Search Results (285)

Open workforce datasets can help to extend research on artificial intelligence (AI) only if they are sufficiently provenance-traceable, have good measurement quality, and have a relational structure suitable for behavioral inference. This study examines a benchmark dataset comprising 12,000 linked records across 15 industry categories and 47,206 AI tool-use records. Sampling, recruitment, questionnaire wording, respondent authentication, ethics procedures, and whether the records are real or synthetic are not documented, so the dataset is treated as a tabular source rather than verified workforce evidence. Analyses are limited to indicators that have been observed directly, including job satisfaction, work–life balance, career outlook, trust in AI, weekly learning hours, AI-use intensity, and employer-provided AI training. Assessment of behavioral interpretation of the data was conducted using Spearman correlations, HC3-robust regressions, false discovery rate adjustment, secondary industry interaction checks, and a relational-realism diagnostic. Concerns about AI replacing jobs were negligible and non-significant on a five-point scale, with an average of 2.745. Training also showed no robust association when evaluated against outcomes that did not contain training. The median absolute Spearman correlation across conceptually related observed variables was 0.0064, with the 95th percentile at 0.0180, which is very low. These estimates reflect the characteristics of the supplied documents rather than employee actions, and do not assess conservation of resources processes or tourism worker outcomes. Results from the analysis demonstrate the importance of checking open workforce data for construct validity, relational validity, sector fit and provenance before testing behavioral theories. Research for regenerative tourism requires reliable sector-specific samples, reliable multi-item measures, longitudinal design, and direct measures of social and destination outcomes. Full article

The rapid evolution of generative artificial intelligence (AI) is substantially changing archival research methodologies in social sciences. Yet, more structured guidance of methodological protocols informing AI use is needed to mitigate emergent threats to validity, particularly in human rights policy. This article offers a methodological case study, combining retrospective documentation of workflow evolution with descriptive analysis of 417 AI-assisted research sessions within the database supplementing standardized data searches of acid-attack violence for 212 WHO-reporting country cases. Data collection analyzed publicly available digital sources and applied systematic review standards. AI use was slowly streamlined in the last phases of the project. The process of blending AI assistants into the archival research required extensive workflow modifications, including pilot-testing and developing specific research protocols for improved AI use. Protocols include standardizing AI version/model selection and prompts, documenting all sessions, and multi-stage auditing. Benefits included improved data triangulation and more extensive archival searches, particularly in synthesizing non-English sources or when traditional searches faced data scarcity. AI assistants can be a useful supplementary assistant in archival research. Yet, researchers must increasingly explore effective strategies to identify and address methodological concerns, including human-in-the-loop protocols. Full article

Previous studies in the Beibu Gulf have documented the distributions and controlling factors of carbonate system parameters in surface waters; however, their dynamics in subsurface and bottom waters remain poorly constrained. Here, we present the first observations of pH and the aragonite saturation state (Ω_arag) in subsurface and bottom waters of the Beibu Gulf during spring and fall 2024. In spring, pH and Ω_arag in subsurface and bottom waters off Ledong were predominantly governed by physical mixing. In contrast, their variability off Dongfang was driven jointly by biological respiration occurring outside the Dongfang oil/gas field and by respiration within the field itself. Quantitative analysis revealed that respiration outside the field increased dissolved inorganic carbon (DIC) concentrations by ~18 ± 3 µmol kg⁻¹, a magnitude comparable to that attributable to in-field respiration (~18 ± 7 µmol kg⁻¹). Collectively, these two respiration sources induced only slightly declines in pH (0.03 ± 0.01 and 0.04 ± 0.01) but statistically significant reductions in Ω_arag (0.18 ± 0.03 and 0.21 ± 0.08, respectively). During fall, carbonate system dynamics in subsurface and bottom waters off both Dongfang and Ledong were dominated by physical mixing. The differential influence of North Pacific Tropical Water (NPTW) resulted in a decline in Ω_arag from 2.99 ± 0.10 off Dongfang to 2.75 ± 0.32 off Ledong. All observed Ω_arag values remained well above the thermodynamic saturation threshold (Ω_arag = 1), indicating no immediate risk of ocean acidification to calcifying organisms in the study area under current conditions. This study helps bridge a critical observational gap in the regional inorganic carbonate system. However, due to sampling constraints, carbonate system parameters are reported here for spring and fall only. Observations for summer and winter, as well as multi-year time-series measurements, are planned for the near future. Full article

