3) The intricate interaction of multiple factors significantly influenced the spatial differentiation of FVC, particularly dual-factor synergies where interactions between socioeconomic and other factors were crucial in determining vegetation coverage. Notably, the coastal zone exhibited a high sensitivity to socioeconomic drivers, highlighting the exceptional sensitivity of coastal ecosystems to human activities. This study provides insights into the variations in vegetation coverage across different geographical zones in coastal regions, as well as the interactions between socioeconomic and natural factors. These findings can help understand the challenges faced in protecting coastal vegetation, facilitating deeper insight into ecosystems responses and enabling the formulation of effective and tailored ecological strategies to promote sustainable development in coastal areas. Full article

Due to its excellent specific strength, corrosion resistance, and biocompatibility, titanium alloy is often used as a biological implant material. In order to address the issues of low hardness and poor wear resistance of the Ti-25Nb-3Zr-2Sn-3Mo titanium alloy, a TiN/Sn coating with good biocompatibility was deposited on its surface using a new composite modification technology of surface mechanical strengthening + surface mechanical coating. By taking advantage of the wear resistance of TiN and the adhesiveness of Sn, a composite coating with corrosion–wear resistance was formed to improve its corrosion–wear resistance. Using TiN/Sn powders of different ratios (10% Sn, 20% Sn, 30% Sn, and 40% Sn) as media, the alloy was subjected to a combined strengthening treatment of surface mechanical attrition and solid-phase coating under a nitrogen atmosphere. The microstructure and mechanical properties of the composite-strengthened layer were tested by means of XRD, SEM-EDS, a nanoindentation tester, a white-light interferometer, and a reciprocating wear tester. Moreover, the corrosion–wear properties of the samples under different loads and electrochemical conditions were analyzed. The results show that the surface composite-strengthened layer of the alloy consisted of a TiN/Sn coating + a mechanical deformed layer. With an increase in the Sn content, the thickness of the TiN/Sn coating continuously increased, while the thickness of the mechanical deformed layer continuously decreased. The composite-strengthened layer had good comprehensive mechanical properties. In the SBF solution, the corrosion–wear resistance of the composite-strengthened samples improved; the degree of wear first decreased and then increased with the increase in the Sn content, and it reached the optimal value when the Sn content was 30%. Compared with the raw sample, the corrosion of the coating sample increased, but the wear significantly decreased. The corrosion–wear synergy factor κ value first increased and then decreased with the increase in the Sn content, reaching a maximum value at the 20% Sn content. This is the result of the combined effect of the corrosion resistance and wear resistance of the coating. Full article

This study integrates space syntax and big data from the catering industry to explore the impact of grid and organic street patterns on the spatial distribution of restaurants from the perspective of urban morphology. Space syntax is a set of theories and techniques for the analysis of spatial configurations. Focusing on five areas of the Macau Peninsula, this study models urban forms using space syntax. Syntactic parameters and Dianping data are analyzed through geographic visualization, correlation analysis, and descriptive statistics. The results reveal that grid-patterned streets provide a relatively equitable commercial environment through a structured hierarchy, whereas organic-patterned streets foster commercial diversity via more complex accessibility patterns. Additionally, at the local network level, a “cultural layer network” mechanism is revealed in organically shaped streets, supporting the stable distribution of different types of restaurants within specific accessibility ranges. For the first time, this study employs high precision (street-level accuracy), multidimensional analysis (number of restaurants and number of reviews), and a systematic methodology (“form-function” research framework) within the same space syntax model to uncover the effects of different urban morphologies on restaurant distribution. Collectively, these findings highlight street morphology’s key role in shaping vibrant commercial street networks in rapidly urbanizing contexts, reveal the morphological–socioeconomic synergy underpinning local catering ecosystems, and offer robust empirical guidance for integrated urban renewal, planning, and design strategies. Full article

