Browsing by Author "Wang, Xiang"
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Item A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018(Copernicus, 2022-01-13) Tao, Hui; Song, Kaishan; Liu, Ge; Wang, Qiang; Wen, Zhidan; Jacinthe, Pierre-Andre; Xu, Xiaofeng; Du, Jia; Shang, Yingxin; Li, Sijia; Wang, Zongming; Lyu, Lili; Hou, Junbin; Wang, Xiang; Liu, Dong; Shi, Kun; Zhang, Baohua; Duan, Hongtao; Earth and Environmental Sciences, School of ScienceWater clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984–2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red blue band ratio algorithm was applied to map SDD for lakes (>0.01 km2) based on the first SDD dataset, where R2=0.79 and relative RMSE (rRMSE) =61.9 %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD <2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of <0.5 and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984–2018, lakes in the Tibetan–Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32±0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60±0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia–Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01–1 km2, whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.271571, Tao et al., 2021).Item Efficient Inference and Dominant-Set Based Clustering for Functional Data(2024-05) Wang, Xiang; Wang, Honglang; Boukai, Benzion; Tan, Fei; Peng, HanxiangThis dissertation addresses three progressively fundamental problems for functional data analysis: (1) To do efficient inference for the functional mean model accounting for within-subject correlation, we propose the refined and bias-corrected empirical likelihood method. (2) To identify functional subjects potentially from different populations, we propose the dominant-set based unsupervised clustering method using the similarity matrix. (3) To learn the similarity matrix from various similarity metrics for functional data clustering, we propose the modularity guided and dominant-set based semi-supervised clustering method. In the first problem, the empirical likelihood method is utilized to do inference for the mean function of functional data by constructing the refined and bias-corrected estimating equation. The proposed estimating equation not only improves efficiency but also enables practically feasible empirical likelihood inference by properly incorporating within-subject correlation, which has not been achieved by previous studies. In the second problem, the dominant-set based unsupervised clustering method is proposed to maximize the within-cluster similarity and applied to functional data with a flexible choice of similarity measures between curves. The proposed unsupervised clustering method is a hierarchical bipartition procedure under the penalized optimization framework with the tuning parameter selected by maximizing the clustering criterion called modularity of the resulting two clusters, which is inspired by the concept of dominant set in graph theory and solved by replicator dynamics in game theory. The advantage offered by this approach is not only robust to imbalanced sizes of groups but also to outliers, which overcomes the limitation of many existing clustering methods. In the third problem, the metric-based semi-supervised clustering method is proposed with similarity metric learned by modularity maximization and followed by the above proposed dominant-set based clustering procedure. Under semi-supervised setting where some clustering memberships are known, the goal is to determine the best linear combination of candidate similarity metrics as the final metric to enhance the clustering performance. Besides the global metric-based algorithm, another algorithm is also proposed to learn individual metrics for each cluster, which permits overlapping membership for the clustering. This is innovatively different from many existing methods. This method is superiorly applicable to functional data with various similarity metrics between functional curves, while also exhibiting robustness to imbalanced sizes of groups, which are intrinsic to the dominant-set based clustering approach. In all three problems, the advantages of the proposed methods are demonstrated through extensive empirical investigations using simulations as well as real data applications.Item Identification of material parameters based on Mohr-Coulomb failure criterion for bisphosphonate treated canine vertebral cancellous bone(2008-10) Wang, Xiang; Allen, Matthew R.; Burr, David B.; Lavernia, Enrique J; Jeremić, Boris; Fyhrie, David PNanoindentation has been widely used to study bone tissue mechanical properties. The common method and equations for analyzing nanoindentation, developed by Oliver and Pharr, are based on the assumption that the material is linearly elastic. In the present study, we adjusted the constraint of linearly elastic behavior and use nonlinear finite element analysis to determine the change in cancellous bone material properties