23results about How to "Verify availability" patented technology

A social network false information detection method based on LLM enhanced comparative learning is used for detecting social network false information under a large language model LLM assisted comparative learning CL framework, and comprises the following steps: S1, data preprocessing and Prompt arrangement: capturing original data from a social network, and formatting; inputting the processed data into a Prompt composer to generate enhanced data so as to expand a training sample of the CL model; s2, LLM-assisted feature extraction and label prediction: matching the data enhanced in the step S1 with original data, and inputting the matched data into a CL model; the CL model extracts discriminative features of false information and performs label prediction; after training is completed, parameters of the CL model are frozen; in the test stage, data are input into the CL model to extract features, and labels are predicted through a classifier; and S3, joint fine tuning: guiding LLM fine tuning according to the contrast loss of the CL model.

The invention belongs to the technical field of biological analysis, and particularly relates to nicking rolling circle amplification, self-loading multi-component nuclease (MNAzyme), a fluorescent RNA aptamer and application of the fluorescent RNA aptamer in miRNA detection. The invention provides an unmarked sensitive sensing platform, which is characterized in that cutting rolling circle amplification is integrated into a self-assembled multi-component nuclease (MNAzyme) and a fluorescent RNA (Ribonucleic Acid) aptamer, and the platform is used for monitoring miR-21. By utilizing the super-sensitivity, programmability and operability of the biosensing environment detection platform, the expression of miRNA in different breast cancer cells can be quantitatively detected, normal cells and different cancer cells can be distinguished, and the biosensing environment detection platform has huge potential in the aspects of biomedical research and clinical diagnosis.

The embodiment of the invention discloses a Beidou satellite orbit maneuver detection method, device and equipment and a medium, and relates to the technical field of satellite orbit monitoring, and the method comprises the steps: obtaining precise ephemeris historical data of a to-be-detected time period, determining all time intervals which are lack of precise ephemeris data and of which the continuous duration is at least a first preset duration, predicated Beidou satellite orbit data are obtained based on TLE ephemeris published before the corresponding time interval and an SDP4 model, and the time interval where orbit maneuver exists is determined according to the comparison result of the predicated Beidou satellite orbit data and precise ephemeris orbit data. And according to the broadcast ephemeris parameters in the time interval in which the orbital maneuver exists, determining a sub-time interval in which the satellite health state parameter is 0 and the continuous duration is at least a third preset duration, and outputting the orbital maneuver time interval. The orbit maneuver detection result obtained based on the method can be directly used for evaluating the availability of the Beidou satellite space signal and verifying the availability performance of the Beidou satellite space signal.

This invention relates to the field of low-altitude emergency response technology and discloses a method for joint scheduling optimization of heterogeneous equipment for low-altitude emergency response tasks. The method includes: obtaining a task set and a set of heterogeneous equipment for the low-altitude emergency response task; constructing a dual-objective joint scheduling model for the low-altitude emergency response task based on the task set and the heterogeneous equipment set; performing non-dominated sorting optimization on the dual-objective joint scheduling model to generate a Pareto optimal solution set for the low-altitude emergency response task; executing the scheduling scheme in the Pareto optimal solution set; and monitoring the heterogeneous equipment of the low-altitude emergency response task in real time based on a preset dynamic rescheduling mechanism to obtain triggering events for the heterogeneous equipment; dynamically rescheduling the scheduling scheme based on the triggering events to generate a scheduling update scheme for the low-altitude emergency response task. This invention can improve the overall success rate, resource utilization efficiency, and system robustness of low-altitude emergency response tasks.

The invention discloses an ultrasonic detection system and method for a bushing lead. The system comprises a transmitting probe and a receiving probe, and the transmitting probe and the receiving probe are arranged on the outer side wall of a bushing; the fault detection main circuit is electrically connected with the transmitting probe and the receiving probe respectively; the upper computer is electrically connected with the fault detection main circuit and is used for controlling the fault detection main circuit to drive the transmitting probe to transmit an ultrasonic signal into the sleeve; the receiving probe receives and transmits an ultrasonic echo signal obtained after the ultrasonic signal is reflected in the sleeve; and the fault detection main circuit is used for processing the received ultrasonic echo signal into a time signal and then displaying the time signal through the upper computer. According to the invention, the detection time can be shortened, the online detection of the high-voltage bushing lead can be realized, the insulation fault can be accurately and timely found, and the reliable operation of the high-voltage bushing lead can be ensured.

