57 results about "Longevity" patented technology

The invention discloses a method for accelerated assessment of healthy life and disease risk based on phenotypic age, and the method comprises the following steps: S101, obtaining baseline data of a target population, the baseline data comprising actual age and multi-system clinical chemistry biomarker data; s102, calculating a phenotypic age according to the baseline data, and determining a phenotypic age acceleration value through regression analysis of the phenotypic age and an actual age; s103, performing aging degree layering on the target population according to the phenotypic age acceleration value; s104, evaluating the association between the aging degree layering and the disease-free survival years and the disease risk through a preset survival analysis model; and S105, outputting an evaluation result, wherein the evaluation result represents the health life difference and the disease risk change of the target population. The biological aging degree is reliably evaluated, and a scientific basis is provided for individualized health management and disease prevention.

The invention relates to a method for predicting the lifespan of an individual, comprising I. providing biological input data of the subject, ii. providing a list of confounding variables, iii. predicting an age-related mortality or disease, preferably the time to death and / or the mortality risk and / or the risk of age-related disease, for the subject by analyzing the data with an algorithm, wherein the algorithm comprises a neural network, which is trained on at least one reference dataset comprising biological data of at least one reference subject by applying: a) a selector layer to filter input data of i., and b) an adversarial learning framework, that removes from the input data the information related to the confounding variables, wherein preferably the adversarial learning framework, is a neural network comprising three elements: a feature extractor (FE), a predictor (P), and a confounder predictor (C). The invention further relates to a device or system comprising means for carrying out the steps of the method according to the invention, a computer program and a computer-readable storage medium.

The invention discloses a method and a system for predicting the service life of an anti-ultraviolet aging composite insulator, and relates to the technical field of composite insulators. The method comprises the following steps: collecting product information of a to-be-evaluated anti-ultraviolet aging composite insulator, determining the corrected predicted life of the to-be-evaluated anti-ultraviolet aging composite insulator based on the product information, and predicting the service life of the to-be-evaluated anti-ultraviolet aging composite insulator based on the corrected predicted life of the to-be-evaluated anti-ultraviolet aging composite insulator. The method comprises the steps of determining an appearance state comparison value of a to-be-evaluated anti-ultraviolet aging composite insulator, determining a microscopic state comparison value of the to-be-evaluated anti-ultraviolet aging composite insulator, determining a comprehensive state value of the to-be-evaluated anti-ultraviolet aging composite insulator, and determining an actual predicted life of the to-be-evaluated anti-ultraviolet aging composite insulator based on the comprehensive state value. The problems that in the prior art, service life prediction is insufficient in accuracy, influences caused by environmental factors are not fully considered, and the service life prediction is lack of comprehensiveness are solved.

The invention relates to the technical field of population prediction, and discloses a population prediction method and device based on combination of an ARIMA model and a queue element method. The method comprises the steps of obtaining historical migration population data of a to-be-predicted region, determining a difference order through ADF test, preliminarily determining the range of an autoregression order and a moving average order by using an autocorrelation function and a partial autocorrelation function, and constructing an ARIMA model; the optimized ARIMA model is adopted to fit historical migration population data, a migration population prediction result is obtained, and migration population data of each age group in the target prediction time period is output in combination with age structure data of floating population of the reference year; taking the migration population data of each age group as input parameters of migration population in a queue element method; according to a preset sum growth rate, selecting a western mode of a numeral-demann region model life table as a death model; and setting the average life expectancy according to a preset birth ratio, and realizing permanent resident population prediction of the to-be-predicted region.

