18 results about "Environmental exposure" patented technology

This invention relates to the field of facility durability assessment technology, and in particular to a life-cycle durability assessment system for cross-sea bridges in highly corrosive coastal environments. The system includes: a multi-source heterogeneous data acquisition module, used to acquire corrosive environment data, structural response data, component apparent damage data, and historical material performance data through a sensor network, image acquisition equipment, and database deployed on the bridge body and its environment; a data fusion and spatiotemporal registration module, connected to the multi-source heterogeneous data acquisition module, used to clean, align, and standardize the acquired heterogeneous data, and establish a mapping relationship between environmental exposure, material damage, and structural response; and a full-link intelligent system encompassing data perception, fusion analysis, AI prediction, dynamic calibration, and assessment decision-making. Through the fusion of physical mechanisms and data-driven approaches, this system achieves a fundamental shift in cross-sea bridge durability assessment from experience-based judgment to accurate prediction, and from passive maintenance to proactive operation and maintenance.

This document provides pull-tab activatable environmental exposure indicators. An exemplary pull-tab activatable environmental exposure indicator includes a substrate, a first indicator area and a second indicator area defined on the substrate, a first reservoir containing a first payload, which includes a first liquefiable material configured to liquefy in response to a first predetermined environmental exposure, a second reservoir containing a second payload, which includes a second liquefiable material configured to liquefy in response to a second predetermined environmental exposure, and a removable sealing layer, wherein the removable sealing layer prevents the first payload from flowing from the first reservoir to the first indicator area when the first liquefiable material has liquefied.and prevents the flow of the second payload from the second reservoir to the second indicator area once the second liquefiable material has liquefied.

This invention, based on the screening and identification of environmental exocomics and metabolomics biomarkers associated with ischemic stroke, discloses an ischemic stroke risk assessment model and model construction method that integrates environmental exocomics and metabolomics biomarkers, improving the comprehensiveness, accuracy, and convenience of prediction. This invention systematically evaluates the association between exposure to mixed organic pollutants and the risk of ischemic stroke, identifying key pollutants; quantifies the impact of pollutant mixtures on the systemic metabolic network and stroke risk, revealing the mediating role of metabolic pathway disorders in pollutant-induced stroke risk; explores the potential of incorporating pollutant exposure information into clinical prediction models to improve the efficacy of ischemic stroke risk stratification, ultimately providing systematic multi-omics evidence for the causal relationship between environmental pollution and ischemic stroke, and offering new technical tools for precision disease prevention.

The application belongs to the field of oral composition and food application, and provides a composition containing choline alfoscerate and application thereof. The composition takes L-alpha-choline alfoscerate as a liquid phase component, takes a complex core formed by pyrroloquinoline quinone disodium salt and cyclodextrin as a core, forms a multi-layer core-shell particle through core particle construction and layer-by-layer assembly of gelatin and sodium alginate, and is cooperatively configured with a dual-phase or dual-cavity storage mode. Therefore, the storage stability of the active ingredient, the integrity of the particle structure and the active release performance when used are considered, the adverse effects of environmental exposure are reduced, and the use convenience is improved. The composition can solve the problem that the memory-improving function and storage stability are difficult to be considered, and the particle structure integrity and the active release performance are restricted by each other, and is suitable for memory-improving food development and application.

The present disclosure relates to a signal hub featuring a switchable plug system, which allows for the interchange of plug types, such as from European Union (EU) to United States (US) standards, without disassembling the device. The system includes a plug housing that fits into a recess on the bottom shell, providing vertical and lateral support when plugged into an outlet. Plug prongs align with shell fastener apertures, secured by a fastener cover to protect against environmental exposure. The system utilizes a spring housing with terminal apertures to guide recess prongs into elastic terminals, ensuring stable electrical connections through compressive force. The ambient air gap between the top and bottom shells facilitates cooling, enhancing operational stability. The flexible support within the plug housing ensures consistent electrical contact, while the spring interconnects allow for vertical and lateral movement, improving impact protection and adaptability across different regions.

