182 results about "Virus transmission" patented technology

The invention provides a virus propagation dynamic prediction method based on a multi-strain multi-region population model and related equipment. The method comprises the following steps: acquiring historical epidemic situation related data of a target area, wherein the historical epidemic situation related data comprises epidemic situation data, virus gene sequence data, population flow data and epidemic situation management policy data related to a target virus in a past time period of each area; arranging the population flow data into an asymmetric population flow matrix between different regions every day; sorting epidemic prevention grades corresponding to different epidemic situation management policies according to the epidemic situation management policy data; and constructing a multi-strain and multi-region population model based on epidemic situation data, virus gene sequence data, a population flow matrix and epidemic prevention grades corresponding to different epidemic situation management policies by taking StatPOMP as a model construction framework, and generating virus propagation dynamic prediction information based on the model. The prediction accuracy of the virus propagation trend can be improved.

The invention provides an Internet of Vehicles virus propagation defense strategy optimization method based on differential game, and belongs to the field of computer information security. The method comprises the following steps of: 1, establishing a node-level dynamic model according to a network topology structure of the Internet of Vehicles; 2, establishing a differential equation model for describing virus transmission according to states (a low-susceptibility state, a high-susceptibility state, an infection state and a recovery state) of nodes; 3, based on the game theory, analyzing the income and loss of attackers and defenders, and constructing a differential game model; and 4, solving an optimal strategy (Nash equilibrium) of the attack and defense parties by utilizing a Hamiltonian function and combining a Pontryagin optimal value principle. And 5, through experiments, comparing the proposed method with a uniform strategy and an uncertain attack strategy, and verifying the effectiveness and superiority of the model in an actual Internet of Vehicles environment.

The invention provides a network virus propagation prediction method based on a space-time diagram attention model, and mainly solves the problems of strong dependence on propagation parameters and low prediction precision in the prior art. The scheme comprises the following steps: 1) constructing a space-time infection state diagram based on a network topology structure and virus historical transmission data; 2) processing the historical virus transmission data by using a sliding window mechanism, and constructing a data set; 3) constructing a prediction model based on the space-time diagram attention network in combination with the diagram attention network and the long-short-term memory network; 4) training the prediction model by using the constructed data set, and evaluating the prediction performance of the model; and 5) predicting the propagation trend of the future network virus by adopting the trained model. According to the method, the spatial topological characteristics and the time evolution law of virus propagation are effectively combined, and meanwhile, a graph attention mechanism is introduced, so that the prediction accuracy and the calculation speed of virus propagation in a large-scale network environment can be remarkably improved.

The invention discloses a live pig epidemic prevention and control flow regulation system and method based on big data, and relates to the technical field of animal health information, and the method comprises the steps: recognizing abnormal live pig signals and track intersection features of structured epidemic prevention feature data through an intelligent algorithm, comparing the virus gene difference degree, constructing a virus propagation network diagram, and carrying out the analysis of the virus propagation network diagram; outputting a high-risk propagation node map; constructing an aerosol dynamics three-dimensional space model by taking a super propagation hub node of the high-risk propagation node map as an original point and combining culture environment parameters, simulating a virus air diffusion path, and generating an environment propagation thermal distribution map; fusing the high-risk propagation node map and the environment propagation thermal distribution map, identifying a cross infection area through a multi-dimensional risk superposition model to perform risk dynamic grading, and outputting a grading early warning report; according to the invention, breakthrough improvement of the live pig epidemic prevention and control capability is realized, key nodes and potential risk areas of epidemic propagation can be accurately identified, and the pertinence of prevention and control measures is improved.

The invention relates to the technical field of network security, and discloses a virus monitoring and early warning method based on network traffic deep analysis, which comprises the following steps: collecting network traffic data in real time through a deep packet inspection technology, extracting traffic features, and constructing a traffic feature sequence based on a time window; establishing an anomaly detection model based on the traffic feature sequence, and identifying an anomaly mode deviating from normal behavior distribution; according to an abnormal behavior detection result, constructing a dynamic model of an equipment infection state, and quantifying an equipment infection risk; and constructing a propagation graph model in combination with an equipment interaction relationship, and simulating a diffusion path and a propagation trend of the virus in the network based on propagation dynamics. According to the method, hidden behaviors of unknown viruses and variant viruses can be accurately monitored, a virus propagation path and an influence range are dynamically predicted, optimal allocation of defense resources is realized in combination with a game theory and linear programming, and the real-time performance of virus monitoring and defense is improved.