caused by bisphosphonate treatment, based on an isotropic form of the Mohr–Coulomb failure model. Thirty-three canine lumbar vertebrae were used in this study. The dogs were treated daily for 1 year with oral doses of alendronate, risedronate, or saline vehicle at doses consistent, on a mg/kg basis, to those used clinically for the treatment of post-menopausal osteoporosis. Two sets of elastic modulus and hardness values were calculated for each specimen using the Continuous Stiffness Measurement (CSM) method (ECSM and HCSM) from the loading segment and the Oliver–Pharr method (EO–P and HO–P) from the unloading segment, respectively. Young's modulus (EFE), cohesion (c), and friction angle (ϕ) were identified using a finite element model for each nanoindentation. The bone material properties were compared among groups and between methods for property identification. Bisphosphonate treatment had a significant effect on several of the material parameters. In particular, Oliver–Pharr hardness was larger for both the risedronate- and alendronate-treated groups compared to vehicle and the Mohr–Coulomb cohesion was larger for the risedronate-treated compared to vehicle. This result suggests that bisphosphonate treatment increases the hardness and shear strength of bone tissue. Shear strength was linearly predicted by modulus and hardness measured by the Oliver–Pharr method (r2 = 0.99). These results show that bisphosphonate-induced changes in Mohr–Coulomb material properties, including tissue shear cohesive strength, can be accurately calculated from Oliver–Pharr measurements of Young's modulus and hardness.Item Morphological Assessment of Basic Multicellular Unit Resorption Parameters in Dogs Shows Additional Mechanisms of Bisphosphonate Effects on Bone(2010-01) Allen, Matthew R.; Erickson, Antonia M; Wang, Xiang; Burr, David B.; Martin, R Bruce; Hazelwood, Scott JBisphosphonates (BPs) slow bone loss by reducing initiation of new basic multicellular units (BMUs). Whether or not BPs simply prevent osteoclasts from initiating new BMUs that resorb bone or also reduce the amount of bone they resorb at the BMU level is not clear. The goal of this study was to determine the effects of BPs on three morphological parameters of individual BMUs, resorption depth (Rs.De), area (Rs.Ar), and width (Rs.Wi). After 1 year of treatment with vehicle (VEH), alendronate (ALN; 0.10, 0.20, or 1.00 mg/kg/day), or risedronate (RIS; 0.05, 0.10, or 0.50 mg/kg/day), resorption cavity morphology was assessed in vertebral trabecular bone of beagle dogs by histology. Animals treated with ALN or RIS at the doses representing those used to treat postmenopausal osteoporosis (0.20 and 0.10 mg/kg/day, respectively) had significantly lower Rs.Ar (−27%) and Rs.Wi (−17%), with no difference in Rs.De, compared to VEH-treated controls. Low doses of ALN and RIS did not affect any parameters, whereas higher doses resulted in similar changes to those of the clinical dose. There were no significant differences in the resorption cavity measures between RIS and ALN at any of the dose equivalents. These results highlight the importance of examining parameters beyond erosion depth for assessment of resorption parameters. Furthermore, these results suggest that in addition to the well-known effects of BPs on reducing the number of active BMUs, these drugs also reduce the activity of osteoclasts at the individual BMU level at doses at and above those used clinically for the treatment of postmenopausal osteoporosis.Item Prediction of soil organic matter using VNIR spectral parameters extracted from shape characteristics(Elsevier, 2022-02) Wang, Xiang; Li, Lin; Liu, Huanjun; Song, Kaishan; Wang, Liping; Meng, Xiangtian; Earth Science, School of ScienceWhether spectral feature parameters (SFPs) can be effectively used to predict soil organic matter (SOM), and its spatial transferability was tested for different regions. In this study, a hybrid model was proposed based on SFPs and local regression method. The topsoil spectra of 221 soil samples from Sanjiang Plain and 187 soil samples from Nong’an county in Northeast China were re-sampled (at 0.01 µm intervals) and converted to the first-derivative curves and CR curves. Two SFPs were extracted on reflectance curves (RSFPs), which were defined as curve length (Lc) and area (Ac) between two absorption positions. Local random forest models with k-means clustering were built using the RSFPs and first-derivative spectra for evaluating the feasibility of RSFPs in these two study areas. After analyzing the results of Chinese soil samples, this method was also applied to Land Use/Land Cover Area Frame Survey (LUCAS) topsoil database in order to evaluate the feasibility of RSFPs outside China. Our results revealed these: (1) high correlation between the RSFPs of soil samples with spectral characteristics of sandy soils and SOM; (2) the importance of Lc relative to Ac in SOM prediction is higher; and (3) SOM prediction using RSFPs