64 results about "Metabolic rate" patented technology

The invention discloses a multivariate heterogeneous data fusion method and system for an equipment operation and maintenance security pre-control system. The method comprises the following steps: receiving a multi-source heterogeneous modal data set; constructing a multivariate heterogeneous data fusion matrix, and calculating to obtain matrix variable elements; according to the matrix variable elements, constructing a multi-source heterogeneous modal data feature fusion calculation formula, and fusing multi-source heterogeneous modal data features; a dynamic metabolism model between the equipment health state and the external environment is constructed, and a digital metabolism rate is obtained; constructing a health prediction model, and analyzing the digital metabolic rate to obtain health degree prediction data; according to the equipment prediction health degree, the equipment prediction health degree is analyzed and judged, an early warning level is obtained, and a self-healing strategy is generated. The method is used for reflecting the operation and maintenance safety of the equipment according to the pre-equipment health degree by fusing the modal features, so that the pre-control of the operation and maintenance safety of the equipment is fed back more intelligently.

The invention discloses an air conditioner control method, device and equipment based on a neural network particle swarm and a medium. The method comprises the following steps: predicting an indoor environment parameter at a next moment through a pre-trained first neural network model according to a current indoor environment parameter; calculating a thermal comfort value at the next moment by combining the human body metabolic rate, the clothing thermal resistance and the parameter; determining a particle swarm constraint condition containing a target thermal comfort value and an air conditioner control parameter range according to the target thermal comfort value and a preset thermal comfort interval; under the constraint, a pre-trained second neural network model is reversely solved through a particle swarm optimization algorithm, and a target air conditioner control parameter combination meeting the target thermal comfort value and with the minimum operation power is obtained; and air conditioner operation is controlled according to the target air conditioner control parameter combination, so that energy consumption is effectively reduced while human body comfort is guaranteed, and the effects of adapting to environment changes in real time and balancing comfort and energy consumption are achieved.

The invention discloses a diet data analysis method and device based on a large language model, and belongs to the technical field of diet data analys.The method comprises the steps that user basic information and taste preferences described by natural languages are collected through a user interface; unstructured data of food is captured regularly, and a healthy diet database is constructed after large language model cleaning and tagging processing; basic metabolic rate and daily total energy consumption are calculated in combination with the basic information of the user, and a nutrient intake target is determined; the big language model application layer generates a daily diet plan containing cooking suggestions; and receiving the diet recorded by the user photographing or natural language, analyzing the diet, comparing the analyzed diet with the nutrition target, and generating personalized feedback containing problems, reasons and adjustment suggestions. The device correspondingly comprises five functional modules. According to the invention, automatic maintenance and personalized analysis of diet data are realized, and intelligence and practicability of diet management are improved.

The invention relates to the technical field of intelligent medical prediction, in particular to an intelligent early warning method and system for adverse reactions of chemotherapy medication of tumor patients, and the method comprises the steps: inputting gene sequencing data and time sequence physiological index data of a current patient into a network model, and outputting an injury stage by the network model; the training data set of the network model comprises gene sequencing data, time sequence physiological index data and injury stages; the acquisition process of the injury stage comprises the following steps: acquiring the relative metabolic rate of the gene sequencing data to chemotherapeutics, and further determining the relative speed of in-vivo toxicity accumulation of the gene sequencing data; after time sequence physiological index data of meaningless physiological fluctuation of a historical patient is smoothed, a nerve injury change curve is obtained according to the time sequence physiological index data, whether a potential subclinical signal segment exists in the nerve injury change curve or not is recognized, and if yes, the injury stage is judged according to the potential subclinical signal segment. According to the method, individualized and accurate risk prediction can be carried out before irreversible nerve injury caused by chemotherapy occurs.

This invention discloses a non-invasive method, system, device, and storage medium for monitoring student attention based on gas sensing, belonging to the field of non-invasive sensing technology. The method includes: calculating a net physiological gas signal based on environmental baseline data and initial gas concentration data of the target student; calculating physiological characteristic indicators of the target student based on the net physiological gas signal, and determining the target student's metabolic rate level based on the physiological characteristic indicators; obtaining a state time-series signal based on the net physiological gas signal according to a preset discrimination criterion; inputting the net physiological gas signal and the state time-series signal into a pre-trained attention monitoring model to obtain the probability distribution of the target student's attention state; and determining the target student's attention state based on the target student's metabolic rate level and the probability distribution of the attention state. This invention assesses the cognitive state by capturing the gas released by the student, achieving non-invasive monitoring.