An MIMO array sparse rapid design method of a fuzzy function generator based on deep learning comprises the following steps: firstly, directly learning a fuzzy function mapping relation corresponding to virtual array configuration and an incident angle by using a deep learning model so as to replace a traditional analysis fuzzy function calculation process depending on a manifold matrix; and then performing efficient performance evaluation on the candidate sparse array based on the fuzzy function generator, and obtaining a sparse array structure meeting the requirements of high resolution and low sidelobe in combination with an optimization strategy. By means of the technology, acceleration of more than 35 times can be achieved on the premise of not explicitly calculating the fuzzy function, the fuzzy function prediction root mean square error (RMSE) lower than 0.1 is kept, and therefore the sparse array design time is greatly shortened. Experiments on a 2T4R K-band MIMO radar prove that the designed array achieves 10 dB sidelobe level in a 100-degree field of view, the angular resolution is improved by about 32.8%, and the effectiveness and engineering application value of the method in high-resolution MIMO sparse array design are proved.

This invention provides a method for collecting gases from the pre-splitting blasting of steeply inclined, extra-thick coal seams, comprising: S1: calculating the blasting parameters for pre-splitting blasting of steeply inclined, extra-thick coal seams and determining the construction location of the blasting holes; S2: combining the blasting parameters, empirical formulas, and theoretical calculations to determine the composition and pressure of the harmful gases generated after the pre-splitting blasting of steeply inclined, extra-thick coal seams, and fixing a gas collection device at the orifice of the blasting hole; S3: selecting an extraction system based on the content of the harmful gases generated after blasting, and discharging the harmful gases collected by the gas collection device through the extraction system; S4: comparing the composition and content of the harmful gases generated after blasting with the gas drawn into the extraction system to verify the extraction effect of the extraction system. The technical solution provided by this invention can solve the problem in existing technologies of not discharging the harmful gases generated after pre-splitting blasting.

The invention relates to the technical field of medical management, in particular to a vascular access outpatient service intelligent management system based on artificial intelligence. The system comprises a patient outpatient service information file integration module, a patient vascular access use risk optimization selection module, a patient vascular access quality abnormity early warning module and a vascular access abnormity feedback management module. The method comprises the following steps: acquiring basic information data of a patient and previous vascular access use record data, performing information file integration processing, performing vascular access suggestion design and access use risk optimization selection, and generating a patient outpatient service optimal selection to establish a vascular access; and monitoring the physiological data of the patient and the use condition data of the vascular access of the patient in real time by using intelligent equipment, performing intelligent abnormal early warning of the vascular access and abnormal feedback management of the vascular access, and generating an abnormal feedback management scheme of the vascular access of the patient so as to execute corresponding abnormal feedback management work of the vascular access of the patient. The efficiency and accuracy of vascular access management can be improved.

The invention discloses a culture medium for promoting rapid proliferation of human endometrial mesenchymal stem cells and a preparation method of the culture medium. The culture medium comprises a serum-free basic culture medium, a solvent and the following components according to the final volume of the culture medium: 0.7-1.3 mM of aesculin, 0.7-1.3 mM of apigenin, 0.7-1.3 mM of baicalin and 7-13 mM of vanillin. The culture medium provided by the invention optimizes proliferation of human endometrial mesenchymal stem cells in primary culture and early culture.

The present invention relates to the control constraint of a four-rotor UAV formation. Through the anti-disturbance tracking control design of the UAV formation based on azimuth information, a new nonlinear controller is proposed to complete the formation formation and tracking tasks of a multi-UAV system in view of the situation that each UAV can only obtain the azimuth information of the neighboring aircraft. For this reason, the present invention adopts a nonlinear robust tracking control method for a multi-UAV system based on azimuth measurement information, and considers the characteristics of the UAV system being susceptible to external disturbances. The Leader-Follower formation method is adopted, and the position drift of the UAV formation system based on azimuth information is corrected by introducing the Leader position information. The backstepping method design is combined with the adaptive design and the robust control design to compensate for the influence of unknown parameters and unknown external disturbances on the multi-UAV formation system. The present invention is mainly applied to design and manufacturing occasions.