In the field of architectural heritage, industrial built heritage plays an important role. Traditional research methods such as literature studies and field surveys have gradually evolved into digital-twin and machine-learning-based approaches. However, the study of industrial heritage remains a challenge. This study employs the PRISMA framework to conduct a systematic review of the existing literature, aiming to elucidate the impact of GIS on industrial heritage sites and its potential limitations. This study conducts a systematic review of GIS-based research on industrial heritage, focusing on studies published between 2000 and 2025. Among the 2166 records initially retrieved from Scopus and the 1771 records initially retrieved from Web of Science, 77 papers were ultimately retained after screening and deduplication. A total of 32 studies were selected based on thematic screening criteria, all of which focused on analysing the spatial characteristics of industrial heritage sites using GIS technology. Among these, 12 core studies were further selected for in-depth qualitative and methodological analysis. These documents form the foundation for exploring research hotspots, methodological approaches, and technological evolution. This review contributes a five-dimensional analytical framework that systematically classifies GIS-based industrial heritage research and identifies eight structural research gaps. The findings indicate that GIS applications remain predominantly focused on spatial mapping and distribution analysis, while their integration with ecological assessment, social and participatory approaches, archaeology, and multi-source technologies remains limited. This review provides a roadmap for integrating advanced spatial analysis tools into future industrial heritage research and planning. Full article

Background/Objectives: Psychiatric inpatient care is characterised by power asymmetries between care providers and care receivers. Despite international guidelines and policies promoting autonomy, involvement, and empowerment, these ideals remain challenging to implement in clinical practice. Psychiatric self-admission has been developed to strengthen autonomy; however, its implementation may challenge established power structures, professional roles, and responsibilities within mental healthcare settings. This study aimed to explore stakeholder perspectives on power transfer during the implementation of psychiatric self-admission in Scandinavia. Methods: A qualitative multi-source study was conducted using semi-structured interviews, focus group interviews, and document collection. Interviews were conducted with 36 participants involved in the development and implementation of self-admission in Denmark, Norway, and Sweden. Additionally, approximately 250 documents were gathered. The documentary material was analysed alongside the interviews and focus groups to provide an understanding of the implementation of self-admission models and how power transfer was represented within these processes. The analyses were inspired by methods in qualitative content analysis and document analysis. Results: Findings on stakeholder perspectives on power transfer during implementation revealed a tension reflected in two subthemes: ‘Responsive and Responsible’, where self-admission was viewed as a necessary response to needs that the healthcare system was unable to address, and ‘Unsafe and Unsound’, where self-admission was associated with uncertainties and risks related to losing control. Conclusions: Implementing psychiatric self-admission, which involved challenging traditional power relations in healthcare, was permeated by trust, distrust, and fear. The findings highlight the need to address stakeholders’ concerns related to safety and professional responsibility. Full article

Natural product (NP)-based neuroregeneration research has generated extensive preclinical evidence over the past five decades. Pharmacological activity across core processes of central nervous system (CNS) repair including neurogenesis, axonal regeneration, and neuroplasticity have been documented. Despite consistent observations of neurite outgrowth, neuroprotection, and partial functional recovery in cellular and animal models, translation into durable clinical therapies has remained limited. Neurotrophins such as nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) similarly exhibit strong regenerative effects in experimental systems, but even direct central administration has failed to produce sustained long-distance axonal regeneration or stable circuit reconstruction. This suggests that delivery constraints alone do not explain the failure to achieve clinically-relevant functional repair. It is proposed herein that this limitation reflects intrinsic constraints in how regenerative signalling is organised across multiple biological scales. Integrating evidence from in vitro and in vivo injury models, we can introduce a Target–Mechanism–Network (T-M-N) approach that systematically maps NPs activity onto a hierarchical regulatory architecture. Across diverse NPs classes, ~55 recurrent molecular targets cluster into 10 functional mechanisms, which converge into four higher-order network control regimes governing energetic competence, regenerative signalling capacity, redox-immune balance, and structural plasticity. This analysis reveals that NPs converge on shared regenerative networks but rarely coordinate all required domains within a unified pharmacological programme. They can thus be seen to represent a pre-organised source of evolutionarily selected pharmacophores encoding discrete elements of neuroregenerative network control. On this basis, pseudo-natural product (PNP) design enabled by computational chemistry and phenotypic screening may provide a strategy to recombine these fragments into engineered scaffolds with improved functional selectivity and regenerative coherence. The need to shift drug discovery from optimisation of individual NPs toward architecture-driven design of multi-functional molecules that address the integrated demands of neuroregeneration is discussed. Full article

