Search Results (25)

The lower Yarlung Zangbo River Basin’s Great Bend region, characterized by extreme topography and intense orographic precipitation processes, presents significant challenges for accurate precipitation estimation using reanalysis products. Therefore, this study evaluates four widely used products (ERA5-Land, MSWEP, CMA, and TPMFD) against station observations (2014–2022) in this critical area. Performance was rigorously assessed using correlation analysis, error metrics (RMSE, MAE, RBIAS), and spatial regression. The region exhibits strong seasonality, with 62.1% of annual rainfall occurring during the monsoon (June-October). Results indicate TPMFD performed best overall, capturing spatiotemporal patterns effectively (correlation coefficients 0.6–0.8, low RBIAS). Conversely, ERA5-Land significantly overestimated precipitation, particularly in rugged northeast areas, suggesting poor representation of orographic effects. MSWEP and CMA underestimated rainfall with variable temporal consistency. Topographic analysis confirmed slope, aspect, and longitude strongly control precipitation distribution, aligning with classical orographic mechanisms (e.g., windward enhancement, lee-side rain shadows) and monsoonal moisture transport. Spatial regression revealed terrain features explain 15.4% of flood-season variation. TPMFD most accurately captured these terrain-precipitation relationships. Consequently, findings underscore the necessity for terrain-sensitive calibration and data fusion strategies in mountainous regions to improve precipitation products and hydrological modeling under orographic influence. Full article

The permanent magnet electrodynamic suspension system (PMEDS) has demonstrated significant advantages in high-speed and ultra-high-speed applications due to its simple structure, low cost, and stable levitation force. However, the weak damping characteristic remains a critical issue limiting its practical implementation. This work investigates a passive damping plate utilizing the end field of onboard magnets, focusing on magnet-damping plate optimization and vehicle dynamics. Firstly, the configuration, operation principles, and electromagnetic parameters of the PMEDS vehicle are elucidated. Secondly, the dependences of magnet-conductive plate specifications on the damping force are examined. An optimization index based on the levitation-to-damping force ratio is proposed to enable collaborative optimization of magnet and conductive plate parameters. Finally, the vehicle dynamic model is developed using Simpack software to investigate payload and speed effects on dynamic responses under random track excitation, validating the effectiveness of the proposed passive damping solution. This study provides technical references for the design, engineering applications, and performance evaluation of passive damping schemes in PMEDS vehicles. Full article

Insulin resistance (IR) is a risk factor for various diseases. Diet plays a crucial role in the development of IR. The high-protein diet (HPD) is gaining popularity for its weight control benefit. However, some types of protein can be metabolized by gut microbiota into trimethylamine (TMA), subsequently oxidized into trimethylamine N-oxide (TMAO) in the liver. However, the underlying mechanism of HPD-induced IR remains unclear. In this study, we firstly investigated whether the HPD can induce IR. Next, we examined liver function and the signaling pathways involved in IR. At last, we detected changes in the composition and function of gut microbiota, particularly concerning TMA production. Our results demonstrated that the HPD induces IR and liver injury, 41% higher TMA concentration than in the control group. Transcriptome results confirmed that insulin-related pathways were enriched in the HPD group, especially the Insrr gene, which regulates insulin action through its receptor, was downregulated. Disrupted gut microbiota, dominated by 65.0% of Firmicutes, which have high potential in TMA production. Moreover, several amino acid metabolism pathways closely linked to IR were enriched in the HPD group. These findings highlight the need for careful dietary management, as the HPD can induce IR and liver injury, with gut microbiota playing a key role in TMA production. Full article

