Abstract: A device for testing overall anchorage performance of a basalt fiber reinforced plastic (BFRP) anchor cable includes an anchor cable anchoring system and a data acquisition system. The anchor cable anchoring system includes a test bed, BFRP arranged over the test bed, and a distributed optical fiber bonded to a surface of the BFRP, the test bed being provided with an anchoring section at one end and an outer anchoring section at the other end, the anchoring section anchors one end of the BFRP, and the outer anchoring section anchors the other end of the BFRP. The data acquisition system includes a modem and a grating connected to two ends of the distributed optical fiber in series, and a center hole jack and a dynamometer arranged between the outer anchoring section and an end of the test bed, and the BFRP penetrates the center hole jack and the dynamometer.

Abstract: The present application relates to the technical field of vehicle control, and in particular, to a driving world model based on a brain-like neural circuit. The driving world model includes: a perception module, an environment memory module, a brain-like neural circuit network module, and a convolutional network module; the perception module includes a two-dimensional feature encoding unit, a three-dimensional feature encoding unit, a summing pooling unit which are connected in sequence; the environment memory module is configured to acquire a current moment and memorize environment dynamics information; the brain-like neural circuit network module is configured to establish a brain-like neural circuit network. The present application uses a monocular camera image as an input image.

Abstract: The present invention relates to a learning-oriented transferable automatic driving method and system driven by a world model. The method includes the following steps: constructing a simulation environment; collecting a large batch of data in the simulation environment, and collecting a small batch of data in the real environment; constructing a world model, and performing model training in the simulation environment by using the large batch of data, wherein the world model takes a camera image as an input to model an environment by using a generative world model; storing and transmitting historical moment information by hidden variables, and outputting an aerial view and a control instruction; and performing domain adaptive transferring training in the real environment on the basis of the small batch of data, and deploying the model in an autonomous vehicle in the real world to achieve virtuality-to-reality transferring general integrated automatic driving.

Abstract: The present disclosure provides a method for generating a backbone network, an apparatus for generating a backbone network, a device, and a storage medium. The method includes: acquiring a set of a training image, a set of an inference image, and a set of an initial backbone network; training and inferring, for each initial backbone network in the set of the initial backbone network, the initial backbone network by using the set of the training image and the set of the inference image, to obtain an inference time and an inference accuracy of a trained backbone network in an inference process; determining a basic backbone network based on the inference time and the inference accuracy of the trained backbone network in the inference process; and obtaining a target backbone network based on the basic backbone network and a preset target network.

Abstract: Provided is a lightweight model training method, an image processing method, a device and a medium. The lightweight model training method includes: acquiring first and second augmentation probabilities and a target weight adopted in an e-th iteration; performing data augmentation on a data set based on the first and second augmentation probabilities respectively, to obtain first and second data sets; obtaining a first output value of a student model and a second output value of a teacher model based on the first data set; obtaining a third output value and a fourth output value based on the second data set; determining a distillation loss function, a truth-value loss function and a target loss function; training the student model based on the target loss function; and determining a first augmentation probability or target weight to be adopted in an (e+1)-th iteration in a case of e is less than E.

Abstract: A thermal power unit-flywheel energy storage cooperative frequency regulation control method and system is provided, which belongs to the technical field of a power grid. First, a real-time output increment of a thermal power unit is predicted, then a real-time frequency regulation power instruction of a flywheel energy storage system is determined based on the predicted real-time output increment of the thermal power unit, and finally the frequency regulation power instruction of the thermal power unit is determined by a difference adjustment coefficient of a governor and a grid frequency deviation. The thermal power unit and flywheel energy storage system is cooperatively controlled by frequency regulation based on the real-time output increment predicted value of the unit, which realizes self-adaptive adjustment of output of the flywheel energy storage system under dynamic working conditions, and improves the grid frequency stability and operation safety of the thermal power unit.

Abstract: The disclosure relates to an aluminum alloy and a component part prepared therefrom. The aluminum alloy comprises: 7-9 wt% of silicon (Si), 0.15-0.45 wt% of chromium (Cr), 0.1-0.3 wt% of vanadium (V), at least 0.01 wt% of strontium (Sr), 0.1-0.2 wt% of titanium (Ti), 0-0.5 wt% of manganese (Mn), 0-0.8 wt% of iron (Fe) and the balance being aluminum and inevitable impurities. The aluminum alloy of the disclosure can be exempt from heat treatment process after casting in the processing process, so as to contribute to energy conservation and emission reduction, and the component part prepared therefrom can achieve desired mechanical properties.

Abstract: The disclosure relates to an aluminum alloy and a component part prepared therefrom. The aluminum alloy comprises: 7-9 wt % of silicon (Si), 0.2-0.7 wt % of manganese (Mn), 0.09-0.4 wt % of iron (Fe), 0.1-0.3 wt % of vanadium (V), 0.1-0.2 wt % of titanium (Ti), 0.01-0.03 wt % of strontium (Sr), and the balance being aluminum and inevitable impurities, wherein the weight ratio of the manganese (Mn) to the iron (Fe) is not less than 1. The aluminum alloy of the disclosure can be exempt from heat treatment process after casting in the processing process, so as to contribute to energy conservation and emission reduction, and the component part prepared therefrom can achieve desired mechanical properties.

Abstract: The present invention discloses the applications of a low molecular polypeptide ZY4 in preparing drugs for anti-acnes, anti-infection, anti-cancer and cosmetics. The low molecular polypeptide ZY4 comprises 17 amino acid residues, with a molecular weight of 2374.0 Da, an isoelectric point of 10.74, and an amino acid sequence of SEQ ID NO:1. The low molecular polypeptide ZY4 in the invention is artificially synthesized, with the advantages of small molecular weight and convenient artificial synthesis. The experiments have showed that the polypeptide ZY4 has obvious antibacterial effect and has significant therapeutic effect on acnes. The polypeptides can inhibit the growth of tumor cells and kill the tumor cells. The low molecular polypeptide ZY4 can be used in the preparation of medicaments or cosmetics having the effect of anti-infective, anti-tumor or anti-acne.