48 results about "Communicable disease" patented technology

The utility model relates to medical instrument technical field especially is involved in a kind of anti-stab needle, including needle body and the protective shell of outer sleeve in the outside of needle body, the needle body includes needle tip, needle seat and needle tube connected in turn, the side of needle seat is also equipped with needle wing, the inside of protective shell is equipped with the passageway for needle body reciprocating sliding, and the side wall of protective shell is also equipped with the notch for needle wing to penetrate, the inner wall of passageway is equipped with first limit piece and second limit piece, when needle tip extends to the outside of passageway first limit piece is limited with needle seat cooperation, when needle tip is retracted to the inside of passageway second limit piece is limited with needle seat cooperation, the utility model protects needle head by protective shell, eliminates needle tip of needle head stab injury, reduces the probability of infection infectious disease by needle tip stab injury, with safe and reliable advantage.

The present application relates to the technical field of public health safety, in particular to an infectious disease tracing method and system based on a space-time graph neural network, which integrates multi-source heterogeneous contact data, constructs a topologically enhanced space-time graph, converts the data into a space-time point cloud, constructs a multi-scale simplex complex, extracts persistent topological features, integrates the features into a graph representation, trains a multi-scale space-time graph neural network, uses multi-level time encoding and a double attention mechanism, designs a topological feature guided message passing, and finally performs topologically guided backpropagation tracing, reversely traces persistent homologous information flow and spectral graph convolution, generates multiple propagation source point hypotheses, and outputs the probability distribution of potential infection sources and the propagation path.

The application discloses a kind of source network load system attack path tracking and security protection method, first, source network load system network attack monitoring collection technology is proposed, and power generation side, energy storage system, load side, power grid operation, environmental factors and network security data are collected.Then, whether the instruction or the information collected is subjected to network attack by verifying whether the instruction and the uploaded power consumption data are reasonable;Secondly, according to the monitored source network load system network attack behavior, based on the mechanism of infectious disease model, the path of the source network load system subjected to network attack is given by reverse tracking the uploaded data subjected to attack.Finally, based on the key network node in the source network load system attack path selected by the sea squirt colony algorithm, the security protection measures are configured, considering the deployment cost and the expected effect, and finally outputting the protection scheme to guide the source network load system to deploy defense measures at the key nodes of the attack path and improve the security of the power grid.

The invention provides a strategic mineral resource overseas supply chain risk space-time monitoring and early warning method and device based on a complex network and an improved SEIR infectious disease model, and is applied to the technical field of data processing. According to the method, on the basis of strategic mineral resource overseas supply chain risk monitoring and early warning, multiple types of data of a supply chain are integrated, a key path is identified based on an algorithm, and network topology information is generated; modeling five types of risk causal relationships by adopting a Bayesian network to obtain risk conduction information; then preprocessing the unstructured text, designing an NLP model, and generating risk identification information; setting evaluation rules according to multi-level requirements, and generating evaluation information; optimizing and improving SEIR model parameters, and generating risk propagation prediction information; defining Agent behavior rules, and generating evolution simulation information; and finally, integrating multi-source data, generating full-process intelligent early warning response information including monitoring, early warning and plan matching, and realizing risk dynamic monitoring and efficient response.

The invention relates to the technical field of public health management and decision-making, and discloses a public health risk comprehensive evaluation and decision-making optimization method based on multi-source information, and a constructed emergent public health event analysis model comprises a medical resource competition sub-model and an infectious disease diffusion sub-model. Model calibration, a nonlinear generalized predictive adaptive control law and comprehensive overflow effect evaluation based on data envelope analysis are adopted to deeply integrate infectious diseases, a resource competition theory, an optimal control theory, operational research and an information theory method; a comprehensive model system capable of reflecting complex system interaction of'epidemic situation-resource-decision-society 'in public health events is constructed, strong robustness and dynamic optimization capability for dealing with uncertainty are achieved, the model precision and reliability are remarkably improved, errors are reduced, the defect that traditional evaluation is single is overcome, and the method is suitable for popularization and application. The overall effect of emergency decision making can be comprehensively evaluated from multiple aspects of medical treatment, society, economy and the like, and efficient and comprehensive decision making support is achieved.