With rural revitalization as China’s national policy priority, rural tourism has been promoted as a pathway to stimulate local economies and advance revitalization objectives. National and local governments have introduced policy measures to support rural tourism development. However, the spatial correspondence between documented policy attention and tourism popularity remains uneven and insufficiently understood. To address this gap, this study develops an integrated evaluation framework combining a text-based measure of documented policy attention, denoted PII, and a Tourism Popularity Index (TPI) using multi-source data from 920 peri-urban villages in Shanghai with rural tourism destination POIs. Spatial analysis reveals disparities between tourism popularity and documented policy attention, and further examines the contextual characteristics associated with this misalignment. The findings indicate that: (1) documented policy attention and rural tourism popularity exhibit pronounced spatial disparities, with high-popularity clusters emerging where favorable resource conditions, accessibility, and higher levels of policy attention coexist; (2) widespread policy–popularity mismatches indicate limited correspondence between the two measures; (3) the selected cases illustrate differences in spatial planning, operational capacity, and market-oriented strategies, cautioning against uniform policy expansion. The study offers a spatially explicit framework for assessing policy–popularity alignment and informing context-sensitive rural tourism governance in highly urbanized regions. Full article

Relay protection operation and maintenance (O&M) involves multi-source documents such as device manuals, O&M records, and industry regulations, with dense professional terminology and dispersed knowledge, making traditional retrieval methods inadequate for precise association. This paper proposes a knowledge graph construction and application method for relay protection O&M that incorporates a neighborhood gating mechanism. First, a domain schema is established covering five core entity types, primary equipment, protection functions, functional components, setting parameters, and secondary circuit signals, along with the semantic relationships between entities. Second, a MacBERT-GNF-CRF entity recognition model is proposed, which introduces a gated neighborhood feature fusion (GNF) mechanism on the basis of pre-trained semantic encoding to enhance local semantic representations near entity boundaries; experimental results show that this model achieves an F₁ score of 0.946. A MacBERT-GNF-RC relation extraction model is constructed to realize automatic discrimination of semantic associations between entity pairs. After entity disambiguation and knowledge fusion, knowledge graph storage and visualization are completed based on Neo4j. Furthermore, a knowledge graph-enhanced alarm question-answering prototype is developed and evaluated using a representative 220 kV composite alarm case and 50 historical alarm cases. Expert evaluation shows that KG augmentation significantly improves alarm interpretation quality and evidence traceability compared to direct LLM answering. Full article

Background/Objectives: Self-management for adults living with intestinal stomas secondary to colorectal cancer encompasses technical ostomy care, physical symptom control, psychological adjustment, and social participation, creating demand for standardised assessment instruments to identify unmet rehabilitation needs. Definitions of generic self-care and stoma-specific self-management remain inconsistent across published literature, and psychometric indicators are incompletely reported across available measurement instruments. This review includes both stoma-specific instruments and generic self-care scales that have been validated or widely applied specifically in colorectal cancer ostomy cohorts. Following JBI scoping review methodology, this work systematically maps all published self-management assessment instruments developed for adults with intestinal stomas secondary to colorectal cancer, summarises their core measurement domains and documented psychometric properties, and identifies prevailing gaps in scale development and validation research. Methods: This scoping review was conducted in accordance with Joanna Briggs Institute methodological guidance and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) reporting checklist. Ten electronic databases were searched from inception to 31 December 2025, with supplementary manual screening of reference lists. Eligible sources were peer-reviewed English or Chinese articles focusing exclusively on adults with colorectal cancer–related intestinal stomas. Two independent researchers completed title/abstract and full-text screening, followed by data extraction using a piloted standardised form. Consistent with descriptive scoping review design, no formal methodological quality evaluation or risk-of-bias assessment was performed. Results: Thirty-two studies involving 12 self-management assessment instruments were finally included. All tools documented Cronbach’s α coefficients ranging from 0.805 to 0.977. Content validity indicators were documented for eight instruments, whereas construct validity verified via factor analysis or structural equation modelling was only available for three tools. Criterion-related validity, cross-cultural validity and responsiveness were scarcely reported across most instruments. Only three instruments were fully developed based on complete and clearly articulated theoretical frameworks. Four consistent core measurement domains were identified across scales: stoma technical care, symptom and complication management, psychological adaptation, and family-social interaction. Conclusions: Although internal consistency metrics are universally reported, comprehensive multi-faceted validity testing and responsiveness evaluation are largely absent from existing published evidence. Cross-cultural measurement invariance between original and locally adapted versions (such as the ESCA and its Chinese revised forms) has rarely been examined. Future research priorities include rigorous cross-cultural adaptation following International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and Consensus-based Standards for the selection of health Measurement INstruments (COSMIN) protocols, full psychometric verification of currently available instruments, and development of brief validated short forms for clinical screening. New instrument development should only be initiated if existing tools fail to capture core rehabilitation priorities identified by patients, caregivers, and clinical staff. No responsiveness metrics were identified across the 32 included colorectal cancer-specific clinical studies. The absence of relevant evidence in this literature pool does not prove that these instruments cannot detect longitudinal changes; formal responsiveness testing is required before applying these tools for long-term outcome monitoring. Full article

