Search Results (567)

In the context of worsening climate change and biodiversity loss, forest carbon offset projects are viewed as important nature-based solutions to mitigate these trends. However, there is limited evidence on whether these projects provide net benefits for biodiversity conservation. This study uses a staggered difference-in-differences model with balanced panel data from 128 counties in Sichuan Province, China, spanning from 2000 to 2020, to examine whether these projects bring biodiversity conservation co-benefits. The results show that the implementation of forest carbon offset projects leads to a 55.1% decrease in the ecosystem service value of forest biodiversity, with the negative impact particularly pronounced in areas facing agricultural land use and livestock pressures. The dynamic effect tests indicate that the benefits of biodiversity conservation generally begin to decline significantly 5 years after project implementation. Additional analyses show that although projects certified under biodiversity conservation standards also exhibit negative effects, the magnitude of decline is substantially smaller compared to uncertified projects, and certified projects achieve greater carbon stock gains. Heterogeneity analysis demonstrates that projects employing native tree species show significant positive effects. Moreover, spatial econometric results demonstrate significant negative spillover effects within an 80 km radius surrounding the project sites, with the effect attenuating over distance. To maximize the potential of forest carbon offset projects in addressing both climate change and biodiversity loss, it is important to mitigate the negative impacts on biodiversity within and beyond project boundaries and to enhance the continuous monitoring of projects that have been certified for biodiversity conservation. Full article

Variations in damper configuration strategies have a direct impact on the seismic damage patterns of long-span deck-type concrete-filled steel tube (CFST) arch bridges. This study developed an analysis and evaluation framework to identify the damage category, state, and progression sequence of structural components. The framework aims to investigate the influence of viscous dampers on the seismic response and damage patterns of long-span deck-type CFST arch bridges under near-fault pulse-like ground motions. The effects of different viscous damper configuration strategies and design parameters on seismic responses of long-span deck-type CFST arch bridges were systematically investigated, and the preferred configuration and parameter set were identified. The influence of preferred viscous damper configurations on seismic damage patterns of long-span deck-type CFST arch bridges was systematically analyzed through the established analysis and evaluation frameworks. The results indicate that a relatively optimal reduction in bridge response can be achieved when viscous dampers are simultaneously installed at both the abutments and the approach piers. Minimum seismic responses were attained at a damping exponent α = 0.2 and damping coefficient C = 6000 kN/(m/s), demonstrating stability in mitigating vibration effects on arch rings and bearings. In the absence of damper implementation, the lower chord arch foot section is most likely to experience in-plane bending failure. The piers, influenced by the coupling effect between the spandrel construction and the main arch ring, are more susceptible to damage as their height decreases. Additionally, the end bearings are more prone to failure compared to the central-span bearings. Implementation of the preferred damper configuration strategy maintains essentially consistent sequences in seismic-induced damage patterns of the bridge, but the peak ground motion intensity causing damage to the main arch and spandrel structure is significantly increased. This strategy enhances the damage-initiation peak ground acceleration (PGA) for critical sections of the main arch, while concurrently reducing transverse and longitudinal bending moments in pier column sections. The proposed integrated analysis and evaluation framework has been validated for its applicability in capturing the seismic damage patterns of long-span deck-type CFST arch bridges. Full article

In order to study the problem of obvious wall thinning in the wellbore caused by proppant backflow and sand production under throttling conditions in tight gas wells. Based on the gas-phase control equation, particle motion equation, and erosion model, the wellbore erosion model is established. The distribution law of pressure, temperature, and velocity trace fields under throttling conditions is analyzed, and the influences of different throttling pressures, particle diameters, and particle mass flows on wellbore erosion are analyzed. The flow field at the nozzle changes drastically, and there is an obvious pressure drop, temperature drop, and velocity rise. When the surrounding gas is completely mixed, the physical quantity gradually stabilizes. The erosion shape of the wellbore outlet wall has a point-like distribution. The closer to the throttle valve outlet, the more intense the erosion point distribution is. Increasing the inlet pressure and particle mass flow rate will increase the maximum erosion rate, and increasing the particle diameter will reduce the maximum erosion rate. The particle mass flow rate has the greatest impact on the maximum erosion rate, followed by the particle diameter. The erosion trend was predicted using multiple regression model fitting of the linear interaction term. The research results can provide a reference for the application of downhole throttling technology and wellbore integrity in tight gas exploitation. Full article