The invention is applicable to the technical field of virus detection, and provides a norovirus detection kit based on a photo-thermal isothermal amplification technology and a detection method, the norovirus detection kit comprises a nucleic acid amplification chamber, the nucleic acid amplification chamber is provided with reaction micropores for nucleic acid amplification; an RT-PRA system, a CRISPR-cas12a system, a blank control and a positive control are placed in the reaction micropore, the RT-PRA system comprises RT-PRA solutions R1-R5, and the CRISPR-cas12a system comprises CRISPR-Cas12a solutions C1-C3; and the photo-thermal film covers the nucleic acid amplification chamber and is used for converting sunlight into heat energy and radiating the heat energy to liquid in the reaction micropores so as to provide reaction temperature for nucleic acid amplification. According to the invention, the portable, rapid and accurate detection of norovirus infection can be realized, the detection cost can be effectively reduced, the application scene is wide, workers can be helped to deduce the virus transmission path, and key support is provided for investigation and analysis of norovirus epidemic situations.

The invention relates to the technical field of path analysis, in particular to a virus propagation path analysis system based on big data, which comprises a data screening module, a virus propagation path module, a path screening module, a space-time network construction module and a virus propagation influence factor analysis module. Random disturbance is added in the virus spreading process, and the diffusion speed of the model can be adjusted along with time through dynamic changes of virus diffusion factors; a G-DBSCAN algorithm is designed in a path screening module, a high-quality virus propagation path is selected from prediction paths of virus propagation, a WA algorithm is introduced into the G-DBSCAN algorithm, the parallelization characteristic and a dynamically optimized de-integration mechanism are excellent in calculation efficiency, a large-scale data set can be processed, and the calculation efficiency is improved. And sparse or non-uniformly distributed virus propagation path data can be better processed, and potential key propagation paths can be identified.

The present invention proposes a method for constructing an epidemic case information extraction framework based on a pre-trained language model, and integrates a named entity recognition network and an implicit category prediction network into an epidemic case information extraction framework. The present invention designs a data labeling rule for infected cases, and proposes an information extraction framework based on a pre-trained language model to automatically extract core elements from cases, wherein the named entity recognition network can accurately identify named entities in case texts and locate key information on case transmission paths; the implicit case category prediction network can efficiently predict implicit categories and determine the main forms of case transmission paths; the framework realizes a structured representation of case texts to further assist disease prevention and control experts in formulating intervention measures for the spread of epidemic viruses.

The application discloses a disease transmission link prediction method and system based on a dynamic hypergraph neural network, aiming to comprehensively depict virus transmission paths and risk levels from multiple dimensions. First, data is collected from a gene database, mobile device logs and clinical texts, virus variation characteristics, population contact relationships and symptom semantic information are extracted respectively, and a dynamic hypergraph that integrates virus strain nodes, individual nodes and regional nodes is constructed. The hyperedge is defined according to molecular similarity, space-time contact and semantic overlap, and the weight is dynamically adjusted according to the transmission intensity of the infectious disease. A multi-modal hypergraph neural network with variation perception is introduced to jointly model and adaptively fuse multiple types of hyperedges and multi-scale features, output node propagation embedding vectors and predict potential transmission chains, perform prevention and control responses, and realize real-time deployment and feedback loop in an edge-cloud collaborative manner, ensuring efficient and accurate infectious disease transmission modeling and intervention control while ensuring data privacy.

In various embodiments, a building layout application generates building designs that reduce virus transmissions. The building layout application generates a first layout design set for a building based on a first design vector set and a baseline layout design. The building layout application executes, multiple times, a stochastic multi-agent virus simulator on a layout design included in the first layout design set and a simulation configuration to generate simulation results. The building layout application computes a risk score associated with both the layout design and a virus based on the simulation results. The building layout application executes evolutionary operations(s) on the first design vector set based on the risk score and at least one other risk score to generate a second design vector set. The building layout application generates a second layout design set for the building based on the second design vector set and the baseline layout design.