Aspect-based sentiment analysis (ABSA) through joint task learning aims to simultaneously identify aspect terms and predict their sentiment polarities. However, existing methods face two major challenges: (1) Most existing studies focus on the sentiment polarity classification task, ignoring the critical role of aspect term extraction, leading to insufficient performance in capturing aspect-related information; (2) existing methods typically model the two tasks independently, failing to effectively share underlying features and semantic information, which weakens the synergy between the tasks and limits the overall performance of the model. In order to resolve these issues, this research suggests a unified framework model through joint task learning, named MTL-GCN, to simultaneously perform aspect term extraction and sentiment polarity classification. The proposed model utilizes dependency trees combined with self-attention mechanisms to generate new weight matrices, emphasizing the locational information of aspect terms, and optimizes the graph convolutional network (GCN) to extract aspect terms more efficiently. Furthermore, the model employs the multi-head attention (MHA) mechanism to process input data and uses its output as the input to the GCN. Next, GCN models the graph structure of the input data, capturing the relationships between nodes and global structural information, fully integrating global contextual semantic information, and generating deep-level contextual feature representations. Finally, the extracted aspect-related features are fused with global features and applied to the sentiment classification task. The proposed unified framework achieves state-of-the-art performance, as evidenced by experimental results on four benchmark datasets. MTL-GCN outperforms baseline models in terms of F1_ATE, accuracy, and F1_SC metrics, as demonstrated by experimental results on four benchmark datasets. Additionally, comparative and ablation studies further validate the rationale and effectiveness of the model design. Full article

Increasing air pollution, rising carbon emissions, and urban shrinkage pose significant challenges for sustainable urban development in China. Exploring the relationship between urban shrinkage and the synergy effect of pollution reduction and carbon mitigation (SPRCR) can contribute to systematically addressing the challenges of urban green development. However, few studies have analyzed all three factors within a unified analytical framework. Therefore, our study takes 288 cities at the prefecture level and above in China as the research objects and endeavors to apply the Coupling Coordination Degree (CCD), Multi-scale Geographically Weighted Regression (MGWR), and Geodetector (v2.1.0) to analyze the influence of urban shrinkage on SPRCR. From our analysis, it was demonstrated that (1) in general, urban shrinkage can inhibit an improvement in the synergistic degree of SPRCR, but the degree of inhibition is weak. (2) The relationship between urban shrinkage and this synergy shows spatial heterogeneity, with the negative impact of urban shrinkage on SPRCR mainly concentrated in the northeast region. (3) The interaction effect between urban shrinkage and construction land expansion is more significant than that between urban shrinkage and other factors, and the enhancement effect is most obvious. Given the regional differences in urban development, our study provides valuable insights for promoting sustainable urban development. Full article

Driven by the dual imperatives of global economic green transformation and the advancement of digital technologies, achieving synergistic enhancement through digitalization and greenization to promote sustainable development has become a focal point for both academia and practical fields. This study, utilizing a sample of Chinese A-share listed companies from 2010 to 2023, aims to explore the transformative potential of digital–green synergy (DGS) for enhancing enterprise sustainable development within the realm of production efficiency improvement. Employing a coupling coordination model based on the entropy-weighted TOPSIS method, the research measures the DGS levels of enterprises. Grounded in strategic synergy theory, the resource-based view, and dynamic capability theory, this study thoroughly investigates the direct impacts of DGS on corporate TFP, intermediary mechanisms, moderating effects, and heterogeneous roles. The research findings robustly demonstrate that DGS can significantly improve enterprise TFP through optimizing resource allocation, reducing cost stickiness, and enhancing operational efficiency, thereby facilitating the dynamic reorganization of production factors and the creation of sustainable value. Furthermore, external factors, such as financing constraints and environmental regulation, alongside internal organizational factors like executive characteristics, are shown to exert significant moderating effects on the effectiveness of DGS. In summary, this research not only highlights the crucial role of DGS in enhancing production efficiency as a driver for high-quality corporate development and the pursuit of sustainable goals but also provides important theoretical guidance for policymakers to incentivize digital and green transformation. It also offers practical insights for enterprise managers to strategically formulate synergistic development strategies, enhance economic benefits, and achieve long-term sustainable performance. Beyond these practical implications, this study further enriches the theoretical landscape by first extending strategic synergy theory to firm-level digital–green synergy in emerging markets; second by enhancing sustainability research by adopting a broader “environment-society” framework; methodologically innovating by developing a novel “goal-strategy-input-technology” synergy measurement framework; and finally, deepening the theoretical understanding of DGS-TFP relationships through mechanism and moderator exploration. Full article

The accelerating processes of globalization and modernization have imposed unprecedented anthropogenic pressures on the cultural diversity of historic districts, leading to the physical degradation of historical heritage and the fragmentation of cultural transmission chains. To address this challenge, this study establishes an innovative spatial-gene theoretical framework that seeks to balance heritage protection with urban development by integrating landscape characteristics and cultural connotations, thereby enhancing the conservation of cultural diversity in historic districts. Focusing on the historic Small Wild Goose Pagoda district as a case study, we developed a comprehensive methodology integrating field research, historical induction, spatial analysis, and place-making. Through this operational framework, we systematically identified four constitutive spatial genes: the mountain–water pattern, the urban-axis, the li-fang, and the architectural courtyard. These genetic elements inform a dual-regeneration strategy that promotes synergy and dialogue between old and new: (1) place-making guided by historical morphological grammar rules and (2) activity organization that reconfigures the value system of “openness and inclusiveness”. This research not only advances spatial-gene theory but also provides a replicable model for regenerating historic districts oriented toward cultural diversity, effectively combining historical authenticity with contemporary functionality to promote sustainable urban development. Full article