This invention relates to a method for synchronous prediction of human thermal injury based on a dynamically coupled physiological model. First, a refined, segmented, multi-layered human physiological thermal model is constructed. Based on this model, a set of coupled biological heat transfer equations is established, embedding an active thermoregulation mechanism mediated by the human central nervous system. This set of equations is solved by deeply and dynamically coupling skin temperature, core temperature, and physiological parameters such as blood perfusion rate, metabolic rate, and sweat evaporation. Subsequently, by setting the initial and boundary conditions of a fire scene operation, the coupled equations are solved in one go using numerical methods. During the same solution process, the system synchronously and in parallel performs segmented skin burn risk assessment and overall human heat stress risk assessment. This invention overcomes the limitations of traditional models in segmented prediction and coupled active thermoregulation, achieving effective synchronous early warning of skin burn risk and overall heat stress risk in various parts of the human body under extreme thermal environments.

The application discloses fluorescent molecules, calcium phosphate nanoparticles thereof, and a preparation method and application thereof. Specifically, the application discloses a compound as shown in formula I, or a salt thereof. The calcium phosphate nanoparticles formed by the fluorescent molecules provided by the application have both improved fluorescence quantum yield and metabolic rate.

The application belongs to the field of biological analysis, and provides a method for precise metabolic flow analysis of TCA cycle based on isotope tracing technology combined with high-resolution mass spectrometry. By optimizing mass spectrometry parameters and liquid chromatography method, one injection within 6 min is realized, and high-throughput, high-sensitivity and high-resolution detection is realized on 11 biomarkers related to TCA cycle metabolic pathways. At the same time, the application innovatively uses LC-MS / MS to decipher 13 C the stepwise position-specific transfer from glucose to subsequent metabolites by glycolysis and TCA cycle, thereby calculating 13 C the integrated steady-state analysis of key metabolic rates of position-specific transfer from sequential precursors to their products (pyruvate dehydrogenase, beta-oxidation, pyruvate carboxylase, isocitrate dehydrogenase and pyruvate cycle). This technology has wide applicability and can potentially characterize mitochondrial metabolism of any tissue or cell.

The present application relates to the technical field of artificial intelligence, and particularly relates to an individualized medication prediction method based on artificial intelligence, comprising: acquiring a plurality of standard historical medical data sets; acquiring metabolic capacity scores and drug metabolism rates corresponding to all data groups; training to obtain relationship models corresponding to all standard historical medical data sets; acquiring liver metabolism parameters, gene expression parameters and each drug name in a treatment scheme of a patient to obtain a drug metabolism rate; and determining a corresponding prediction drug amount determination method according to whether the drug types in the treatment scheme have a competitive relationship. The present application integrates drug metabolism enzyme-related gene expression and liver metabolism function, simultaneously incorporates drug absorption competition and metabolism enzyme competition when drugs are used in combination, corrects the final output prediction drug amount when drugs are used in combination, so that the model is more suitable for the actual drug use scene, and the accuracy of the prediction result is increased.

The application belongs to the technical field of biological medicine, and particularly relates to a radix morindae officinalis-inulin composition and application thereof in a kidney fibrosis product. The radix morindae officinalis-inulin composition provided by the application is composed of radix morindae officinalis polysaccharide, inulin and water, can exert the synergistic effect of the two polysaccharides, improve the physical and chemical properties and biological activity of the radix morindae officinalis-inulin composition, can significantly enhance the metabolic rate of urea nitrogen creatinine of the kidney, and can significantly reduce the fibrosis positive area, and has a significant effect on the treatment of kidney fibrosis diseases. The raw materials of the composition are based on natural polysaccharides, have good safety and degradability, and meet the high safety requirements of biological materials in the medical field. Compared with the existing single component, the composite design can realize multi-target effect, significantly improve the treatment effect, and has a great market competitive advantage.