The present application relates to the field of intelligent medical auxiliary decision-making technology, and discloses a ladder treatment scheme recommendation method based on asthma control level and drug response phenotype. The present application aims to solve the problem that the existing scheme cannot identify the deep reason of uncontrolled condition, leading to blind step-up treatment. The present application excludes non-compliance interference by checking the drug execution rate, and improves the authenticity of condition assessment. The present application uses environmental exposure characteristics to adaptively correct the exhaled nitric oxide determination threshold, and eliminates the deviation of smoking on inflammation recognition. The present application combines the logic tree voting of multi-dimensional biological indicators to lock the drug response phenotype. Finally, based on the double index of condition state and phenotype, the present application locates the upgrade or transformation treatment path and generates a recommended scheme. The present application realizes the precise typing and differentiated drug administration of asthma treatment, effectively reduces the drug exposure risk of hormone-insensitive patients while ensuring the clinical efficacy.

The present disclosure presents wearable sensor apparatuses, systems, and related methods. One such apparatus is in the form of a wearable sensor device that comprises a processor and a plurality of gas sensors integrated on the wearable sensor device, in which the gas sensors measure an amount of NO2, SO2, and O3 present in ambient air. The wearable sensor device further comprises a peak flow meter sensor integrated on the wearable sensor device; a temperature sensor integrated on the wearable sensor device; a GPS sensor integrated on the wearable sensor device; one or more transceivers integrated on the wearable sensor device; and an electronic display, wherein the processor is coupled to the electronic display and is operable to display sensor data measured from the wearable sensor device.

The application discloses an unmanned mine vehicle-mounted environment monitoring and dynamic path planning method and system, belongs to the technical field of unmanned mine transportation, and aims to solve the problems that the existing unmanned mine vehicle lacks environment sensing capability, path planning does not consider pollution risk, and a purification strategy lags behind, leading to easy erosion of core equipment and energy consumption redundancy. The application collects multi-source environment data through a vehicle-mounted multi-sensor, constructs a dynamic pollution space-time model by fusing mine area fixed monitoring station data, realizes predictive hierarchical purification regulation by using a model predictive control framework, adds an environment exposure cost factor in a path planning cost function, realizes the collaborative decision of purification power regulation and path re-planning, can optimize operation energy consumption on the premise of protecting core equipment from high pollution erosion, and effectively improves the operation reliability and operation efficiency of the unmanned mine vehicle.

The application relates to the technical field of patrol path optimization, and discloses an intelligent recommendation system for an external stand pipe inspection path, which comprises the following: an inspection unit records facade positions, center heights and inspection operation modes; an evaluation unit performs risk assessment on each inspection unit according to historical defect information, stand pipe types and environmental exposure conditions, obtains an inspection unit risk level, and forms an inspection unit time window constraint; a processing unit constructs an inspection service graph; a recommendation unit determines a to-be-inspected unit, generates a candidate inspection path on the inspection service graph, combines the candidate inspection paths into multiple inspection task packages, performs resource scheduling in combination with skill information and available time information of an inspection team, and obtains an inspection path recommendation result corresponding to each inspection team. The application reduces the overall inspection time and the number of high-cost inspection operation mode switching times, and improves the external stand pipe inspection safety and operation and maintenance management efficiency.

The invention relates to an integrated multimodal artificial intelligence platform designed to function as an autonomous hospital system providing end-to-end health prevention, screening, diagnosis, treatment optimization, and longitudinal digital-twin-based monitoring. The platform introduces a closed-loop clinical architecture that continuously analyzes heterogeneous patient data including radiology, pathology, genomics, laboratory findings, longitudinal clinical records, wearable streams, and environmental exposures. A multimodal transformer (MT-X) generates a unified patient-specific representation, enabling high-precision diagnostic and prognostic inference. A novel Autonomous Screening Interval Generator (ASIG) dynamically determines individualized screening schedules based on calibrated risk models and temporal disease-evolution forecasting. A Digital Twin Engine (DTE) simulates tumor progression, metastasis probability, toxicity trajectories, and therapy response. An Adaptive Therapy Optimization Engine (ATOE), based on reinforcement learning, identifies optimal treatment strategies tailored to patient biology and system-level constraints. The invention is industrially applicable to hospitals, centers, national screening programs, tele-networks, and Al-enabled health systems. The integrated nature of the invention, the closed-loop framework, and the combination of digital-twin simulation with intelligent screening and therapy design constitute a substantial improvement beyond conventional medical Al solutions.