The utility model relates to the technical field of medical instruments, in particular to a sickbed isolation device. The device comprises four groups of supporting mechanisms, isolating mechanisms and four groups of connecting mechanisms, the isolation mechanism comprises an isolation cover body covering the outer side of the sickbed, an isolation curtain fixedly arranged on one side in the isolation cover body so as to divide the isolation cover body into a first space and a second space, and an air filtering assembly arranged in the first space; the first fixing assembly is arranged between the ground and the isolation cover body in a sealed mode and used for fixing the isolation cover body, and the second fixing assembly is arranged between the ground and the isolation curtain in a sealed mode and used for fixing the isolation curtain. The device solves the problem that infectious viruses can be diffused to the outside air when medical staff enter and exit from the isolation assembly.

This application relates to the fields of artificial intelligence and public health technology, and in particular to an intelligent early warning method and related device for respiratory infectious diseases. The method includes acquiring time-series body temperature data and cough audio signals; acquiring facial images and extracting facial flushing features; determining the abnormal intensity value corresponding to the cross-fusion features; determining the flushing index corresponding to the facial flushing features; determining carbon dioxide concentration and relative humidity, and constructing an environmental compensation factor based on the carbon dioxide concentration and relative humidity; performing a weighted calculation on the abnormal intensity value, flushing index, and environmental compensation factor to obtain an abnormality score; and determining the early warning level based on the abnormality score. This application can improve the timeliness and accuracy of early warning.

The present invention relates a composition for use in increasing the longevity and / or enhancing healthy aging of a subject, particularly a human subject, and methods thereof. The composition comprises at least one of: isoscabertopin; 1,7-Bis (hydroxyphenyl)-4-hepten-3-one; eupafolin; isokuranetin, (E) - aldosecologanin, or any combination thereof, and increases expression of or activates a transcription factor selected from the group consisting of: nuclear factor (erythroid-derived 2)-like 2 (NRF2), Forkhead box O3 (FOXO3) and Grainy head 1 (GRHL1). Non-therapeutic or therapeutic uses and methods are disclosed herein. The extending longevity includes stimulating innate immunity, resistance against oxidative stress, inhibition of tumor cell growth, treating or preventing age-related diseases and disorders, which include: inflammation and inflammatory diseases, non-communicable diseases including: cardiovascular diseases, arthropathies, cancer, neurodegenerative diseases, diabetes, frailty, decline of physical fitness, decline of physical endurance or combinations thereof.

The invention discloses an intelligent analysis system for public health decision and trend prediction. The intelligent analysis system comprises the following steps: establishing a random optimal control system state equation containing a drift term, a diffusion term and a control function, and an objective function; a disturbance term is introduced into the state equation, and an original optimal control problem is converted into a random differential game problem; constructing a smooth trajectory estimation function based on the observation data, and defining a joint objective function; solving a random differential game problem to obtain an optimal control function and a system parameter estimator; the method is applied to a random control SIRD infectious disease model, and dynamic estimation of time-varying parameters is achieved; and on the basis of an estimation result, predicting a future disease transmission trend, and providing decision support for prospective planning and accurate configuration of public health resources. According to the method, a system with high noise and time-varying parameters can be effectively processed, the prediction precision and robustness are improved, and a quantitative basis is provided for prevention and control of infectious diseases.

The invention relates to the technical field of electrical digital data processing, and discloses an infectious disease risk prediction system and method based on a detection sharing network, and the system comprises a dynamic topology mapping module which constructs a logic connection map, carries out the real-time statistics of instantaneous connectivity, and corrects a conduction weight through a sparsity correction coefficient which is negatively correlated with the instantaneous connectivity; the state potential energy injection module is used for locking a positive node as an active source; the probability circulation calculation module is used for iteratively calculating risk propagation in the local subgraph and introducing time domain causal verification; according to the invention, by introducing a degree-weight reverse suppression mechanism and a time domain mask, the problems of topology short circuit and time sequence inversion caused by high-density noise data are solved.