Techniques for predicting an amount of at least one biomaterial produced or consumed by a biological system in a bioreactor are provided. Process conditions and metabolite concentrations are measured for the biological system as a function of time. Metabolic rates for the biological system, including specific consumption rates of metabolites and specific production rates of metabolites are determined. The process conditions and the metabolic rates are provided to a hybrid system model configured to predict production of the biomaterial. The hybrid system model includes a kinetic growth model configured to estimate cell growth as a function of time and a metabolic condition model based on metabolite specific consumption or secretion rates and select process conditions, wherein the metabolic condition model is configured to classify the biological system into a metabolic state. An amount of the biomaterial based on the hybrid system model is predicted.

The invention provides a ketogenic diet component or composition as well as a preparation method and application thereof, and relates to the technical field of foods. According to the ketogenic diet component or composition, the ghee replaces lard oil to serve as a fat source, the ghee moistens intestines and stomach, harmonizes spleen and warms middle, and the ketogenic diet component or composition is rich in various fatty acids beneficial to a human body, such as unsaturated fatty acids, medium-short chain fatty acids and the like, and further contains nutritional ingredients such as vitamin A, vitamin D, vitamin E, vitamin K and the like; the butter contains high medium-chain and short-chain fatty acids which can be quickly absorbed and utilized by a human body, so that quick energy is provided for the brain and the body, and the metabolic rate is increased. The ghee has rich milk flavor, so that the taste and flavor of ketogenic diet food can be remarkably improved, and the acceptability and satisfaction of consumers are improved. The ghee is in a solid state at normal temperature, is easy to store and transport, has good stability in the cooking process, is not easy to oxidize and deteriorate, and can keep the quality and nutrition of food for a long time.

A device collects aquatic field metabolic rate data related to a water-breathing animal having at least one gill opening. The device has at least one oxygen probe, which measures and records oxygen consumption or oxygen extraction data at the at least one gill opening. The device is configured to collect metabolic data when the animal is in a natural environment. A method for determining a metabolic rate of the animal located in a water environment includes measuring metabolic rate data via at least one gill oxygen probe which is inserted into the at least one gill opening; measuring ambient data in the water environment via at least one ambient oxygen probe; and estimating a whole animal metabolic rate.

A bioreactor chamber for growing a cell culture in a liquid medium includes a controller, sensors coupled to the bioreactor chamber, and a control device for varying gas and / or fluid flow within the bioreactor chamber. The sensors measure a plurality of sensor parameters in the liquid medium. Sensor data from each sensor is received at predetermined time intervals. The desired cell growth configuration and the sensor data from each sensor are input into a cell culture control machine learning model. Based on output data from the cell culture control machine learning model, control circuit commands are sent to the control device to control at least one of displaying a cell culture parameter prediction, gas flow, liquid flow of nutrient solution, or removal of waste from the liquid medium.

The present invention provides a scalp cooling device, including a covering part for wrapping a patient's scalp and a cooling part disposed within the covering part. This device can wrap around the patient's scalp and provide a cooling effect, causing the blood vessels in the scalp skin to constrict, reducing the blood flow to the scalp hair follicles, thereby reducing the intake of chemotherapeutic drugs by the hair follicles. Additionally, it lowers biochemical activity, thereby reducing the sensitivity of hair follicles to chemotherapy damage, and reduces the metabolic rate of the hair follicles, thus protecting the patient's hair follicles and preventing or mitigating hair loss caused by chemotherapy. Notably, the cooling part includes a gel-like coolant, which contains a moisture moderator and edible propylene glycol that maintains moisture and provides emulsifying and stabilizing effects, thus offering a long-lasting and stable cooling effect, enhancing the device's effectiveness in preventing hair loss.

A system for automated biopsy analysis is provided. The system includes a biopsy needle holder and delivery system configured to secure a biopsy needle, a sample transfer system configured to transfer a biopsy sample from the biopsy needle to a well of a multi-well plate, a liquid handling system configured to dispense and aspirate liquid to and from the well of the multi-well plate, an optical measurement system configured to measure a fluorescent signal from the well, and a control system configured to control operation of the biopsy needle holder and delivery system, the sample transfer system, the liquid handling system, and the optical measurement system. The system enables automated processing and analysis of biopsy samples, improving efficiency and reproducibility of metabolic rate determination and other tissue analysis.

