6results about How to "Build security" patented technology

The invention discloses a carbon emission prediction and novel power system planning method and system in the urban power field. The method comprises the following steps: calculating the energy demand quantity of each department according to the urban total production value GDP, population, industrial structure and energy consumption characteristic data; calculating the total carbon emission amount of the electric power department based on the energy demand in combination with the carbon emission factor; on the basis of the total carbon emission amount of an electric power department, urban energy endowment, emission reduction tasks, emission reduction policies and power generation technology improvement are considered, and on the basis of economy, population and electricity consumption parameters of an electric power demand end, various development situations of low carbon, zero carbon and negative carbon of an electric power system are designed; predicting carbon emission and carbon emission reduction corresponding to the demand end in each scene, and obtaining an emission reduction path from the demand end; and establishing a power system multi-scene optimization planning model by taking the lowest net present value of the total cost of the system as an objective function and taking urban power related constraints as constraint conditions, and calculating a power generation installed capacity development path meeting the system cost and the related constraints.

The present invention discloses a live transmission operation system and method based on drone and electric lifting technology, which mainly relates to the field of high-altitude live transmission operation. It includes a drone carrying component, an anti-fall protection component, and an insulating rope component arranged in sequence from top to bottom. The beneficial effect of the present invention is that it can solve the technical problems of limited operation range and insufficient operation safety when performing live transmission operation on existing overhead lines, realize operation operation at any position of the overhead line, and the constructed operation system is safer and more solid, which greatly improves the safety of high-altitude live transmission operation.

The invention discloses a recombinant herpes simplex virus, a neural circuit tracing virus tool and application. The invention discloses a clinical strain of a herpes simplex virus HSV1-CH001, and the collection number of the clinical strain is CCTCC (China Center For Type Culture Collection) NO: V202463. The invention also discloses a recombinant herpes simplex virus, which is obtained by recombining and inserting an exogenous gene expression cassette into the genome of the herpes simplex virus HSV1-CH001. The herpes simplex virus HSV1-CH001 is recombined and inserted into a fluorescent protein gene or other exogenous genes, a clinical strain virus is subjected to visual and other recombination transformation to construct a novel tool virus vector, and efficient tracing of neural circuit markers and exogenous gene delivery expression can be achieved.

This invention relates to the field of biomedical materials technology. It discloses a metal-organic hydrogel-mediated soluble microneedle patch, its preparation method, and its applications. The microneedle patch comprises a matrix and needles, wherein the matrix and needles contain a metal-organic hydrogel, polydimethylsiloxane, and a poorly soluble target drug. This application innovatively applies a metal-organic hydrogel to the preparation of a soluble microneedle patch, constructing an amphiphilic matrix with polydimethylsiloxane. This enables the preparation of soluble microneedle formulations containing uniformly distributed poorly soluble drugs, expanding the application scenarios for poorly soluble drugs and improving resource utilization. It has significant value in the formulation preparation of poorly soluble drugs.

The invention provides a process industry soft measurement modeling method for cross-production-line transverse information fusion, and the method is based on an end-to-end neural network model which is formed by connecting a time sequence feature extraction network in a self-encoder form and a regression network in a front-and-back manner. A two-stage soft measurement model training strategy of pre-training-time sequence feature information fusion training is provided, and a performance index soft measurement model is safely, effectively and accurately established on a process industrial production line with insufficient data accumulation by introducing data of the production line with rich data accumulation. Therefore, soft measurement is carried out on some performance indexes which are difficult to directly measure or high in measurement cost in the process industry, and reference and guidance are provided for monitoring, optimizing and controlling various parameters in the production process of the process industry.

The invention discloses a low-voltage distribution network power failure area studying and judging method based on graph neural network and fuzzy feature fusion, and the method comprises the following steps: collecting multi-source measurement data, carrying out the normalization, time alignment and feature construction, and forming node features; modeling the abnormal degree of the measured data based on a fuzzy membership function, and fusing multi-dimensional observation information by using soft union operation to generate a user side-superior side multi-source fuzzy evidence; introducing a time decay adjacency matrix, a node type embedding matrix and a power balance consistency constraint, and establishing a power distribution network dynamic representation model based on a space-time diagram neural network; and the node features are input into a double-task output structure, so that intelligent identification and user-level research and judgment of the power failure area are realized. According to the method, a fuzzy evidence fusion mechanism and a physical consistency constraint mechanism are introduced into a space-time diagram neural network framework, a dynamic multi-layer research and judgment system for the low-voltage power distribution network is constructed, and collaborative optimization of a data layer, a model layer and a reasoning layer is achieved.