The invention relates to the technical field of data processing, in particular to a virus propagation prediction method based on a neural network, and the method comprises the steps: collecting real-time data; inputting a model prediction threshold value; determining an abnormal propagation event; determining a propagation event type; judging the virus transmission risk; determining a risk level; and adjusting a propagation threshold value and performing early warning. According to the method, the real-time infection rate, the positive rate and the population flow change rate are combined, efficient analysis is performed by using the neural network model, and the virus propagation trend and risk can be accurately predicted. Through intelligent adjustment of the propagation threshold, changes of different epidemic situation development stages can be dynamically responded, abnormal propagation events can be recognized in advance, early warning can be given out in time, and public health departments can be helped to quickly recognize potential virus propagation risks and take effective control measures. The problems of low propagation dynamic change response speed and low prediction accuracy due to dependence on a traditional mathematical model and static parameter setting are effectively solved.

The invention discloses a mask prevention and control system based on a respiratory infectious disease virus field, and belongs to the technical field of infectious disease prevention and control. The mask prevention and control system based on the respiratory infectious disease virus field comprises the following modules: a data acquisition module, a transmission module, a data analysis and prediction module, a user interface module, a mask prevention and control optimization module and a public health data platform. According to the mask prevention and control system based on the respiratory infectious disease virus field, the virus concentration, environmental conditions and user health data are monitored in real time through the high-density sensor network and the intelligent chip, the virus propagation trend and a high-risk area are accurately predicted based on a machine learning algorithm, early warning information is issued in time, and the safety of a user is improved. According to the health state and the surrounding environment of the user, the protection mode of the mask is dynamically adjusted, personalized protection is provided, and targeted protection suggestions are generated in combination with the health data and the environment data of the user to help the user to reduce the infection risk.

The invention discloses an infection risk assessment method and system for operating room nursing, and belongs to the field of operating room nursing. Infection protection analysis is carried out based on data of medical protection equipment of medical staff in the operating room, infection risk assessment is carried out based on an operating room virus transmission analysis result and an infection protection analysis result in the operating room, and finally infection risk early warning is carried out based on an obtained infection risk assessment result. The infection risk in the operation process is accurately estimated according to the transmission characteristics of the viruses and the operation protection characteristics, the protection evaluation accuracy in the operation process is improved, and the infection risk is avoided.

The invention discloses a disease transmission link prediction method and system based on a dynamic hypergraph neural network, and aims to comprehensively describe a virus transmission path and a risk level from multiple dimensions. The method comprises the following steps: firstly, collecting data from a gene database, a mobile equipment log and a clinical text, respectively extracting virus variation characteristics, a crowd contact relationship and symptom semantic information, and constructing a dynamic hypergraph fusing virus strain nodes, individual nodes and region nodes; the hyperedge is defined according to molecular similarity, space-time contact and semantic overlap, and the weight is dynamically adjusted along with the infectious disease transmission intensity. A multi-modal hypergraph neural network of variation perception is introduced, joint modeling and adaptive fusion are performed on multi-type hyperedge and multi-scale features, a node propagation embedded vector is output, a potential propagation chain is predicted, prevention and control response is executed, and real-time deployment and feedback closed loop are realized in an edge-cloud cooperation mode. And efficient and accurate infectious disease transmission modeling and intervention control are completed on the premise of ensuring data privacy.

An apparatus includes multiple first reservoirs and multiple second reservoirs joined with a substrate. Selected ones of the multiple first reservoirs include a reducing agent, and first reservoir surfaces of selected ones of the multiple first reservoirs are proximate to a first substrate surface. Selected ones of the multiple second reservoirs include an oxidizing agent, and second reservoir surfaces of selected ones of the multiple second reservoirs are proximate to the first substrate surface.

The invention discloses a biological data anomaly detection method based on semantic information fusion, and relates to the technical field of computer processing, and the method comprises the following steps: S01, constructing biological entity nodes and relation edges through a depth map neural network, generating an adjacency matrix and a node attribute matrix, aggregating node neighbor information by using a message passing mechanism, and generating a node attribute matrix; a biological network architecture model is obtained; s02, constructing a semantic fusion space based on a large model, analyzing deep semantic information and node association information of nodes, and synthesizing a few abnormal node candidate sets; and S03, adding the composite node candidate sets into the original data set one by one through an edge generator, and inputting the composite node candidate sets into a reinforcement learning module for screening. According to the method, classification and risk assessment of biological data are optimized by utilizing large-model semantic analysis and biological network construction, so that abnormal biological data can be quickly identified through multi-source data fusion and deep learning analysis in the early stage of virus transmission, and accurate detection and intelligent early warning are realized.

