7results about How to "Improve imbalance" patented technology

The invention discloses a traditional Chinese medicine tea drink for preventing and treating oral mucosa diseases and a preparation method of the traditional Chinese medicine tea drink. The traditional Chinese medicine tea drink is prepared from 10-15 parts of radix astragali, 8-12 parts of radix codonopsis, 6-10 parts of radix salviae miltiorrhizae, 5-9 parts of radix angelicae sinensis, 3-6 parts of fructus psoraleae, 6-9 parts of rhizoma polygonati, 6-9 parts of radix adenophorae, 6-10 parts of rhizoma atractylodis macrocephalae, 5-9 parts of radix ophiopogonis, 3-5 parts of radix glycyrrhizae, 4-6 parts of pericarpium citri reticulatae and 5-8 parts of herba taraxaci. Aiming at the core pathogenesis of low immunity, long-term deficiency, long-term deficiency and kidney-yang insufficiency of patients suffering from oral mucosa diseases, qi tonifying, blood activating and kidney-qi strengthening are taken as a core treatment method, the formula is scientific and reasonable, all the medicinal materials act synergistically, the overall immune function of the body is adjusted, T lymphocyte subpopulation imbalance and cell factor network disorder are improved, and the curative effect is good. The oral mucosa microcirculation is improved, local inflammation is relieved, the immunity of a patient is improved fundamentally, the recurrence rate of oral mucosa diseases is reduced, and the problems that an existing tea drink is not high in pertinence and limited in curative effect are solved. The tea drink is appropriate in taste, good in compliance, high in safety and suitable for people with various oral mucosa diseases and low immunity.

This application discloses a training method, apparatus, electronic device, and storage medium for a neural network, belonging to the field of data processing technology. The method includes: obtaining a first predicted probability value predicted by a first neural network among two adjacent neural networks in M ​​neural networks when a training sample is used as input; a second neural network in the M neural networks uses the first predicted probability value as the initial value of the input weights to perform weighted processing on the training samples to obtain a weighted result; the second neural network obtains a calculation result based on the weighted result and a preset deviation value, and determines the prediction error value between the calculation result and the actual result of the training samples based on the calculation result and a preset loss function, wherein the loss function has a reward score; updating the reward score based on the prediction error value; and updating the input weights and deviation value based on the prediction error value and the updated reward score until the loss function converges, at which point the training of the second neural network ends.

The present application relates to the technical field of bellows preparation, and particularly relates to a cathode device for preparing an electrodeposited bellows and a preparation method, which comprises a frame body, a core mold assembly, a cathode wire assembly and a power transmission assembly. The frame body is internally provided with the core mold assembly, part of the cathode wire assembly and the power transmission assembly. The inner wall of the cylindrical groove of the frame body is provided with annular sawteeth. The core mold assembly comprises a horizontal connecting rod and a core mold body, the other end of the core mold body extends into the frame body, and each aluminum alloy core mold of the core mold body is detachably connected with a nylon external gear meshing with the annular sawteeth at the end away from the horizontal connecting rod. The present application can effectively control the rotating speed of a single core mold during the electrodeposition process, ensure the stable and uniform rotation of the core mold in the circumferential direction, thereby improving the imbalance of the circumferential current density and ion transmission conditions during the electrodeposition process, and ensuring that the prepared single-layer or multi-layer bellows has a uniform wall thickness in the circumferential direction.

The application discloses a PCB defect image detection method based on an improved deep learning algorithm. In view of the deficiencies of the YOLOv3 deep convolutional neural network model, such as imbalance of positive and negative samples, feature expression of small defects of the PCB, and extraction of important feature information of the image, the application proposes an improvement method of replacing the MSELoss function in the original YOLOv3 model with the FocalLoss function, so as to dynamically control the weights of positive and negative samples and difficult and easy classification samples. Meanwhile, the application embeds the SPP module in the branch small target detection head and parallelly integrates the CBAM module into the YOLOv3 model, so that the model can pay more attention to the defect information in the image, thereby improving the overall feature extraction capability of the model. The method can detect different types of PCB defect images, and compared with the original YOLOv3 model, the sensitivity and other indicators are improved, has good performance in the PCB defect detection task, can reduce the missed detection rate and the false detection rate, and better realizes the automatic and intelligent detection of the PCB defects.

The utility model discloses a sewage treatment dosing system which comprises at least one sodium hypochlorite adding line, the sodium hypochlorite adding line comprises a sodium hypochlorite storage tank, a pumping device, a valve, a low-pressure pipe and a check valve which are sequentially connected through a pipeline, the outlet end of the check valve is connected with a dosing pipe, and the dosing pipe extends to a dosing point for dosing. The pipeline comprises a main pipeline connected with the sodium hypochlorite storage tank and a plurality of branch pipelines, the pumping device, the valve, the low-pressure pipe and the check valve are all located on the branch pipelines, and a back pressure valve is arranged on the pipeline between the valve and the low-pressure pipe. The back pressure valves are arranged at the pipeline positions of the branch pipes, and the problem that the pesticide amount of the branch pipes is unbalanced is greatly solved through adjustment of the back pressure valves; in addition, the pressure of the valve element of the back pressure valve is set to be of an automatic adjusting structure, adjustment can be conducted according to needs in the using process so that different opening degrees can be provided, in addition, the back pressure valve can also be used as a control valve, and forward and reverse flushing can be provided when cleaning is needed.

This invention provides the application and method of Streptomyces S16-1 in promoting the growth and salt stress tolerance of Leymus chinensis, belonging to the field of microbial technology. Streptomyces S16-1 was isolated from saline soil, with the preservation number CCTCC M 20251940, and its 16S rDNA sequence is shown in SEQ ID NO:1. The Streptomyces S16-1 has functional activities such as salt and alkali tolerance, phosphorus solubilization, nitrogen fixation, and production of 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase. The microbial fertilizer is obtained by expanding the culture of Streptomyces S16-1. Compared with chemical fertilizers, the microbial fertilizer used in this invention is more environmentally friendly. It can not only improve soil fertility and help plants improve their salt and alkali resistance, but also promote the balance and diversity of soil microbial communities, which helps maintain the health and stability of the soil ecosystem.

This application relates to an ultra-wideband dual-mode mixer circuit with an on-chip balun. The circuit includes: an LO port of a local oscillator differential balun unit connected to the signal output from the local oscillator source in a vector network analysis (VNA) system; an RF port of a mixer unit connected to the test signal preprocessed by the VNA system; an output port of the local oscillator differential balun unit connected to the local oscillator input port of the mixer unit; and an output port of the mixer unit connected to the input port of an intermediate frequency (IF) amplifier unit. The local oscillator signal in the VNA system is processed by the local oscillator differential balun unit to obtain two local oscillator differential signals. The high-frequency test signal preprocessed by the VNA system is input through the RF port of the mixer unit to obtain two radio frequency (RF) differential signals. The two RF differential signals are mixed with the two local oscillator differential signals to obtain the desired IF signal. The IF signal is finally amplified by the IF amplifier unit and output from the output port of the IF amplifier unit, thus solving the problems of low integration, large size, and poor isolation in ultra-wideband mixers.