Search Results (17,698)

The genus Paphiopedilum (Orchidaceae) has high ornamental value due to its long flowering period, brilliant flower color, and peculiar floral morphology. Guangxi is the center of ecological diversity of Paphiopedilum, and therefore it is urgent to conduct rescue studies on the genetic resources and genetic structure of this genus in Guangxi. In this study, the genetic diversity of 39 populations from eight Paphiopedilum species in Guangxi was analyzed using ten selected EST-SSR primer pairs and fluorescent PCR amplification. The results show that genetic diversity varied among species, with large differences in expected heterozygosity (He). The highest genetic diversity was observed in P. barbigerum (I = 0.923; He = 0.480), while P. dianthum (I = 0.179; He = 0.098) showed the lowest diversity. From the genus perspective, molecular variance analysis (AMOVA) revealed that 57% of the genetic variation occurred among populations and 43% within populations, with inter-population variation being the main source of genetic variation. From a species perspective, genetic differentiation varied, with inter-individual differentiation ranging from 79% to 95%. The percentage of molecular variance indicated that genetic variation mainly occurred among individuals, which was the main source of total variation. According to the principle of maximum likelihood, the optimal K value was determined to be 6, and 760 Paphiopedilum samples were divided into six subgroups. The results of this study not only identify priority populations for conservation and establish a germplasm repository to preserve existing resources, but also provide references for research on asexual reproduction, seed propagation, and hybrid breeding of Paphiopedilum, thereby promoting the conservation and sustainable utilization of Paphiopedilum germplasm resources. Full article

Heart failure with preserved ejection fraction (HFpEF) is a multifactorial cardiovascular disorder characterized by diastolic dysfunction, systemic inflammation, and myocardial fibrosis. Emerging evidence indicates that macrophage polarization imbalance plays a central role in HFpEF pathogenesis. Traditional Chinese medicine (TCM) has demonstrated therapeutic potential in modulating macrophage activity through pathways such as NO/cGMP/PKG, TGF-β/Smads, and PI3K/Akt, thereby exerting anti-inflammatory, antifibrotic, and antioxidant effects. In this review, we conducted a literature search in PubMed, Google Scholar, Web of Science, and CNKI for studies published up to May 2025, using the terms “HFpEF”, “Traditional Chinese Medicine”, and “macrophage”. A total of 19 relevant studies were included. We highlight representative TCM metabolites and TCM formulas, such as resveratrol, Qishen Yiqi Pill, Shenfu Injection, etc. And we summarize their mechanisms in regulating M1/M2 macrophage polarization. Finally, we identify current challenges, including limited HFpEF-specific models and insufficient mechanistic validation, and propose directions for future research. Full article

To reduce welding deformation during the automated welding of thick-walled pipes in shipbuilding and thereby improve welding quality, a segmented multi-layer multi-pass welding sequence optimization and process improvement strategy is proposed. Firstly, based on a welding model for thick-walled pipes, a multi-layer multi-pass welding trajectory equation is established. A double-ellipsoidal moving heat source is adopted to design a circular multi-layer multi-pass double-ellipsoidal heat source model. Secondly, three circular pipe workpieces with different wall thicknesses are selected, and four segmented welding sequences are simulated using welding finite element analysis (FEA). Finally, based on the optimal segmented welding sequence, the welding process is improved, and optimal welding process parameters are determined based on deformation and residual stress analysis. The results of the segmented multi-layer multi-pass welding sequence optimization show that the skip-symmetric welding method yields the best results for thick-walled circular pipes. Compared to other welding sequences, it reduces welding deformation by an average of 6.50% and welding stress by an average of 5.37%. In addition, process improvement tests under the optimal welding sequence indicate that the best welding quality is achieved under the following conditions: for 10 mm thick pipes—200 A current, 24 V voltage, and 11.5 mm/s welding speed; for 15 mm thick pipes—215 A, 24.6 V, and 10 mm/s; and for 20 mm thick pipes—225 A, 25 V, and 11 mm/s. Full article

