Search Results (145)

Against the backdrop of the energy revolution, global energy demands are rising. Solar–wind hybrid energy storage plants (SWHESPs) are undoubtedly a research hotspot in this field for enhancing energy efficiency. However, the primary challenge in constructing SWHESPs is site selection. This paper aims to comprehensively investigate the site selection process for SWHESPs and determine the optimal site scientifically and objectively by considering various aspects, including technology, society, environment, and economy. This study employs a literature review and the Delphi method to establish the site selection index system of SWHESPs. The triangular fuzzy number (TFN) is used in relative similarity as an objective weight, while the Decision-Making Test and Evaluation Laboratory (DEMATEL) is used as a subjective weight. The comprehensive weights are computed using the Lagrange optimization method. Additionally, the options are ranked and evaluated using Geographic Information System (GIS) and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods based on prospect theory. The study also performs comparative and sensitivity analyses to confirm the effectiveness of the proposed methods. Proper siting can optimize the efficiency of resource use, which not only helps achieve more efficient use of clean energy but also promotes local economic development and job creation. Full article

Pinus radiata D. Don is planted in South Central Chile on a wide range of sites using genetically improved genotypes for timber production. As drought events are expected to increase with ongoing climatic change, the variability in gas exchange, which could impact growth and water use, needs to be evaluated. In this study, we assessed the genotypic variability of leaf-level light-saturated photosynthesis (A_sat), stomatal conductance (g_s), transpiration (E), intrinsic water use efficiency (iWUE), and Chlorophyll a fluorescence (OJIP-test parameters) among 30 P. radiata genotypes (i.e., full-sib families) from third-cycle parents at age 6 years on three sites in Central Chile. We also evaluated tree height (HT), diameter at breast height (DBH), and stem index volume (VOL). Families were ranked for HT as top-15 and bottom-15. In the OJIP-test parameters we observed differences at the family level for the maximum quantum yield of primary PSII photochemistry (Fv/Fm), the probability that a photon trapped by the PSII reaction center enters the electron transport chain (ψ_Eo), and the potential for energy conservation from photons captured by PSII to the reduction in intersystem electron acceptors (PI_ABS). Fv/Fm, PI_ABS, and ψ_Eo ranged from 0.82 to 0.87, 45 to 95, and 0.57 to 0.64, respectively. Differences among families for growth and not for leaf-level physiology were detected. DBT, H, and VOL were higher in the top-15 families (12.6 cm, 8.4 m, and 0.10 m³, respectively) whereas A_sat, g_s, E, and iWUE were similar in both the top-15 and bottom-15 families (4.0 μmol m⁻² s⁻¹, 0.023 mol m⁻² s⁻¹, 0.36 mmol m⁻² s⁻¹, and 185 μmol mol m⁻² s⁻¹, respectively). However, no family by site interaction was detected for growth and leaf-level physiology. The results of this study suggest that highly improved genotypes of P. radiata have uniformity in leaf-level physiological rates, which could imply uniform water use at the stand-level. The family variation found in PI_ABS suggests that this parameter could be incorporated to select genotypes tolerant to environmentally stressful conditions. Full article

The quality of water in the Red River is a complex interplay between human-induced changes and inherent natural variables. This research utilized the snapshot sampling approach, garnering water quality data from 45 sampling sites in the Red River and crafting 24 environmental indicators related to land use and inherent natural determinants at the catchment scale. Through Spearman rank correlation and redundancy analyses, relationships among land use, natural variables, and water quality were elucidated. Our variance partitioning revealed differentiated impacts of land use and natural factors on water quality. Pivotal findings indicated superior water quality in the Red River, driven mainly by land use dynamics, which showed a distinct geomorphic gradient. Specific land use attributes, like cropland patch density, grassland’s largest patch index, and urban metrics, were pivotal in explaining variations in parameters such as total nitrogen, ammonia, and temperature. Notably, the configuration of land use had a more profound influence on water quality than merely its components. In terms of natural influences, while topography played a dominant role in shaping water quality, other factors like soil and weather had marginal impacts. Elevation was notably linked with metrics like total phosphorus and suspended solids, whereas precipitation and slope significantly determined electrical conductivity and chlorophyll-a models. In sum, incorporating both land use configurations and natural determinants offers a more comprehensive understanding of water quality disparities in the Red River’s ecosystem. For holistic water quality management, the focus should not only be on the major contributors like croplands and urban areas but also on underemphasized areas like grasslands. Tweaking cropland distribution, recognizing the intertwined nature of land use and natural elements, and tailoring land management based on topographical variations are essential strategies moving forward. Full article

