Search Results (31,158)

In the Anthropocene, dryland ecosystems—natural and semi-natural ecosystems—are highly sensitive to anthropogenic warming, and their carbon cycling dynamics are easily disrupted by this trend. In this perspective, we propose a novel yet long-overlooked conceptual framework. It reveals that the oxygen footprint, defined as the atmospheric oxygen consumption-to-production ratio, could serve as an important diagnostic indicator for assessing the impacts of anthropogenic warming on dryland carbon cycling. This framework can be divided into three parts, including the increasing oxygen footprint, warming effects on dryland carbon cycling, and direct or indirect links between oxygen footprint and carbon-cycle responses. In short, it centers on the core logical chain: oxygen footprint-anthropogenic warming-dryland carbon cycling. This work strives to enhance dryland sustainability by filling essential knowledge gaps, combining separate research findings, and providing actionable field guidance for ecosystem management. Full article

Pathogenic fungi and their synergistic interactions with bark beetles, leading to vascular dysfunction, physiological stress, and eventual tree mortality, increasingly threaten forest ecosystems. Because fungal colonization often precedes visible macroscopic symptoms, early detection remains a critical yet challenging task in forest health monitoring. This study proposes a real-time deep learning-based object detection framework for identifying harmful fungi in proximity to host trees to support early intervention strategies. A custom dataset comprising 8900 images was constructed to represent two classes: Healthy and Unhealthy trees, where fungal presence is detected either directly on the tree or within its immediate ecological vicinity (e.g., near root systems). A fine-tuned YOLOv11 detection architecture is developed and augmented with a squeeze-and-excitation (SE)-like attention mechanism to enhance texture-sensitive feature representation. The model is trained and evaluated using precision, recall, F1-score and mean Average Precision (mAP). Experimental results demonstrate an overall mAP@0.5 of 0.825, with class-wise average precision values of 0.926 (Healthy) and 0.724 (Unhealthy). The Healthy class achieved classification accuracy of 0.92, while 0.71 of Unhealthy instances were correctly detected. F1-Confidence and recall-Confidence metrics indicate that optimal operational performance occurs within a confidence threshold range of 0.30–0.35, balancing false positives and false negatives. Despite the approximately balanced class distribution (50.6% Healthy and 49.4% Unhealthy), detection performance for the Unhealthy class was comparatively lower because of its greater intra-class variability, heterogeneous fungal appearance, and subtle visual manifestations. Findings demonstrate the feasibility of deploying real-time object detection models for early-stage fungal surveillance and highlight the importance of confidence calibration for operational disease monitoring systems. Full article

Rapid urbanization has significantly altered land use patterns in Deqing County, placing increasing pressure on its ecosystem. This study establishes a Driving Force–Pressure–State–Impact (DPSI) framework and selects ten indicators to evaluate ecological sensitivity for 2014, 2019, and 2024. It then couples this framework with the PLUS model to simulate land use and ecological sensitivity changes under the following three 2034 scenarios: natural development (ND), ecological protection (EP), and urban development (UD). Results show that ecological sensitivity exhibits a “high west, low east” spatial pattern and it fluctuated with an initial decline followed by a rise from 2014 to 2024, though the overall trend was a slow decrease. Land use type (weight 0.342), distance to rivers (weight 0.191), and distance to roads (weight 0.146) were the dominant influencing factors, together depicting Deqing’s ecological landscape of “western forests, eastern farmlands, and dense water networks”. The PLUS model demonstrated good validation accuracy (Kappa = 0.81), and the contributions of driving factors shifted over time. Multi-scenario simulation indicates that the ecological protection (EP) scenario is more suitable for sustainable urban development. We recommend implementing differentiated ecological control zones, integrating sensitivity evaluation into planning decisions, and improving the differentiated ecological compensation mechanism. Full article

Agricultural production is an important source of global carbon emissions, yet differences in system boundaries and emission factors among previous studies have limited comparisons across crops and regions. This study investigated the distribution, emission sources, and regional disparities of agricultural carbon emissions across 31 major crop-producing provinces in China, using a unified life cycle assessment (LCA) framework based on agricultural input, crop production, and agronomic data in 2024. Carbon emissions per unit area (CEA) and per unit yield (CEY) were quantified under consistent accounting boundaries, and the contributions of different emission sources together with their spatial characteristics were discussed. CEA generally showed higher values in the central and eastern regions of China and Xinjiang, but lower values in southwestern and northeastern China. Xinjiang contributed the highest total carbon emissions (about 1.6 × 10⁵ t), primarily because extensive cotton cultivation requires intensive irrigation, mechanized operations, and plastic-film mulching, leading to high emissions from fertilizer use, energy consumption, and agricultural film. Rice exhibited the highest carbon emissions (accounting for 30% of all 11 types of crops), followed by cotton and tobacco, while soybeans, rapeseed, and sugar beets had relatively low emission intensities. Fertilizer production and application were the dominant emission sources for most upland crops, while methane emissions from flooded paddy fields accounted for the largest share of rice carbon emissions. Spatial clustering analysis further indicated that high-emission regions were concentrated in central and eastern China, while northeastern China formed distinct low-emission clusters. This study provided a consistent assessment of carbon emissions from major crops across China, offering a reference basis for formulating emission reduction strategies for different crops and regions. Full article