Small RNAs (sRNAs) are pivotal in regulating gene expression and are involved in a diverse array of biological processes. Among these, microRNAs (miRNAs) and phased small interfering RNAs (phasiRNAs) have been extensively investigated over the past decades. We conducted an in-depth analysis of deep sequencing data from the gymnosperm Ginkgo biloba, encompassing sRNA, transcriptome, and degradome libraries. Our analysis identified a total of 746 miRNAs and 654 phasiRNA precursor (PHAS) loci, with 526 (80%) of the PHAS loci predicted to be triggered by 515 miRNAs (69%). Several miRNA-PHAS modules, particularly the miR159/miR319-PHAS module, were found to potentially regulate reproductive development by targeting GAMYB genes and triggering phasiRNA biogenesis. The miR390-PHAS module appears to be involved in flavonoid biosynthesis by targeting key enzyme genes such as chalcone synthase (CHS) and anthocyanin synthase (ANS). Through target gene identification and coexpression analysis, we uncovered two distinct models of complex regulatory networks: growth-related factors like ARF and GRF seem to be regulated exclusively by miRNAs (Model 1), while certain disease resistance-related genes are predicted to be regulated by both miRNAs and phasiRNAs (Model 2), indicating diverse regulatory mechanisms across different biological processes. Overall, our study provides a comprehensive annotation of miRNA and PHAS loci in G. biloba and elucidates a post-transcriptional regulatory network, offering novel insights into sRNA research in gymnosperms. Full article

Quality function deployment (QFD) is a customer-oriented quality management tool used to maximize customer satisfaction by considering the correlations between customer requirements and engineering characteristics. However, the conventional QFD method exhibits some shortcomings when used in real situations, especially in terms of correlation evaluation and engineering characteristic ranking. Therefore, the objective of this study is to propose a new QFD approach based on linguistic distribution assessments and the CRiteria Importance Through Inter-Criteria Correlation (CRITIC) method to improve the effectiveness of the traditional QFD. Specifically, linguistic distribution assessments are utilized to describe the relationships between customer requirements and engineering characteristics. The CRITIC method is extended and used to determine the ranking orders of the engineering characteristics identified in QFD. To demonstrate the feasibility and practicality of the proposed QFD, a case example regarding the performance management system’s development is presented. It is shown that the QFD approach proposed in this paper can not only represent experts’ uncertain linguistic relationship evaluations flexibly but also determine more reliable importance rankings of engineering characteristics in production planning. Full article

Background: Trace elements (TEs) are essential nutrients for the human body and have a significant impact on fertility and hormone levels in women of reproductive age, underscoring the importance of understanding sociodemographic variations in their concentrations within this population. Objective: To investigate the socio-demographic factors influencing blood concentrations of four essential TEs, including iron, zinc, copper, and selenium among women of reproductive age. Methods: A cross-sectional analysis of women aged 20–44 years was performed using the National Health and Nutrition Examination Survey, 1999–2018. Serum iron data were analyzed for 9211 women across 10 cycles, while serum copper, zinc, and selenium data were available for 1027 women across 3 cycles. Generalized linear and logistic regressions examined the individual associations of socio-demographic factors, including age, race and ethnicity, education, and poverty index ratio, with iron, zinc, copper, and selenium concentrations treated as continuous and categorical outcomes, respectively. A qualitative heatmap explored the joint associations between the socio-demographic factors and the four essential TEs. Results: Reduced iron concentrations and increased risks of insufficiency occurred in older, Black, low-education, or low-income women. Black women were more likely to have lower zinc and selenium concentrations and an increased risk of zinc insufficiency but higher copper concentrations. The qualitative heatmap found that older, Black, low-education, and low-income women generally had lower concentrations of the four TEs, particularly iron (β = −0.10; p < 0.01). Conclusions: Socially disadvantaged women are more likely to present with lower TE concentrations, and these specific population groups should be targeted by replenishment planning by public health initiatives. Full article