Viticis Fructus (VF), a fruit known for its unique flavor profile and various health benefits, demonstrates substantial quality variations depending on its area of production. Traditional methods of production area verification based on internal compound analysis are hampered by a number of technical limitations. This investigation systematically characterized the cuticular wax composition of VF sample from a diverse variety of production areas. Quantitative analyses were conducted to evaluate the spatial distribution patterns of the wax constituents. Significant regional variations were observed: Anhui sample exhibited the highest total wax content (21.39 μg/cm²), with n-alkanes dominating at 76.67%. High-latitude regions showed elevated triterpenoid acid levels, with maslinic acid (0.53 μg/cm²) and ursolic acid (0.34 μg/cm²) concentrations exceeding those of their low-latitude counterparts by four- and three-fold, respectively. Altitudinal influence manifested in long-chain alcohol accumulation, as triacontanol reached 0.87 μg/cm² in high-altitude sample. Five key biomarkers demonstrated direct quality correlations: eicosanoic acid, n-triacontane, dotriacontanol, β-amyrin, and α-amyrin. This study established three novel origin identification protocols: single-component quantification, multi-component wax profiling, and wax ratio analysis. This work not only reveals the latitudinal dependence of VF wax composition, but also provides a scientific framework for geographical authentication. Our findings advance wax-based quality evaluation methodologies for fruit products, offering practical solutions for production area verification challenges in food raw materials. Full article

As semiconductor devices demand higher input–output density and faster signal transmission, fan-out panel-level packaging has emerged as a promising solution for next-generation electronic systems. However, the hygroscopic nature of epoxy molding compounds raises critical reliability concerns under high-temperature and high-humidity conditions. This study investigates the hygrothermal stress of a single fan-out panel-level package unit through experimental characterization and numerical simulation. Thermal–mechanical analysis was conducted at 100 °C and 260 °C to evaluate the strain behavior of two commercial epoxy molding compounds in granule form after moisture saturation. The coefficient of moisture expansion was calculated by correlating strain variation with moisture uptake obtained under 85 °C and 85% relative humidity, corresponding to moisture sensitivity level 1 conditions. These values were directly considered into a moisture -thermal coupled finite element analysis. The simulation results under reflow conditions demonstrate accurate principal stress and failure location predictions, with stress concentrations primarily observed at the die corners. The results confirm that thermal effects influence stress development more than moisture effects. Finally, a structural sensitivity analysis of the single-package configuration showed that optimizing the thickness of the dies and epoxy molding compound can reduce maximum principal stress by up to 12.4%, providing design insights for improving package-level reliability. Full article

This paper proposes a lightweight gaze-tracking architecture named GhostBlock-Augmented Look to Coordinate Space (L2CS), which integrates GhostNet-based modules and depthwise separable convolution to achieve a better trade-off between model accuracy and computational efficiency. Conventional lightweight gaze-tracking models often suffer from degraded accuracy due to aggressive parameter reduction. To address this issue, we introduce GhostBlocks, a custom-designed convolutional unit that combines intrinsic feature generation with ghost feature recomposition through depthwise operations. Our method enhances the original L2CS architecture by replacing each ResNet block with GhostBlocks, thereby significantly reducing the number of parameters and floating-point operations. The experimental results on the Gaze360 dataset demonstrate that the proposed model reduces FLOPs from 16.527 × 10⁸ to 8.610 × 10⁸ and parameter count from 2.387 × 10⁵ to 1.224 × 10⁵ while maintaining comparable gaze estimation accuracy, with MAE increasing only slightly from 10.70° to 10.87°. This work highlights the potential of GhostNet-augmented designs for real-time gaze tracking on edge devices, providing a practical solution for deployment in resource-constrained environments. Full article

The velocity distribution at the deflector jet outlet significantly influences the pressure characteristics of the pilot stage, thereby affecting the dynamic performance of the servo valve. Conventional mathematical models fail to account for the influence of dynamic velocity distribution on pilot stage pressure characteristics, resulting in significant deviations from actual situations. As the deflector shifts, the secondary jet velocity distribution transitions from a symmetric to an asymmetric dynamic profile, altering the pressure within the receiving chambers. To address this, a dynamic skewed velocity distribution model is proposed to more accurately capture the pressure characteristics. The relationship between the skewness coefficient and deflector displacement is established, and the pressure calculation method for the receiving chambers is refined accordingly. A comparative analysis shows that the proposed model aligns most closely with computational fluid dynamics results, achieving a 98% match in velocity distribution and a maximum pressure error of 1.43%. This represents an improvement of 84.98% over the normal model and 82.35% over the uniform model, confirming the superior accuracy of the dynamic skewed model in pilot stage pressure calculation. Full article