This study explores the development and characterization of lipid nanostructures (NLCs) containing natural deep eutectic solvents (NaDESs) derived from taperebá peel extract (Spondias mombin), a by-product rich in bioactive phenolic compounds, including ellagic acid and quercetin. The taperebá extract exhibited a high polyphenol content (2623 mg GAE/L) and notable antioxidant activity, as demonstrated by DPPH (258 mM TEAC/100 mL) and ABTS (495 mM TEAC/100 mL) assays. NLCs were developed using NaDESs to enhance the stability and bioavailability of the antioxidant compounds. Physicochemical characterization confirmed the formation of stable, nanometric, and monodispersed formulations with efficient encapsulation. Biological evaluation of the NLC-TAP-NaDES formulation demonstrated its remarkable capacity to mitigate oxidative stress in cells subjected to H₂O₂-induced ROS generation. Fluorescence imaging revealed a significant reduction in intracellular ROS levels in treated cells compared to untreated controls, confirming the antioxidant efficacy of the formulation. This outcome underscores the synergy between NaDESs and NLC systems in protecting and delivering phenolic compounds. This study highlights the potential of utilizing underexplored by-products, such as taperebá peels, to develop sustainable and effective antioxidant delivery systems. The NLC-TAP-NaDES platform combines nanotechnology with green chemistry principles, presenting significant implications for the treatment of oxidative stress-related conditions and broader applications in pharmaceutical and nutraceutical sciences. These findings contribute to advancing sustainable innovations in antioxidant therapies, leveraging the dual benefits of bioeconomy and high-performance nanomaterials. Full article

The escalating conflict between ecosystem degradation and the rising demands of humanity has rendered the attainment of a scientific balance between ecosystem services and human well-being a critical concern in research on human–environment coupling and sustainable development. Metropolitan areas are pivotal in long-term sustainable development strategies and regional equity due to rapid urbanization and the tension between ecosystem degradation and human well-being. This study proposes a novel perspective, transitioning from a “cascade” to a “coupling” approach in examining the relationship between ecosystem services and human well-being. Taking the Xi’an metropolitan area as the research subject, the research employs a coupling coordination degree model to analyze the spatiotemporal characteristics of their relationship across multiple scales. The key findings of the paper are as follows: (1) We found a severe shrinkage in the ecosystem service value (2000–2020). The ecosystem services in the Xi’an metropolitan area were significantly compromised under the pressure of homogenized human well-being improvement, resulting in weak coupling and coordination between the two. (2) There was a spatial imbalance between supply and demand. Ecosystem service values displayed a core-to-periphery increasing spatial pattern, while human well-being levels exhibited a core-to-periphery decreasing distribution, indicating a marked spatial mismatch. (3) Diverse coupling dynamics within the region were identified. Driven by factors such as the resource distribution, land use, scale effects, and benefit allocation, the coupling relationships between ecosystem services and human well-being varied across development stages and contexts. Ecosystem services functioned as either flexible facilitators or constraints on human well-being improvement. This research provides a blueprint for sustainable development, offering a framework to balance urban growth with ecological health while ensuring equitable well-being across the Xi’an metropolitan area. The study highlights the need for strict ecological space protection, enhanced urban development quality, and integrated human–environment system management. Efforts should focus on minimizing land use trade-offs and spatial competition, strengthening spatial synergy in supply–demand coupling, and promoting sustainable regional development. Full article