This application relates to the field of medical data processing, proposing a medical data processing method, related apparatus, and storage medium. The method includes: acquiring electronic health records, genomic data, family medical history, lifestyle and behavioral data, and environmental exposure data of a target user within a preset time window; determining the target user's temporal characteristics, static baseline characteristics, and interaction characteristics; predicting the risk value of the target user for a target disease in multiple future time periods; determining the risk gradient value of the target user for the target disease in each future time period; and determining a health screening strategy for the target disease based on the risk value and risk gradient value of the target disease in multiple future time periods. This application predicts the future risk value and risk gradient value of the target disease using multimodal data of the target user, and formulates targeted health screening strategies, fully considering individual differences. The formulated health screening strategies are more tailored to each individual's actual situation.

This invention discloses a cadmium protection method and system based on ensemble learning, relating to the field of pollution control technology. It includes basic information acquisition: obtaining past cadmium protection information. The invention first establishes cadmium pollution information corresponding to basic information through information decomposition. The degree of cadmium pollution is determined by the position of the basic information within the cadmium pollution information. Based on the degree of cadmium pollution, a corresponding reference library is selected and matched with the basic information to obtain basic protection information. A redundant protection generation method combines dietary exposure variables with environmental exposure variables. An ensemble machine learning algorithm is used to accurately predict and collaboratively optimize the cadmium load in the body, achieving integrated closed-loop management of "pollution monitoring - risk identification - intelligent optimization of intervention strategies - quantification of effects," improving prevention and control efficiency. By integrating environmental monitoring, exposure assessment, and collaborative intervention, a comprehensive protection approach is adopted to achieve full-chain, intelligent, and collaborative prevention and control of cadmium exposure risk.

The application discloses an ischemic stroke risk assessment model combining environmental exposure group biomarkers and clinical risk factors and a model construction method. The application integrates exposure group data and clinical risk factors into a risk prediction model, and provides an ischemic stroke risk assessment model combining environmental exposure group biomarkers and clinical risk factors and a model construction method. The application provides quantitative evidence support for the influence of organic pollutants on ischemic stroke for the first time, and fills the research gap in the related field. The application integrates pollutant exposure data into the risk prediction model, significantly improves the prediction accuracy of ischemic stroke, and fully verifies the practical application value of exposomics in early warning of diseases.

Described are additive manufacturing methods and systems that can deposit an occluding material in the form of a “cocoon” over previously deposited build material. The occluding material protects previously deposited layers from overexposure to the local environment and can allow exposure times of build material to be better controlled. The occluding material is removed following formation of the build product.

The application discloses an ischemic stroke risk assessment model combining environmental exposomics and lipidomics biomarkers and a model construction method. The application systematically evaluates the correlation between mixed organic pollutant exposure and ischemic stroke risk, identifies key pollutants, quantifies the influence degree of the pollutant mixture on the whole body lipid network and the ischemic stroke risk, reveals the intermediary role of lipid pathway disorder in the pollutant-induced ischemic stroke risk, explores the potential of incorporating pollutant exposure information into a clinical prediction model to improve the ischemic stroke risk stratification performance, provides an ischemic stroke risk assessment model combining environmental exposomics and lipidomics biomarkers and a model construction method, and finally provides systematic multi-omics evidence for the causal relationship between environmental pollution and ischemic stroke, and provides a new scientific basis for precise prevention of diseases.

The application belongs to the technical field of intelligent management of ancient buildings, and provides an ancient building wood component diagnosis and prevention intelligent management method combined with digital twinning, comprising: processing the main diagnosis surface image of the wood component by using a damage diagnosis model to obtain damage state recognition results; integrating the static attribute data of the wood component, and environment exposure data, damage state recognition results and maintenance data to obtain a structured digital twinning archive; obtaining the feature vector of the wood component at each historical time point based on the structured digital twinning archive, and stacking them in time sequence into a three-dimensional feature tensor; inputting the three-dimensional feature tensor into a multi-task time series prediction model to obtain the future damage prediction result of the wood component and the damage influence weight of the historical time point; calculating the SHAP value of the index; generating damage cause description; matching the damage cause description with a decision rule library to obtain the maintenance decision instruction of the wood component and sending it. The accuracy and forward-looking nature of the future damage prediction result of the wood component are improved, and a decision closed loop is formed.