Background/Objectives: The prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is significantly affected by inflammatory state and immune dysregulation. The systemic inflammatory response index (SIRI), which reflects neutrophil, monocyte, and lymphocyte dynamics, has emerged as a potential marker of immune-inflammatory status. However, its role in predicting HBV-ACLF outcomes remains unclear. This research aims to elucidate the prognostic value of SIRI and its dynamic changes combined with disease severity scores in predicting the outcomes of HBV-ACLF. Methods: The study included HBV-ACLF patients enrolled in a multicenter clinical study between July 2019 and April 2024. Based on 90-day outcomes, the participants were categorized into survival and death groups. Clinical data and SIRI values were collected on days 0 (baseline), 3, 7, and 14. Independent prognostic factors were identified using Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. The predictive value of dynamic SIRI changes combined with disease severity scores was evaluated using receiver operating characteristic (ROC) curves. Results: A total of 153 patients with HBV-ACLF were analyzed, including 104 in the survival group and 49 in the death group. SIRI values were significantly lower in the survival group than in the death group across all time points. Multivariate Cox regression analysis identified that an increased ΔSIRI at day 3 (ΔSIRI3), a higher MELD score, and a lower albumin level were independently associated with increased 90-day mortality. The combination of SIRI on day three (SIRI3) and MELD-Na score on day three (MELD-Na3) demonstrated the highest predictive performance, with an AUC of 0.817 (95% CI: 0.750–0.883). Conclusions: The combination of the SIRI and MELD-Na score on day three provides a strong predictive value for the short-term prognosis of HBV-ACLF, highlighting its potential utility in early prognostic evaluation. Full article

Twin pregnancies have a higher risk of preterm birth (PTB) than single pregnancies, but studies about prenatal air pollution exposure and PTB in twin pregnancies are still scarce. To explore associations of prenatal fine particulate matter (PM_2.5) exposure with PTB in twins, we collected birth data from 21 hospitals across China. Data on PM_2.5 and its compositions (NO₃⁻, BC, NH₄⁺, SO₄²⁻, and OM) were collected from Tracking Air Pollution. Generalized linear models were used to examine associations of air pollution with PTB. Each IQR increment in PM_2.5, NH₄⁺, SO₄²⁻, NO₃⁻, BC, and OM during entire pregnancy, the OR (95% CI) were 1.46 (1.34–1.59), 1.54 (1.39–1.70), 1.34 (1.25–1.44), 1.44 (1.30–1.59), 1.28 (1.20–1.37), and 1.28 (1.18–1.38), respectively. The results of trimester-specific analyses followed the patterns as seen during the entire pregnancy (all p < 0.05). The PAF of PTB attributable to PM_2.5 was 40.75% (95% CI: 32.5%, 48.26%) in the total population. Participants living in warmer regions and lower residential greenness were more susceptible to PM_2.5. Our findings suggest pregnant women should avoid severe air pollution exposure throughout pregnancy. Reducing heat exposure and increasing green spaces in communities can reduce PTB risk. Full article

In complicated scenarios, due to the low precision of float solutions and poor reliability of fixed solutions, it is challenging to achieve a balance between accuracy and reliability of the integer least squares (ILS) estimation. To address this dilemma, the best integer equivariant (BIE) estimation, which makes a weighted sum of all possible candidates, has recently been attached great importance. The BIE solution approaches the float solution at a low ILS success rate, maintaining positioning reliability. As the success rate increases, it converges to the fixed solution, facilitating high-precision positioning. Furthermore, the posterior variance of BIE estimation provides the capability of reliability evaluation. However, in environments with a limited number or a deficient configuration of available satellites, there is a sharp decline in the strength of the GNSS precise positioning model. In this case, the exactness of weight allocation for integer candidates in BIE estimation will be severely compromised by unmodeled errors. When the ambiguity is incorrectly fixed, the wrongly determined optimal candidate is probably assigned an excessively high weight. Therefore, the BIE solution in a weak GNSS model always exhibits a significant positioning error consistent with the fixed solution. Moreover, the posterior variance of BIE estimation approximately resembles that of a fixed solution, losing error warning ability. Consequently, the BIE estimation may exhibit lower reliability compared to the ILS estimation employing a validation test with a loose acceptance threshold. To improve the positioning performance in weak GNSS models, a BIE ambiguity resolution (AR) method based on Tikhonov regularization is proposed in this paper. The method introduces Tikhonov regularization into the least squares (LS) estimation and the ILS ambiguity search, mitigating the serious impact of unmodeled errors on the BIE estimation under weak observation conditions. Meanwhile, the regularization factors are appropriately selected by utilizing an optimized approach established on the L-curve method. Simulation experiments and field tests have demonstrated that the method can significantly enhance the positioning accuracy and reliability in weak GNSS models. Compared to the traditional BIE estimation, the proposed method achieved accuracy improvements of 73.6% and 69.3% in the field tests with 10 km and 18 km baselines, respectively. Full article