The invention provides an isolation device, and relates to the technical field of infectious disease prevention and control isolation, the isolation device comprises an isolation monitoring base, the top end surface of the isolation monitoring base is provided with a treading groove, and the center of the bottom surface of the inner end of the treading groove is fixedly provided with a proximity sensing assembly; through fixed installation of a matching strip block and a door plate of a room door, when an isolated person opens the room door of the room for prevention and control isolation of infectious diseases, first, information is wirelessly transmitted to a monitoring center, and second, information is transmitted to the monitoring center; therefore, an isolation prevention and control worker in the monitoring center can know the current behavior of opening the door of the isolated person at the first time, and the problem that key behaviors such as approaching or opening the door cannot be found and processed in time due to the lack of behavior supervision on the isolated person when the person is isolated in a single room is solved. And the hidden danger of virus transmission caused by isolation failure exists.

The present invention is a two-state feedback controller that takes into account the influence of spatio-temporal diffusion and individual contact heterogeneity. The controller design method includes: Step 1: Establish an SIR epidemic model; Step 2: Apply a two-state feedback controller to the SIR epidemic model; Step 3: Linearize the SIR epidemic model under the action of the two-state feedback controller at the equilibrium point to obtain the characteristic equation of the linearized controlled SIR epidemic model; Step 4: Select the time delay as the bifurcation parameter, and through stability analysis and bifurcation analysis of the characteristic equation of the linearized controlled SIR epidemic model, select appropriate state feedback parameters to make the model locally asymptotically stable near the equilibrium point. The two-state feedback controller of the present invention can perform feedback regulation control according to the state variables of susceptible individuals and infected individuals at the same time, and does not affect the characteristics of the original system, so as to efficiently and safely regulate the virus transmission process.

The present invention discloses a method for analyzing virus transmission in the cabin of a civil airliner, including collecting parameters of the civil airliner, constructing a physical model of the cabin in a selected space using 3D modeling software; performing mesh division on the constructed physical model of the cabin; simulating the physically modeled cabin after mesh division; determining the simulated path of virus diffusion, as well as the velocity field and concentration field of diffusion according to the simulation results; calculating the probability of infection risk for passengers in the cabin under different states of the personalized ventilation outlet above the infected passenger based on the mathematical model of virus transmission in the cabin of a civil airliner. The present invention provides suggestions for flight crew and passengers to reasonably arrange cabin activities and use personal protective equipment, reduce the infection risk of other passengers, isolate infected persons as much as possible, block virus transmission, and is of great significance to the physical health of passengers and flight crew.

This invention discloses a purifying fan, comprising a base, a fan housing, an impeller, a motor, and a purification component. The fan housing has an air chamber and is equipped with an air inlet and an air outlet, both communicating with the air chamber. The base is connected to the fan housing by a fixing member. The motor is mounted on the base, and the impeller is placed in the air chamber. The motor is connected to the impeller via a rotating shaft to drive the impeller to rotate. The purification component includes a purification shell, an ion generator, and an ion purification element. The purification shell is located on the side near the air inlet and has a purification chamber. The ion purification element is located in the purification chamber, and the ion generator is electrically connected to the ion purification element. The purification shell is equipped with an air collection port and an air guide port communicating with the purification chamber, and the air guide port is connected to the air inlet. This device not only functions as a fan but also purifies indoor air, reducing dust and microorganisms in the air and lowering the risk of virus transmission.

