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642 results on '"Wu, Jiaping"'

152. Bayesian maximum entropy interpolation of sea surface temperature data: A comparative assessment.

Author

Gao, Zekun, Jiang, Yutong, He, Junyu, Wu, Jiaping, and Christakos, George

Subjects
OCEAN temperature, MAXIMUM entropy method, INTERPOLATION, LATITUDE, STANDARD deviations, OCEAN-atmosphere interaction, KRIGING, OCEAN dynamics
Abstract

Sea surface temperature (SST) is an important oceanography attribute that has been used to study ocean climatic conditions, ocean dynamics and air-sea interactions. In the present work, the Bayesian maximum entropy (BME) method was used to interpolate a FY-3 C /VIRR satellite dataset in the region with coordinates 120°-150°W and 45°-60°S and during January 2020. A novel approach of constructing valuable soft data was developed by combining BME interpolation with highly correlated SST day and night data differences. The BME interpolation accuracy was assessed by cross-validation, and the results showed that the average RMSE (root mean squared error) was 0.700 and the average bias was 0.441°C. Furthermore, using the Argo data as a basis of comparison, the coverage and accuracy of the BME interpolation of the FY-3 C/VIRR satellite SST dataset were compared numerically with those of the Ordinary Kriging (OK) interpolation of the FY-3 C/VIRR satellite SST dataset and the Optimum Interpolation Sea Surface Temperature (OISST) of the AVHRR satellite SST dataset. It was found that BME had the best SST interpolation performance among the three methods with the lowest average bias and the largest correlation coefficient. Although OISST had a full product coverage rate overall (due to its use of more perfect treatment means), BME's coverage rate (97.5%) considerably improved that of the FY-3 C/VIRR SST data. Also, both the BME and OK products maintained a 12hrs temporal resolution and a 0.05 decimal degrees longitude/latitude spatial resolution, which is an improvement over OISST data with a 24hrs time resolution and a 0.25 decimal degrees longitude/latitude spatial resolution. Another advantage of BME is that because of its broad theoretical support its performance in practice can be improved further as more knowledge sources become available (which can only be incorporated by BME). [ABSTRACT FROM AUTHOR]

Published
2022
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165. Stocks and losses of soil organic carbon from Chinese vegetated coastal habitats.

Author

Fu, Chuancheng, Li, Yuan, Zeng, Lin, Zhang, Haibo, Tu, Chen, Zhou, Qian, Xiong, Kuanxu, Wu, Jiaping, Duarte, Carlos M., Christie, Peter, and Luo, Yongming

Subjects
SOIL erosion, CARBON in soils, CLIMATE change mitigation, CARBON cycle, SEDIMENTATION & deposition
Abstract

Global vegetated coastal habitats (VCHs) represent a large sink for organic carbon (OC) stored within their soils. The regional patterns and causes of spatial variation, however, remain uncertain. The sparsity and regional bias of studies on soil OC stocks from Chinese VCHs have limited the reliable estimation of their capacity as regional and global OC sinks. Here, we use field and published data from 262 sampled soil cores and 181 surface soils to report estimates of soil OC stocks, burial rates and losses of VCHs in China. We find that Chinese mangrove, salt marsh and seagrass habitats have relatively low OC stocks, storing 6.3 ± 0.6, 7.5 ± 0.6, and 1.6 ± 0.6 Tg C (±95% confidence interval) in the top meter of the soil profile with burial rates of 44 ± 17, 159 ± 57, and 6 ± 45 Gg C/year, respectively. The variability in the soil OC stocks is linked to biogeographic factors but is mostly impacted by sedimentary processes and anthropic activities. All habitats have experienced significant losses, resulting in estimated emissions of 94.2–395.4 Tg CO2e (carbon dioxide equivalent) over the past 70 years. Reversing this trend through conservation and restoration measures has, therefore, great potential in contributing to the mitigation of climate change while providing additional benefits. This assessment, on a national scale from highly sedimentary environments under intensive anthropogenic pressures, provides important insights into blue carbon sink mechanism and sequestration capacities, thus contributing to the synchronous progression of global blue carbon management. [ABSTRACT FROM AUTHOR]

