54results about How to "Real-time assessment" patented technology

The invention belongs to the technical field of battery fault prediction, and relates to a storage battery health state assessment method, system and device and a medium. The method comprises the following steps: acquiring key operation parameters of the storage battery; calculating storage battery health state evaluation index parameters by using the key operation parameters; the storage battery health state evaluation index parameters comprise the storage battery internal resistance, the internal resistance change rate, the storage battery charging state, the storage battery operation age limit and the storage battery operation temperature; preprocessing the storage battery health state evaluation index parameters to obtain preprocessed health state evaluation data; inputting the preprocessed health state evaluation data into a constructed health degree evaluation model to obtain a storage battery health degree representing the health state of the storage battery; and performing trend dynamic prediction on the health degree of the storage battery through a time sequence analysis algorithm to obtain a trend prediction result. The problem that an existing method is not accurate enough in battery fault prediction is solved.

The invention relates to the field of water pipe leakage monitoring, and discloses a buried water pipe leakage monitoring system and method, and the system comprises a monitoring module and a data collection module which is used for collecting data and transmitting the data to a monitoring platform; the leakage data processing and analyzing module is used for processing the data of the monitoring platform to obtain a leakage coefficient and an environment compensation coefficient respectively, calculating a leakage evaluation index of each water conveying pipe according to the leakage coefficient and the environment compensation coefficient, comparing the leakage evaluation index with a leakage threshold interval, and determining the leakage value of each water conveying pipe; if the leakage evaluation index exceeds the leakage threshold value interval, it is judged that leakage exists in the current water conveying pipe, if the leakage evaluation index is located in the leakage threshold value interval, it is judged that the leakage state of the current water conveying pipe is undetermined and needs to be further checked, and if the leakage evaluation index is lower than the leakage threshold value interval, it is judged that the state of the water conveying pipe is safe; and finally, according to a judgment result of the leakage data processing and analyzing module, alarm is automatically triggered and related personnel are notified.

The invention provides an innovative integrated system which aims at monitoring the workload of medical staff and providing psychological support for patients at the same time. The system collects physiological and behavioral data of medical staff and physiological and psychological state information of a patient in real time through a multi-modal data acquisition technology. And by utilizing an advanced machine learning algorithm, the system can intelligently evaluate the workload of the medical personnel and predict the overwork risk. Meanwhile, according to individual requirements of the patient, the system generates customized psychological support schemes including emotion recognition, psychological education, social support and professional consultation. In addition, the system has the real-time feedback and intervention functions, and it is ensured that medical workers and patients get attention and help in time. The intelligent user interface design improves the user experience, and strict data security and privacy protection measures guarantee the security of user information. According to the design of the system, the efficiency and quality of medical care work are improved, the overwork risk of medical staff is reduced, comprehensive psychological care is provided for patients, the psychological welfare of the patients is enhanced, and overall rehabilitation of the patients is promoted.

The invention provides a method, a device and a system for online detection of arc extinguishing performance of a circuit breaker, and belongs to the field of online detection of electrical equipment of a power system. The method comprises the following steps: acquiring a circuit breaker closing current i (t); selecting a sampling point corresponding to the moment that i (t) is greater than 0.01 kA as a closing current sampling initial value for backward sampling to form a closing current sequence; performing empirical mode decomposition on each item in the sequence to obtain a closing current sequence trend item sequence, performing accumulation on each item to obtain an accumulation result k (N), and adding the accumulation result k (N) into a sequence k (n = N); when N is greater than or equal to 15, clustering the sequence k (n is equal to N) by adopting a K-means algorithm, and determining whether the number K of clustering centers is greater than 1 based on a clustering error square sum threshold condition; if not, determining that the current arc extinguishing performance of the circuit breaker is good; if the judgment result is yes, determining that the current arc extinguishing performance of the circuit breaker is abnormal; and when the arc extinguishing performance state of the circuit breaker is abnormal, generating an early warning signal for early warning prompt.