The invention discloses a residual life prediction method and system for an engineering mechanical structural member. The method comprises the steps that S1, a multi-dimensional original data set of the mechanical structural member is collected through a multi-source sensor; s2, performing time-frequency domain feature extraction based on multi-dimensional original data set matching in combination with the inherent frequency and the fault feature frequency, and obtaining a high-dimensional degradation feature set through wavelet packet analysis in combination with characterization damage evolution; s3, utilizing a pre-trained physical memory neural network fusion model CP-NMN to carry out adaptive dimension reduction optimization on the high-dimensional feature set, and obtaining a cross-working-condition same-dimensional health index; and S4, based on the same-dimensional health indexes, dynamically predicting the residual life by adopting a long-short-term memory network, and presetting a life threshold to realize engineering early warning, so that effective monitoring of the health state of the structural member and life prediction can be realized.

This application relates to a method, apparatus, device, and medium for predicting the lifespan of magnetic liners based on artificial intelligence. It is applied in the field of magnetic liner lifespan prediction technology. The method includes: acquiring initial historical lifespan data and initial customer operating condition data; preprocessing the initial historical lifespan data and the initial customer operating condition data to obtain historical lifespan data and customer operating condition data; analyzing the historical lifespan data and the customer operating condition data according to multiple prediction methods to obtain various lifespan prediction information for the current customer. The prediction methods include empirical formula method, AI model prediction method, layered wear state method, and similar operating condition matching method; verifying the historical errors of various prediction methods based on the historical lifespan data; and fusing the various lifespan prediction information based on the historical errors to obtain target lifespan information. This application has the effect of improving the accuracy of magnetic liner lifespan prediction.

This invention provides the application of substances targeting the CYTB-187AA gene and / or protein in the preparation of drugs for delaying aging and / or prolonging lifespan. The research results of this invention indicate that by reducing the expression of CYTB-187AA protein and / or inhibiting its activity, the aging process can be effectively delayed, thereby achieving the goal of extending healthy lifespan or lifespan. The research results of this invention are of great significance for scientific research on aging mechanisms and the development of anti-aging intervention strategies.

Methods for identifying an amino acid alteration associated with a biological trait are provided. Methods of extending the longevity of a human subject and methods of extending the longevity of a non-human subject are also provided as are methods of determining is a subject is suitable to have their longevity extended.

A computer-implemented method for identifying the ageing test conditions for accelerated ageing tests of a product, wherein the method comprises: obtaining at least one parameter of the product; perfo

The invention belongs to the technical field of dehumidifier detection devices, and particularly relates to a rotating wheel service life detection device which is characterized by comprising a signal acquisition unit, a data processing unit and an interactive output unit. The signal acquisition unit is in signal communication with the data processing unit and is used for acquiring multi-dimensional physical parameters of operation of the dehumidification rotating wheel; a data storage unit and a physical model algorithm are arranged in the data processing unit, and the data processing unit is used for calling rated parameters and calculating characteristic indexes; whether the dehumidification performance of the current rotating wheel is healthy or not can be judged through the performance achievement rate and the regeneration composite coefficient, whether the current rotating wheel is blocked or aged or not can be judged by combining the pressure difference, different maintenance schemes are provided, the detection precision is high, and the cost is low.

To provide a method for predicting the residual life of a hose with which the residual life of a hose can be easily predicted.SOLUTION: A method for predicting the residual life of a hose includes: a deterioration model creation step of, for a hose of the same type as a hose in use, by using fluid in the hose in use, determining the relationship between the usage time and the physical property value of rubber for an inner tube rubber layer configured by including rubber affected by the physical property of the fluid, and creating a deterioration model of the inner tube rubber layer; a usage time calculation step of, for the hose in use, calculating the usage time of the inner tube rubber layer from the start of usage until the time of execution of prediction; and a residual life prediction step of predicting the residual life of the hose in use based on the usage time calculated in the usage time calculation step and the deterioration model created in the deterioration model creation step.SELECTED DRAWING: Figure 9

Systems and methods are disclosed for a multi-omics clock designed to predict remaining lifespan in mammals for the purpose of preclinical drug prioritization.