Traditional park designs no longer meet the diverse needs of young users amid rising visitor numbers and environmental challenges. Exploring the impact of mountain city parks on youth is crucial, yet localised studies on their spatial perceptions in such unique environments are lacking. Landscape design based on spatial perception evaluation offers a promising approach for renewing mountain parks to address these complex needs. Therefore, a pilot study was conducted in Chongqing’s Pipa Mountain and Eling Parks, involving questionnaire surveys and on-site spatial data collection. Using principal component analysis to select the visual and auditory indicators most related to environmental satisfaction in the overall park and various types of gathering spaces, the results showed that the first principal component of the visual environment in the entrance platform and key nodes (r = 0.41, r = 0.45), as well as the first principal component of the auditory environment in the entrance platform, path platform, and elevated points (r = 0.67, r = 0.85, r = 0.68), all showed significant positive correlations with environmental satisfaction (p < 0.01). Moreover, naturalness and aesthetics were identified as the main factors influencing environmental satisfaction. A random forest model analysed nonlinear relationships, ranking spatial factors by importance. Simultaneously, SHAP analysis highlighted the effects of key factors like elevation changes, green view index, colour diversity, and natural elements. Elevation changes were positively correlated with satisfaction at elevated points but showed a negative correlation in the overall park environment and other gathering spaces. This study explored space-perception dynamics in mountain city parks, proposing strategies to improve environmental quality in various gathering spaces and the park. These findings support creating liveable mountainous environments and guide “human-centred health,” quality enhancement, and sustainable development in renewing mountain city parks. Full article

The effects of different exogenous carbon types on the chemical structural characteristics and stability of soil organic carbon in dryland farmland remain unclear. Based on a four-year fixed-site experiment in a typical dryland farmland on China’s Loess Plateau, this study systematically analyzed the impacts of different carbon sources on soil enzyme activities, organic carbon content, chemical structural characteristics, and their interrelationships under five treatments: (i) no fertilization (T₀); (ii) 100% chemical nitrogen, phosphorus, and potassium fertilizers (CK); (iii) 50% CK + fermented cattle manure (T₁); (iv) 50% CK + corn straw (T₂); (v) 50% CK + mixed fermented cattle manure/corn straw (T₃). The results showed that the activities of β-glucosidase and N-acetylglucosidase ranked in the order T₁ > T₂ > T₃ and T₃ > T₂ > T₁, respectively. Specifically, β-glucosidase activity under T₁ increased by 35.26% compared to CK, while N-acetylglucosidase activity under T₃ increased by 30.78% relative to CK. Compared to CK, the T₁, T₂, and T₃ treatments increased soil organic carbon by 26.84%, 11.27%, and 18.63%, and alkyl carbon content by 7.67%, 2.91%, and 5.57%, respectively. Additionally, T₁ and T₃ treatments elevated aromatic carbon content by 20.59% and 176.47% relative to CK. The organic carbon activity index under T₁ was the lowest, decreasing by 10.04% compared to CK. Structural equation modeling (SEM) path analysis revealed that the addition of different exogenous carbon sources in dryland farming primarily influenced the structure and stability of soil organic carbon by directly or indirectly enhancing the activities of glucosidase, β-acetylglucosidase, and alkaline phosphatase, with T₁ demonstrating the most significant improvement. Full article

