7 results about "Cell Migration Process" patented technology

The invention discloses a semi-supervised optical flow prediction method for cell migration path tracking. The technical problem that a model obtained by directly using existing synthetic optical flow data for training is difficult to be directly applied to the field of cell tracking is solved. Firstly, in view of the limitation that an existing convolution kernel is fixed under the condition of processing non-rigid motion of cells, an anisotropic convolution block of a novel convolution mode is provided, and details of motion edges in a cell image are accurately modeled; and then, in order to solve the problem that movement of the optical flow is difficult to distinguish due to dense textures in a cell image sequence, a multi-dimensional feature fusion mechanism is built, and the mechanism integrates multi-dimensional feature relationships in the horizontal direction, the vertical direction and the channel direction so as to ensure that the model can capture dynamic features in the cell image more comprehensively and accurately. Secondly, aiming at the problem of cell image label missing, a semi-supervised learning method is explored so as to reduce dependence on accurate labels.

This invention discloses a phase compensation method for ship targets using ISAR based on block phase gradient autofocus. The steps include: pulse compression; range cell migration correction; range-oriented block segmentation; block phase compensation; calculation of the offset between adjacent image blocks; and image block alignment and stitching. This invention performs range-oriented block segmentation of the target echo, overcoming the shortcomings of existing technologies that ignore the spatial variation of rotational phase error, leading to defocusing in ship imaging, thus improving the accuracy of phase compensation and achieving good image focusing effect. Because this invention uses a phase gradient autofocus algorithm to compensate for the phase error within each block, and then uses a cross-correlation method to align and stitch the images of each block region, it overcomes the shortcomings of parameter estimation methods, such as complexity, time consumption, and poor real-time performance, and has the advantages of simple implementation, high efficiency, and strong real-time performance.

A semi-supervised optical flow prediction method for cell migration path tracking is proposed. It addresses the technical challenge of directly applying models trained using existing synthetic optical flow data to cell tracking. First, recognizing the limitations of existing convolutional kernels fixed in handling non-rigid cell motion, a novel heterogeneous convolutional block with a specific convolutional mode is proposed to accurately model the details of motion edges in cell images. Second, to address the difficulty in distinguishing motion in cell image sequences due to dense textures, a multi-dimensional feature fusion mechanism is established. This mechanism integrates multi-dimensional feature relationships across horizontal, vertical, and channel dimensions, ensuring the model can more comprehensively and accurately capture dynamic features in cell images. Third, to address the issue of missing cell image labels, a semi-supervised learning method is explored to reduce reliance on accurate labels.

The application discloses a cell migration method and device, a base station and a storage medium. The method comprises the following steps: in the case that a condition for starting cell migration is reached, a first base station determines a first change feature; the first change feature represents a change feature corresponding to historical service load of a first baseband card of the first base station in a first time period; a starting time point of the first time period represents a time point when the service load on the first baseband card reaches the condition for starting cell migration; based on the first change feature, the first base station controls the first baseband card to start cell migration or maintain a normal working state.

The application discloses an antibacterial fiber membrane releasing peroxide in situ and a preparation method thereof, and relates to the technical field of fiber membrane preparation.The fiber membrane comprises a fiber membrane core layer and a fiber membrane shell layer coated outside the fiber membrane core layer, and metal peroxide nanoparticles are dispersed in the fiber membrane shell layer; the fiber membrane core layer is a non-water-soluble high polymer, and the fiber membrane shell layer is a water-soluble high polymer and a non-water-soluble high polymer.The application provides a large number of adhesion sites by combining the fiber structure and instant patterning at a wound site, promotes cell adhesion and guides cell migration, and metal peroxide nanoparticles released along with the patterning process react with moisture in the internal environment to release hydrogen peroxide, oxygen and metal ions, thereby achieving the effects of sterilization and promoting blood vessel regeneration simultaneously.The application solves the problem that the existing skin repair materials cannot achieve sterilization and cell growth promotion.

A terminal controls cell migration of the terminal in accordance with low-layer-based mobility control. A terminal receives, from a network, a message including an execution condition of a cell migration. A terminal executes cell migration when a stop execution condition applied when a source cell as a migration source or a candidate cell as a migration destination transitions to a stop state is satisfied.

A method of controlling scaling in a virtualized radio access network (vRAN), including determining a cell migration situation based on information about a key performance indicator (KPI) of a first pod; based on the cell migration situation, transmitting, to the first pod, at least one cell migration message related to a second pod with which the first pod is to perform cell migration; and in case that the cell migration being terminated, receiving a cell migration termination message from the first pod.