The invention relates to the field of biological sequencing, in particular to a reverse transcription system, a pre-amplification system, an enzyme digestion interruption system and application. The invention provides a reverse transcription system which comprises a reverse transcription buffer solution, a reverse transcription primer and reverse transcriptase, the reverse transcription buffer solution is prepared from the following components: 5XFirstStandBuffer, 5MBeta and 100mM of DTT (Dimethyl Terephthalate); the reverse transcription primer comprises 100mM < MgCl2 > and 100mu m < MTSO >; the reverse transcriptase comprises the following components: 40 U / [mu] L of RNA (Ribonucleic Acid) sensor and 200 U / [mu] L of Alpha ReverseTransscriptase. Based on the basic principle of Smart-seq and the prior art, the system and the existing formula of the Smart-seq experimental process are adjusted, so that the full-length transcript of the single cell is successfully amplified, and certain stability is kept.

The invention discloses a method for generating ultraviolet band tunable laser, which comprises the following steps of: providing near-infrared ultrafast laser with the central wavelength of lambda p as a pump light source, and enabling the pump light intensity of the pump light source to exceed a self-phase modulation threshold value; the pump light is focused and then enters a nonlinear optical crystal, and the pump light generates self-phase modulation light lambda s through a self-phase modulation effect; the nonlinear optical crystal is non-centrosymmetric; the self-phase modulation light lambda s and the pump light lambda p are subjected to five-wave mixing according to phase matching conditions, and ultraviolet laser with the output frequency being omega o and the corresponding wavelength being lambda o is generated; the space direction of the nonlinear optical crystal is adjusted to change the phase matching condition of five-wave mixing, and then continuous tuning of the output light frequency omega o is achieved. The method has the remarkable advantages of being short in wavelength, high in intensity and narrow in line width, the overall performance of deep ultraviolet laser output is improved, the special application requirements of multiple short-wavelength ultraviolet lasers can be met, and the defects of the prior art are overcome.

The invention belongs to the technical field of digital image processing, and particularly relates to an insulator hydrophobicity image edge detection algorithm under a CPS system considering a deconvolution deblurring algorithm, and the guarantee of insulator performance and the safe development of power grid construction cannot be separated. Hydrophobicity serves as an important parameter for detecting the performance of an insulator and is particularly important for an image edge detection algorithm of the insulator. According to the method, a deconvolution deblurring algorithm is combined, and a traditional edge detection method is improved. In order to solve the problem that image restoration is not ideal, the robustness of hydrophobic image blurring core estimation is enhanced by adopting an adaptive weight. In addition, the convergence of the algorithm is improved, the operation time is controlled, and the practicability and feasibility of the algorithm are further realized. The average operation time is shortened by about two thirds. And the edge detection algorithm under the deconvolution deblurring algorithm ignores the step, so that the convergence of the algorithm in the edge detection of the hydrophobic image is greatly improved, and the hydrophobic image can be quickly and accurately output.

The invention discloses a radio telescope radio frequency interference suppression method based on semi-supervised deep learning, and the method comprises the steps: precisely extracting two-dimensional time-frequency data from a standardized FITS file, and carrying out the multi-layer two-dimensional wavelet transformation of the obtained two-dimensional time-frequency data, low-frequency components and high-frequency components (including transverse high frequency, longitudinal high frequency and diagonal high frequency) corresponding to each layer are decomposed, and RFI elimination is carried out on the decomposed low-frequency components and the high-frequency components of each layer through a DnCNN denoising method based on semi-supervised learning in combination with a channel attention mechanism; and taking the low-frequency component after the RFI elimination processing and the high-frequency component of each layer as input, combining the components through inverse wavelet transform, and reconstructing non-interference time-frequency two-dimensional data in which the RFI signal is effectively suppressed. According to the method, the RFI can be effectively suppressed, the signal-to-noise ratio is remarkably enhanced, and the high fidelity of data is kept.