Cold recycled mixtures with bitumen emulsion (CRME) serving in seasonally frozen regions are susceptible to mechanical deterioration under repeated freeze-thaw (F-T) cycles, which is primarily manifested as interfacial damage and crack propagation. However, the micro-mechanical processes associated with the transmission and dissipation of frost-heaving stresses induced by water-ice phase transition within the interfacial transition zone (ITZ) between reclaimed asphalt pavement (RAP) and asphalt mortar remain to be further characterized. In this study, a numerical simulation approach coupling frost heave effects with the phase transition of water-ice particles was developed based on X-ray computed tomography (CT) and the discrete element method (DEM), and the micro-mechanical parameters of the RAP-asphalt mortar ITZ were determined through laboratory experiments. Combined with acoustic emission (AE) monitoring, the damage evolution characteristics of cold recycled mixtures and the associated interfacial damage mechanisms under freeze-thaw action were systematically investigated. The results indicate that the optimal micro-parameters of the RAP-asphalt mortar ITZ can be taken as approximately 85% of those of virgin asphalt mortar. After 20 freeze-thaw cycles, the number of shear cracks and tensile cracks in ITZ on RAP surface reached 493 and 92, respectively, which were much higher than 11 and five on the surface of new aggregate. ITZ was the main control weak area of freeze-thaw damage. Compared with the unfrozen specimens, the minimum effective contact number of mortar decreased by 1.63%, 4.52% and 8.52% respectively after 5, 10 and 20 freeze-thaw cycles, and the total effective contact number decreased from 75,842 to 69,383. Freeze-thaw cycles significantly reduce the strain energy storage capacity of CRME: the maximum energy storage capacity of the adhesive spring decreased from 2.15 J in the non-freeze-thaw state to 1.28 J in 10 cycles (a decrease of 40.47%) and 1.16 J in 20 cycles (a decrease of 46.05%), and the damage mode changed from brittle fracture to interface-controlled energy dissipation. The proposed water-ice phase transition-based DEM framework provides a reliable numerical tool for investigating freeze-thaw damage mechanisms and supporting durability-oriented design of cold recycled pavement materials. Full article

Manual judgment in coal-slurry flotation suffers from dynamic hysteresis and sensitivity to illumination and dust. In contrast, froth images characterize macroscopic flotation appearances, while tailings ash content reflects the internal pulp quality, and the two sources provide complementary information. This paper proposes a flotation condition recognition method based on the fusion of froth images and tailings ash content data. Visualization via violin plots shows the high correlation between ash content and flotation states. In this framework, froth images are designated as primary inputs and ash content as auxiliary signals, with an optimal fusion-weight ratio determined through ablation experiments. Multimodal models based on ResNet18, MobileNetV2, and MobileNetV3 are compared, and image-only and tailings-ash-only models are used to assess the value of multimodal fusion. Experiments demonstrate that Multimodal MobileNetV3 achieves an accuracy of 94.65%, outperforming Multimodal MobileNetV2 at 87.98%, Multimodal ResNet18 at 86.13%, the image-only model at 86.43%, and the tailings-ash-only model at 81.63%. t-SNE visualization indicates that multimodal fusion enhances feature discrimination and clustering. This method effectively improves classification accuracy and provides a new approach for intelligent working condition recognition in coal preparation plants. Full article