The invention discloses a prediction method and system for prolonging human life years by health intervention service, and relates to the technical field of data processing, and the method comprises the steps: building a health prediction model, and according to all-cause mortality and disease morbidity data of different genders and age groups, calculating a health prediction model; predicting the death probability of the crowd of each age group, the number of years of survivors of each age group, the total number of years of survivors and the expected life; in combination with the prevalence condition of general population health risk factors and the relative risk degree of all-cause death, calculating the life number of individuals who carry out health intervention earnings on different risk factors, and calculating the overall health score of the current individual; evaluating the health condition of the current individual according to the total health score of the current individual, discovering key risk factors, and making an intervention scheme. The life expectancy of healthy or chronic disease patients can be measured and calculated, and the method is suitable for application scenes of health intervention service evaluation.

This invention discloses a method and system for predicting the remaining lifespan of individual sensors based on Bayesian statistics, relating to the field of equipment health status monitoring and lifespan prediction technology. The invention provides a method comprising: establishing a general degradation model and prior distribution using historical degradation data; collecting monitoring data of a specific target sensor under real or accelerated stress in the field; updating the posterior distribution of model parameters based on Bayesian statistical inference and Gibbs sampling to generate a specific degradation model for that individual sensor; and calculating the remaining lifespan based on this specific model and a failure threshold. This invention achieves a breakthrough from "group lifespan assessment" to "accurate prediction of individual lifespan" through data-driven adaptive correction, significantly reducing over-maintenance costs and enhancing equipment operational safety.

Method for controlling a device (100) and / or an adherence machine, wherein the method comprises: acquiring (S10) biomarker data, wherein the biomarker data describe at least one measurable parameter of an individual's biomarker; acquiring (S20) estimation data, wherein the estimation data describe at least one average life expectancy for the individual; determining (S30) individual data based on the acquired estimation data and the acquired biomarker data, wherein the individual data describe at least one individual life expectancy of the individual; determining (S40) control data based on the individual data, wherein the control data represent at least one control command for a device (100) to be controlled, for changing the at least one measurable parameter of the biomarker and / or for changing an individual's behavior;Control (S50) of the device (100) based on the determined control data, wherein at least one adjustable parameter of the device (100) is changed; and / or wherein at least one optical, haptic and / or acoustic interface of the device (100) is activated and / or deactivated based on the determined control data; and / or control of an adherence machine based on the determined control data. The invention also relates to a system or computer program (product).

Chronological age is an important predictor of morbidity and mortality, however it is unable to account for heterogeneity in the decline of physiological function and health with advancing age. Several attempts have been made to instead define a “biological age” using multiple physiological parameters in order to account for variation in the trajectory of human aging; however, these methods require technical expertise and are likely too time-intensive and costly to be implemented into clinical practice. Accordingly, a metabolomic signature of biological aging was developed that can predict changes in physiological function with the convenience of a blood sample. A weighted model of biological age was generated based on multiple clinical and physiological measures in a large group of healthy adults and was then applied to a cohort of healthy older adults who were tracked longitudinally over a 5-10 year timeframe. Plasma metabolomic signatures were identified that were associated with biological age, including some that could predict whether individuals would age at a faster or slower rate. These results not only have clinical implications by providing a simple blood-based assay of biological aging, but also provide insight into the molecular mechanisms underlying human healthspan.

This invention relates to a method and system for predicting the lifespan of CNC tools considering real-world scenarios. The prediction method runs on an edge device that is communicatively connected to a cloud platform. The prediction method includes the following steps: acquiring basic data of the real-world scenario, extracting features of the real-world scenario, and matching the features of the real-world scenario with preset scenario features; obtaining the adaptation evaluation results of the lifespan prediction models in the model library of the cloud platform with the current real-world scenario based on the matching results; generating a corresponding lifespan prediction model based on the adaptation evaluation results, and predicting the lifespan of CNC tools under the current real-world scenario. Compared with existing technologies, this invention combines model recommendation and optimization algorithms to achieve scenario-consistent prediction of remaining tool lifespan, and has advantages such as scenario adaptability and high prediction accuracy.