Building-use information underpins urban building energy modeling, disaster risk assessment, and evidence-based planning, yet semantic labels are missing for most buildings in open databases; the most widely available proxies are OpenStreetMap (OSM) building-type tags, which largely denote type or physical form rather than independently observed current use. Machine learning models that infer such building-type tags from footprint morphology promise scalable label enrichment, but it remains unclear how well such models travel between cities. This exploratory study benchmarks the cross-city transferability of morphology-based OSM building-type-tag inference using an interpretable, openly documented, and computationally lightweight machine learning pipeline; inference of actual current use would require external validation against authoritative records and is treated here as a downstream hypothesis only. From OpenStreetMap extracts of five European cities (Berlin, Amsterdam, Vienna, Barcelona, and Budapest), 3.22 million building footprints were processed and 197,747 labeled buildings were sampled, each described by 22 footprint- and context-level morphometric indicators. Gradient boosting classifiers achieved within-city macro-F1 of 0.831–0.914 (binary residential/non-residential) and 0.595–0.699 (four-class) under spatially blocked cross-validation. On the class-enriched benchmark samples, pairwise transfer retained 85.7% of within-city performance on average, with a minimum of 61.5%; when the same transferred predictions are reweighted to each target’s observed tagged-subset prevalence, mean transferred macro-F1 falls to 0.621 and non-residential precision to 0.09–0.50, and source rankings can reorder, so the class-enriched matrix does not by itself support operational source selection. Transfer degradation was positively associated with the Wasserstein distance between the morphological feature distributions of city pairs (Spearman ρ = 0.66 descriptively; the association is dominated by Amsterdam and largely disappears when Amsterdam pairs are excluded, ρ = 0.13). SHAP analysis indicated that building-size heterogeneity was a recurring predictive signal across the five models, whereas adjacency- and density-related signals varied more across cities. Learning-curve analyses on the class-enriched benchmark indicate that a pooled multi-city model is able to rival locally trained models on comparable class-enriched samples when the target city is morphologically similar to the source pool, but small local samples quickly dominate otherwise; these fractions refer to the class-enriched benchmark samples and do not translate directly into city-level annotation budgets. The proposed pipeline runs end-to-end on a standard computer with exclusively free and open data and software, providing an openly documented benchmark for AI-assisted urban analytics and hypothesis-generating evidence on when morphology-based tag models may be reused across cities. Full article