is comparable to the first-derivative spectra, and the best result has an R2 of 0.76 and an RMSE of 7.43 g kg−1. Our results suggest that RSFPs can be used to predict SOM and have good spatial transferability after applying in two study areas. RSFPs with specific geometric meaning have high potential to predict other soil properties in Northeast China. Our results also provide a reference for SOM mapping using hyper-spectral satellites.Item Spatial transmission and meteorological determinants of tuberculosis incidence in Qinghai Province, China: a spatial clustering panel analysis(Springer (Biomed Central Ltd.), 2016-06-02) Rao, Hua-Xiang; Zhang, Xi; Zhao, Lei; Yu, Juan; Ren, Wen; Zhang, Xue-Lei; Ma, Yong-Cheng; Shi, Yan; Ma, Bin-Zhong; Wang, Xiang; Wei, Zhen; Wang, Hua-Fang; Qiu, Li-Xia; Department of Epidemiology, Richard M. Fairbanks School of Public HealthBACKGROUND: Tuberculosis (TB) is the notifiable infectious disease with the second highest incidence in the Qinghai province, a province with poor primary health care infrastructure. Understanding the spatial distribution of TB and related environmental factors is necessary for developing effective strategies to control and further eliminate TB. METHODS: Our TB incidence data and meteorological data were extracted from the China Information System of Disease Control and Prevention and statistical yearbooks, respectively. We calculated the global and local Moran's I by using spatial autocorrelation analysis to detect the spatial clustering of TB incidence each year. A spatial panel data model was applied to examine the associations of meteorological factors with TB incidence after adjustment of spatial individual effects and spatial autocorrelation. RESULTS: The Local Moran's I method detected 11 counties with a significantly high-high spatial clustering (average annual incidence: 294/100 000) and 17 counties with a significantly low-low spatial clustering (average annual incidence: 68/100 000) of TB annual incidence within the examined five-year period; the global Moran's I values ranged from 0.40 to 0.58 (all P-values < 0.05). The TB incidence was positively associated with the temperature, precipitation, and wind speed (all P-values < 0.05), which were confirmed by the spatial panel data model. Each 10 °C, 2 cm, and 1 m/s increase in temperature, precipitation, and wind speed associated with 9 % and 3 % decrements and a 7 % increment in the TB incidence, respectively. CONCLUSIONS: High TB incidence areas were mainly concentrated in south-western Qinghai, while low TB incidence areas clustered in eastern and north-western Qinghai. Areas with low temperature and precipitation and with strong wind speeds tended to have higher TB incidences.Item Theoretical analysis of alendronate and risedronate effects on canine vertebral remodeling and microdamage(2009-05) Wang, Xiang; Erickson, Antonia M; Allen, Matthew R.; Burr, David B.; Martin, R Bruce; Hazelwood, Scott JBisphosphonates suppress bone remodeling activity, increase bone volume, and significantly reduce fracture risk in individuals with osteoporosis and other metabolic bone diseases. The objectives of the current study were to develop a mathematical model that simulates control and 1 year experimental results following bisphosphonate treatment (alendronate or risedronate) in the canine fourth lumbar vertebral body, validate the model by comparing simulation predictions to 3 year experimental results, and then use the model to predict potential long term effects of bisphosphonates on remodeling and microdamage accumulation. To investigate the effects of bisphosphonates on bone volume and microdamage, a mechanistic biological model was modified from previous versions to simulate remodeling in a representative volume of vertebral trabecular bone in dogs treated with various doses of alendronate or risedronate, including doses equivalent to those used for treatment of post-menopausal osteoporosis in humans. Bisphosphonates were assumed to affect remodeling by suppressing basic multicellular unit activation and reducing resorption area. Model simulation results for trabecular bone volume fraction, microdamage, and activation frequency following 1 year of bisphosphonate treatment are consistent with experimental measurements. The model predicts that trabecular bone volume initially increases rapidly with 1 year of bisphosphonate treatment, and continues to slowly rise between 1 and 3 years of treatment. The model also predicts that microdamage initially increases rapidly, 0.5–1.5-fold for alendronate or risedronate during the first year of treatment, and reaches its maximum value by 2.5 years before trending downward for all dosages. The model developed in this study suggests that increasing bone volume fraction with long term bisphosphonate treatment may sufficiently reduce strain and damage formation rate so that microdamage does not accumulate above that which is initiated in the first two years of treatment.