The invention relates to the technical field of cerebral apoplexy rehabilitation, in particular to a cerebral apoplexy patient upper limb rehabilitation evaluation system which comprises a motion capture module, an analysis module, a processing module, a training module, a feedback module, an optimization module and a sharing module. The analysis module performs analysis according to the data acquired by the motion capture module; the processing module formulates a training plan according to the analyzed illness state; the training module is used for training the patient according to the evaluation result; the feedback module is used for feeding back the training effect; according to the system, the training result of the patient can be comprehensively evaluated in real time, the training plan is adjusted in time according to the rehabilitation progress of the patient, the rehabilitation plan and the training mode are continuously optimized, the optimization module can gradually adapt to the individual difference and rehabilitation requirements of the patient, more accurate rehabilitation suggestions are provided, and the rehabilitation efficiency is improved. Therefore, the rehabilitation effect is obviously improved.

The invention discloses an EMC (Electro Magnetic Compatibility) state evaluation system and method applied to a capacitor, and relates to the technical field of capacitor state evaluation, the evaluation system comprises a plurality of function modules which run in sequence, and the function modules are respectively an arrangement collection module, a signal processing module, a feature extraction module, a state evaluation module and an alarm feedback module; the technical key points are as follows: the system builds a life prediction model, generates a life prediction index of the capacitor according to the change trend of a comprehensive performance estimation value, and analyzes the change trend of the life prediction index in different periods, so that potential problems can be found in time, and corresponding maintenance measures can be taken; the normal operation of the capacitor is ensured; the service life is prolonged; the overall scheme not only solves the technical problem of capacitor performance and life evaluation, but also realizes real-time and accurate evaluation, and provides powerful support for normal operation and maintenance of the capacitor.

The invention relates to the technical field of medical instruments, in particular to an electromagnetic ultrasonic device for treating osteoporosis, which comprises a bed body, an electromagnetic ultrasonic probe, a data acquisition module, a data processing module and an artificial intelligence analysis module, an ultrasonic treatment assembly and an electromagnetic treatment assembly are integrated in the electromagnetic ultrasonic probe; the ultrasonic treatment assembly emits ultrasonic waves and transmits the ultrasonic waves to bones through soft tissues for ultrasonic treatment; the electromagnetic treatment assembly generates an alternating electromagnetic field to stimulate bone cells; physiological signal data are analyzed in real time through an artificial intelligence algorithm, physiological state changes are predicted, output parameters of PEMF and LIPUS are automatically adjusted to adapt to individual physiological differences, and personalized treatment is achieved.

The invention discloses an intelligent identification method and device for rotator cuff injury, and relates to the technical field of rehabilitation medicine, and the method comprises the steps: constructing a data collection module, collecting rotator cuff motion data in a motion capture mode, an electromyographic signal mode and a medical image mode, and carrying out the time-space alignment and fusion processing of the collected data through a Kalman filter; carrying out biomechanical modeling on the basis of the fused data, carrying out intelligent identification analysis on a biomechanical model by adopting improved convolution operation, carrying out spatial information fusion in combination with a graph convolution network, and outputting global motion state representation by self-adaptive expansion convolution; and based on the global motion state representation, dividing risk levels, predicting damage risks in real time, and providing an early warning signal. According to the method, the association mechanism of the multi-dimensional sensor data and the risk level is established, so that the shoulder joint movement risk can be accurately evaluated in real time. The shoulder joint injury prevention effect is remarkably improved, and the sports injury risk is effectively reduced.

The invention provides a group-type multi-role-playing virtual simulation training method and system and a medium, and the method comprises the steps: carrying out the simulation training in response to a virtual simulation training scene selected by at least one teacher user, and determining the number and types of roles participating in the virtual simulation training scene; n of the M trainees apply to participate in the virtual simulation training scene, the N trainees are allocated as roles, the mapping relation between the roles and the N trainees is determined, and scoring permissions of the remaining Q trainees are configured; recording training process data of N trainees participating in group training; obtaining evaluation data of roles played by the Q user students on the N student users; obtaining an evaluation score of each student user participating in the virtual simulation training scene according to the mapping relation; and finally, based on the obtained Q evaluation scores, determining training scores of the user trainees participating in training.

The invention relates to a transformer substation three-dimensional model data fusion method based on edge calculation, which comprises the steps of data acquisition, preprocessing, dimension reduction, state evaluation model establishment and equipment state evaluation, and can monitor the state of transformer substation equipment in real time, accurately evaluate the health condition of the equipment and improve the reliability of the transformer substation. And the method and the device are widely applied to the technical field of transformer substations.

