8results about How to "Easy to explore" patented technology

This invention discloses a method for preparing HVC NPs for the diagnosis and treatment of Parkinson's disease and their applications. The probe HV in the HVC NPs responds to H2O2 and viscosity, utilizing near-infrared fluorescence imaging capabilities to achieve real-time monitoring of Parkinson's disease biomarkers, helping us better understand the occurrence and development of Parkinson's disease. With the assistance of RVG29, the HVC NPs effectively cross the blood-brain barrier. The curcumin within them can reduce cell apoptosis, lower oxidative stress levels, scavenge excess reactive oxygen species, combat inflammation, and reduce α-synuclein aggregation, demonstrating effective anti-Parkinson's disease effects at the cellular and experimental animal levels. This nanomaterial provides a new strategy for integrated research on the diagnosis and treatment of Parkinson's disease.

The utility model discloses a laboratory mouse multi-layer three-dimensional cage structure which comprises a supporting bottom plate for feeding laboratory mice, two ends of the supporting bottom plate extend to form mounting plates, two sides of the supporting bottom plate are provided with side plates, the top of each mounting plate is provided with a separation net, each mounting plate is provided with a ventilation plate, and the other side of each mounting plate is provided with a mounting groove. An inserting groove is formed below the mounting groove, a turning cover plate is mounted in the inserting groove, and a supporting layer is inserted in the inserting groove; a water feeder is installed on the side plate, a feeding opening is further formed in the side plate, and a feeding trough is installed outside the side plate; the multi-layer three-dimensional layout is achieved through the slot type supporting layer, the space utilization rate is increased, the water feeder and the feeding system are independent, the requirement of experimental mice for the activity space is met, and separation net holes are matched with the transparent observation plate to form the three-dimensional activity space; due to the inclined plane design of the feeding trough and the sealing structure of the flip head, the feed residue rate is reduced; the inserting groove type supporting layer is matched with a supporting block locking structure, and the excrement leakage risk is completely eradicated.

The application provides a method for identifying the inflammatory activity grade of ulcerative colitis based on dynamic graph multi-instance learning, which comprises data collection, data preprocessing, dynamic graph multi-instance learning model construction for inflammation activity diagnosis and model evaluation. The data collection mainly comprises collecting pathological images of ulcerative colitis patients, digitizing through a digital scanner, and excluding a part of pathological images containing problems such as blur, discoloration and abnormal staining, and finally determining the grading label of each pathological image by senior gastrointestinal pathology experts. The data preprocessing mainly comprises processing the digital pathological images, converting the digital pathological images into image blocks, then using a visual basic model to extract features from each image block, and finally constructing a dynamic graph multi-instance learning model for training. The application promotes the exploration of the internal relationship of the image blocks input into the WSI, and improves the prediction effect of the model.

The invention discloses a composite material hot press molding production scheduling method based on a man-hour uncertainty dynamic transmission mechanism. In order to solve the problems that in the hot press molding process of the composite material, the working hours have uncertainty and are easily transmitted and amplified among multiple batches and multiple devices, a working hour uncertainty dynamic transmission mechanism is constructed, and the propagation rule of the workpiece machining time uncertainty between a batch layer and a machine layer is described; on this basis, constraints including an equipment capacity constraint and a workpiece and equipment matching constraint are comprehensively considered, a scheduling optimization model with minimization of the maximum completion time as an optimization target is established, and an optimization adjustment strategy is deduced; and finally, designing a mixed meta-heuristic algorithm to solve the scheduling optimization model in combination with an optimization adjustment strategy, thereby realizing efficient search of an optimal scheduling scheme. According to the method provided by the invention, the influence of uncertainty on the design of the production scheduling scheme can be effectively reduced, and the scheduling efficiency and stability of the composite material hot press molding process are improved.

This invention relates to a dieless spinning machine and spinning process, belonging to the field of dieless spinning machines. The dieless spinning machine and spinning process of this invention include a chuck mechanism, a spindle mechanism, a tailstock mechanism, at least two sets of external spinning mechanisms, and at least two sets of internal spinning mechanisms. Each set of external spinning mechanisms includes an external spinning wheel, and each set of internal spinning mechanisms includes an internal spinning wheel. The internal and external spinning wheels perform synchronous interpolation movements along the axial and radial directions. The radial gap between the internal and external spinning wheels is controlled and matched in real time according to the axial variation of the preset wall thickness of the wheel rim blank. Dynamic pressure support replaces the fixed mandrel, working together to achieve dieless spinning forming of the wheel rim blank. This invention has advantages such as significantly reducing production costs, improving production flexibility, improving forming quality, expanding the range of applicable materials, and facilitating automation integration.

A reinforcement learning system, method, and computer program code for controlling an agent to perform multiple tasks while interacting with an environment. The system learns options, where an option comprises a sequence of primitive actions performed by the agent under the control of an option policy neural network. In implementations, while the agent interacts with the environment, the system discovers options useful for multiple different tasks by a meta-learning reward for training the option policy neural network.

The invention discloses a simulation calculation method and device for sand core gas generation, electronic equipment and a storage medium, the method and device are applied to the electronic equipment, and specifically, initial and boundary conditions set by a user are received in response to a setting request of the user; calculating the initial and boundary conditions based on a discrete control equation obtained by processing a preset gas production diffusion control equation to obtain a gas production rate; and calculating according to the gas production rate to obtain the gas generation pressure and speed of the sand core. According to the scheme, simulation calculation of sand core gas generation can be achieved, a data basis is provided for further simulating the processes of gas accumulation, diffusion, casting entering and the like in the sand core casting process, people can conveniently explore the mechanism of gas hole generation and the influence on the casting process, and therefore theoretical support and prediction are provided for reducing the influence of sand core gas generation on the casting product performance; and a casting manufacturer is effectively helped to improve the percent of pass of castings.

This invention relates to an intelligent control system for drilling operations in coalbed methane fault zones, belonging to the field of intelligent drilling control technology. The system includes: a data acquisition module for acquiring single-point inclination data from multiple measuring points in the current working section of the target coalbed methane fault zone; a trajectory construction module for constructing a predicted drilling trajectory curve; a drill bit life prediction module for real-time acquisition of the target drill bit's working status data, extracting multiple wear features, and calculating the remaining working life of the target drill bit at the current time point; a well deviation prediction module for calculating the well deviation deviation between the target drill bit and the predicted drilling trajectory curve; a parameter adjustment module for adjusting the original working parameters of the target drill bit at the current time point to obtain optimal working parameters; and a control module for controlling the target drill bit to drill in the current working section. This invention improves the intelligence level of drilling operations by constructing a predicted drilling trajectory curve and optimizing the original working parameters of the target drill bit based on the remaining working life.