A method of control of an indoor space, in particular of parameters, preferably of well-being, of the indoor space; wherein the control method comprises the following steps of : determining, in particular calculating and / or measuring, at least three first parameters, preferably at least four or five first parameters, selected from the group of parameters : temperature; humidity; relative air speed; heat insulation of persons and / or current month; metabolic rate of persons; noise; carbon dioxide; carbon monoxide; volatile organic compounds (VOC); airborne particulate matter of the PM1 type; airborne particulate matter of the PM2. 5 type, airborne particulate matter of the PM10 type; - calculating an index, preferably related to well-being in said space, using the at least three parameters, preferably the at least four or five parameters; - comparing said index, preferably related to well-being in said space, to at least a threshold value range; if said index is outside the at least one threshold value range, defining how at least one second parameter must vary in order to bring said index within the at least one threshold range; wherein said second parameter is selected from the group of parameters : air speed, temperature, humidity, noise, carbon dioxide, carbon monoxide, volatile organic compounds (VOC); airborne particulate matter of the PM1 type, airborne particulate matter of the PM2. 5 type, airborne particulate matter of the PM10 type; and defining an action to be performed to achieve the defined change of said at least one second parameter.

A method for estimating a metabolic rate of a user includes obtaining pulse oximetry data for the user for a period of time. The method includes determining a rate of decline in oxygen saturation of blood of the user that is associated with a breathing rate of the user for the period of time based, at least in part, on the pulse oximetry data. The method includes estimating the metabolic rate of the user for the period of time based, at least in part, on the rate of decline in the oxygen saturation of the blood that is associated with the breathing rate of the user. The method includes providing a notification indicative of the metabolic rate for the period of time.

Provided are a resting metabolic rate detection method. In one example method, the wearable device can display a first resting metabolic rate and display a second resting metabolic rate after obtaining exercise data of a user; wherein the first metabolic rate is different from the second resting metabolic rate.

The invention relates to the technical field of lung function evaluation, in particular to an atomization image analysis method for lung ventilation function evaluation. The method comprises the following steps: firstly, acquiring lung atomization images under various concentrations by changing the concentration of aerosol; based on image block level analysis, the lung is divided into different functional regions (such as lung lobe and airway regions), particle distribution difference characteristics of different image blocks are compared to quantify deposition indexes, and regional ventilation uniformity is reflected; sub-regions are further divided in combination with density clustering, the number change of atomized particles is analyzed across time points, and a metabolic rate index is calculated to represent local metabolic activity; and finally fusing the deposition index and the metabolic rate index to generate a ventilation obstruction evaluation value. According to the method, through space-time sequence multi-parameter coupling, the breathing mode and individual difference interference are effectively reduced, the ventilation function and the metabolism state are synchronously analyzed, a quantitative basis is provided for pulmonary ventilation disorder analysis, and evaluation comprehensiveness and clinical decision accuracy are remarkably improved.

The invention discloses a heat stress prediction method for high-temperature and high-humidity mine operators. The method comprises the following steps: measuring environmental parameters of a high-temperature and high-humidity mine; physiological parameters of miners with different adaptation days are monitored; performing integrated analysis on the data, and determining the heat and moisture resistance and the static metabolic rate of the original miner clothing when the dynamic correction is not performed; according to the adaptive days and the real-time heart rate of the miner, the metabolic rate of the miner during operation is dynamically predicted; according to different wind speeds and relative humidity, carrying out dynamic comprehensive correction on the heat and humidity resistance values of the miner clothes worn by the operator; on the basis of the metabolic rate, the corrected miner clothing parameters and the actual environment parameters, a human body heat balance equation is carried out to calculate the rectum temperature and the accumulated sweating amount of the miner; dynamically evaluating the current heat stress state of the miner; and the heat stress state and the maximum allowable working time of the current working condition are generated through calculation. According to the method, the heat stress of the mine workers can be dynamically and accurately predicted in combination with environment-metabolic rate-clothing, and occupational health and safety of the miners are effectively guaranteed.

