The exposure of field-grown maize seedlings to weed volatiles affects their growth and seed quality.

Plants exposed to volatiles emitted from artificially damaged conspecific or heterospecific plants exhibit increased resistance to herbivorous insects. Here, we examined whether volatiles from artificially damaged weeds affect maize growth and reproduction. Seven days after germination, maize seedlings were exposed to volatiles emitted by artificially damaged mugwort (Artemisia indica var. maximowiczii) or tall goldenrod (Solidago altissima) plants either separately, or as a mixture of the two, for seven days. Unexposed seedlings were used as controls. Treated and control seedlings were cultivated in an experimental field without any insecticides applied. Plants exposed to either of the three volatile treatments sustained significantly less damage than controls. Additionally, seedlings exposed to either goldenrod or mixed volatiles produced more leaves and tillers than control plants. Furthermore, a significant increase in the number of ears was observed in plants exposed to the volatile mixture. In all treated plants, ear sugar content was significantly higher than that in the controls. Further, we cultivated seedlings that were either exposed to the volatile mixture or unexposed, under the conventional farming method using pesticides. Similar significant differences were observed for sugar content, number of tillers, leaves, damaged leaves, and ears. Laboratory experiments were conducted to further evaluate the mechanisms involved in the improved performance of volatile-treated plants. A significant reduction in the growth of common armyworm (Mythimna separata) larvae was observed when maize plants were exposed to the volatile mixture. This treatment did not affect the amount of jasmonic acid in the seedlings, whereas salicylic acid content increased upon exposure. The characteristic differences in chemical composition of mugwort and goldenrod volatiles were confirmed and, in turn, the volatile mixture differed significantly from the volatiles of either species.

Development of a Machine Learning-Based Damage Identification Method Using Multi-Point Simultaneous Acceleration Measurement Results.

It is necessary to assess damage properly for the safe use of a structure and for the development of an appropriate maintenance strategy. Although many efforts have been made to measure the vibration of a structure to determine the degree of damage, the accuracy of evaluation is not high enough, so it is difficult to say that a damage evaluation based on vibrations in a structure has not been put to practical use. In this study, we propose a method to evaluate damage by measuring the acceleration of a structure at multiple points and interpreting the results with a Random Forest, which is a kind of supervised machine learning. The proposed method uses the maximum response acceleration, standard deviation, logarithmic decay rate, and natural frequency to improve the accuracy of damage assessment. We propose a three-step Random Forest method to evaluate various damage types based on the results of these many measurements. Then, the accuracy of the proposed method is verified based on the results of a cross-validation and a vibration test of an actual damaged specimen.

Dual-Color Fluorescence Imaging of EpCAM and EGFR in Breast Cancer Cells with a Bull's Eye-Type Plasmonic Chip.

Surface plasmon field-enhanced fluorescence microscopic observation of a live breast cancer cell was performed with a plasmonic chip. Two cell lines, MDA-MB-231 and Michigan Cancer Foundation-7 (MCF-7), were selected as breast cancer cells, with two kinds of membrane protein, epithelial cell adhesion molecule (EpCAM) and epidermal growth factor receptor (EGFR), observed in both cells. The membrane proteins are surface markers used to differentiate and classify breast cancer cells. EGFR and EpCAM were detected with Alexa Fluor® 488-labeled anti-EGFR antibody (488-EGFR) and allophycocyanin (APC)-labeled anti-EpCAM antibody (APC-EpCAM), respectively. In MDA-MB231 cells, three-fold plus or minus one and seven-fold plus or minus two brighter fluorescence of 488-EGFR were observed on the 480-nm pitch and the 400-nm pitch compared with that on a glass slide. Results show the 400-nm pitch is useful. Dual-color fluorescence of 488-EGFR and APC-EpCAM in MDA-MB231 was clearly observed with seven-fold plus or minus two and nine-fold plus or minus three, respectively, on the 400-nm pitch pattern of a plasmonic chip. Therefore, the 400-nm pitch contributed to the dual-color fluorescence enhancement for these wavelengths. An optimal grating pitch of a plasmonic chip improved a fluorescence image of membrane proteins with the help of the surface plasmon-enhanced field.

Enhanced fluorescence microscopy with the Bull's eye-plasmonic chip.

A Bull's eye-plasmonic chip composed of concentric circles was applied to enhanced fluorescence microscopy. Among one dimensional (1-D), 2-D, and Bull's eye periodic structures, the Bull's eye-plasmonic chip provided the most enhanced fluorescence intensity under the epi-fluorescence microscope, because incident light through the objective lens with all azimuthal angles can be effectively applied to the surface plasmon resonance- field (excitation field) and the plasmon-enhanced emission was also effectively collected. In the fluorescence observation of a single nanoparticle, the enhanced fluorescence images for a microsphere with ϕ 2 µm and a nanosphere with ϕ 200 nm were observed. For the nanospheres with ϕ 40 and 20 nm, the fluorescence image, which was undetectable on a glass slide, was observed in a spatial resolution of roughly diffraction limit on the Bull's eye-plasmonic chip. Furthermore, the use of an appropriate pinhole at the aperture stop in the incident optical system improved the fluorescence enhancement. The applicability of a Bull's eye-plasmonic chip to fluorescence imaging was demonstrated.