This study investigates the aroma differences among various peach and nectarine varieties by sensory evaluation, electronic nose (E-nose) analysis, and metabolomics. Peach is a significant fruit crop in China, and identifying unique fragrances is essential for germplasm selection and cultivar improvement. Six peach and nectarine varieties were collected from the National Peach Germplasm Repository in Nanjing, China. Sensory evaluation revealed significant differences in aroma and taste, with ”Zi Jin Hong 3” and “Bai Mi Pan Tao” showing high scores for aroma, sweetness, and overall sensory quality, while “Tachibanawase” had the lowest overall impression score. E-nose analysis showed distinct response values among varieties, with sensors W1S, W1W, and W5S exhibiting the highest sensitivity. GC-MS identified 446 metabolites, including esters and terpenes. PCA and OPLS-DA differentiated metabolite profiles among varieties, revealing significant differences in metabolite expression. The integration of these techniques provides a comprehensive understanding of aroma differences, highlighting the potential for identifying unique germplasms for breeding high-quality cultivars with charming flavor, and offering a theoretical foundation for raw material selection and process optimization in the deep-processing industry of peach fruits in future research. Full article

Within the framework of a dynamic memory-event-triggered mechanism (DMETM), this paper proposes an estimate-based secure control algorithm for nonlinear networked control systems (NNCSs) that suffer from hybrid attacks. Firstly, a sampled-data observer is employed utilizing the output signals to estimate the states. Secondly, due to the limitation of data transmission capacity in NNCSs, a novel DMETM with auxiliary variable is proposed, which effectively leverages the benefits of historical sampled data. In the process of network data transmission, a hybrid attack model that simultaneously considers the impact of both deception and denial of service (DoS) attacks is introduced, which can undermine signal integrity and disrupt data transmission. Then, a memory-event-triggered controller is developed, and the mean square stability of the NNCSs can be ensured by selecting some appropriate values. Finally, a numerical simulation and a practical example are given to illustrate the meaning of the designed dynamic memory-event-triggered control (DMETC) algorithm. Full article

Rhizosphere microbiota are key drivers of plant nutrition, immunity, and stress tolerance. Abies ziyuanensis L. K. Fu & S. L. Mo (Pinaceae) is an endangered conifer endemic to China, and its persistence may depend on its interactions with its belowground microbiome. However, how soil-borne bacterial functional groups respond to, and potentially support, A. ziyuanensis remains unclear. Based on amplicon high-throughput sequencing data of the 16S rRNA gene and soil physicochemical properties, the bacterial community structure in the rhizosphere soil of A. ziyuanensis in Yinzhu Laoshan National Nature Reserve in Guangxi Zhuang Autonomous Region, China, was analyzed, and the potential ecological functions and phenotypic characteristics of the bacterial community were predicted to determine the functional taxa characteristics (nitrogen cycle, phototrophy, and chemoheterotrophy) and dominant soil environmental factors. Proteobacteria, Acidobacteria, Actinobacteria, Planctomycetes, Verrucomicrobia, and Chloroflexi were the dominant bacterial taxa in the A. ziyuanensis rhizosphere soil, and all bacteria were significantly positively correlated with soil NO₃⁻-N (R = 0.47, p = 0.0079). Based on FAPROTAX, the A. ziyuanensis rhizosphere soil bacterial community had chemoheterotrophic-related functions, which were more prevalent than nitrogen cycle- and phototrophic-related functions, and the relative abundance of bacteria with nitrogen cycle-related functions was higher than that of those with phototrophic functions. The nitrogen nutrient- and phototrophic-related functional taxa in the rhizosphere soil bacterial community had significant correlations with soil physicochemical properties, whereas the chemoheterotrophic-related functional taxa did not show a significant correlation. Based on BugBase phenotype prediction, Acidobacteria, Proteobacteria, and Chloroflexi made the greatest contribution to the phenotype, with pathogenic and stress tolerance being the most important phenotypes. The pathogenic and stress-tolerant bacteria all belonged to Proteobacteria. The rhizosphere bacteria exhibited rich diversity and dominated several biogeochemical cycling processes. This study identifies beneficial rhizosphere bacteria of A. ziyuanensis, providing a theoretical basis for conserving soil bacterial diversity and guiding the targeted recruitment of functional bacteria by the endangered plant. Full article