Consensus molecular subtype 4 (CMS4) colorectal cancer (CRC) is associated with an aggressive clinical course and poor survival, yet the biological basis of heterogeneity within this subtype remains incompletely understood. DNA methylation is an epigenetic mechanism involved in transcriptional regulation, cellular differentiation, and colorectal tumorigenesis. Here, we integrated single-cell RNA sequencing (scRNA-seq), bulk data, and promoter DNA methylation data to characterize CMS4-associated cancer cell states and methylation-related features. Using the scAB algorithm, we integrated scRNA-seq with bulk CMS4 data and identified CMS4-related cells distributed across multiple patients. Single-cell analyses of cell–cell communication and transcriptional regulation revealed a CMS4-related cancer cell population characterized by macrophage migration inhibitory factor (MIF)-centered intercellular communication, enhanced caudal type homeobox 1 (CDX1) and Kruppel-like factor 5 (KLF5) regulon activity, and gene modules enriched in differentiation-related pathways. CytoTRACE analysis further stratified CMS4 cancer cells into poorly and well-differentiated states, yielding 802 differentially expressed genes (DEGs). Linking these differentiation-associated DEGs with bulk expression and promoter methylation data identified 218 methylation-associated DEGs showing significant inverse methylation expression correlations, suggesting a link between differentiation-related heterogeneity and promoter methylation. Univariable Cox regression followed by LASSO regression further prioritized eight genes for construction of the methylation and differentiation-related prognostic model (MeDiff-PM). MeDiff-PM consistently stratified overall survival in the TCGA CMS4 cohort and two independent validation cohorts, with cutoff-independent continuous Cox analyses further supporting its prognostic association across cohorts. And MeDiff-PM remained prognostically significant after adjustment for available clinical variables. High MeDiff-PM risk scores were associated with activation of P53, WNT, and ubiquitin-mediated proteolysis pathways and with consistent predicted drug response differences for compounds across three CMS4 cohorts. While individual in silico knockout analysis suggested links between MeDiff-PM genes and metallothionein-related and immune-associated transcriptional responses. Collectively, these findings indicate that methylation-associated differentiation features represent a molecular dimension of intra-CMS4 heterogeneity and provide a biologically informed framework for prognostic stratification within CMS4 CRC. Full article

Reliable cropland, forestland, and grassland maps support resource assessment and ecological management in arid and semi-arid Central Asia. Existing land-cover products often delineate these classes differently, vary in reliability across classes and locations, and may share the same errors even when they agree. This study formulates multi-product fusion as a pixel- and class-specific reliability decision problem. To address this problem, we propose a reliability-adaptive fusion framework, the Discrepancy-Aware Reliability-Adaptive Fusion Network (DRAFNet), using 2020 maps from three global 30 m land-cover products—FROM-GLC Plus, GLC-FCS30D, and GlobeLand30—and variables representing aridity, temperature, precipitation, elevation, and slope. Unlike fixed-weight fusion methods and segmentation models that use the source products only as input channels, DRAFNet retains the categorical source decisions and adjusts each contribution according to its estimated reliability for the assigned class and location. Weight removed from an unreliable source is transferred to a residual expert, which provides an alternative prediction when the source products are unreliable or share the same error. Voting entropy and geo-environmental variables provide contextual information for this decision. On independent test samples from the five Central Asian countries, DRAFNet achieved an overall accuracy (OA) of 0.8275, a Kappa coefficient of 0.7698, a mean intersection over union (mIoU) of 0.7046, and a macro-averaged F1 score (Macro F1) of 0.8241. These values were 0.95–1.38 percentage points higher than those of U-Net++, the strongest benchmark. Local comparisons indicated more coherent spatial patterns and clearer boundaries in areas of pronounced disagreement. The mean and median absolute log-ratio deviations from area statistics reported by the Food and Agriculture Organization of the United Nations (FAO) were 0.618 and 0.450, respectively, both lower than those of the source products. These results support land-resource assessment and ecological management in Central Asia. Full article

Obstructive Sleep Apnea Syndrome (OSAS) is associated with systemic inflammation and immune dysfunction, yet the specific metabolic alterations within immune cells remain poorly understood. In this exploratory study, we characterized the metabolome of peripheral mononuclear cells (PMNCs) from patients with OSAS and healthy controls to investigate potential immunometabolic signatures associated with the disease. Initial analyses identified 21 nominally differentially abundant metabolites between OSAS patients and controls, suggesting trends such as the depletion of carnitines and alterations in fatty acid and neurotransmitter metabolism. However, following correction for multiple testing (False Discovery Rate, FDR), only putatively annotated cis,cis-muconic acid remained statistically significant. Furthermore, pathway enrichment analysis highlighted exploratory trends primarily associated with SLC-mediated transmembrane transport and energy metabolism. Our findings indicate that while OSAS PMNCs exhibit metabolic shifts suggestive of cellular stress, most of these alterations represent nominal trends that require validation in larger cohorts. The robust identification of putatively annotated cis,cis-muconic acid highlights a potential target of interest. In this exploratory pilot study, given the absence of polysomnographic and objective hypoxia parameters in most participants, observed metabolic alterations are described as associated with, rather than directly caused by, intermittent hypoxia. Overall, this study provides a hypothesis-generating framework for future research on the immunometabolic consequences of OSAS. Full article

