Numerical studies of manipulation and separation of microparticles in ODEP-based microfluidic chips.

A novel optical-induced dielectrophoresis (ODEP) method employing a pressure-driven flow for the continuous separation of microparticles is presented in this study. By applying alternate current electric field on conductive indium tin oxide substrate and projecting the light geometry into the photoconductive layer, an inhomogeneous electric field is locally induced. The particles experience the dielectrophoretic force when passing through the lighting area, where the strongest electrical field gradient exists.

Identification and detection of microplastic particles in marine environment by using improved faster R-CNN model.

Microplastics refer to plastic particles measuring less than 5 mm, which has led to serious environmental problem and the detection of these tiny particles is crucial for understanding the corresponding distribution and impact on the marine environment. In this paper, an improved faster region-based convolutional neural network (R-CNN) model was developed for the identification and detection of microplastic particles. In the proposed model, the residual network-50 (ResNet-50) is employed as the backbone with the replacement of the traditional one to enhance the feature extraction capability and the feature pyramid networks (FPN) module is introduced together for solving the multi-scale target detection.

MdWRKY9 overexpression confers intensive dwarfing in the M26 rootstock of apple by directly inhibiting brassinosteroid synthetase MdDWF4 expression.

Dwarfing rootstocks enable high-density planting and are therefore highly desirable in modern apple (Malus domestica) production. M26 is a semi-dwarfing rootstock that is used worldwide, but identifying intensive dwarfing rootstock is a major goal of apple breeding programs. Herein, we show that MdWRKY9 mediates dwarfing by directly inhibiting the transcription of the brassinosteroid (BR) rate-limiting synthetase MdDWF4 and reducing BR production.