When unmanned aerial vehicles (UAVs) perform transmission line ice cover detection, it is often due to the variable shooting angle and complex background environment, which leads to difficulties such as poor ice-covering recognition accuracy and difficulty in accurately identifying the target. To address these issues, this study proposes an improved icing detection model based on HCDFI–You Only Look Once version 8 (HCDFI-YOLOv8). First, a cross-dense hybrid (CDH) parallel heterogeneous convolutional module is proposed, which can not only improve the detection accuracy of the model, but also effectively alleviate the problem of the surge in the number of floating-point operations during the improvement of the model. Second, deep and shallow feature weighted fusion using improved CSPDarknet53 to 2-Stage FPN_Dynamic Feature Fusion (C2f_DFF) module is proposed to reduce feature loss in neck networks. Third, optimization of the detection head using the feature adaptive spatial feature fusion (FASFF) detection head module is performed to enhance the model’s ability to extract features at different scales. Finally, a new inner-complete intersection over union (Inner_CIoU) loss function is introduced to solve the contradiction of the CIOU loss function used in the original YOLOv8. Experimental results demonstrate that the proposed HCDFI-YOLOv8 model achieves a 2.7% improvement in mAP@0.5 and a 2.5% improvement in mAP@0.5:0.95 compared to standard YOLOv8. Among twelve models for icing detection, the proposed model delivers the highest overall detection accuracy. The accuracy of the HCDFI-YOLOv8 model in detecting complex transmission line environments is verified and effective technical support is provided for transmission line ice cover detection. Full article

Diaporthe eres is a harmful pathogen affecting Hongyang kiwifruit (Actinidia chinensis) after harvest, yet the antioxidant defense strategies are not well understood. This research thoroughly examines the dynamics of the antioxidant response during the infection process. Significant findings indicate an initial 3-day latent period (0–3 dpi) that allowed for pathogen establishment, followed by irreversible tissue breakdown characterized by water-soaked lesions at 4 dpi. The study identified a biphasic activation pattern of superoxide dismutase (SOD) with dual activity peaks (1 dpi and 4 dpi), orchestrated by mitochondrial hub gene CEY00_Acc02790 that coordinates peroxidase (POD) networks, while peroxidase (POD) activity exhibited a synchronized but temporary increase, peaking at 4 dpi. Further bioinformatic analysis revealed the possible functional specialization of POD isoforms: α-helix-rich extracellular variants drove cell wall reinforcement through lignification, while random coil-dominant intracellular variants formed to mitigate cytoplasmic reactive oxygen species (ROS) damage, establishing dual physicochemical barriers. Malondialdehyde (MDA) levels rose significantly by 3 dpi, indicating permanent membrane damage. Collectively, these findings elucidate the mechanistic foundation of the Actinidia–Diaporthe pathosystem, identifying the bimodal SOD response and POD specialization as prime targets for developing resistant cultivars and precision postharvest interventions, ultimately reducing losses through biochemical interception of pathogenesis. Full article