The invention discloses an intelligent assessment method and system for regional geological disaster risk, and relates to the technical field of intelligent assessment. During operation of the system, various real-time data related to debris flow are acquired by integrating real-time sensors and satellite remote sensing data, original data are preprocessed and stored in a data storage system; based on the collected data, a physical model and a machine learning model are constructed, a debris flow disaster risk index MRI, a rainfall intensity coefficient RIC, a geological vulnerability coefficient GVC and a hydrodynamic pressure coefficient HPC are obtained after calculation, the probability of debris flow occurrence is predicted, and a result is output according to the model. The debris flow disaster risk index MRI is compared with a preset first safety threshold value M and a preset second safety threshold value N, the risk level of debris flow occurrence is evaluated, different areas are managed in a classified mode, debris flow early warning is given out according to real-time monitoring data and risk evaluation results, and automatic emergency response measures are supported.

The invention discloses a farmland abandoned risk comprehensive assessment and prediction method and device and a medium, and relates to the technical field of computers, and the method comprises the steps: obtaining a data source of a to-be-detected region, obtaining an abandoned farmland extraction result through data preprocessing, time sequence data synthesis and machine classification learning, further determining abandoned farmland pattern spots of the to-be-detected region, and obtaining abandoned farmland image spots of the to-be-detected region. Determining the abandoned farmland rate according to the abandoned farmland pattern spots, carrying out the assignment of the abandoned farmland risk indexes according to the abandoned farmland rate, carrying out the comprehensive evaluation of the abandoned farmland risk, and determining the abandoned farmland risk grade; determining a regression coefficient based on a cultivated land abandoned rate and a cultivated land abandoned risk index assignment result by using a logistic regression model; determining the contribution rate of the abandoned farmland risk index to the abandoned farmland based on the regression coefficient; and predicting the abandoned farmland risk based on the regression coefficient and the contribution rate. According to the invention, scientific, effective, comprehensive and real-time comprehensive assessment and prediction can be carried out on the abandoned farmland risk.

The invention relates to a function point duplicate checking method, a function point duplicate checking device and function point duplicate checking equipment based on large language model application, which are used for judging whether two function points in system or software development are duplicated or not by taking coincidence and similarity of the two function points on an operation dimension and an object attribute dimension as standards. And during the period, a current obtained result is evaluated through a reflection mechanism, and a more complete duplicate checking result is obtained through deep analysis. And whether the two function points are repeated or not is judged by combining the two dimensions of operation and object attributes, so that the problem that whether the two function points are repeated or not cannot be effectively judged in the traditional technology is solved. The Reflexion framework is referred to, and the ReAct mechanism-based agent is created, so that self-reflection can be performed while judgment is generated, self output is analyzed and evaluated in real time, and the judgment accuracy and adaptability are effectively enhanced.

The invention provides a river network regulation and control method under a rainstorm condition. The method comprises the following steps: acquiring pollutant data at key water quality sections of a main river channel and a secondary river channel of a target river network; and constructing a hydrodynamic model of the target river network based on the pollutant data, the water passing area data of the river network, the hydraulic radius data, the section flow data, the water level data and the flow distance data. Acquiring climate data of the urban area where the river network is located, the pollutant concentration of rainstorm runoff, the actual position of the rainwater pump station and the influence range of the rainwater pump station; and determining the drainage flow, the urban area in the drainage area and the runoff water depth generated by the rainstorm. Obtaining the amount of rainwater entering the river. And setting a removal rate parameter for the hydrodynamic model. And simulating the water quality of the river network under the rainstorm condition by using the amount of rainwater entering the river based on the hydrodynamic model after the removal rate parameter is set to obtain a simulation result. According to the method provided by the invention, the river network regulation and control result under the rainstorm condition can be accurately evaluated.

The invention discloses a tunnel anchor cable damage intelligent detection and early warning system, and belongs to the technical field of multi-source data detection, a multi-source data acquisition module detects the strain degree of an anchor cable through a wireless resistance strain gauge, and detects the wall thickness of the anchor cable through a wireless ultrasonic emission sheet; data collected by the wireless resistance strain gauge and the wireless ultrasonic transmitting sheet are transmitted to the wireless sensor, in the wireless sensor, received resistance change signals and ultrasonic signals are amplified and filtered, the signals are converted into digital signals through an analog-to-digital converter, the data are compressed, and the compressed data are transmitted to the wireless sensor. Then the data is transmitted to a data analysis and early warning module; and the data analysis and early warning module is used for predicting the residual life of the anchor cable and evaluating the risk level according to the processing results of the two different data, and carrying out early warning after a preset value is reached. The wireless anchor cable detection device is high in precision, low in cost and high in practicability and does not damage the anchor cable.