This study highlights the significant environmental and health risks associated with heavy metal contamination (As, Cd, Cr, and Pb) in Oreochromis niloticus (Nile tilapia) from two locations: the Khon Kaen municipal landfill (study site) and the Thapra commercial fish farm (reference site). It also evaluates potential human health risks and investigates genotoxicity and oxidative stress markers, including malondialdehyde, hydrogen peroxide (H₂O₂), catalase (CAT), and superoxide dismutase (SOD) in fish. Heavy metal concentrations were analyzed using inductively coupled plasma optical emission spectrometry. To determine genetic differentiation, inter-simple sequence repeats with dendrogram construction and genomic template stability (%GTS) were applied. The results showed that the average concentrations of As, Cd, Cr, and Pb in water samples were 0.0848, 0.536, 1.23, and 0.73 mg/L, respectively. These values exceeded safety limits, and the average Cd in sediment (1.162 mg/kg) was above regulatory thresholds. In fish muscle, the average metal concentrations (mg/kg) followed the order Cr (1.83) > Pb (0.69) > Cd (0.096) > As (0.0758), with Pb exceeding food quality standards. The bioaccumulation factor ranked as Cr > Pb > As > Cd. Health risk assessments, including health risk index and carcinogenic risk, suggested Pb contamination poses significant health risks through fish consumption. From dendrogram results, the %GTS of O. niloticus from the landfill and reference sites were 46.34 to 71.67% and 87.34 to 96.00%, respectively. This suggests that fish from the landfill site exhibited greater genetic diversity compared to those from the reference site. Specific oxidative stress markers revealed higher levels of H₂O₂ and significantly lower activities of CAT and SOD in landfill O. niloticus than in the reference site. These results emphasize the urgent need for environmental monitoring, stricter pollution controls, and improved waste management strategies to protect aquatic ecosystems and human health. Full article

Cyanobacteria harmful blooms (Cyano-HABs) have become a globally critical environmental issue, threatening freshwater ecosystems by degrading water quality and posing risks to human and aquatic life. Chlorophyll-a (Chl-a), a key biomarker of bloom intensity, offers crucial insights into algal bloom dynamics. However, predicting Chl-a concentrations remains challenging due to the complex interactions between various environmental factors. This study utilizes machine learning (ML) models to predict Chl-a concentrations, focusing on Lake Taihu in China, a large eutrophic lake that serves as an example of numerous freshwater lakes suffering from Cyano-HABs. The research leverages nine critical water quality parameters—water temperature, pH, dissolved oxygen, turbidity, electrical conductivity permanganate index, ammonia nitrogen, total phosphorus, and total nitrogen—to develop an ensemble ML model using XGBoost, known for its ability to handle nonlinear relationships and integrate multiple variables. The XGBoost model achieved superior predictive accuracy with an R² value of 0.78 and RMSE of 8.97 mg/m³ on the test set, outperforming traditional models like linear regression, decision trees, multi-layer perceptrons, support vector regression, and random forests. Feature importance analysis identified electrical conductivity, turbidity, and water temperature as the most significant predictors of Chl-a levels. This study further enhances model interpretability through Pearson correlation analysis, which quantifies the relationships between Chl-a concentrations and other water quality factors. Additionally, we employed principal component analysis (PCA), mutual information, Spearman rank correlation coefficients, and SHAP models to analyze feature importance and model interpretability in ML. The model’s robustness was tested across multiple monitoring sites in Lake Taihu, demonstrating its potential for broader application in other eutrophic lakes facing similar environmental challenges. By providing a reliable tool for forecasting Chl-a concentrations, this research contributes to the development of early warning systems that can help mitigate the impacts of Cyano-HABs, aiding in more effective water resource management. Full article

 Background/Objectives: Extrapulmonary neuroendocrine carcinomas (EP-NECs) are rare, aggressive malignancies with no standardized treatment approach. Although platinum-based chemotherapy is considered the first-line therapy, overall survival (OS) and progression-free survival (PFS) remain limited. This study aims to evaluate the clinical and pathological characteristics of EP-NEC patients, their treatment responses, and survival outcomes. Methods: This retrospective observational study included 29 EP-NEC patients diagnosed and followed between 2015 and 2024. Clinical and demographic data, tumor localization, disease stage, administered treatments, and survival outcomes were analyzed. Kaplan–Meier survival analysis was used to assess OS and PFS, with subgroup comparisons performed via the log-rank test. Results: The most common primary tumor sites were the pancreas (21%), prostate (17%), and cervix (14%). At diagnosis, 55.2% of patients had metastatic disease. First-line platinum-based chemotherapy achieved an objective response rate of 82.1%, with a median PFS of 8.16 months and a median OS of 14.16 months. Surgical intervention significantly improved survival (p = 0.020), while a high Ki-67 proliferation index (>80%) was associated with worse PFS (p = 0.032). Other factors, including smoking status and liver-directed therapies, had no significant impact on survival. Conclusions: EP-NECs present with a poor prognosis despite platinum-based chemotherapy achieving high response rates. Surgical resection improves survival outcomes, whereas high Ki-67 expression is associated with a worse prognosis. These findings highlight the need for further research into novel therapeutic strategies for EP-NECs. Full article