Background/Objectives: Respiratory syncytial virus (RSV) causes morbidity in older adults with cardiovascular disease, in whom infection may precipitate severe lower respiratory tract disease, hospitalization, functional decline, and cardiovascular destabilization. We evaluate the evidence for RSV vaccination in cardiovascular disease and propose a jurisdiction-adaptable framework for integrating vaccination into cardiovascular care. Methods: Observational studies, randomized trials, pragmatic and test-negative studies, prespecified cardiovascular analyses of DAN-RSV, and eligibility recommendations were narratively synthesized and translated into a pathway encompassing patient identification, eligibility and risk assessment, vaccine delivery and co-administration, documentation, and follow-up. Results: Acute cardiac events are frequent during RSV hospitalization, and cardiovascular risk may persist after infection. Randomized trials establish protection against RSV-associated lower respiratory tract disease and respiratory illness, while real-world studies support effectiveness against RSV-related hospitalization. DAN-RSV reduced all-cause cardiorespiratory hospitalization but did not demonstrate significant reductions in cardiovascular hospitalization, myocardial infarction, heart failure (HF) hospitalization, atrial fibrillation, stroke, cardiovascular death, or major adverse cardiovascular events; observational associations with lower post-vaccination cardiovascular-event rates remain hypothesis-generating. The framework prioritizes adults aged ≥ 75 years and those aged 50–74 years with high-risk cardiovascular conditions where consistent with national recommendations, embeds vaccination assessment across cardiology, HF, primary care, pharmacy, and long-term care, and incorporates co-administration, documentation, and outcome surveillance. Conclusions: The principal contribution is a pathway for moving RSV vaccination from recommendation to routine preventive care for adults with cardiovascular disease. It anchors implementation in established RSV and cardiorespiratory benefits while treating cardiovascular-event reduction as a research priority rather than a demonstrated indication. Full article

Synergistic pollution–carbon mitigation is critical for China’s dual carbon targets. Taking coal-resource Shanxi Province as the case, this study developed an integrated Long-range Energy Alternatives Planning (LEAP)–Community Multiscale Air Quality (CMAQ) coupled framework combined with a three-dimensional vector model to simulate energy consumption, CO₂, and major air pollutant emissions (CO₂, CO, SO₂, NO₂, PM_2.5, and PM₁₀) under Baseline and Policy scenarios (2026–2050). The core novelty of this study lies in methodological innovation: the multi-model linkage realizes full-chain energy-emission-atmosphere simulation, remedying the isolation flaw of single models in prior research. The results indicated that low-carbon levels would rise steadily in both scenarios from 2026 to 2050. The Policy scenario achieved superior long-term low-carbon performance compared with the Baseline scenario and narrowed gaps in underdeveloped social subsystems, despite short-term transition costs. This scenario optimized the overall energy structure yet failed to fully reduce emission loads from residential and transport sectors. It drastically cut carbon and pollutant emissions, optimized spatial emission patterns, and decoupled most air pollutants from carbon emissions. However, this scenario still had prominent limitations: phased delays in emission abatement, strong coupling of CO, NO₂ and carbon emissions, and rising residential carbon emissions. Further pollution–carbon synergy assessment revealed worsening multi-dimensional imbalances under the Baseline scenario. While the Policy scenario experienced temporary systemic imbalance, its long-term coordination level improved steadily. This finding verified that systematic, long-term low-carbon governance constituted the core driver of Shanxi’s green transition. Targeted phased, classified collaborative governance strategies were proposed to resolve structural transformation risks for resource-based regions. Full article