The application provides a dengue virus protection and mosquito vector control antigen composition and application thereof. The antigen composition comprises a combination of dengue virus type 1-4 envelope protein domain III polypeptide and Aedes aegypti midgut mucin AaMuc1 antigen polypeptide; the amino acid sequences of the dengue virus type 1-4 envelope protein domain III polypeptide are respectively shown as SEQ ID NO. 1, SEQ ID NO. 2, SEQ ID NO. 3 and SEQ ID NO. 4; and the amino acid sequence of the Aedes aegypti midgut mucin AaMuc1 antigen polypeptide is shown as SEQ ID NO. 5. The prepared vaccine can induce the body to produce neutralizing antibodies against dengue virus type 1-4, achieve the protection of human body from dengue virus infection, induce the production of active antibodies targeting Aedes aegypti midgut mucin 1, inhibit and kill the dengue virus transmission vector Aedes aegypti, and achieve the dual prevention and control of dengue fever from two dimensions of infection prevention and transmission interruption.

The utility model relates to an endoscope pipeline brush which comprises a shell, a rotating shaft and a pliers pipeline brush. A cavity is formed in the shell, an extending hole is formed in one side of the shell, the rotating shaft is arranged in the cavity and rotationally connected between the two inner side walls of the shell, one end of a brush rod of the pliers pipeline brush is fixedly connected with the rotating shaft, and the other end of the brush rod is wound by the rotating shaft, extends out of the extending hole and is connected with a brush head of the pliers pipeline brush. According to the technical scheme, the brush rod of the plier pipeline brush can be wound around the rotating shaft in the shell, occupied storage space is reduced, the plier pipeline brush can be pulled out by a specified length to be used according to use requirements, operation flexibility is improved, and the situation that a traditional plier pipeline brush is too long and not easy to operate is avoided; the brush rod part which does not extend out can be kept clean, virus transmission is reduced, and the cross infection risk is reduced.

The invention discloses a laccase-responsive termite-killing nano capsule as well as a preparation method and application thereof. The preparation method comprises the following steps: dissolving the imidacloprid powder in a cosolvent to obtain an imidacloprid solution, dispersing the carboxylated organic metal framework in the cosolvent to obtain an organic metal framework solution, mixing and stirring the two obtained solutions, and then centrifugally drying to obtain the imidacloprid nano-capsule. An imidacloprid-loaded carboxylated organic metal framework is obtained; the preparation method comprises the following steps: preparing a nano capsule, dissolving the nano capsule in a citric acid buffer solution, adding an aqueous solution of 1-ethyl-(3-dimethylaminopropyl) carbodiimide hydrochloride and an aqueous solution of N-hydroxysuccinimide, adding an aqueous solution of sodium lignin sulfonate, stirring, centrifuging and drying to obtain the nano capsule. The nano capsule provided by the invention can be specifically released under the action of laccase in intestinal tracts of termites, can be directly sprayed on body surfaces of the termites, cannot cause quick knockdown of the termites, and has a good virus transmission effect.

This utility model discloses a positive and negative pressure switching fresh air system, comprising: an intake fan connected to an air distribution box via pipes, the air distribution box connected to the intake valves of each room via pipes and silencers; a return fan connected to a collection box via pipes, the collection box connected to the return air valves of each room via pipes; when the intake fan is turned on and all the intake and return air valves of all rooms are fully open, all rooms are in a positive pressure state; when the return fan is turned on and all the intake and return air valves of all rooms are fully open, the return air volume is greater than the intake air volume, and all rooms are in a negative pressure state; when both the intake and return air fans are fully open, if room 1 opens its intake valve and closes its return air valve, room 1 is in a positive pressure state; if room 2 opens its return air valve and closes its intake valve, room 2 is in a negative pressure state; positive pressure rooms prevent virus intrusion, and negative pressure rooms prevent virus spillover; infected individuals live in negative pressure rooms, and uninfected individuals live in positive pressure rooms, which can prevent cross-infection among family members and is very suitable for the current virus transmission situation.

The present invention relates to a computer-implemented method for determining the need to add a mitigating agent to feed to inactivate viruses that may be present in the feed. A preferred mitigating agent is a mixture comprising benzoic acid tablets and a powder comprising eugenol and thymol. The mixture rapidly inactivates viruses even when added only in low concentrations. This is particularly applicable to (but not limited to) porcine epidemic diarrhea virus (PEDV). Thus, by the present invention, the animal feed is substantially free of harmful viral RNA.

