Browsing by Author "Chen, Yu"

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    Convolutional neural network model for soil moisture prediction and its transferability analysis based on laboratory Vis-NIR spectral data
    (Elsevier, 2021-12) Chen, Yu; Li, Lin; Whiting, Michael; Chen, Fang; Sun, Zhongchang; Song, Kaishan; Wang, Qinjun; Earth Sciences, School of Science
    Laboratory visible near infrared reflectance (Vis-NIR, 400–2500 nm) spectroscopy has the advantages of simplicity, fast and non-destructive which was used for SM prediction. However, many previously proposed models are difficult to transfer to unknown target areas without recalibration. In this study, we first developed a suitable Convolutional Neutral Network (CNN) model and transferred the model to other target areas for two situations using different soil sample backgrounds under 1) the same measurement conditions (DSSM), and 2) under different measurement conditions (DSDM). We also developed the CNN models for the target areas based on their own datasets and traditional PLS models was developed to compare their performances. The results show that one dimensional model (1D-CNN) performed strongly for SM prediction with average R2 up to 0.989 and RPIQ up to 19.59 in the laboratory environment (DSSM). Applying the knowledge-based transfer learning method to an unknown target area improved the R2 from 0.845 to 0.983 under the DSSM and from 0.298 to 0.620 under the DSDM, which performed better than data-based spiking calibration method for traditional PLS models. The results show that knowledge-based transfer learning was suitable for SM prediction under different soil background and measurement conditions and can be a promising approach for remotely estimating SM with the increasing amount of soil dataset in the future.
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    Coupling Coordination Relationship between Urban Sprawl and Urbanization Quality in the West Taiwan Strait Urban Agglomeration, China: Observation and Analysis from DMSP/OLS Nighttime Light Imagery and Panel Data
    (MDPI, 2020-10) Lu, Chunyan; Li, Lin; Lei, Yifan; Ren, Chunying; Su, Ying; Huang, Yufei; Chen, Yu; Lei, Shaohua; Fu, Weiwei; Earth Sciences, School of Science
    Urban sprawl is the most prominent characteristic of urbanization, and increasingly affects local and regional sustainable development. The observation and analysis of urban sprawl dynamics and their relationship with urbanization quality are essential for framing integrative urban planning. In this study, the urban areas of the West Taiwan Strait Urban Agglomeration (WTSUA) were extracted using nighttime light imagery from 1992 to 2013. The spatio-temporal characteristics and pattern of urban sprawl were quantitatively analyzed by combining an urban expansion rate index and a standard deviation ellipse model. The urbanization quality was assessed using an entropy weight model, and its relationship with urban sprawl was calculated by a coupling coordination degree model. The results showed that the urban area in the WTSUA experienced a significant increase, i.e., 18,806.73 km2, during the period 1992–2013. The central cities grew by 11.08% and noncentral cities by 27.43%, with a general uneven city rank-size distribution. The urban sprawl showed a circular expansion pattern, accompanied by a gradual centroid migration of urban areas from the southeast coast to the central-western regions. The coupling coordination level between urban expansion and urbanization quality increased from serious incoordination in 1992 to basic coordination in 2013. Dual driving forces involving state-led policies and market-oriented land reform had a positive influence on the harmonious development of urban sprawl and urbanization quality of the WTSUA. This research offers an effective approach to monitor changes in urban sprawl and explore the coupling coordination relationship between urban sprawl and urbanization quality. The study provides important scientific references for the formulation of future policies and planning for sustainable development in urban agglomerations.