Metallurgical R&D search is difficult for a practical reason: useful evidence is rarely defined by one keyword. A production-support question can depend at the same time on material grade, process route, defect mechanism, property, test method, and numerical conditions. Conventional retrieval-augmented generation (RAG) pipelines largely treat document chunks as independent text and can therefore miss relations that matter for process monitoring, fault diagnosis, and engineering decision support. We evaluate a confidence-adaptive graph-enhanced retrieval layer for metallurgical RAG in a controlled synthetic benchmark with explicitly specified generation and evaluation rules. The benchmark contains 300 generated heterogeneous records derived from a seven-block source distribution and 30 material–process–defect–property archetypes, together with 180 frozen queries: 60 exact, 60 paraphrased, and 60 multi-hop. The main run evaluates robustness to incomplete structured metadata, with 10% missing and 4% erroneous categorical fields. Entity and relation extraction from raw documents is outside the evaluated scope. We compare BM25, TF-IDF, latent semantic analysis, a sparse + dense hybrid, graph-only retrieval, two ablations, and the proposed adaptive hybrid. On the complete query set, the proposed method obtains MRR = 0.992, Precision@5 = 0.980, Recall@10 = 0.859, and nDCG@10 = 0.948. Relative to the sparse + dense hybrid, nDCG@10 increases by 0.186 (24.4%); the paired 95% bootstrap interval is in the range of 0.166–0.206, and the Holm-adjusted Wilcoxon p-value is 2.59 × 10⁻²⁹. Under severe degradation with 40% missing and 16% erroneous metadata, the adaptive method retains mean nDCG@10 = 0.791, compared with 0.650 for graph-only retrieval and 0.762 for the metadata-independent sparse + dense hybrid. A 5000-run Monte Carlo analysis estimates 6763 chunks and 58.70 MB for indexed vectors plus metadata at a 512-token chunk size and 64-token overlap. The results show how the retrieval rule behaves under controlled conditions; they are not evidence of plant-level effectiveness or of the quality of generated answers. Those questions require external, expert-labeled validation. Full article

The Sanchakou tremolite jade deposit in Qinghai Province represents a significant contact-metasomatic jade resource. Unlike typical contact-metasomatic (D-type) deposits—commonly associated with intermediate-to-acidic intrusions and magnesian carbonate protoliths—the Sanchakou deposit is genetically linked to a relatively SiO₂-poor gabbro intrusion and dolomite. This atypical geological setting raises fundamental questions concerning the sources of ore-forming components and the nature of metasomatic processes involved. To address these questions, this study integrates petrographic observations, whole-rock major- and trace-element geochemistry, and Sr isotopic analyses of tremolite jade, host dolomite wallrocks, gabbro, and their hydrothermally altered counterparts to constrain the origins of Ca, Mg, and Si and to reconstruct the metasomatic evolution of the system. Our results reveal a multi-sourced contribution to ore formation: Ca is derived exclusively from dolomite; >98% of Si originates from an external crustal fluid; and Mg is supplied predominantly (77%) from dolomite, with the remaining 23% sourced from altered gabbro. Strontium isotopic data further confirm the involvement of a gabbro-derived fluid characterized by elevated ⁸⁷Sr/⁸⁶Sr ratios but low Sr concentrations. A well-defined, continuous metasomatic sequence—comprising silicification → diopsidization → tremolitization → nephritization—is clearly documented. The deposit formed in a post-collisional extensional tectonic setting, driven by heat-induced double metasomatism. This study clarifies the provenance and evolutionary pathways of ore-forming materials in this atypical contact-metasomatic system and provides a genetic framework for analogous jade deposits associated with mafic intrusions. Full article