Herbaceous peony (Paeonia lactiflora Pall) is resistant to drought but not waterlogging. The main production areas of peony are prone to waterlogging, seriously affecting the growth and development of herbaceous peony. Polyamines have been observed to significantly enhance the ability of plants to defend and repair adverse damage and affect the synthesis and accumulation of the endogenous growth hormones indole-3-acetic acid (IAA) and abscisic acid (ABA). In this study, two herbaceous peony varieties (‘Lihong’, ‘Qihualushuang’) with different waterlogging tolerances were selected for artificial simulated waterlogging treatment to observe their morphological indexes and to determine their endogenous polyamine and hormone contents. Simultaneously, transcriptome sequencing and bioinformatics analysis were performed, focusing on screening differentially expressed genes in the polyamine metabolism pathway. The results showed that flood-tolerant varieties of herbaceous peony respond to waterlogging stress by continuously synthesizing spermidine (Spd) and spermine (Spm) through putrescine (Put) to counteract adversity. In the waterlogging-intolerant varieties, the expression of polyamine oxidase-related genes was annotated; their response to waterlogging stress was the simultaneous degradation of Spm and Spd to Put in the process of synthesis, and a decrease in the accumulation of Spm and Spd led to the early appearance of the symptoms of damage. In addition, polyamines influence key hormones that respond to plant adversity (IAA; ABA). The objective of this work was to initially analyze the mechanism of the polyamine signaling pathway in response to flooding in herbaceous peonies for further in-depth research on the mechanism of flooding tolerance in herbaceous peony, screen flood-tolerant varieties, and promote of their use. Full article

The performance of nano-zero-valent iron for heavy metal remediation can be enhanced via incorporation into bimetallic carbon composites. However, few economical and green approaches are available for preparing bimetallic composite materials. In this study, novel Co/Fe bimetallic biochar composites (BC@Co/Fe-X, where X = 5 or 10 represents the CoCl₂ concentration of 0.05 or 0.1 mol L⁻¹) were prepared for the adsorption of Pb²⁺. The effect of the concentration of cross-linked metal ions on Pb²⁺ adsorption was investigated, with the composite prepared using 0.05 mol L⁻¹ Co²⁺ (BC@Co/Fe-5) exhibiting the highest adsorption performance. Various factors, including the adsorption period, Pb²⁺ concentration, and pH, affected the adsorption of Pb²⁺ by BC@Co/Fe-5. Further characterisation of BC@Co/Fe-5 before and after Pb²⁺ adsorption using methods such as X-ray diffraction and X-ray photoelectron spectroscopy suggested that the Pb²⁺ adsorption mechanism involved (i) Pb²⁺ reduction to Pb⁰ by Co/Fe, (ii) Co/Fe corrosion to generate Fe²⁺ and fix Pb²⁺ in the form of PbO, and (iii) Pb²⁺ adsorption by Co/Fe biochar. Notably, BC@Co/Fe-5 exhibited excellent remediation performance in simulated Pb²⁺-contaminated water and soil with good recyclability. Full article

To identify herbaceous peony cultivars with strong photosynthetic productivity, we compared the photosynthetic characteristics of 20 herbaceous peony cultivars based on four photosynthetic characteristics parameters and established light–response curves under a light intensity gradient, using CIRAS-3 portable photosynthetic dynamic monitoring. The net photosynthetic rate (Pn) showed a “unimodal” diurnal variation pattern, with a peak around 12:00. The diurnal pattern of the transpiration rate was the same as that of Pn. Stomatal conductance values (Gs) showed similar patterns among the cultivars, with only small differences. The daily variation in intracellular CO₂ concentration (Ci) showed an opposite trend to that of Pn. When the photosynthetically active radiation was 0–400 μmol·m⁻²s⁻¹, Pn increased linearly and gradually with increasing light intensity. ‘Xueyuanhonghua’, ‘Qingwen’, ‘Taohuafeixue’, ‘Chifen’, and ‘Qihualushuang’ showed high photosynthetic productivity. ‘Xueyuanhonghua’, ‘Fushi’, ‘Qingwen’, ‘Tianshanhongxing’, ‘Qingtianlan’, ‘Dafugui’, and ‘Hongfushi’ had high light saturation points and the highest light resistance. ‘Xueyuanhonghua’, ‘Qingwen’, ‘Taohuafeixue’, ‘Tianshanhongxing’, ‘Qingtianlan’, ‘Guifeichacui’, ‘Chifen’, and ‘Hongxiuqiu’ had low light compensation points. Thus, two cultivars with strong photosynthetic productivity, ‘Xueyuanhonghua’ and ‘Qingwen’, can be cross-bred to obtain both light- and shade-tolerant plants. This study provides a theoretical basis for breeding new cultivars with high photosynthetic productivity. Full article