The invention discloses a pseudo-neural network transmission method based on air computing, and mainly solves the problems of large information transmission error and large resource overhead in the prior art. According to the implementation scheme, an air computing quasi-neural network transmission platform comprising a source node, a relay node and a destination node is built; initializing parameters of the pseudo-neural network; each node regulates and controls the signal according to the processing weight parameter, transmits a training symbol from a source node to a relay node and then forwards the training symbol to a destination node; the destination node calculates an error and an error gradient, reversely propagates the error and the error gradient to the relay node, and forwards the error and the error gradient to the source node to update processing weight parameters of each node; the forward transmission of the training symbols and the back propagation of the error gradient are repeatedly executed until the conditions are met; and transmitting the to-be-transmitted information from the source node to the relay node according to the current processing weight parameter, and forwarding the to-be-transmitted information to the destination node to recover the to-be-transmitted information. The method can reduce information transmission errors and node resource overhead, and can be used for wireless ad hoc network information transmission under the condition that node resources are limited.

The application discloses a bearing fault diagnosis method based on multi-source time-frequency feature fusion, and comprises the following steps: acquiring a bearing vibration signal and a rotating speed signal; constructing a bearing fault identification model based on a multi-source time-frequency feature extraction and fusion framework, which is used for identifying the bearing fault; training the bearing fault identification model to obtain a trained bearing fault identification model; and inputting the bearing vibration signal and the rotating speed signal into the trained bearing fault identification model to realize bearing fault classification. Through the combination of multi-source information fusion and an attention mechanism, the application improves feature expression capability and fault identification precision under the premise of ensuring model calculation efficiency, and provides an effective implementation method for bearing fault diagnosis under complex working conditions.

The invention provides a method for detecting intestinal cancer HER2 positive circulating tumor cells, and relates to the technical field of medical detection, the sensitivity of the method to intestinal cancer patient detection reaches 100%, which means that the circulating tumor cells in the intestinal cancer patient can be extremely accurately detected, a reliable basis is provided for early diagnosis and timely treatment, and the method is suitable for clinical application. According to the method, the survival rate and life quality of patients can be improved, the polyp sample detection specificity is as high as 100%, intestinal cancer patients and polyp control samples can be accurately distinguished, misdiagnosis and misjudgment are effectively avoided, a highly accurate result is provided for clinical diagnosis, the method is highly consistent with a clinical diagnosis result, and the method is suitable for clinical diagnosis. And the reliability and the practicability are further verified. The method has a good effect in the aspect of auxiliary diagnosis of intestinal cancer patients, important diagnosis information can be provided for medical workers, formulation of treatment schemes can be guided, the detection method is clear and definite in operation steps and easy to implement and popularize, and repeatability and stability of the method are ensured.

The invention belongs to the technical field of preparation of carbon-based materials, and particularly relates to a fluorescent carbon dot based on ampicillin sodium as well as a preparation method and application of the fluorescent carbon dot. The preparation method comprises the following steps: dispersing ampicillin sodium in distilled water, carbonizing the ampicillin sodium by a solvothermal method, and separating and purifying to obtain the water-soluble N-doped fluorescent carbon dots emitting blue fluorescence. The prepared carbon dots show excellent optical behaviors, excellent light stability and excellent water solubility. The prepared carbon dots can be used for detecting Fe < 3 + > and Cu < 2 + > in real environment water samples and living cells, and are good in selectivity and high in sensitivity. Compared with other carbon dot-based fluorescence sensing methods, the detection method provided by the invention is equivalent to or better than other carbon dot-based fluorescence sensing methods.

