Assessing the effects of accumulated Cd(II) on seed germination and root development of Arabidopsis thaliana

In this study, Arabidopsis thaliana was used as a model system to assess the toxic effects of cadmium on plant development and growth. The germination and growth of A. thaliana was inhibited by Cd(II), and the inhibitory effect was dosage-dependent. The significant decrease of germination rates and root growths of A. thaliana were observed from 50 mg/L and 25 mg/L of CdCl2, respectively. Although both shoot and root growths were suppressed by Cd(II), root developments were more sensitive to Cd(II) than shoot developments, as evidenced by shoot growths observed over 50 mg/L of CdCl2. In the concordance to this result, it was also observed that the expression of DR5::VENUS, a visual marker of auxin response, was dependent on the Cd(II) concentration and was strongly reduced from 5 mg/L of CdCl2. In addition, the E. coli-based biosensors were employed to quantify accumulated Cd(II) in plants to understand the correlation between toxic effects and Cd(II) in plants. As a result, it was revealed that 0.012 mg/g and 0.138 mg/g of Cd(II) in dried plants were corresponded to the concentration inhibiting root developments and root growths, respectively. Although it needs further investigations, the findings play a significant role in assessing the toxic effects of Cd(II) based on the relationship between the toxic effects and accumulated Cd(II) concentrations in plants.

Visual Calibration for Multiview Laser Doppler Speed Sensing

We present a novel calibration method for a multi-view laser Doppler speed sensing (MLDSS) system. In contrast with the traditional method where only the laser geometry is independently calibrated, the proposed method simultaneously optimizes all the laser parameters and directly associates the parameters with a motion sensing model. By jointly considering the consistency among laser Doppler velocimetry, the laser geometry and a visual marker tracking system, the proposed calibration method further boosts the accuracy of MLDSS. We analyzed the factors influencing the precision, and quantitatively evaluated the efficiency of the proposed method on several data sets.