The invention discloses an anti-demagnetization protection system and method for motor control. The method comprises the following steps: acquiring counter electromotive force of a motor winding and real-time counter electromotive force of each phase of winding of a motor under a fault-free condition; respectively subtracting the counter electromotive force of the motor winding under the fault-free condition from the real-time counter electromotive force of each phase winding of the motor to obtain the maximum difference value of the real-time counter electromotive force of the phase windings of the motor; and comparing the maximum difference value of the real-time counter electromotive force of the motor phase winding with a demagnetization fault threshold value to judge whether the motor is in a demagnetization fault, if the motor is not in the demagnetization fault state, the motor operates normally, and if the motor is in the demagnetization fault state, demagnetization protection is carried out. According to the invention, real-time on-line and high-sensitivity effective evaluation and identification can be carried out on the demagnetization fault degree and the fault mode of the motor.

The present invention provides a method, system and equipment for monitoring the quality of trenching operations based on rapeseed planting, and relates to the technical field of agricultural engineering. The present invention cleans and standardizes the collected data, calculates the characteristic value deviation and generates a characteristic vector, and then establishes a quality evaluation model through a neural network convolution structure to output a trench quality index. The evaluation index is calculated in combination with the temperature and humidity data of the actual environment, and the threshold is dynamically corrected to form a correction value. By comparing the trench quality index and the correction value, it is determined whether the trench meets the trenching quality standard. The present invention realizes dynamic matching and optimization of the trench quality standard and the rapeseed planting demand by collecting and processing the trench characteristic data after the trenching machine operation and combining the relevant parameters of the trench after trenching.

The invention provides an audit business process oriented system automatic test method and system. The method comprises an auditing business process data indexing step, a large model training step, a large model test case script generation step and a test case script integrated operation step. By training the large model and understanding various specific auditing business processes and rules, the large model can automatically generate dynamic and flexible test case scripts, and simulates the auditing business processes of the user under the Playwright framework for testing, so that the test efficiency is improved, the labor cost is reduced, the test coverage rate and the test quality are improved, and the test efficiency is improved. Therefore, the technical problem is solved.

The present invention provides a battery state evaluation system, including a characteristic acquisition unit, a scenario prediction unit, a state prediction unit, a health state prediction unit and a communication unit. The characteristic acquisition unit receives and processes passive and active data to generate shape variables and improved variables; the scenario prediction unit uses an artificial intelligence model to predict the battery usage mode; the state prediction unit combines various variables, dynamically outputs the internal variables of the secondary battery cell and updates the battery state model; the health state prediction unit evaluates the health and charging level of the battery; and the communication unit transmits the results to the user or system in real time. The system realizes accurate monitoring and efficient management of the battery state.

The invention discloses a children leukemia prognosis evaluation and early warning method, which comprises the following steps: acquiring historical clinical detection data of a children leukemia patient after treatment, and obtaining prognosis life limits of the children leukemia patient represented by different historical clinical detection data; constructing a prognosis evaluation model, training the prognosis evaluation model by using historical clinical detection data, and outputting a convergent prognosis evaluation model; collecting new clinical detection data of the child leukemia patient after treatment; respectively inputting the biological marker detection data set, the gene expression data set and the treatment reaction data set into a convergent prognosis evaluation model, calculating the probability of poor prognosis, constructing a risk model of the probability of poor prognosis, calculating the risk coefficient of poor prognosis, and evaluating the prognosis effect of the children leukemia patient. According to updating of prognosis clinical detection data of children leukemia patients, evaluation can be carried out in real time, and timeliness and high efficiency of big data analysis are embodied.