Hearing aid technology adaptation and user satisfaction are influenced by multiple interacting demographic, clinical, and behavioral factors, making reliable prediction of outcomes challenging with conventional statistical approaches alone. This study proposes an explainable machine learning framework to investigate the multidimensional determinants of hearing aid satisfaction by integrating demographic characteristics, hearing aid-related variables, and patient-reported outcomes obtained from the Hearing Aid Technology Adaptation and Satisfaction Scale (HATASS). Five regression algorithms—Linear Regression, Decision Tree Regression (DTR), Random Forest Regression (RFR), Support Vector Regression, and Gradient Boosting Regression (GBR)—were comparatively evaluated using a five-fold cross-validation strategy. Predictive performance was assessed using the root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination ($R^2$), while model interpretability was investigated through cross-validated out-of-bag permutation feature importance analysis. Among the evaluated algorithms, Random Forest Regression achieved the most consistent predictive performance, yielding the lowest average RMSE (14.225) and the highest average $R^2$ (0.146) under the adopted validation framework. Although the overall predictive performance remained modest, the explainability analysis consistently identified age as the most influential predictor, followed by onset year, education level, hearing aid usage duration, and daily hearing aid use. In contrast, gender, battery type, tinnitus, and vertigo contributed comparatively less to model predictions. These findings indicate that hearing aid adaptation and satisfaction arise from complex nonlinear interactions among demographic, behavioral, clinical, and device-related characteristics rather than isolated linear associations. The proposed framework provides an interpretable, internally validated analytical approach for investigating hearing aid technology adaptation and satisfaction and establishes a foundation for future studies that integrate comprehensive audiological measurements, longitudinal follow-up data, and independent external validation to support the development of more transparent and personalized hearing healthcare systems. Full article

Asphalt pavements undergo progressive mechanical changes during service life due to traffic loading, temperature variations, moisture and material ageing. Embedded strain sensors can support in-situ pavement performance monitoring, but their response is strongly affected by experimental variables that must be identified before reliable long-term ageing indicators can be established. This study establishes an in-situ baseline mechanical monitoring framework for asphalt pavements using embedded resistive strain transducers. KM-100HAS sensors were installed in an asphalt test section and evaluated through controlled field campaigns. A 17-point cross-pattern loading procedure was used to validate sensor location and orientation after construction. Load-free monitoring windows were analysed to estimate strain–temperature sensitivity and assess thermal correction of static loading–recovery tests. The results showed that loading position strongly conditions the measured strain response. Passive monitoring indicated that strain–temperature sensitivity depends on both temperature level and sensor location. In the mechanical tests, normalization of the recovery branch and logarithmic fitting over the first 200 s provided a consistent recovery-shape descriptor. The resulting slope, $b_{\mathrm{l}\mathrm{o}\mathrm{g}200}$, showed a strong linear relationship with the recovery percentage after 10 min (R² = 0.855). The proposed workflow provides a standardized baseline protocol for asphalt pavement monitoring and its mechanical evolution. Full article

The Greater Mekong Subregion (GMS) has emerged as a strategic logistics hub due to rapid economic integration and the expansion of cross-border road transportation. However, international road logistics networks in the region must address several competing objectives, including minimizing transportation costs, reducing delivery times, and balancing transport distances among trading partners. To overcome these challenges, this study proposes an innovative hybrid computational framework that integrates the classical Transportation Problem with the Pythagorean methodology (TPPM). The proposed approach consolidates multiple transportation objectives into a unified performance metric based on the Pythagorean concept, thereby enabling simultaneous optimization under practical constraints. In addition, geographic inputs derived from Google Maps and Google Earth via web platforms, which are reliable open-source GIS tools, are incorporated into the transportation model to improve spatial accuracy. A simulated dataset comprising 35 suppliers and 42 customers, representing major logistics nodes in the GMS, is developed to evaluate the proposed method. The computational results indicate that the TPPM approach outperforms the conventional single-objective Classical Transportation Problem (CTP) by producing higher solution quality and more balanced performance. Overall, the findings demonstrate that the proposed hybrid method is a robust decision-support tool for sustainably enhancing the resilience of international logistics planning in emerging economic regions. Full article

QR codes are widely used in digital authentication, mobile payment, access control, and information exchange, making QR code-based covert communication and hidden message delivery relevant to cybersecurity applications. This study proposes a QR code-based information-hiding method via module content modification based on corner-pixel grayscale adjustment. Secret bits are embedded into a QR code image through subtle grayscale adjustments of module corner pixels. To reduce visually noticeable embedding artifacts, embedding in adjacent module corners that share identical original grayscale values is prohibited, thereby preventing noticeable local contrast that could reveal hidden content. Gradient-based smoothing is further applied to suppress contrast artifacts within module interiors after embedding. A theoretical analysis of bilinear interpolation and quarter subregion averages is presented to justify the proposed extraction thresholds. Experiments across multiple QR code versions, error-correction levels, and embedding parameters show that the proposed method achieves an average embedding rate of approximately 1.9 bits per module while generally maintaining QR code readability across the tested commercial scanning devices. Exploratory random-noise experiments further show that hidden-message recovery remains possible up to the observed highest tolerable noise rates in the tested realizations. A comparison with four representative methods indicates that the proposed method achieves substantially higher embedding rates under the adopted comparison framework, demonstrating its potential for high-capacity QR code information-hiding while enabling successful hidden-message recovery under the evaluated conditions. Full article