This bibliometric review analyzes global research on COVID-19 vaccine side effects, focusing on publication trends, collaborations, and key topic areas. Using VOSviewer and Bibliometrix for data analysis and visualization, this study examines 1353 unique papers indexed in Scopus and Web of Science (2020–2024). The results indicate a significant increase in publications in 2021 and 2022, with the United States, China, and Europe contributing the most. While many studies focused on common side effects, such as headache, fatigue, and injection-site pain, rare but serious adverse events, such as myocarditis, thrombocytopenia, Guillain–Barré syndrome, pericarditis, and thrombosis, were also reported. However, regions with limited research infrastructure, particularly in developing countries, remain underrepresented despite the critical need for vaccine safety studies in these areas. Additionally, journals such as Vaccines, Vaccine, and Human Vaccines and Immunotherapeutics, all ranked Q1, dominate the publication volume, ensuring wide dissemination through open-access availability. This analysis also highlights global collaboration networks, identifying key authors and regions with high levels of co-authorship. Thematic mapping distinguishes niche topics focused on rare and severe side effects from driving topics addressing more common reactions. This review, therefore, underscores the importance of scaling up research efforts in underrepresented regions and strengthening global collaborations to ensure effective pharmacovigilance. Finally, future research should prioritize the long-term, ongoing monitoring of side effects and address disparities in scientific output, particularly in developing countries where vaccine safety data are urgently needed. Full article

This study investigates the complex interaction of biophysical and meteorological factors that drive evapotranspiration (ET) in saline environments. Leveraging a total of 182 cloud-free Landsat 5/8 time-series data from 1988 to 2019, we employed the Surface Energy Balance System (SEBS) model to quantify ET and investigate its relationships with soil salinity, vegetation cover, groundwater depth, and landscape metrics. We validated the predicted ET at two experimental sites using ET observation calculated by a water balance model. The result shows an R² of 0.78 and RMSE of 0.91 mm for the SEBS predicted ET, indicating high accuracy of the ET estimation. We detected abandoned saline farmland patches across Hetao and extracted the normalized difference vegetation index (NDVI), salinization index (SI), and the predicted ET for analysis. The results indicate that ET is negatively correlated with SI with a Pearson correlation coefficient (r) up to −0.7, while ET is positively correlated with NDVI (r = 0.4). In addition, we designed a control-variable experiment in the Yichang subdistrict to investigate the effects of groundwater depth, land aggregation index, soil salinity index, and the area of abandoned saline farmland patches on ET. The results indicate that increased NDVI could significantly enhance ET, while smaller saline farmland patches exhibited greater sensitivity to groundwater recharge, with higher averaged ET than larger patches. Moreover, we analyzed factor importance using Lasso regression and Random Forest (RF) regression. The result shows that the ranking of the importance of the features is consistent for both methods and for all the features, with NDVI being the most important (with an RF importance score of 0.4), followed by groundwater table depth (GWTD), and the influence of the surface area of abandoned saline farmland being the weakest. We found that smaller patches of abandoned saline farmland were more sensitive to changes in groundwater levels induced by nearby irrigation, affecting their averaged ET more dynamically than larger patches. Decreasing patch size over time indicates ongoing changes in land management and ecological conditions. This study, through a multifactor analysis of ET in abandoned saline farmland and its intrinsic factors, provides a reference for evaluating the dry drainage efficiency of abandoned saline farmland in a dry drainage system. Full article