As the demand for cultural and recreational services grows, the mismatch between the supply and demand of park services significantly affects residents’ well-being. Optimizing the spatial layout of park services is a focal point of urban park and green space research. Taking Hangzhou, Zhejiang Province, as a case study, this research analyzes the spatial patterns and balance of park service supply and demand. Utilizing the Grey Wolf Optimization Model optimized by the K-Nearest Neighbor Model (GWO-KNN), this study proposes construction objectives for optimizing park services. The results indicate the following: (1) significant differences exist in the park service demands of residents in different residential environments; (2) there is a noticeable spatial disparity in park service supply among various residential areas with an overall positive correlation between park service supply levels and resident demands, yet an imbalance exists; (3) this study categorizes spatial types into low-service coordination, high-service coordination, low-service imbalance, and high-service imbalance; (4) the GWO-KNN Model is applied with optimization objectives being the innovative aspect of this study. Strategies for each park category are proposed: emphasizing suburban park construction by utilizing surrounding green resources and adding diverse facilities; introducing facilities friendly to vulnerable groups to meet the needs of diverse populations; enhancing the complementary advantages between “new” and “old” cities by moderately increasing park sizes and improving cultural and facility development levels; optimizing spatial structure with limited land resources to construct an urban park network system. This study aims to provide theoretical and technical support for optimizing urban park and green space systems. Full article

The preoperative differentiation of breast phyllodes tumors (PTs) from fibroadenomas (FAs) plays a critical role in identifying an appropriate surgical treatment. Although several imaging modalities are available, reliable differentiation between PT and FA remains a great challenge for radiologists in clinical work. Artificial intelligence (AI)-assisted diagnosis has shown promise in distinguishing PT from FA. However, a very small sample size was adopted in previous studies. In this work, we retrospectively enrolled 656 breast tumors (372 FAs and 284 PTs) with 1945 ultrasound images in total. Two experienced ultrasound physicians independently evaluated the ultrasound images. Meanwhile, three deep-learning models (i.e., ResNet, VGG, and GoogLeNet) were applied to classify FAs and PTs. The robustness of the models was evaluated by fivefold cross validation. The performance of each model was assessed by using the receiver operating characteristic (ROC) curve. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also calculated. Among the three models, the ResNet model yielded the highest AUC value, of 0.91, with an accuracy value of 95.3%, a sensitivity value of 96.2%, and a specificity value of 94.7% in the testing data set. In contrast, the two physicians yielded an average AUC value of 0.69, an accuracy value of 70.7%, a sensitivity value of 54.4%, and a specificity value of 53.2%. Our findings indicate that the diagnostic performance of deep learning is better than that of physicians in the distinction of PTs from FAs. This further suggests that AI is a valuable tool for aiding clinical diagnosis, thereby advancing precision therapy. Full article

