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• Farmland shelterbelt systems (FSSs) can improve ecosystem functions over controls. • Environmental factors exhibit spatiotemporal heterogeneities in different FSSs. • Different patterns of FSSs had beneficial water retention and nutrient supply functions. • There were close relationships between environmental factors and ecosystem functions in FSSs. • Results provide a theoretical basis for ecological restoration in ecofragile regions. The farmland shelterbelt system is considered an effective form of land management to improve the eco-environment and soil quality in fragile agricultural areas. Clarifying the effects of farmland shelterbelt patterns on ecosystem functions can guide ecological restoration in fragile ecosystems. Four typical farmland shelterbelt patterns (i.e., two-line pattern, four-line pattern, five-line pattern, and eight-line pattern) in desert oasis ecotones of Hetao irrigated area, northern China, were selected in this study. In these treatments, measurements of soil properties at a depth of 0–100 cm; vegetation attributes; microclimate; and soil water, carbon, nitrogen, and phosphorus storage were performed during three growing seasons in 2019–2021. The results demonstrated that the four-line pattern had higher soil organic content (0.339 g·kg−1), total nitrogen content (0.517 g·kg−1), and total phosphorus content (0.577 g·kg−1) than the other treatments, as well as the highest soil water (237.44 mm), carbon (544.93 g·m−2), nitrogen (953.72 g·m−2), and phosphorus storage (859.04 g·m−2) at the 0–100-cm soil layer. Moreover, dynamic variations in soil water and salt contents showed opposite trends during the growing season, i.e., they showed a gradual decrease and increase, respectively. Furthermore, principal component analysis, correlation matrix analyses, and network association analyses indicated close relationships among environmental factors, nutrient storage, and related ecosystem functions under different farmland shelterbelt patterns. The results of this investigation provide a useful theoretical basis for agricultural management and ecological restoration in ecofragile regions. [ABSTRACT FROM AUTHOR]

• The eco-hydrological benefits under planted and natural forest were compared. • Soil properties and vegetation attributes differ among different vegetation types. • Soil water storage (SWS) in natural forest is more than that in planted forests. • Herbaceous attributes are key eco-factors to hydrological regulation functions. • Results provide a support and guidance for afforestation in a close-to-nature way. Vegetation restoration serves as a long-term and important strategic initiative in ecologically-fragile locations worldwide, while the ecological effects of long-term vegetation restoration must be thoroughly investigated to support ecological restoration in these regions. The Loess Plateau is a typical area where the eco-environment has been improved by vegetation restoration in China, wherein four representative sites: the P. tabulaeformis planted forest, P. orientalis planted forest, R. pseudoacacia planted forest and the natural Secondary forest were selected as examples of typical planted and natural forests in this study. To analyze the ecological benefits of different vegetation restoration types and discuss a more sustainable pattern of afforestation in the future, soil properties in 0–100 cm, vegetation attributes at four synusiae, and hydrological regulation functions (the rainfall distributions of 23 rainfall events and 10 years of soil water storage) were measured and compared. The results showed that: (1) the soil properties of natural Secondary forest , in particular, soil water-retention capacities, were better than those of the planted forests; (2) the biomass of arborous synusia in natural Secondary forest was less than that in the planted forests, whereas it was significantly higher at shrub and herbaceous synusiae; (3) there were differences in rainfall redistribution among the natural and planted forests examined in this study, and the natural forest exhibited the highest soil water storage (414.33 mm) during the last decade; (4) according to the structural equation model (SEM), the vegetation attributes at arborous and herbaceous synusiae had the most direct and total effect on the hydrological regulation functions in the ecosystems. The results indicate that afforestation should be conducted in a way of near-natural restoration, which can provide guidance for future vegetation restoration in the Loess Plateau and other ecologically vulnerable areas. [ABSTRACT FROM AUTHOR]

Farmland shelterbelt system (FSS) in oasis desert ecotones can effectively improve ecosystem services, especially in fragile agricultural areas. However, the spatial-temporal heterogeneity of its ecological effects still needs further clarity, because the interactions are complex and multiple. Understanding this allows us to know the key practical significance of ecological construction and agricultural management. In this study, four typical patterns of FSS (i.e. two lines pattern, TWLP; four lines pattern, FOLP; five lines pattern, FILP; eight lines pattern, EILP) were selected in a desert oasis ecotone in northern China to assess the distributions at vertical (0–100 cm), horizontal (0–3 H) and temporal (May- October) scales of soil properties, vegetation attributes, microclimates and variations of soil moisture storage (SMS) and soil salt contents (C) during the three growing seasons. The results showed that the major difference in soil properties and vegetation attributes of FSSs are the soil particle composition and canopy size, respectively. In FOLP and EILP, the silt contents were 51.6% and 41.5% respectively. The canopy size ranked from the highest to lowest values as follows: FOLP (8.70 m2) > EILP (6.91 m2) > TWLP (4.64 m2) > FILP (4.47 m2). Compared to the control, all patterns of FSSs registered significant effects on microclimate improvement. The FOLP and FILP achieved the same effects as well as EILP, with less spatial costs. Moreover, the variations of SMS and C were mainly different at the vertical scale. As indicated by the Redundancy (RDA) and variation partitioning (VP) analyses, soil properties played a more important role in reserving soil water and controlling soil salinity than vegetation attributes and microclimates, which the independent influence can explain 48.5% of total influence among all factors. Our results provide an efficient theoretical basis for FSS construction and agricultural water management practices. • Farmland shelterbelt system (FSS) can improve ecosystem services. • A spatio-temporal heterogeneity of ecosystem functions in FSSs is observed. • Soil properties play a more important role in controlling soil water content and salinity. • Results provide an efficient theoretical basis for agricultural water management in deserts. [ABSTRACT FROM AUTHOR]

A new method is proposed to establish the statistical fractal model for liver diseases classification. Firstly, the fractal theory is used to construct the high-order tensor, and then Generalized N-dimensional Principal Component Analysis (GND-PCA) is used to establish the statistical fractal model and select the feature from the region of liver; at the same time different features have different weights, and finally, Support Vector Machine Optimized Ant Colony (ACO-SVM) algorithm is used to establish the classifier for the recognition of liver disease. In order to verify the effectiveness of the proposed method, PCA eigenface method and normal SVM method are chosen as the contrast methods. The experimental results show that the proposed method can reconstruct liver volume better and improve the classification accuracy of liver diseases. [ABSTRACT FROM AUTHOR]

A novel method is proposed to establish the classifier which can classify the pancreatic images into normal or abnormal. Firstly, the brightness feature is used to construct high-order tensors, then using multilinear principal component analysis (MPCA) extracts the eigentensors, and finally, the classifier is constructed based on support vector machine (SVM) and the classifier parameters are optimized with quantum simulated annealing algorithm (QSA). In order to verify the effectiveness of the proposed algorithm, the normal SVM method has been chosen as comparing algorithm. The experimental results show that the proposed method can effectively extract the eigenfeatures and improve the classification accuracy of pancreatic images. [ABSTRACT FROM AUTHOR]