As the scale of real estate project financing (PF) of large construction companies in South Korea increase, discontinued construction projects and PF default rates in the financial world are also rapidly increasing. Furthermore, the percentage of PF bad debts in South Korea today has increased as much as about three times compared to that in 2023. The increase in bad debt rates results mainly from the moderate supply of new funds, delays in non-performing PF arrangements, and so forth. To address this problem, it is necessary to restart the development of non-performing real estate PF development sites through successful bidding and to review the valuation basis for development projects. Therefore, this study aims to derive internal and external characteristics of non-performing real estate PF development sites in South Korea and examine the effects of specific factors on their successful bidding. In addition, significant variables are selected based on the analysis result; the analytic hierarchy process (AHP) analysis is performed to establish a new valuation system for real estate development projects. After careful consideration of various literature reviews and expert opinions, an analysis model is established to ensure the suitability of the study model with the error range minimized. As AHP was performed based on the newly established hierarchy, the higher ranks of each valuation factor were derived based on priority and importance, and the valuation basis was rearranged accordingly. The conclusion was derived through a comprehensive review of the results of the two analyses above. It was verified that certain factors—business feasibility assessment, work performance assessment, and basic evaluation—played key roles in the success and successful bidding of real estate projects. This point suggests that strict project management and performance standards must be set based on the economic achievements of financial validity indexes and business performance capabilities. Stable profit distribution and business transparency are also viewed as vital factors for the success of projects. Therefore, this study reestablishes the valuation basis for development projects in South Korea and presents policy suggestions on location propriety and business advancement based on the analysis of non-performing PF bid decision factors and the development project valuation basis. Full article

Urban landscape lakes are increasingly at risk of nitrogen-induced eutrophication. Microbial nitrogen transformation plays a crucial role in reducing nitrogen levels in these lakes. However, the relationships between microbial communities, nitrogen functional genes, and nitrogen dynamics in water and sediment, along with their underlying mechanisms, remain unclear. In this study, we systemically investigated the spatial distributions of physicochemical indicators in the overlying water and sediment in a typical urban landscape lake, Zizhuyuan Park, and the microbial communities and nitrogen cycling genes in the surface sediments of the lake connection (CO), side (SI), and center (CE) were evaluated via macrogenetic sequencing technology to analyze their relationships with environmental factors. The results revealed that the concentrations of TN, NO₃⁻, and NH₄⁺ in the lake water were within the ranges of 1.36~2.84, 0.98~1.92, and 0.01~0.29 mg·L⁻¹, respectively. The concentrations of TN, NO₃⁻, and NH₄⁺ in the sediments ranged from 1.17~3.47 g·kg⁻¹, 0.88~1.94 mg·kg⁻¹, and 5.61~10.09 mg·kg⁻¹, respectively. The contents of NH₄⁺ in water, TN and NO₃⁻ in sediments were significantly different in spatial distribution (p < 0.05). At the CE site, the Shannon diversity index was the highest and differed significantly from the values at the SI and CO sites (p < 0.01).The sediments of Central Lake contained a total of 36 phyla and 1303 genera of microorganisms. Proteobacteria (62.88–64.83%) and Actinobacteria (24.84–26.62%) accounted for more than 85% of the microorganisms. Nitrospirae, Ignavibacteriae, and Bacteroidetes were significantly different (p < 0.05) at the CE, and Planctomycetes were significantly different (p < 0.05) at the CO. The functional gene nrfA exhibited the highest abundance, followed by napA, nosZ, nirS, hao, ureC, norB, nifH, nirK, hdhA, nifB, and amoA. The abundances of hao and nifH differed significantly at various locations in Central Lake (p < 0.05). The key nitrogen transformation processes in the sediments, ranked by contribution rate, were DNRA, denitrification, nitrification, ammoniation, nitrogen fixation, and anammox. The six nitrogen processes showed significant differences (p < 0.01) in spatial distribution. The pH, TN, NO₃⁻, NH₄⁺, C/N ratio of the sediment, and NH₄⁺ in the lake water impact the microbial community and nitrogen conversion process. The sediment should be cleaned regularly, and the water cycle should be strengthened in urban landscape lakes to regulate microorganisms and genes and ultimately reduce nitrogen and control eutrophic water. This study can provide a reference for improving and managing lake water environments in urban landscapes. Full article