This invention relates to the interdisciplinary field of artificial intelligence and smart education, specifically disclosing a campus risk intelligent early warning method based on multi-source data. The method includes: constructing a campus digital twin spatial model integrating data from academic affairs, access control, consumption, social interactions, and location; identifying initial risk individuals who meet psychological health and behavioral abnormality indicators; constructing a dynamic risk transmission network based on social association, spatial co-occurrence, and behavioral similarity; introducing an improved behavioral infectious disease dynamics model to simulate the risk diffusion process; and generating high, medium, and low-level early warning signals based on the degree of risk accumulation and network centrality, and pushing tiered intervention suggestions. Through the above technical solution, this invention improves the foresight, accuracy, and effectiveness of campus risk early warning and intervention.

The application provides a delay calibration method and device in an infectious disease space collection population model, and belongs to the technical field of infectious disease transmission modeling and risk assessment; the application adopts a delay time discretization method to convert continuous distribution into a discrete probability vector; an infected person allocation algorithm based on matrix operation and a time axis translation algorithm based on matrix operation are designed; the efficiency is significantly improved, and the time complexity is reduced from to; experimental verification shows that the processing speed of a 100-million-population city is at least improved by 7 times, and the processing speed of a single 100-million-population city can be improved by more than 10 times; the whole algorithm is based on matrix operation under a determined dimension variable, so it is easier to use GPU to accelerate operation, and then the algorithm can be extended to a real-time epidemic monitoring and early warning system in the future.

The utility model discloses an intrusion alarm device of an electric control access control system, which comprises a shell component, a control component, a locking component and a sterilization component, the front end of the shell component is fixedly connected with the control component, the interior of the shell component is fixedly connected with the locking component, the upper end of the shell component is fixedly connected with the sterilization component, and the lower end of the shell component is fixedly connected with the control component. The device is characterized by further comprising a shell assembly. The left end of the shell is in sliding connection with the locking insertion rod through a sliding groove; the sliding groove is formed in the left end of the shell; the inner groove is formed in the front end of the shell; the laser detectors are fixedly connected to the upper end and the lower end in the shell; the false screws are rotationally connected to the four corners of the shell; the thread groove seats are fixedly connected to the four corners of the rear end of the shell; and by arranging the sterilization assembly capable of sterilizing the device, the device can be automatically sterilized after a person with infectious diseases uses the device, and the situation that the device is infected by germs, and consequently the device is infected by the germs is avoided.

The invention relates to the technical field of infectious disease investigation, in particular to a modular processing-based questionnaire form intelligent configuration method. Comprising the following steps: a modular component construction step: packaging each element, including but not limited to an input box, a pull-down menu, a single selection box, a check box and a text area, of the questionnaire form into independent modular components, each modular component having a unique identifier and a predefined functional interface and being used for interacting with other components or systems; a configuration information acquisition step: acquiring configuration demand information of a user for the questionnaire form, wherein the configuration demand information comprises but is not limited to form themes, data types needing to be collected, form layout requirements, logical relationship requirements among form items and target audience feature information; according to the invention, variability of infectious disease investigation requirements can be realized, and modular flexible configuration of the investigation form is realized.

An MCP flooding attack detection method based on behavior characteristics comprises the following steps: collecting and learning a large amount of legal MCP traffic, extracting parameter length, request interval, nesting depth and response time characteristics, and constructing four-dimensional normal distribution as a legal traffic model based on the parameters, the request interval, the nesting depth and the response time characteristics; the probability density of the feature vector of each new request under the legal model is calculated to judge the abnormal request and the attack type thereof, finally, an SIR infectious disease dynamic model and an ARIMA time sequence model are further innovatively integrated to predict the zombie node scale and the attack trend, and the prediction result is used as input to automatically trigger and adjust a defense strategy; according to the method, botnet attack detection is carried out on the large language model integrated with the MCP protocol by utilizing the multi-dimensional behavior characteristics, so that attack detection and an adaptive defense strategy are effectively realized, and a security protection capability is also provided for a complex network environment in which the large language model is integrated with the MCP protocol; the invention further comprises a system, equipment and a storage medium for implementing the method.