Clear cell renal cell carcinoma (ccRCC), the most common RCC subtype, displays significant intratumoral heterogeneity driven by metabolic reprogramming, which complicates our understanding of disease progression and limits treatment efficacy. This study aimed to construct a comprehensive cellular and transcriptional landscape of ccRCC, with emphasis on gene expression dynamics during malignant progression. An integrated analysis of 90 scRNA-seq samples comprising 534,227 cells revealed a progressive downregulation of sodium ion transport-related genes, particularly CHP1 (calcineurin B homologous protein isoform 1), which is predominantly expressed in epithelial cells. Reduced CHP1 expression was confirmed at both mRNA and protein levels using bulk RNA-seq, CPTAC proteomics, immunohistochemistry, and ccRCC cell lines. Survival analysis showed that high CHP1 expression correlated with improved prognosis. Functional analyses, including pseudotime trajectory, Mfuzz clustering, and cell–cell communication modeling, indicated that CHP1⁺ epithelial cells engage in immune interaction via PPIA–BSG signaling. Transcriptomic profiling and molecular docking suggested that CHP1 modulates amino acid transport through SLC38A1. ZNF460 was identified as a potential transcription factor of CHP1. Virtual screening identified arbutin and imatinib mesylate as candidate CHP1-targeting compounds. These findings establish CHP1 downregulation as a novel molecular feature of ccRCC progression and support its utility as a prognostic biomarker. Full article

The increasing deployment of photovoltaic and energy storage systems (ESSs) in modern power grids has highlighted the critical challenge of component degradation, which significantly impacts system efficiency, operational costs, and long-term reliability. Conventional energy dispatch and optimization approaches fail to adequately mitigate the progressive efficiency loss in PV modules and battery storage, leading to suboptimal performance and reduced system longevity. To address these challenges, this paper proposes a quantum-enhanced degradation pathway optimization framework that dynamically adjusts operational strategies to extend the lifespan of PV storage systems while maintaining high efficiency. By leveraging quantum-assisted Monte Carlo simulations and hybrid quantum–classical optimization, the proposed model evaluates degradation pathways in real time and proactively optimizes energy dispatch to minimize efficiency losses due to aging effects. The framework integrates a quantum-inspired predictive maintenance algorithm, which utilizes probabilistic modeling to forecast degradation states and dynamically adjust charge–discharge cycles in storage systems. Unlike conventional optimization methods, which struggle with the complexity and stochastic nature of degradation mechanisms, the proposed approach capitalizes on quantum parallelism to assess multiple degradation scenarios simultaneously, significantly enhancing computational efficiency. A three-layer hierarchical optimization structure is introduced, ensuring real-time degradation risk assessment, periodic dispatch optimization, and long-term predictive adjustments based on PV and battery aging trends. The framework is tested on a 5 MW PV array coupled with a 2.5 MWh lithium-ion battery system, with real-world degradation models applied to reflect light-induced PV degradation (0.7% annual efficiency loss) and battery state-of-health deterioration (1.2% per 100 cycles). A hybrid quantum–classical computing environment, utilizing D-Wave’s Advantage quantum annealer alongside a classical reinforcement learning-based optimization engine, enables large-scale scenario evaluation and real-time operational adjustments. The simulation results demonstrate that the quantum-enhanced degradation optimization framework significantly reduces efficiency losses, extending the PV module’s lifespan by approximately 2.5 years and reducing battery-degradation-induced wear by 25% compared to conventional methods. The quantum-assisted predictive maintenance model ensures optimal dispatch strategies that balance energy demand with system longevity, preventing excessive degradation while maintaining grid reliability. The findings establish a novel paradigm in degradation-aware energy optimization, showcasing the potential of quantum computing in enhancing the sustainability and resilience of PV storage systems. This research paves the way for the broader integration of quantum-based decision-making in renewable energy infrastructure, enabling scalable, high-performance optimization for future energy systems. Full article