The construction industry plays a crucial role in the development of emerging economies; however, project constraints can pose significant challenges to achieving social sustainability. Therefore, this study investigates the nexus between project constraints and social sustainability factors within Pakistan’s construction industry. The study adopted a quantitative approach and analyzed the collected data through descriptive and inferential tests. Data were collected from 100 civil engineers registered with the Pakistan Engineering Council (PEC) through structured questionnaires. Analysis methods included the mean, standard deviation, Relative Importance Index (RII), and multiple regression tests. Cost (mean = 3.98) and time (mean = 3.90) emerged as the most significant project constraints, while poor safety on sites had the lowest means (3.49). In social sustainability factors, improving quality of life (mean = 3.73) ranked highest, with diversity in the workforce scoring lower (mean = 3.35). RII revealed cost (RII = 0.796) and time (RII = 0.780) as top constraints, while safety ranked lowest (RII = 0.698). Multiple regression showed that cost (slope = 0.390, p = 0.027) and unskilled workforce productivity (slope = 0.312, p = 0.073) significantly affect client social sustainability. Consultants prioritized poor productivity (slope = 0.623, p = 0.003), and contractors showed positive trends in cost and planning. The study highlights challenges like workforce skill gaps and safety enforcement, stressing the need for interventions to enhance social sustainability outcomes in Pakistan’s construction sector. Full article

Background: Head and neck carcinosarcoma (HNCS) is a rare and highly aggressive malignancy with limited research, resulting in an incomplete understanding of disease progression and a lack of reliable prognostic tools. This study aimed to retrospectively analyze the clinical characteristics and outcomes of HNCS patients using data from the Surveillance, Epidemiology, and End Results (SEER) database and to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS). Methods: Patients diagnosed with HNCS from 1975 to 2020 were identified in the SEER database. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic indicators, with the optimal model selected using the minimal Akaike Information Criterion (AIC). The identified prognostic factors were incorporated into nomograms to predict OS and CSS. Model performance was assessed using the concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Survival curves were generated using Kaplan–Meier analysis and compared via the log-rank test. Results: A total of 152 HNCS patients were included, with 108 assigned to the training cohort and 44 to the validation cohort in a 7:3 ratio. Prognostic factors including age, primary tumor site, marital status, radiotherapy, chemotherapy, tumor size, pathological grade, and tumor stage were incorporated into the nomogram models. The models demonstrated strong predictive performance, with C-index values for OS and CSS of 0.757 and 0.779 in the training group, and 0.777 and 0.776 in the validation group, respectively. AUC values for predicting 3-, 5-, and 10-year OS were 0.662, 0.713, and 0.761, and for CSS the values were 0.726, 0.703, and 0.693. Kaplan–Meier analysis indicated significantly improved survival for patients with lower risk scores. The 3-, 5-, and 10-year OS rates for the entire cohort were 54.1%, 45.6%, and 35.1%, respectively, and the CSS rates were 62.9%, 57.5%, and 52.2%, respectively. Conclusions: This study provides validated nomograms for predicting OS and CSS in HNCS patients, offering a reliable tool to support clinical decision-making for this challenging malignancy. These nomograms enhance the ability to predict patient prognosis and personalize treatment strategies. Full article

The effectiveness of grouting management is closely linked to the safety of mining operations, making the scientific and accurate evaluation of mine water hazard grouting management a critical issue that demands immediate attention. Current evaluation technologies for grouting effectiveness are limited by singularity in indicator assignment, reliance on isolated indicators, and the generalization of weak metrics. Using the top and bottom grouting project of the 110504 working face at the Banji coal mine in Anhui Province as a case study, both theoretical and practical insights were integrated. Drilling fluid consumption, final grouting pressure, water permeability, and dry material per unit length were selected as key indicators to establish a comprehensive grouting effect evaluation index system. To address the limitations of previous assignment methods, this study proposes a novel approach that combines the Precedence Chart (PC) with the Criteria Importance Through Intercriteria Correlation (CRITIC) method. This integrated approach resolves the issues of singularity and subjectivity in prior assignment techniques. The evaluation system was constructed based on a single indicator framework, incorporating a comprehensive evaluation model that uses the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking and the Rank Sum Ratio (RSR) for classification support. The model demonstrates a high goodness-of-fit, with a value of 0.938, indicating strong performance. The model’s results were visualized in the form of a grouting effect zoning map, further validated through comparisons with actual on-site water discharge data and exploration borehole water inflow measurements. A maximum recorded influx of 70 m³/h, aligning with the relatively weak grouting zones identified in the evaluation. The findings demonstrate that the proposed model exhibits a high degree of reliability and scientific rigor, providing valuable theoretical guidance for enhancing coal body stability and minimizing coal loss. Full article