The invention discloses a semi-closed foldable transparent bedspread suitable for aerosol blocking, and belongs to the technical field of respiratory infectious disease protection equipment. Comprising a cross rod, supporting side rods are symmetrically and fixedly connected to the outer side wall of the cross rod, vertical plates are fixedly connected to the upper surfaces of the supporting side rods, short columns are symmetrically and fixedly connected to the outer side walls of the vertical plates, inner rods are rotatably connected to the outer side walls of the short columns, and inner columns are fixedly connected to the outer side walls of the short columns; outer rods are rotationally connected to the outer side walls of the inner columns, fixing rods are fixedly connected between the two inner rods, fixing rods are fixedly connected between the two outer rods, and a foldable transparent outer cover is fixedly connected to the outer side walls of the two fixing rods and the outer side wall of the cross rod jointly.

The invention provides a medical resource allocation method and system, computer equipment and a storage medium, and belongs to the field of public health and preventive medicines.The method comprises the steps that firstly, related data of a target area is collected to construct an improved six-bin SEIRD model, the comprehensive root-mean-square error of six-bin actual and predicted data is minimized through a particle swarm optimization algorithm, and then the target area is obtained; and determining the optimal parameter of each new serious infectious disease stage, and synchronously outputting multi-chamber prediction data. Constructing a multi-objective optimization function, taking minimization of the total number of untreated patients, maximization of patient medical conditions and minimization of medical distance as objectives, adopting dynamic weight coefficient linear combination, combining five types of rigid constraints such as area distribution, hospital capacity and shelter construction, substituting prediction data into solution stage by stage, and solving the prediction data. And outputting an emergency medical treatment point construction time sequence, a spatial layout and a patient distribution strategy. And data of other bins are used for correcting stage division of major infectious diseases, constraint conditions and optimization targets, so that decision scientificity is guaranteed.

The invention provides a community information dissemination system and method based on a random directed hypergraph theory, which introduces community structures and attributes on the basis of a traditional information dissemination model on the basis of the directed hypergraph theory, simulates high-order asymmetric interaction in a real society through a method of randomly adding directed hyperedges, and provides a community information dissemination system and method based on the random directed hypergraph theory. According to the method, roles and susceptibility degrees of different individuals in information propagation are distinguished, and a new social information propagation model and a theoretical calculation method of the influence density of the social information propagation model are constructed. In practical application, community network model parameters are set according to a to-be-analyzed information spreading scene, a random simulation experiment is carried out by using a Monte Carlo algorithm, so that the influence density approaches a theoretical value, and spreading of information, influence or infectious diseases in a complex network in a real society can be better simulated, understood and explained; the critical value of the key control parameter can be quickly found, and the control and management of the information spreading can be further realized.

This invention discloses a method for evaluating the academic influence of researchers based on semantic mining and entropy weighting. It constructs a unique digital identity for researchers through knowledge graph alignment technology, connecting heterogeneous data from multiple sources; it extracts deep academic features using large-scale model semantic mining and graph neural network analysis; it promotes objective, multi-dimensional evaluation of researchers through a combination of entropy weighting, coupling coordination degree, and TOPSIS; it establishes an infectious disease transmission model and Prophet time-series prediction to achieve dynamic influence characterization; and it creates a self-learning closed-loop system through collaborative optimization and parameter evolution. Finally, it outputs a multi-dimensional profile and interpretable report of researchers, providing scientific decision support for research management.

Aspects of the present disclosure are directed to a Biological and Chemical Threat Prediction and Reasoning System (BiCEPS). BiCEPS can leverage Artificial Intelligence (AI) and Machine Learning (ML) approaches on uniquely pre-processed data derived from wearable devices to enable early detection, monitoring, and possibly prevention (or containment) of communicable diseases that can result in pandemics. Such communicable diseases may hereinafter be referred to as biological and / or chemical threats or simply threats.