Fruit yield and quality improvement are challenges for researchers and farmers. This study reveals that the main fruit traits of blueberry (Vaccinium ashei ‘Bluegem’) were significantly improved after hydrogen (H₂)-based irrigation, assessed by the increased single fruit weight (14.59 ± 6.66%) and fruit equatorial diameter (4.19 ± 2.39%), decreased titratable acidity, increased solid–acid and sugar–acid ratios. The enhancement of fruit quality was confirmed by the increased total volatiles, vitamin C contents, and antioxidant capacity. Using weighted protein co-expression network analysis (WPCNA), proteomic interrogation revealed that serine carboxypeptidase-like proteins I/II (SCPLI/II), ADP ribosylation factor 1/2 (ARF1/2), and UDP-glucosyltransferase 85A (UGT85A) might be functionally associated with the increased fruit weight and size driven by H₂. Reduced organic acid accumulation was caused by the regulation of the specific enzymes involved in sucrose metabolism (e.g., α-amylase, endoglucanase, β-glucosidase, etc.). H₂ regulation of fatty acid degradation (e.g., acyl CoA oxidase 1 (ACX1), acetyl CoA acyltransferase 1 (ACAA1), etc.) and phenylpropanoid metabolism were used to explain the improved fruit aroma and anthocyanin accumulation. Meanwhile, the upregulated heat shock protein 20/70 matched with the enhanced antioxidant activity. Together, this study provides a novel approach for yield and quality improvement in horticultural crops. Full article

Optimal dietary calcium (Ca) and phosphorus (P) requirements remain undetermined for Ningxiang pigs, a valuable indigenous Chinese breed. This study conducted a continuous feeding trial with two growth phases (grower: 30–50 kg; finisher: 50–80 kg) using fixed Ca/P ratios to systematically evaluate the effects of Ca/P levels on growth performance and mineral metabolism. A total of 180 pigs per phase were allocated to four Ca/P levels. During the grower phase, a dietary regimen of 0.83% Ca/0.67% P significantly increased the average daily feed intake (ADFI), average daily gain (ADG), and apparent total tract digestibility (ATTD) of energy and P. In the finisher phase, 0.60/0.48% Ca/P showed optimal growth performance, upregulated jejunal mineral transporters (CaSR and SLC34A2), enhanced bone mineralization (metatarsal ash content), and improved intestinal morphology (duodenal and jejunal villus height, jejunal villus surface area). This regimen also selectively enriched Peptostreptococcaceae abundance, indicating improved host–microbe interactions. Based on these findings, stage-specific nutritional strategies were recommended: 0.83% Ca/0.67% P during the grower phase and 0.60% Ca/0.48% P during the finisher phase. These protocols synergistically improve microbial ecology, intestinal function, and bone metabolism, thereby maximizing the growth potential of Ningxiang pigs. Full article

Developing early-heading wheat cultivars is an important breeding strategy to utilize light and heat resources, facilitate multiple-cropping systems, and enhance annual grain yield. Psathyrostachys huashanica Keng (2n = 2x = 14, NsNs) possesses numerous agronomically beneficial traits for wheat improvement, such as early maturity and resistance to biotic and abiotic stresses. In this study, we found that a cytogenetically stable wheat–P. huashanica 7Ns disomic addition line showed (9–11 days) earlier heading and (8–10 days) earlier maturation than its wheat parents. Morphological observations of spike differentiation revealed that the 7Ns disomic addition line developed distinctly faster than its wheat parents from the double ridge stage. To explore the potential molecular mechanisms underlying the early heading, we performed transcriptome analysis at four different developmental stages of the 7Ns disomic addition line and its wheat parents. A total of 10,043 differentially expressed genes (DEGs) were identified during spike development. Gene Ontology (GO) enrichment analysis showed that these DEGs were linked to the carbohydrate metabolic process, photosynthesis, response to abscisic acid, and the ethylene-activated signaling pathway. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these DEGs were involved in plant hormone signal transduction (ARF, AUX/IAA, SAUR, DELLA, BRI1, and ETR), starch and sucrose metabolism (SUS1 and TPP), photosynthetic antenna proteins (Lhc), and circadian rhythm (PRR37, FT, Hd3a, COL, and CDF) pathways. In addition, several DEGs annotated as transcription factors (TFs), such as bHLH, bZIP, MADS-box, MYB, NAC, SBP, WRKY, and NF-Y, may be related to flowering time. Our findings reveal spike development-specific gene expression and critical regulatory pathways associated with early heading in the wheat–P. huashanica 7Ns addition line, and provide a new genetic resource for further dissection of the molecular mechanisms underlying the heading date in wheat. Full article