According to the high-quality rice planting method, cow milk enzyme liquid fertilizer rich in various nutrients is sprayed in the rice seedling raising stage and the seedling reviving stage, comprehensive nourishing is provided for growth of rice in the seedling stage, rapid and robust growth of rice seedlings is facilitated, and then the rice seedlings can grow in the booting stage, the final flowering stage and the pustulation stage of rice. Specially-made fermented milk is sprayed to the leaf surfaces of the rice, protein in the milk is subjected to combined action of EM bacteria and fermentation, macromolecules such as protein, fat and lactose in the milk are converted into nutritional ingredients such as amino acid which can be easily absorbed by the rice, necessary rich nutrients are provided for growth of the rice, the absorption efficiency of the leaf surfaces to the nutrition is improved, and the rice quality is improved. Further, the taste and the quality of the rice are improved. The fermented milk and the cow milk enzyme liquid fertilizer provided by the invention are both environment-friendly green chemical fertilizers, so that negative effects of chemical fertilizers on human bodies and environments are reduced, and agriculture is helped to proceed towards the direction of sustainable development.

The invention belongs to the technical field of computer vision, and discloses a visible light video-based multi-feature fusion blood oxygen estimation method, which comprises the following steps of: 1, acquiring and preprocessing rPPG signals; 2, constructing a blood oxygen estimation model based on mathematical theory; 3, constructing a blood oxygen estimation model based on data driving; and 4, comprehensively processing prediction results of the blood oxygen concentration estimation model based on the mathematical principle and the blood oxygen concentration estimation model based on the data driving method, and outputting a double-model fusion result. According to the method, rPPG signal acquisition, data preprocessing, feature extraction and a deep learning model are combined, a mathematical-based blood oxygen estimation model and a data driving method-based blood oxygen estimation model are respectively constructed, and finally, prediction results of the two models are fused, so that higher prediction precision and higher robustness are achieved, and the method is suitable for popularization and application. And the generalization ability of the model is improved.

The invention discloses a construction method and application of a high-density genotype interpolation panel for dairy cows in southern China. The construction method comprises the following steps of chip data processing, selection of an interpolation reference panel, quality control of original data, data correction and construction of an interpolation panel. According to the method, a high-density genotype interpolation panel of dairy cows in southern China is constructed, the genetic similarity between a reference group and a target group is improved, the accuracy and efficiency of interpolation are effectively improved, and particularly, the accuracy of groups with relatively close genetic relationship is higher; data used in the interpolation process comprise 10K and 50K SNP chip data, which indicates that the interpolation panel has wide adaptability to different data types, can keep consistent performance in different types of genetic data, and verifies the reliability and practicability of the interpolation panel; the data can be complemented more finely through the two-step interpolation process, the interpolation error is reduced, and the interpolation effect is improved.

This invention discloses a method and system for four-way linkage management of engineering costs based on a hybrid large model, belonging to the interdisciplinary field of engineering digitization and artificial intelligence. The method uses a multi-constraint fusion scientific computing hybrid large model as its technical foundation, constructing the model through a four-in-one mechanism of data pre-setting, boundary setting, threshold pre-setting, and dynamic data import. It adopts a hybrid architecture of decision trees and recurrent neural networks, integrating five types of constraints: construction period, resources, cost, changes, and engineering specifications. Based on this, it achieves three-dimensional synchronization, three-value quantification, three-calculation comparison, and intelligent risk control linkage, with the bill of quantities item as the smallest accounting unit. When the cost deviation exceeds the threshold, an early warning is automatically triggered, and the root cause is traced back along the data correlation link, realizing a closed-loop management system of "early warning, location, and processing." This invention solves the pain points of traditional methods, such as inaccurate calculations, delayed early warnings, and untraceable data, significantly improving the accuracy, efficiency, and reliability of cost management. This technical solution has been evaluated and certified by the Ministry of Housing and Urban-Rural Development (Jiankeping [2023] No. 066).

The invention discloses a fusion protein, the fusion protein comprises an antibody binding structural domain and an RNA editing structural domain, the antibody binding structural domain is a pAG structural domain and comprises a functional structural domain of Protein A and Protein G, and the RNA editing structural domain comprises a rat APOBEC1 enzyme deamination structural domain and / or a human ADAR2 enzyme deamination structural domain. The fusion protein can be used for simultaneously identifying an RBP target and providing transcriptome information in the same sample, can be used for representing an RNA-protein interaction spectrum, has relatively high reliability and sensitivity, is suitable for researching RBP functions in tissue slices and single cells, and has a wide application prospect in research of functional mechanisms of RBP in development and disease processes.