The invention relates to the technical field of knowledge fusion, in particular to an infectious disease transmission risk real-time prediction system based on multi-source data fusion, which comprises a source knowledge registration module, a credible knowledge correction module, a regional knowledge convergence module, an associated knowledge constraint module and a prediction knowledge generation module. According to the method, a case report source identification code, an administrative division code, a space-time unit identification, a case state identification and a symptom classification identification are written into a knowledge registration unit, a space-time knowledge boundary is constructed to form a change track, and after state participation region collection, regional case distribution is presented by fusing a knowledge structure. The case state change directions among the regions form a corresponding relation in a continuous space-time unit and are converted into propagation association knowledge, and the evolution sequence of the regional knowledge structure is mapped into propagation risk prediction content, so that the risk level and the change trend are continuously generated based on the knowledge relation, and the influence of single data fluctuation on prediction expression is avoided. And the consistency and interpretability of the information in propagation risk prediction are improved.

The invention relates to the technical field of epidemiological investigation, in particular to an epidemiological questionnaire processing method based on keyword recognition and structured extraction. Comprising the following steps: establishing an epidemiological knowledge graph, performing semantic modeling on infectious disease business knowledge, constructing a directed graph structure containing entities, attributes and relationships, and forming an epidemiological feature knowledge graph; defining an epidemiological investigation information label identification table, performing abstract analysis and association integration on information elements in an epidemiological investigation text record, and establishing a label system comprising a label type, a starting label name, a middle label name and an ending label name; establishing an epidemiological investigation auxiliary labeling library, selecting classical investigation records, performing pre-labeling in combination with the knowledge graph, and labeling entities, attributes and relationships according to rules of the label identification table; according to the method, the fundamental defect of the semantic analysis level in the prior art can be solved, and the intelligent and efficient level of flow scheduling work is improved.

1. Name of the product in this design: Graphical User Interface for a Regional Infectious Disease Monitoring, Early Warning and Emergency Command Information Platform for Electronic Equipment. 2. Intended use of this design: for use in electronic devices. 3. The key design features of this product are its graphical user interface. 4. Images or photos that best illustrate the design key points: Interface state change diagrams. 5. This product is designed with a graphical user interface (GUI), and the rear view, left view, right view, top view, bottom view, and 3D view are omitted. 6. Uses of graphical user interfaces: for monitoring, early warning and management of infectious diseases on electronic devices. 7. Description of the changing states of the graphical user interface: The main view is the login interface. After entering the username and password, the interface changes as shown in the diagram.

The invention relates to a portable infectious disease analysis device which comprises a portable analysis box, a display screen is fixedly connected to one side of the top of the portable analysis box, a first reserved groove is formed in the bottom, close to one side of the display screen, of the inner side of the portable analysis box, a blood analysis assembly is installed on the inner side of the portable analysis box, and the blood analysis assembly is located at the top of the first reserved groove; a stable auxiliary assembly is installed on the inner side of the first reserved groove. Through the arrangement of the blood analysis assembly, when multiple persons are subjected to queuing detection, disposable blood collection devices and blood collection soft bottles can be alternately used, the cross infection phenomenon can be avoided, meanwhile, through the arrangement of the stable auxiliary assembly, the fingers can be bundled while the to-be-detected fingers are fixed, and the detection efficiency is improved. Therefore, blood flow at the tail end of the finger can be reduced, and the finger blood collection effect can be improved.

The application provides a network mental health service demand prediction model construction method, which is used for constructing a network mental health service demand prediction model with better prediction accuracy. The method comprises the following steps: obtaining consultation data of help-seeking behaviors on a mental health service platform and infectious disease case data; extracting mental health topic features of the help-seeking behaviors on the mental health service platform, mental health language features of the help-seeking behaviors on the mental health service platform, and time features of the help-seeking behaviors on the mental health service platform in quantity from the consultation data, and extracting time features of the infectious diseases in case quantity from the infectious disease case data, and taking the four as sample data; training an initial model through the sample data, and taking the trained model as the network mental health service demand prediction model.