A viral transmission barrier suitable for group settings encountered in places such as school or workplace cafeterias. The article aspect is a viral transmission barrier for tables with a height and a top surface with a length, a width, and a perimeter configured to accommodate a group of at least two people that may be strangers sitting in chairs at the perimeter and each having a section of table perimeter before them. Specifically, the article aspect comprises four elements, a multitude of vertical side panels, at least one neighboring vertical panel, a releasably attaching element, and a horizontal ceiling panel. The method aspect is aa method of using a viral transmission barrier to prevent the transmission of airborne viral particles from an infected person to others of a group of at least two people that may include strangers and are sitting in chairs at a table with a perimeter and each having at least 24 in, (61 cm) of perimeter before them at a function where masks are not worn. Specifically, the method comprises five steps.

The invention provides a fluorescent quantitative PCR (polymerase chain reaction) detection primer, a kit and a method for a novel variable chalmavirus VP gene, and belongs to the technical field of virus detection. A specific primer is designed and synthesized according to a conserved sequence of a VP gene of the novel variant chalmavirus, a recombinant plasmid is constructed, then the recombinant plasmid is used as a standard substance to establish a standard curve, a real-time fluorescent quantitative PCR detection system aiming at the novel variant chalmavirus is constructed, and specific detection of the novel variant chalmavirus is realized. The detection method can be used for quantitatively detecting the novel variant chalmavirus in the to-be-detected sample, and has the characteristics of high speed, high sensitivity, strong specificity and the like; the method provides a key technical support for molecular epidemiological investigation of the Sepamavirus in animal populations, is helpful for realizing early screening of infected individuals and timely blocking of virus transmission, and has important practical significance for guaranteeing population health and maintaining high mountain ecosystem stability.

The present application provides an asynchronous multi-threaded self-service sampling method, server-side equipment, system and electronic terminal, including: obtaining the identity identification information of the person to be tested, thereby obtaining the detection task corresponding to the person to be tested; classifying the detection tasks of the same type into the same detection task queue, and queuing and managing different detection task queues and their corresponding detection tasks through multi-threading; responding to the asynchronous online self-service sampling request information of the person to be tested, supervising and guiding the online self-service sampling process of the person to be tested by conducting online video in the corresponding thread to obtain qualified self-service sampling samples; thereby realizing safe and efficient self-service sampling of asynchronous multi-threading. The present application can realize self-service, parallel multi-person, continuous multi-frequency sampling through asynchronous multi-threading, and the person to be tested can complete the sampling work at home by themselves, thereby reducing the risk of virus transmission.

The present invention relates to a method for early prediction and early warning of large-scale outbreaks of pathogenic microorganisms. The method monitors domestic sewage at fixed locations to obtain virus content data; performs filtering, cleaning and difference processing on the data; estimates the parameters of the virus dynamics transmission model in different patches; estimates the characteristics of virus transmission between patches; constructs a priority management method and a two-dimensional risk control map; integrates the parameters of the virus dynamics transmission model in different patches, the characteristics of virus transmission between patches and the priority management method, displays the dynamic growth and extinction process of the virus in a large set of patches, and predicts the transmission trend. By integrating the intra-plaque and inter-plaque transmission models, large-scale outbreaks can be predicted and warned 4-6 weeks in advance, and communities where sustained outbreaks may occur can be found. According to the transmission characteristic indicators of the virus in different regions, different regions are ranked for risk, and the allocation of social prevention and control resources is optimized.

The utility model discloses an automatic cleaning laying hen breeding cage, including hencoop, excrement cleaning mechanism, crib cleaning mechanism and control panel, control panel is installed on one side of hencoop, the hencoop is formed by connecting cage body and frame, excrement cleaning mechanism includes collecting tank, screw transmission group, support seat, cleaning box and cleaning roller, and the cleaning roller is connected with the collecting tank. The feeding trough cleaning mechanism comprises a flow guide pipe and a scraping plate. The chicken coop is provided with the excrement cleaning mechanism, the feeding trough cleaning mechanism and the control panel, excrement generated by laying hen breeding can be automatically collected, excrement adhering to the bottom face of the chicken coop can be cleaned, peculiar smells and virus spreading in a breeding house are reduced, meanwhile, residual feed in the feeding trough is cleaned, and the breeding efficiency is improved. Bacteria breeding in the feeding trough is avoided, a good feeding environment is provided for laying hens, and the egg laying yield is increased.