The invention belongs to the technical field of structure health monitoring and safety assessment, and discloses a photovoltaic flexible support structure health assessment method and system. Firstly, acceleration signals, inclination angle data and cable force data of the photovoltaic flexible support are collected; extracting inherent frequencies, vibration modes and modal damping ratios of the first three orders of the structure based on a random subspace recognition method, analyzing inclination angle data to obtain static displacement or dynamic rotation angles of key nodes, obtaining a cable force distribution state by combining cable force data, and integrating to form a dynamic feature vector; inputting the vector into a pre-trained structure health assessment model, and outputting a damage position and degree; and when the damage degree exceeds a preset threshold value, a report containing the position of the damaged component, the damage degree and the disposal suggestion is automatically generated. Through cooperation of multi-source data fusion and an intelligent algorithm, real-time, accurate and automatic evaluation of structural health and accurate damage positioning are realized, a scientific basis is provided for preventive maintenance, safe operation of a photovoltaic power station is effectively guaranteed, and the operation and maintenance cost is reduced.

The present invention provides a dynamic method and system for thermal fatigue assessment of integrated circuit packaging, which relates to the field of integrated circuit technology, including using a genetic algorithm to determine the arrangement position of a temperature sensor, collecting a temperature data sequence of the temperature sensor array and its corresponding time information; establishing a thermal-mechanical coupling analysis model including a geometric model, a material constitutive relationship and a load boundary, and meshing the thermal-mechanical coupling analysis model to obtain a finite element model; based on the finite element model, using a nonlinear iterative algorithm to periodically solve to obtain a solder joint stress-strain field data sequence and its corresponding time information, establishing a modified Coffin-Manson model that considers the temperature-stress-time coupling effect, calculating the fatigue damage increment of the solder joint and accumulating it in real time, and evaluating the thermal fatigue state of the integrated circuit packaging structure according to the rate of change of the accumulated fatigue damage value.

The application discloses a kind of real pipe section grouting protection methods of gas surface extraction well in mining area, to overcome the passive protection defects in the prior art mining area ground well protection technology, can be changed from passive resistance rock deformation into active regulation rock movement, reduce the deformation energy acting on wellbore from the root, realize the purpose of active control rock movement to protect wellbore;Based on the real-time monitoring and judgment of wellbore body strain, the timely capture and intervention of wellbore risk state can be realized, and the problem of intervention lag of traditional method can be solved;Through target area selection guided by key stratum theory and well layout design based on rock movement law, the grouting energy can be accurately applied to the key rock structure for controlling wellbore deformation, which can greatly improve the pertinence and efficiency of protection measures;Relying on the closed-loop control logic with "wellbore strain feedback" as the core, dynamic optimization and accurate stopping of grouting process can be realized, so that the protection effect can be evaluated in real time, the grouting amount is controllable, and the safety and economy of the project are improved.

The application provides a kind of blade state detection method and device, it is related to wind power generator operation and maintenance field, to real-time, accurately monitor and evaluate the state of blade.The method comprises: obtaining real-time measurement data, a real-time measurement data includes the data of each dimension sampled at each sampling time point in a sampling time range;The real-time measurement data is input into the mapping network to obtain the data representation of the real-time measurement data, wherein the mapping network is trained using health data as training samples, and the health data refers to measurement data collected when the blade is in a healthy state;Obtain the data representation of the health data, which is obtained using the mapping network;According to the similarity between the data representation of the real-time measurement data and the data representation of the health data, determine the state of the blade.

The embodiment of the present invention provides a method and system for evaluating the state of charge of a lithium-ion battery. The method includes: obtaining the original IC curve during the charging process of the lithium-ion battery; filtering the original IC curve to obtain a smooth IC curve; dividing the IC curve to obtain a preset number of sections, and determining the fitted SOC-IC function of each section; updating the fitted SOC-IC function based on the adjustment coefficient associated with the size to obtain a reference SOC-IC function; and obtaining the variation law of the SOC-IC function coefficient of the lithium-ion battery with the charging rate, updating the reference SOC-IC function according to the variation law and the current charging rate to obtain the SOC-IC function, and evaluating the state of charge of the lithium-ion battery based on the SOC-IC function. The present invention constructs a SOC-IC function, uses the IC value measured during the charging process of the lithium battery to evaluate the battery SOC, and can achieve real-time and accurate evaluation of the SOC during the entire charging process.