Confronted with severe global challenges, including water scarcity, excessive use of chemical fertilizers and pesticides, and heavy metal contamination in soils, conventional agricultural technologies exhibit marked limitations in integrated water–fertilizer management and non-point source pollution control. Leveraging their excellent water retention capacity, intelligent sustained-release properties, and environmental responsiveness, hydrogels offer innovative solutions to advance sustainable agricultural development. This review comprehensively outlines the fundamental types, crosslinking mechanisms, and key functional properties of hydrogels, with a focused discussion on their agricultural deployment as high-efficiency soil conditioners, fertilizer vectors, and pesticide carriers; it deciphers the microscopic water-holding mechanisms under the tristate water model, delineates the divergent water-uptake and retention behaviors between ionic and non-ionic hydrogels, and clarifies the cyclic water-holding and release mechanisms of hydrogels during soil amelioration. Thise paper further synthesizes hydrogel-enabled environmental remediation applications, in which heavy metals and pesticide residues in soils and aquatic systems are removed via functional-group coordination adsorption or photocatalytic degradation; concurrently, hydrogels have been shown to activate plant systemic immunity through calcium-signaling pathways, thereby inducing broad-spectrum antiviral defense responses. Moreover, hydrogels can be integrated into precision agriculture frameworks to enable real-time monitoring of crop physiological status and to support targeted irrigation and fertilization management. This work also evaluates the role of hydrogels in promoting seed germination, root system development, crop metabolic regulation, and stress resilience, while introducing tailored application strategies across distinct plant growth stages. Their documented economic advantages include water conservation, enhanced crop yields, reduced dependence on synthetic fertilizers, and lower labor costs. Nevertheless, the large-scale implementation of hydrogels continues to face multifaceted challenges—particularly poor degradability and latent ecological risks, as conventional polyacrylamide (PAM)-based gels resist soil mineralization and retain potentially neurotoxic monomers, leaving a critical gap in multi-annual field data concerning their non-target interference with native soil aggregate evolution, pore distribution, and rhizospheric carbon–nitrogen footprints. Mechanistically, many hydrogels with tensile strengths below 1 MPa are highly susceptible to three-dimensional network collapse under high-salinity osmotic shock and tillage mechanical stress, exhibiting a precipitous drop in water retention after more than three wet–dry cycles due to deficient long-term structural stability. Compounding these technical gaps are elevated production costs and low farmer adoption, driven by the absence of texture-specific performance thresholds—such as an available water increment ≥ 40% for sandy soils—and the lack of established life-cycle cost models and farmer incentive mechanisms for bio-based hydrogels. Moving forward, hydrogel technology should pivot toward materials innovation and cost-reduction engineering to broaden its applicability, employ ≥3-year, multi-habitat regional trials to delineate ecological benefit–risk boundaries, and ultimately position hydrogels as pivotal enablers of sustainable, green agricultural paradigms. Full article

Coastal geomorphology is a key component of nearshore representation on nautical charts. However, its cartographic generalization remains constrained by incomplete knowledge-system modeling, limited task-oriented guidance, and insufficient quantitative descriptions of generalization quality. To address these limitations, this study proposes a knowledge-graph-based approach for cartographic generalization of coastal geomorphology in nautical charts. A three-layer graph framework, consisting of a concept layer, an entity layer, and a rule layer, was constructed around shorelines, coastline categories, and generalization rules. Textual knowledge extraction and spatial-feature extraction were then conducted using cartographic specifications, historical chart samples, and expert-experience documents to support the unified organization and population of multi-source knowledge. A reasoning mechanism integrating spatial constraints and semantic associations was further developed to generate quantitative reference indicators and evaluate shoreline generalization quality. The results show that the proposed knowledge graph can organize domain knowledge in a structured and traceable form, identify rule-compliance differences among different shoreline generalization results, and provide descriptive reference benchmarks for quality evaluation. The method offers a knowledge-driven basis for improving the objectivity and explainability of coastal geomorphology generalization in nautical-chart production. Full article

Coal fires are a significant source of greenhouse gas emissions and ecological pollutants, yet their emission characteristics and carbon accounting remain poorly constrained. To reveal the pollutant generation characteristics and carbon emission levels of the typical underground coal fire area in Sulabulak, Xinjiang, this study integrated laboratory simulation, multi-source remote sensing inversion, and in situ field monitoring. Thermogravimetric analysis, a high-temperature tube furnace, HSC thermodynamic simulation, and multi-source remote sensing data from Landsat-8/9 and Sentinel-1A were employed to investigate the gaseous products and heavy metal migration mechanisms at different combustion stages, and to delineate the spatial extent of different combustion states in the fire area. A coal loss model was then constructed by coupling experimentally determined carbon emission factors with remote sensing-derived areas and was compared with an emission flux model based on field measurements. The results show that the coal oxidation process proceeds through three distinct stages, with indicator gas ratios (CO₂/CO and C₂H₄/C₂H₆) serving as effective indicators for combustion state identification. Heavy metal partitioning is governed by elemental volatility and redox conditions: As and Se partition predominantly into the gas phase, while Zn becomes enriched in fly ash. Remote sensing time series analysis documents continuous fire expansion accompanied by progressive surface subsidence. By cross-validating the indirect coal loss model (constrained by remote sensing area) against the direct emission flux model (constrained by field measurements), we estimate the current annual GHG emission of the Sulabulak fire area at approximately 0.65 × 10⁴ t CO₂ equivalent. This study proposes a coupled “micro-experiment–macro-remote sensing–field measurement” approach for carbon emission accounting, providing reliable data support for environmental pollution control and the development of carbon inventories for coal fires in arid regions. Full article