When used for ornamental purposes, the herbaceous peony is usually propagated by root ramets, but the replanting of divided seedlings in the original planting area results in poor growth and development. No research has reported on a compound microbial agent used for herbaceous peony. The purpose of this experiment is to provide a reference for low–cost soil improvement in production, promote the growth and development of herbaceous peony, and solve the problem of planting back obstacles. In this study, 3–year–old seedlings of herbaceous peony ‘Zifengyu’ were selected and planted into an ordinary garden and replanted soils. Four root irrigation treatments were conducted using the compound microbial agent ‘Junzhongjun’ to determine the physicochemical properties of rhizosphere soil, root physiology, and growth and development of ‘Zifengyu’ under different soil conditions. The growth and development of the aboveground parts of herbaceous peony were promoted by the treatment of the compound microbial agent in the following order: garden soil > sieved–root soil > unsieved–root soil. Root vigour was enhanced in the following sequence: sieved–root soil > unsieved–root soil > garden soil. The organic matter and available potassium in the rhizosphere soil of herbaceous peony increased, and the promotional effect in the sieved–root soil was significantly better than that in the other two soils. The results show that the compound microbial agent is low in cost and has a stimulating effect on the growth and development of herbaceous peony. In the process of production, the residual broken roots in the soil can be sieved and combined with the application of the compound microbial agent to further alleviate the barriers of replanting. The concentration and frequency of agent application should be further optimized at a later stage. Full article

Herbaceous peony (Paeonia lactiflora Pall.) is a famous ornamental plant, and the study of its flower color is of great significance for cultivating new flower varieties. To explore the factors driving the formation and change of herbaceous peony flower color, we selected five herbaceous peony varieties at four flowering stages to determine the change in flower color, petal area, and microstructure. We also examined the composition and content of petal pigments, soluble sugar and soluble protein content, pH value of cell fluid, and water content. Finally, we analyzed the correlations between each factor. We found that Pn3G5G, Pg3G5G, and Cy3G5G were the main anthocyanin components in red and purple petals. Qu3G, Qu7G, Is3G, and lutein play important roles in yellow petal formation. The change in herbaceous peony flower color during the flowering process is directly caused by changes in the anthocyanin and carotenoid content in petals. In addition, changes in other physiological indices also influence the change in flower color. This study explored the physiological and biochemical factors affecting the color of herbaceous peony petals, which has an important practical significance for studying the physiological mechanism of herbaceous peony flower color formation and color breeding of new flowers. Full article

In order to improve the tracking adaptability of autonomous vehicles under different vehicle speeds and road curvature, this paper develops a weight adaptive model prediction control system (AMPC) based on PSO-BP neural network, which consists of a dynamics-based model prediction controller (MPC) and an optimal weight adaptive regulator. Based on the application of MPC to achieve high-precision tracking control, the optimal weight under different operating conditions obtained by automated simulation is used to train the PSO-BP neural network offline to achieve online adjustment of MPC weight. The validation results of the Prescan-Carsim-Simulink joint simulation platform show that the adaptive control system has better tracking adaptation capability compared with the original classical MPC control. The control strategy was also verified on an autonomous vehicle test platform, and the test results showed that the adaptive control strategy improved tracking accuracy while meeting the vehicle’s requirements for real-time control and lateral stability. Full article

Paeonia lactiflora Pall. is widely used in medicine, garden applications, and as a potted ornamental. Cultivated varieties of paeonifloras suitable for cut flowers are urgently needed. In this study, the pollen morphology of P. lactiflora was studied and the characters of different varieties were compared, so as to provide reference for selecting suitable parents for new hybrid varieties. We examined the pollen morphology of 15 herbaceous peony varieties using scanning electron microscopy and analyzed the external pollen morphology and genetic relationship of the varieties. The pollen grains of the studied varieties were spheroidal or subspheroidal, bilaterally symmetrical monads, circular in polar view, and circular or elliptical in equatorial view. The exine of the pollen grains was observed as being relatively smooth under the light microscope, with the area around the equatorial axis having more lumina under the scanning electron microscope. The pollen grain exine sculpture was either reticular or pit type. The pollen apertures were tricolporate, arranged longitudinally, and equally spaced. The pollen grains were of two sizes: medium and small. The differences between the varieties were mainly reflected in the exine sculpture of the pollen. The closer the genetic relationship between the 15 peony varieties, the more subtle the differences in the exine sculpture. In the same cluster group, the morphological characteristics of herbaceous peony pollen were correlated with the shapes of flower and scale buds and the texture of the petals. However, the study identified no direct correlation with the cultivar type and flower color. Full article