This invention discloses a method and system for assessing equipment health and predicting remaining lifespan based on a dual degradation mechanism. The method includes: initializing the equipment's health and vulnerability; updating the health based on a preset natural wear rate within each discrete time step; if a fault event occurs within the current time step, calculating the damage amount based on the severity, duration, and current vulnerability of the fault event, and updating the health and vulnerability accordingly; if the fault is resolved, calculating the recovery amount of the health based on a preset recovery factor, and updating the health accordingly; updating the vulnerability based on a preset forgetting factor; and calculating the remaining lifespan of the equipment based on the updated health and a preset failure threshold. Compared with existing technologies, this invention achieves real-time accurate assessment of equipment health status and precise prediction of remaining lifespan through a dual degradation mechanism of natural aging and fault impact, and its damage memory effect.

Provided herein are methods for assessing ageing process, lifespan, life expectancy, biological age and the rate of aging by determining pangenome gene alterations. Also provided are methods for increasing lifespan and / or inhibiting aging.

This application provides a model-building method and apparatus for estimating relay lifespan. The method includes: obtaining a single-condition Weibull life estimation model for estimating relay lifespan; obtaining a lifespan model parameter variation function; establishing a comprehensive-condition Weibull life estimation model for estimating relay lifespan based on the single-condition Weibull life estimation model and the lifespan model parameter variation function; discretizing the comprehensive-condition Weibull life estimation model to obtain a discretized model; and simplifying the discretized model to obtain an iterative relay lifespan estimation model. Therefore, implementing this method can effectively and accurately obtain the relay lifespan.

A method for lifetime prediction and monitoring of a device, and a corresponding system are provided. The method comprises calculating a probability density function over time for an aging variable based on solving equation(s) from an aging model with an End of Life (EOL) boundary condition, wherein the boundary condition includes a first boundary condition and a second boundary condition, wherein the first boundary condition is a no-flux boundary condition and the second boundary condition is an absorbing or partly absorbing boundary condition, measuring an condition related observable of the device; obtaining first data representing measurement of the observable, calculating a likelihood for the aging variable from the first data, updating the calculated probability density function of the aging variable based on the likelihood, and generating a signal indicating a health prediction of the device based on the probability density function, the aging model and the EOL boundary condition.

A system method for selecting an intervention based on effective age, the system including at least a server, the at least a server designed and configured to obtain user data, project an actuarial life expectancy using a user chronological age, determine a telomeric age factor of the user by calculating a variance between the actuarial life expectancy and a projected actual mortality date, calculate an effective age of the user based on the telomeric age factor, and select an intervention from a plurality of configured to reduce the effective age.

The invention discloses a solid state disk remaining life prediction method, a memory and a computer program product, and relates to the technical field of storage, the solid state disk remaining life prediction method comprises the following steps: obtaining a first multi-dimensional health index associated with the service life of a solid state disk, the first multi-dimensional health index comprising a plurality of health indexes of different dimensions; performing index fusion processing on the first multi-dimensional health index by using a pre-trained convolutional auto-encoder network to obtain a first fused health index; determining a fault threshold corresponding to the first fusion health index by using a preset degradation model; and utilizing a pre-trained gating attention unit network to predict the residual life of the solid state disk according to the first fusion health index and the fault threshold. The embodiment of the invention can improve the accuracy of predicting the residual life of the solid state disk.

To provide a system that predicts a user's remaining lifespan using a new approach. [Solution] The present invention provides a system for predicting a user's remaining lifespan, the system comprising: receiving means for receiving data relating to a user, the data including data relating to the user's personality and data relating to the user's health; derivation means for deriving the probability that the user is willing to use an AI agent that provides health guidance, based on the data relating to the personality; and prediction means for predicting the user's remaining lifespan, based on the health data and the probability.

Methods for identifying an amino acid alteration associated with a biological trait are provided. Methods of extending the longevity of a human subject and methods of extending the longevity of a non-human subject are also provided as are methods of determining is a subject is suitable to have their longevity extended.