A direct spatial and spectral observation of CdSe and CdSe/CdS quantum dots (QDs) as probes in live cells is performed by using a custom molecular hyperspectral imaging (MHI) system. Water-soluble CdSe and CdSe/CdS QDs are synthesized in aqueous solution under the assistance of high-intensity ultrasonic irradiation and incubated with colon cancer cells for bioimaging. Unlike the traditional fluorescence microscopy methods, MHI technology can identify QD probes according to their spectral signatures and generate coexpression and stain titer maps by a clustering method. The experimental results show that the MHI method has potential to unmix biomarkers by their spectral information, which opens up a pathway of optical multiplexing with many different QD probes.
The atmospheric pollution and air quality issues are getting worse in China, the formation mechanism of aerosols and their environment effects attracted more and more attention. Aerosol Optical Depth (AOD) is one of the most important parameters which can indicate the atmospheric turbidity and aerosol load. High-quality AOD data are significant for the study in the atmospheric environment (i.e., air quality). This paper used MODIS/Terra AOD in 2008 to improve the coverage of MODIS/Aqua AOD, which was based on linear regression analysis model. RMSE between estimation value and Aqua<sub>AOD</sub> detected through satellite is 0.132. The average value of test data was 0.812. The average of regression result was 0.807. It showed that the regression model between AOD<sub>Terra</sub> and AOD<sub>Aqua</sub> worked well. Also, we built two sets of estimation models (MODIS AOD and OMI AOD) through stepwise regression analysis model. One is using OMI AOD and meteorological elements to estimate MODIS AOD. The value of RMSE was 0.113, which represents 13.916% of the average(R<sup>2</sup>=0.782). The other one is using MODIS AOD and meteorological elements to estimate OMI AOD. RMSE of the model is 0.132, which represents 18.182% of the average (R<sup>2</sup>=0.726).
Phycocyanin (PC) in the blue-green algae is usually used to detect the quantity of the blue-green algae, and it has a special absorption at 620nm waveband. Taihu Lake has become severely turbid and eutrophic in recent years. However, the accuracy of empirical models varies highly. Therefore, it is very useful to find a model which can retrieve PC concentration in a good accuracy. In this work, four models (i.e. single band model, the radio model, the first-derivative model, the three-band model and empirical ratio model) were developed based on remote sending reflectance and measured PC concentration in Taihu Lake in May, 2010 to retrieve PC concentration and then to find out which one is the best. The results show that the 2<sup>nd</sup> order polynomial models generally had a better performance than the line models. The three-band model was the most optimal model because it had the highest values of R<sup>2</sup> and the lowest values of RMSE.