Published
2021
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182. New Generation Nanomedicines Constructed from Self-Assembling Small-Molecule Prodrugs Alleviate Cancer Drug Toxicity

Author

Wang, Hangxiang, primary, Lu, Zhongjie, additional, Wang, Lijiang, additional, Guo, Tingting, additional, Wu, Jiaping, additional, Wan, Jianqin, additional, Zhou, Liqian, additional, Li, Hui, additional, Li, Zhen, additional, Jiang, Donghai, additional, Song, Penghong, additional, Xie, Haiyang, additional, Zhou, Lin, additional, Xu, Xiao, additional, and Zheng, Shusen, additional

Published
2017
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194. Cancer Nanomedicines Stabilized by π-π Stacking between Heterodimeric Prodrugs Enable Exceptionally High Drug Loading Capacity and Safer Delivery of Drug Combinations

Author

Wang, Hangxiang, primary, Chen, Jianmei, additional, Xu, Chang, additional, Shi, Linlin, additional, Tayier, Munire, additional, Zhou, Jiahui, additional, Zhang, Jun, additional, Wu, Jiaping, additional, Ye, Zhijian, additional, Fang, Tao, additional, and Han, Weidong, additional

Published
2017
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198. Ultrasensitive electrocatalytic detection of COX-2 rs20417: relying on 3D interconnected architecture of Pt-LSSUs@PAA nanostructures for sensor interface modification.

Author

Yang, Yan and Wu, Jiaping

Subjects
*PEPTIDE nucleic acids, *ELECTROLYTIC reduction, *ASPIRIN, *ELECTROPHILES, *OXIDATION-reduction reaction, *NANOSTRUCTURES, *CARDIOVASCULAR agents
Abstract

Mutated COX-2 has become the new molecular marker of aspirin resistance. However, there is still a technical 'bottleneck' for direct and sensitive detection of circulating COX-2 mutant gene. In this work, we reported a simple and ultrasensitive electrochemical method for COX-2–765G/C (rs20417) detection for the first time. Polyallylamine (PAA) functionalised Pt nanostructures with long-spined sea urchin-like morphology (Pt-LSSUs@PAA) was synthesised by a simple chemical method for the construction of nano-sensing interface. Ru(NH3)63+ is used as a primary electron acceptor that is electrostatically attracted to peptide nucleic acid modified electrodes and Fe(CN)63− is introduced into the redox system as secondary electron acceptor to regenerate Ru3+ after electrochemical reduction for multiple redox cycles. Different pulse voltammetry was applied to record the electrochemical signals. Under optimal conditions, the DNA sensors showed a wide linear relationship, from 10 fM to 1 nM, with detection limits of 3.3 fM (S/N = 3). This study will provide the basis for the precise use of aspirin, and it has important guiding value for individual drug testing of cardiovascular disease. [ABSTRACT FROM AUTHOR]

Published
2019
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200. Remote sensing mapping of macroalgal farms by modifying thresholds in the classification tree.

Author

Zheng, Yuhan, Duarte, Carlos M., Chen, Jiang, Li, Dan, Lou, Zhaohan, and Wu, Jiaping

Subjects
REMOTE sensing, REMOTE-sensing images, VEGETATION mapping, CLASSIFICATION, FARMS
Abstract

Remote sensing is the main approach to map aquatic vegetation, and classification tree (CT) is superior to various classification methods. Based on previous studies, modified CT can be developed from traditional CT by adjusting the thresholds based on the statistical relationship between spectral features to classify different images without ground-truth data. However, no studies have yet employed this method to resolve marine vegetation. In this study, three Gao-Fen 1 satellite images obtained on 30 January 2014, 5 November 2014 and 21 January 2015 were selected, and two features were then employed to extract macroalgae farms. Results show that the overall accuracies of traditional CTs for three images are 92.0, 94.2 and 93.9%, respectively, whereas those of the two corresponding modified CTs for images obtained on 21 January 2015 and 5 November 2014 are 93.1 and 89.5%, respectively. This indicates modified CTs can map macroalgae with multi-date imagery and monitor their spatiotemporal distribution in coastal environments. [ABSTRACT FROM AUTHOR]

Published
2019
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