Background: Combination therapy with antibiotics and phages has been suggested to increase the antibacterial activity of both antibiotics and phages. We tested the in vitro activity of five antibiotics belonging to different classes in combination with lytic bacteriophages against multidrug-resistant metallo-β-lactamase (MBL)-producing Pseudomonas aeruginosa isolates. Material/Methods: A total of 10 non-repetitive well-characterized MBL-producing P. aeruginosa isolates (5 NDM, 5 VIM) co-resistant to aminoglycosides and quinolones were used. Phage–antibiotic interactions were assessed using an ISO-20776-based broth microdilution checkerboard assay in 96-well microtitration plates. Two-fold dilutions of colistin (8–0.125 mg/L), ciprofloxacin, meropenem, aztreonam, and amikacin (256–4 mg/L) were combined with ten-fold dilutions of five different phages (5 × 10⁹–5 × 10⁰ PFU/mL) belonging to Pakpunavirus, Phikzvirus, Pbunavirus, and Phikmvvirus genus. Plates were incubated at 35 ± 2 °C for 24 h, and the minimum inhibitory concentration of antibiotics (MIC_A) and phages (MIC_P) were determined as the lowest drug and phage concentration, resulting in <10% growth based on photometric reading at 550 nm. Interactions were assessed based on the fractional inhibitory concentration index (FICi) of three independent replicates and clinical relevance based on the reversal of phenotypic resistance. The statistical significance of each drug alone and in combination with phages was assessed using GraphPad Prism 8.0. Results: Synergistic and additive interactions were found for 60–80% of isolates for all drugs. FICis were statistically significantly lower than 0.5 for colistin (p = 0.005), ciprofloxacin (p = 0.02), meropenem (p = 0.003), and amikacin (p = 0.002). Interactions were found at clinically achievable concentrations for colistin, meropenem, and amikacin, and a reversal of phenotypic resistance was observed for most strains (63–64%) for amikacin and meropenem. Antagonism was found for few isolates with all antibiotics tested. Phage vB_PaerM_AttikonH10 and vB_PaerP_AttikonH4 belonging to Phikzvirus and Phikmvvirus genus, respectively, showed either synergistic (FICi ≤ 0.35) or additive effects with most antibiotics tested. Conclusions: Synergy was observed for most drugs and phages with amikacin, showing strong synergy and reversal of phenotypic resistance against most isolates. Taking into account the wide utility of jumbo phages obtained, the findings of vB_PaerM_AttikonH10 in combination with different classes of antibiotics can enhance the activity of currently ineffective antibiotics against MBL-producing P. aeruginosa isolates. Full article

As a national strategic development area, the Yellow River Basin (YRB) has seen progress in research on the synergy efficiency of pollution reduction and carbon reduction (SEPCR). However, there are still notable gaps. The theoretical framework for this area is lacking, leading to diverse and inconsistent conclusions. Additionally, difficulties in data collection and processing, along with incomplete and inconsistent data, negatively affect the accuracy of research findings. Current studies tend to focus on single aspects and lack a comprehensive and systematic analysis of the SEPCR across the entire basin. There is insufficient understanding of key network nodes, connections, and overall structural characteristics. A scientific assessment of its spatial correlation structure has far-reaching implications for the national battle against pollution and the realization of “dual carbon” goals. This study is based on panel data from 75 cities in the YRB from 2006 to 2022. It employs an ultra-efficiency SBM model to measure the SEPCR. Additionally, it utilizes a modified gravity model and social network analysis to explore the spatial network correlation structure in depth. Furthermore, the QAP model is used to clarify the mechanisms of various influencing factors. The research findings indicate that there is an imbalance in the spatial and temporal distribution of the SEPCR in the YRB. Although there is a fluctuating upward trend over time, significant internal spatial disparities exist. While the gaps between regions are gradually narrowing, there are still evident research disparities. Moreover, the spatial connectivity of the SEPCR in the YRB is gradually strengthening, with overall network connectivity also improving, yet there remains a considerable distance from an ideal state. The network density shows a decreasing trend from the downstream to the midstream and then to the upstream regions, with significant differences in spatial network centrality among these areas, particularly pronounced between the midstream and upstream regions. Differences in economic development levels, technological development levels, and industrial structure development levels promote the formation of spatial correlations in SEPCR, while disparities in energy utilization have a suppressive effect. Full article

Traditional villages are intricate socio-spatial systems shaped by multi-scalar interactions encompassing natural, cultural, and hierarchical dimensions. Despite their significant cultural and ecological value, conventional unit-based conservation methods often overlook systemic interdependencies within and between villages, leading to spatial fragmentation, inefficient resource utilization, and the erosion of distinct cultural identities. To address these limitations, this study proposes a cluster-based protection framework, integrating complex network theory with GIS-supported spatial network analysis. Focusing on Rongcheng’s coastal villages in Shandong Province, the research develops a multi-scale analytical model, incorporating macro-regional clusters, meso-level village group dynamics, and micro-unit cultural nodes. By leveraging clustering effects, the model enhances connectivity, cultural synergies, and network resilience. The findings offer a systematic and scalable conservation strategy, providing actionable insights to align heritage preservation with regional development and ecological sustainability, while ensuring broad applicability across diverse geographical and cultural contexts. Full article