scholarly journals Electrokinetic supercharging: stacking mechanism and applications to high-sensitivity analysis from small ion to biopolymers for capillary and microchip electrophoresis.

2008 ◽  
Vol 52 (3) ◽  
pp. 117-122
Author(s):  
Zhongqi Xu ◽  
Kazuaki Ito ◽  
Akihiro Arai ◽  
Takeshi Hirokawa
2021 ◽  
Vol 13 (2) ◽  
pp. 188
Author(s):  
Tingting Li ◽  
Irena Hajnsek ◽  
Kun-Shan Chen

Soil moisture is one of the vital environmental variables in the land–atmosphere cycle. A study of the sensitivity analysis of bistatic scattering coefficients from bare soil at the Ku-band is presented, with the aim of deepening our understanding of the bistatic scattering features and exploring its potential in soil moisture retrieval. First, a well-established advanced integral method was adopted for simulating the bistatic scattering response of bare soil. Secondly, a sensitivity index and a normalized weight quality index were proposed to evaluate the effect of soil moisture on the bistatic scattering coefficient in terms of polarization and angular diversity, and the combinations thereof. The results of single-polarized VV data show that the regions with the maximum sensitivity and high quality index, simultaneously, to soil moisture are in the forward off-specular direction. However, due to the effect of surface roughness and surface autocorrelation function (ACF), the single-polarized data have some limitations for soil moisture inversion. By contrast, the results of two different polarization combinations, as well as a dual-angular simulation of one transmitter and two receivers, show significant estimation benefits. It can be seen that they all provide better ACF suppression capabilities, larger high-sensitivity area, and higher quality indices compared to single-polarized estimation. In addition, dual polarization or dual angular combined measurement provides the possibility of retrieving soil moisture in backward regions. These results are expected to contribute to the design of future bistatic observation systems.


Bioanalysis ◽  
2018 ◽  
Vol 10 (24) ◽  
pp. 2047-2067 ◽  
Author(s):  
Weiwei Han ◽  
Yajun Zheng ◽  
Theoneste Muyizere ◽  
Zhiping Zhang

2013 ◽  
Vol 17 (2) ◽  
pp. 461-478 ◽  
Author(s):  
L. Loosvelt ◽  
H. Vernieuwe ◽  
V. R. N. Pauwels ◽  
B. De Baets ◽  
N. E. C. Verhoest

Abstract. Compositional data, such as soil texture, are hard to deal with in the geosciences as standard statistical methods are often inappropriate to analyse this type of data. Especially in sensitivity analysis, the closed character of the data is often ignored. To that end, we developed a method to assess the local sensitivity of a model output with resect to a compositional model input. We adapted the finite difference technique such that the different parts of the input are perturbed simultaneously while the closed character of the data is preserved. This method was applied to a hydrologic model and the sensitivity of the simulated soil moisture content to local changes in soil texture was assessed. Based on a high number of model runs, in which the soil texture was varied across the entire texture triangle, we identified zones of high sensitivity in the texture triangle. In such zones, the model output uncertainty induced by the discrepancy between the scale of measurement and the scale of model application, is advised to be reduced through additional data collection. Furthermore, the sensitivity analysis provided more insight into the hydrologic model behaviour as it revealed how the model sensitivity is related to the shape of the soil moistureretention curve.


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