Hyperspectral image cross-scene classification (HSICC) tasks are confronted with tremendous challenges due to spectral shift phenomena across scenes and the tough work of obtaining labels. Unsupervised domain adaptation has proven its effectiveness in tackling this issue, but it has a fatal limitation of intending to narrow the disparity between source and target domains by utilizing fully labeled source data and unlabeled target data. However, it is costly even to attain labels from source domains in many cases, rendering sufficient labeling as used in prior work impractical. In this work, we investigate an extreme and realistic scenario where unsupervised domain adaptation methods encounter sparsely labeled source data when handling HSICC tasks, namely, few-shot unsupervised domain adaptation. We propose an end-to-end refined bi-directional prototypical contrastive learning (RBPCL) framework for overcoming the HSICC problem with only a few labeled samples in the source domain. RBPCL captures category-level semantic features of hyperspectral data and performs feature alignment through in-domain refined prototypical self-supervised learning and bi-directional cross-domain prototypical contrastive learning, respectively. Furthermore, our framework introduces the class-balanced multicentric dynamic prototype strategy to generate more robust and representative prototypes. To facilitate prototype contrastive learning, we employ a Siamese-style distance metric loss function to aggregate intra-class features while increasing the discrepancy of inter-class features. Finally, extensive experiments and ablation analysis implemented on two public cross-scene data pairs and three pairs of self-collected ultralow-altitude hyperspectral datasets under different illumination conditions verify the effectiveness of our method, which will further enhance the practicality of hyperspectral intelligent sensing technology. Full article

Objectives: To investigate the relationship between serum magnesium levels, prescribed oral magnesium replacement, and major adverse cardiovascular events (MACE) in type-2 diabetes mellitus (T2D). Research design and methods: This nationwide retrospective study analyzed 1,284,940 US Veterans (≥18 years) with T2D who had outpatient serum magnesium testing between 1999–2021 in the Veterans Health Administration. The relationship between serum magnesium levels and MACE (hospitalizations for acute myocardial infarction, heart failure, ischemic stroke, or all-cause mortality) was determined using multivariable-adjusted Cox-regression models. Using a new-user-design and propensity-score-matching approach, we further related the use of prescribed oral magnesium and MACE among patients with hypomagnesemia (serum magnesium <1.8 mg/dL) and normomagnesemia (serum magnesium 1.8–2.3 mg/dL). Results: Of 1,284,940 patients with T2D, 229,210 (17.8%) patients had hypomagnesemia, and 117,674 (9.2%) patients had hypermagnesemia (serum magnesium >2.3 mg/dL). Compared to patients with normomagnesemia (serum magnesium 1.8–2.3 mg/dL), those with either hypomagnesemia or hypermagnesemia had elevated hazards for MACE. The risk increased with the severity of serum magnesium abnormalities in both directions—low (hazard ratios [HRs] 1.11–1.20) and high (HRs 1.04–1.39)—in a parabolic pattern. Oral magnesium was prescribed to 9.7% and 0.7% of patients with hypomagnesemia and normomagnesemia, respectively. After propensity-score-matching balanced across 64 baseline characteristics, oral magnesium was associated with a lower MACE risk in 40,766 matched patients with hypomagnesemia (HR 0.89; 95% confidence interval [CI], 0.84–0.93), especially those on proton-pump-inhibitors or thiazides. Oral magnesium was not related to MACE in 11,838 matched patients with normomagnesemia (HR 1.07; 95% CI, 0.97–1.17). Conclusions: In patients with T2D, both hypomagnesemia and hypermagnesemia were associated with higher one-year MACE risks compared to normomagnesemia. Prescribed oral magnesium was associated with a reduced MACE risk in hypomagnesemia but not in normomagnesemia. Full article

In gas transmission stations, flame arrestors are typically installed in pipelines and venting systems to prevent the flames resulting from accidental ignition or deflagration of combustible gases during transmission from propagating through the pipelines. During actual operation, the presence of solid particulates in the gas compromises the flame-arresting efficacy and increases the failure rate of current pipeline flame arrestors. This study employs an integrated approach combining theoretical analysis and numerical simulation to establish a numerical model for flame arrestors that accounts for solid particle deposition effects. The model reveals the distribution characteristics of velocity fields, pressure fields, gas phase volumetric concentration fields, and solid deposition rate fields within pipeline flame arrestors. It systematically investigates the influence mechanisms of porosity, flame arrestor core thickness, inlet flame velocity, arrestor length, particle size, particle concentration on pressure drop, flame arrestment velocity, and deposition rate. These findings provide theoretical support for optimizing flame arrestor structural design and reducing operational failure rates. Full article