Nitrate leaching from agricultural soils is a major contributor to groundwater contamination and non-point source pollution. Controlling this loss remains challenging due to the complexity of soil–water–nutrient interactions under intensive farming practices. Biochar, a porous, carbon-rich material derived from biomass pyrolysis, has emerged as a promising amendment for nitrate mitigation. This review summarizes recent advances in understanding the roles of biochar in nitrate retention and transformation in soils, including both direct mechanisms—such as surface adsorption, ion exchange, and pore entrapment—and indirect mechanisms—such as enhanced microbial activity, soil structure improvement, and root system development. Field and laboratory evidence shows that biochar can reduce NO₃⁻-N leaching by 15–70%, depending on its properties, soil conditions, and application context. However, inconsistencies in performance due to differences in biochar types, soil conditions, and environmental factors remain a major barrier to widespread adoption. This review also suggests current knowledge gaps and research needs, including long-term field validation, biochar material optimization, and integration of biochar into precision nutrient management. Overall, biochar presents a multifunctional strategy for reducing nitrate leaching and promoting sustainable nitrogen management in agroecosystems. Full article

The formation, development, and spatial distribution of CUHIs are influenced by urban spatial heterogeneity, yet the scale and seasonal dependencies of the effects of urban morphology modulation on CUHIs have not been fully explored, needing further study. Based on multi-source data for the Yangtze-Huaihe River Valley (YHRV), this study employs the XGBoost model to systematically investigate the effects of two-dimensional (2D)/three-dimensional (3D) urban morphological indicators on CUHIs and their inherent scale–seasonal dependencies. Results show significant provincial heterogeneity in YHRV’s CUHIs: Shanghai exhibits the highest CUHI intensity (CUHII) across all seasons, with a peak of 1.55 °C in winter, followed by Zhejiang and Jiangsu. Seasonally, winter CUHII averages 0.6–0.8 °C (the highest), followed by autumn, while spring and summer have lower values. The effect of the modulation of urban morphology on CUHIs exhibits distinct spatiotemporal dependence: in winter and autumn, CUHII is mainly dominated by the percentage of landscape (PLAND) and largest patch index (LPI) at the 4 km buffer scale (correlation coefficients r = 0.475 and 0.406 for winter); in spring and summer, the 2 km buffer scale shows a more balanced regulatory role of multiple urban morphological indicators. Notably, 2D indicators of urban morphology are consistently more influential in regulating CUHIs than 3D indicators. The Hefei station case effectively validates the model’s sensitivity to changes in urban morphology. This study provides a quantitative basis for season–scale collaborative regulation of urban thermal environments in the YHRV. Future research will integrate climatic factors into XGBoost via screening, reconstruction, and interaction quantification to enhance its predictability for transient heat island processes. Full article

The harsh environment in Arctic regions presents significant challenges to ship stability, particularly when ice accumulation and hull damage occur simultaneously, potentially increasing the risk of instability. This study addresses this critical issue by proposing a comprehensive stability assessment framework for ships operating in Arctic regions. Utilizing the DTMB-5415 ship model, the evaluation integrates both static and dynamic stability under combined ice accumulation and damage conditions. Firstly, an ice accumulation prediction model was developed to estimate ice accumulation over various durations. Subsequently, the static stability of damaged ships with ice accumulation was evaluated. Computational Fluid Dynamics (CFD) simulations were then conducted to calculate roll damping coefficients and analyze the effects of damage location and ice accumulation on free roll decay behavior. A single-degree-of-freedom (SDOF) roll motion model was constructed, incorporating roll damping coefficients and wave excitation moments to simulate roll responses in random wave environments. Extreme value prediction was employed to estimate the short-term extreme response distribution of roll motions. The results indicate that ship stability decreases significantly when ice accumulation and hull damage occur simultaneously. This integrated framework provides a systematic foundation for evaluating ship stability in the Arctic environment, specifically accounting for the combined effects of ice accretion and hull damage. Full article

Since 2007, the Yellow Sea has experienced the world’s largest green tides, with Ulva prolifera O.F. Müller as the dominant species. Those blooms severely impacted the local tourism and aquaculture, resulting in significant economic losses, as well as negative social and ecological consequences. Unlike other global green tides, those in the Yellow Sea are characterized by long-distance drifting and an astonishing scale. These destructive events display significant temporal and spatial variability, which is largely driven by dynamic environmental conditions and human activities. In this review, we summarize recent advancements in understanding the spatiotemporal patterns of long-distance transport, the interannual variability in bloom size, and the underlying mechanisms driving these fluctuations. Additionally, we highlight important knowledge gaps that need further investigation to support the development of effective management strategies for mitigating the impacts of green tides in the Yellow Sea. Full article