Abstract: System and method for sensing movement such as chest movement of each of a plurality of target test subjects by: transmitting, at each of N transmitting antennas (TXs) of a phased multiple-input multiple-output (phased-MIMO) radar, a common frequency modulated continuous wave (FMCW) signal in each of a plurality of time division multiplex (TDM) slots, each TDM slot having associated with it a respective weight selected in accordance with a transmit steering vector configured to cause a coherent summation of transmitted signal in a desired direction ?0 toward at least one target; receiving target-reflected energy associated with the transmitted FMCW signals at a virtual array formed by stacking signal from P TDM slots received via M receiving antennas (RXs) of the phased-MIMO radar; and processing an output of the virtual array to extract therefrom signal received from the desired direction ?0 to determine thereby target movement in the desired direction ?0.

Abstract: A formulation includes a plurality of polymers including a hydrophobic polymer backbone (for example, formed via radical polymerization), a first plurality of pendant groups attached to the hydrophobic polymer backbone and including at least one cationic group, and a second plurality of pendant groups attached to the hydrophobic polymer backbone and including at least one hydrophilic polymer, a first therapeutic compound, and a second therapeutic compound, wherein the second therapeutic compound is different from the first therapeutic compound and includes a nucleic acid.

Abstract: The present disclosure provides a drop impact prediction method and system for heavy equipment airdrop based on a neural network. The drop impact prediction method includes the following steps: S1: acquiring a plurality of sets of sample data by using a finite element model for drop simulation of heavy equipment airdrop; S2: determining structural parameters of a BP neural network, and pre-processing the structural parameters; S3: constructing a BP neural network model; and S4: predicting a drop impact situation of heavy equipment airdrop in an actual application process by using the trained BP neural network model.

Abstract: A method for image processing, an electronic device, and a storage medium are provided. The method includes: acquiring a current frame image captured by a camera and motion parameters of a gyroscope when capturing the current frame image, determining a region of interest of the current frame image, determining and displaying, based on the region of interest and the motion parameters, a display area of a next frame image. A region of interest of a previous frame image and a motion state of a gyroscope when capturing the previous frame image are determined, a display area of a subsequent frame image is determined based on the region of interest and the motion state; the display area is no longer fixed at a center of a field of view, but rather adjusted based on the region of interest and the motion state, thus facilitating tracking of an object.

Abstract: The invention relates to a method and means for the non-invasive diagnosis of type II diabetes mellitus. The glycation state is determined in at least one glycation position of selected plasma proteins.

Abstract: Embodiments of the present invention provide a method and a system for detecting a malicious code. The method includes obtaining first system information and second system information, and detecting the malicious code by identifying difference between the first system information and the second system information, which thus can detect an unknown malicious code, improve the system security, and can be easily implemented.