The utility model discloses a device for simulating expiration, and relates to the technical field of simulation testing, the device comprises a first air supply part and an atomization part, the atomization part is provided with a liquid preparation cavity, the liquid preparation cavity is used for placing a prefabricated substance solution, an atomization structure is arranged in the liquid preparation cavity, the first air supply part is communicated with the atomization structure, and the atomization structure is communicated with the first air supply part. And the atomization structure atomizes the prefabricated substance solution under the action of high-pressure air provided by the first air supply part. The embodiment of the utility model provides a device for simulating expiration, which can truly simulate airflow exhaled by a person so as to simulate an expiration clinical sample, so that research results such as a detection method, a sampling tool, a detection device and the like can be effectively evaluated in real time in a research and development stage through expiration.

The present application relates to the technical field of textile automation control, and discloses a textile printing and dyeing process parameter adaptive control method and system and a storage medium, which comprises the following steps: outputting a torque instruction of a superimposed sine waveform to a frequency conversion servo guide roller to excite fabric warp tension fluctuation, synchronously collecting transient absorbance data of a working liquid boundary layer through a sensor array; calculating the phase delay of the absorbance data relative to the torque instruction based on orthogonal coherent demodulation operation to generate a transient spatial phase matrix; after low-pass filtering the matrix, converting the phase trend deviation into an original pressure compensation vector of a corresponding segmented bending-proof roller hydraulic cylinder by using a control stiffness conversion matrix; and combining the cloth running transmission delay and the mechanical inherent time constant to calculate a pre-trigger lead time, and sending a target pressure setting instruction in advance at a trigger node to adjust the independent hydraulic cylinder. The present application realizes online perception of fabric microscopic liquid absorption rate difference and eliminates the dynamic control dead zone caused by mechanical execution hysteresis.

The invention discloses a polarization / hypersensitivity / inertial navigation tight combination modeling and adaptive fusion method, and belongs to the technical field of bionic polarization integrated navigation. According to the method, polarized light intensity measured by a polarization sensor and sun image coordinates measured by a solar sensor are used as measurement and are subjected to tight combination modeling with an inertial measurement unit, and an expansion state equation including incident light intensity and degree of polarization and a nonlinear measurement equation are established. A self-adaptive fusion strategy is designed based on a dual credibility discrimination function of a polarization degree and a distance between a sun image coordinate and a sun-sensitive principal point coordinate, and a measurement mode of a polarization sensor, a sun-sensitive sensor or a combination of the polarization sensor and the sun-sensitive principal point is dynamically selected. And estimating a state quantity in real time through unscented Kalman filtering, and correcting a navigation error. The original light intensity information measured by the polarization sensor and the original sun image coordinate information measured by the solar sensor are directly used for measurement, so that the nonlinear transfer effect is inhibited. According to the invention, the orientation precision and environmental adaptability of the integrated navigation system in a complex environment are improved.

The invention discloses a ship bus duct electrical performance detection method and system, and relates to the technical field of ship electrical appliances, and the method comprises the steps: a first detection assembly detects an initial electrical performance index of a target bus duct according to a preset static strategy, and activates a second detection assembly when the index reaches a limit value; and the edge data processor performs dynamic operation to detect real-time operation state information, analyzes the information to obtain a real-time state feature set, inputs the real-time state feature set into the electrical performance evaluation model to obtain a real-time electrical performance index, and stops detection of the target bus duct if the real-time index does not reach a limit value. The technical problems that in the prior art, ship bus duct electrical performance detection is not comprehensive and inaccurate, and real-time performance and intelligence are insufficient are solved, and the technical effects that comprehensive, real-time, accurate and intelligent detection and evaluation of the ship bus duct electrical performance are achieved, and the safety and reliability of a ship electrical system are improved are achieved.

The invention discloses a real-time security transaction risk assessment method, and relates to the technical field of transaction risk assessment, and the method comprises the steps: S1, data collection: collecting personal investor transaction instructions, features and transaction environment information from multiple channels, providing a comprehensive data basis for risk assessment, and covering transaction behaviors, backgrounds and external environment factors; according to the invention, through multi-channel data acquisition, personal transaction information, investor characteristics and transaction environment aspects are covered, a comprehensive data basis is laid for risk assessment, in the risk assessment process, risk indexes and levels in multiple aspects of transaction errors, knowledge and experience mismatching and transaction environment influence are respectively calculated, multiple factors are comprehensively considered, and the risk assessment accuracy is improved. The one-sidedness of single factor evaluation is avoided, and the operation risk of the investor can be measured more accurately.