The invention provides a remote intelligent diagnosis and treatment real-time interaction method and system based on 5G + AR. The method belongs to the cross technical field of telemedicine, augmented reality (AR) and 5G communication. The method comprises the following steps: establishing a remote intelligent diagnosis and treatment system architecture, generating remote diagnosis and treatment infrastructure data, performing equipment connection configuration through a 5G high-speed network, and constructing a 5G + AR remote diagnosis and treatment network environment. GPU accelerated rendering improves the display effect of virtual information, and the intuition and immersion of diagnosis and treatment guidance are enhanced; according to the method, the high requirements of complex scenes such as severe infectious diseases on remote diagnosis and treatment can be met, the real-time performance, interactivity and clinical availability can be remarkably improved, and the problems of misdiagnosis and missed diagnosis caused by incomplete information, unsmooth interaction and the like are effectively avoided.

The application provides a medical resource configuration method and system, computer equipment and a storage medium, and belongs to the field of public health and preventive medicine. The method comprises the following steps: first, collecting relevant data of a target area to construct an improved six-warehouse SEIRD model, minimizing the comprehensive root mean square error of the actual and predicted data of the six-warehouse by using a particle swarm algorithm, determining the optimal parameters of each stage of a new major infectious disease, and synchronously outputting multi-warehouse prediction data. Then, a multi-objective optimization function is constructed, the total number of untreated patients is minimized, the medical conditions of patients are maximized, and the distance to a hospital is minimized, a dynamic weight coefficient linear combination is adopted, five types of rigid constraints such as regional distribution, hospital capacity and shelter construction are combined, the prediction data is substituted into the function stage by stage for solving, and the construction time sequence, spatial layout and patient allocation strategy of an emergency medical treatment point are output. Other warehouse data is used for correcting the division of major infectious disease stages, constraint conditions and optimization objectives, and the scientific nature of decision-making is ensured.

The application provides a kind of port infectious disease intelligent monitoring early warning method and system, the method comprises: obtaining the health condition information of passenger self-declaration, the transmission condition data of infectious disease appeared in flight origin and flight destination environment data;According to the health condition information corresponding to each passenger, the health classification data of each passenger is determined;According to health classification data, whether each passenger is a suspicious passenger is analyzed;According to the transmission condition data of infectious disease appeared in flight origin and flight destination environment data, the transmission speed score of infectious disease in destination is calculated;The number of suspicious passengers is counted, and different warning information is sent to airport staff according to the number of suspicious passengers and the transmission speed score of infectious disease in destination.The individual health anomaly and external transmission environment are organically combined in the application, a comprehensive risk assessment system is formed, which is beneficial to precise early warning.

The invention discloses a positive and negative pressure convertible medical pressurizing cabin system for plateau first-aid transfer, and relates to the technical field of medical instruments, the system comprises a totally-enclosed rigid medical pressurizing main cabin arranged on a vehicle; the integrated pressure control and life maintenance unit is communicated with the medical pressurizing main cabin; the integrated pressure control and life maintenance unit comprises a pressure regulation and control module, a central controller, a pressure sensing array, an environment monitoring module and a medical gas interface, the operation safety and reliability are improved through the environment monitoring and self-checking functions embedded in the system, and the positive pressure working mode and the negative pressure working mode are designed to be convertible; the same equipment can flexibly cope with various public health emergencies such as plateau disease first aid and infectious disease isolation and transfer, and the use efficiency and comprehensive emergency guarantee capability of limited first aid resources in plateau areas are effectively improved.

The present application relates to the technical field of public health assessment, in particular to a kind of infectious disease cross-border input propagation risk automatic evaluation system and method, comprising: collecting global epidemic monitoring, cross-border personnel flow, destination city vulnerability and pathogen characteristics multi-source dynamic data.Improved space-time propagation model algorithm is used, relies on multi-level traffic network topology and heterogeneous population contact mode to optimize propagation dynamics, generates epidemic evolution simulation and risk output intensity.Cross-border personnel flow data is aggregated by trajectory analysis, personnel migration network and traffic intensity are extracted, and vulnerability index is obtained by quantifying city multidimensional vulnerability data.Multiple assessment elements are input into risk assessment fusion calculation engine to generate quantitative input propagation risk results for each destination city, and risk spatiotemporal distribution map is constructed by combining geographic information and pushed to risk early warning and decision support platform.