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    Effects of Granule Dendrobii on chronic atrophic gastritis induced by N-methyl-N'-nitro-N-nitrosoguanidine in rats
    (Baishideng, 2022) Wu, Yue; Li, Yu; Jin, Xiao-Ming; Dai, Guan-Hai; Chen, Xuan; Tong, Ye-Ling; Ren, Ze-Ming; Chen, Yu; Xue, Xiao-Min; Wu, Ren-Zhao; Anatomy, Cell Biology and Physiology, School of Medicine
    Background: Dendrobium officinale is an herb of Traditional Chinese Medicine (TCM) commonly used for treating stomach diseases. One formula of Granule Dendrobii (GD) consists of Dendrobium officinale and American Ginseng (Radix Panacis quinquefolii), and is a potent TCM product in China. Whether treatment with GD can promote gastric acid secretion and alleviate gastric gland atrophy in chronic atrophic gastritis (CAG) requires verification. Aim: To determine the effect of GD treatment on CAG and its potential cellular mechanism. Methods: A CAG model was induced by feeding rats N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) for 12 wk. After oral administration of low, moderate, and high doses of GD in CAG rats for 8 wk, its effects on body weight, gastric mucosa histology, mucosal atrophy, intestinal metaplasia, immunohistochemical staining of proliferating cell nuclear antigen (PCNA) and B-cell lymphoma-2, and hemoglobin and red blood cells were examined. Results: The body weights of MNNG-induced CAG model rats before treatment (143.5 ± 14.26 g) were significantly lower than that of healthy rats (220.2 ± 31.20 g, P < 0.01). At the 8th week of treatment, the body weights of rats in the low-, moderate-, and high-dose groups of GD (220.1 ± 36.62 g) were significantly higher than those in the untreated group (173.3 ± 28.09 g, all P < 0.01). The level of inflammation in gastric tissue of the high-dose group (1.68 ± 0.54) was significantly reduced (P < 0.01) compared with that of the untreated group (3.00 ± 0.00, P < 0.05). The number and thickness of gastric glands in the high-dose group (31.50 ± 6.07/mm, 306.4 ± 49.32 µm) were significantly higher than those in the untreated group (26.86 ± 6.41/mm, 244.3 ± 51.82 µm, respectively, P < 0.01 and P < 0.05), indicating improved atrophy of gastric mucosa. The areas of intestinal metaplasia were significantly lower in the high-dose group (1.74% ± 1.13%), medium-dose group (1.81% ± 0.66%) and low-dose group (2.36% ± 1.08%) than in the untreated group (3.91% ± 0.96%, all P < 0.01). The expression of PCNA in high-dose group was significantly reduced compared with that in untreated group (P < 0.01). Hemoglobin level in the high-dose group (145.3 ± 5.90 g/L), medium-dose group (139.3 ± 5.71 g/L) and low-dose group (137.5 ± 7.56 g/L) was markedly increased compared with the untreated group (132.1 ± 7.76 g/L; P < 0.01 or P < 0.05). Conclusion: Treatment with GD for 8 wk demonstrate that GD is effective in the treatment of CAG in the MNNG model by improving the histopathology of gastric mucosa, reversing gastric atrophy and intestinal metaplasia, and alleviating gastric inflammation.
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    A semi-analytical algorithm for deriving the particle size distribution slope of turbid inland water based on OLCI data: A case study in Lake Hongze
    (Elsevier, 2021-02) Lei, Shaohua; Xu, Jie; Li, Yunmei; Li, Lin; Lyu, Heng; Liu, Ge; Chen, Yu; Lu, Chunyan; Tian, Chao; Jiao, Wenzhe; Earth Sciences, School of Science
    The particle size distribution (PSD) slope (ξ) can indicate the predominant particle size, material composition, and inherent optical properties (IOPs) of inland waters. However, few semi-analytical methods have been proposed for deriving ξ from the surface remote sensing reflectance due to the variable optical state of inland waters. A semi-analytical algorithm was developed for inland waters having a wide range of turbidity and ξ in this study. Application of the proposed model to Ocean and Land Color Instrument (OLCI) imagery of the water body resulted in several important observations: (1) the proposed algorithm (754 nm and 779 nm combination) was capable of retrieving ξ with R2 being 0.72 (p < 0.01, n = 60), and MAPE and RMSE being 4.37% and 0.22 (n = 30) respectively; (2) the ξ in HZL was lower in summer than other seasons during the period considered, this variation was driven by the phenological cycle of algae and the runoff caused by rainfall; (3) the band optimization proposed in this study is important for calculating the particle backscattering slope (η) and deriving ξ because it is feasible for both algae dominant and sediment governed turbid inland lakes. These observations help improve our understanding of the relationship between IOPs and ξ, which are affected by different bio-optic processes and algal phenology in the lake environment.