The present invention relates to a composition for preventing, alleviating, or treating fatty liver, comprising gintonin derived from red ginseng meal as an active ingredient. The present invention uses gintonin isolated from by-products of red ginseng, which is widely used as a health functional food, and thus has almost no side effects, is safe, and has the advantage of lowering unit cost to enable long-term administration. In addition, anti-obesity, metabolic rate increase, and liver fat accumulation inhibitory effects thereof were identified through specific experiments, and thus the present invention is expected to be effectively used as a pharmaceutical, food or the like for preventing, alleviating, or treating fatty liver disease.

The invention provides an intestinal flora metabolite monitoring-based depression drug dose dynamic adjustment method and device, and is applied to the field of medical data processing. The method comprises the following steps: acquiring intestinal flora metabolite data including short-chain fatty acid concentration and drug in-vitro parameters including metabolic rate; processing the data to capture action rules of metabolites and drugs, and generating initial dose regulation reference data and metabolic risk prompts; simulating interaction under different doses, and combining a safety threshold and an active target to obtain a target adjustment parameter and a curative effect prediction report; through drug half-life period and environmental stability correction, a scheme considering both curative effect and safety is formed. Further generating a comprehensive strategy fused with a metabolism rule; and finally integrating the information to generate dose regulation effect evaluation information containing in-vitro effective rate and metabolic safety coefficient.

The invention relates to the technical field of medical nursing, in particular to a traditional Chinese medicine and western medicine combined nursing intervention method and system for gynecological chronic pelvic pain, and the method comprises the following steps: generating pelvic blood stasis blocking sign data based on pelvic microcirculation and muscular tension, tracking a pain point transfer path, and dividing a transfer path to obtain a channel-following targeted link set; calling the targeted link set to analyze the cooperative relationship to generate an osmotic drug delivery configuration table, and extracting the effusion absorption rate according to the configuration table to establish an intervention association evaluation data set. In the invention, the pelvic ischemia state is analyzed to construct a blood stasis index, track a pain point transfer path and divide a targeted transfer route of a target, the deep targeted permeability of local tissues is strengthened, the administration period is solved to optimize electrochemistry and channel warming and cold expelling mechanisms, the deep focus transdermal driving force is enhanced, and the pain-inducing factor metabolic rate is increased; the retention time of hydrops is reduced, the painless duration of a patient is prolonged, and the comprehensive nursing and rehabilitation quality of the gynecological chronic pelvic pain is comprehensively improved.

The invention belongs to the technical field of energy efficiency management, and discloses an air conditioner energy-saving potential analysis method based on a smart energy management system. The method comprises the steps of collecting activity types and calculating to obtain a metabolic rate coefficient; acquiring indoor and outdoor temperature and age distribution, and calculating to obtain dynamic comfortable temperature; calculating according to the metabolic rate coefficient to obtain a thermal load distribution map and a dynamic air supply amount; calculating according to the dynamic comfortable temperature to obtain a temperature adjustment potential; according to the thermal load distribution map, the dynamic air supply amount and the temperature adjustment potential, a predictive control strategy is obtained through calculation; analyzing according to the comfort interval and the service life of the equipment to obtain a list of the equipment with abnormal standby energy consumption; acquiring real-time power of equipment, and calculating to obtain an energy efficiency attenuation rate; and analyzing the list of the equipment with the abnormal standby energy consumption and the predictive control strategy to obtain optimization parameter update. The energy efficiency of the air conditioner is accurately optimized through multi-dimensional dynamic analysis, and the energy-saving effect of the building is remarkably improved.

The invention provides an intelligent anesthesia scheme generation method and device based on patient physical sign data, and relates to the technical field of automatic process.The method comprises the steps that by obtaining perioperative period multi-source physical sign data and completing time alignment and artifact elimination, the temperature correction metabolic rate and the perfusion zoom coefficient are calculated in combination with a core body temperature track, and the target target is obtained; correcting the pharmacokinetic parameters to obtain a body temperature dependent clearance rate and a central ventricle distribution volume; a pharmacodynamic model is established on the basis, anesthesia depth priori estimation is calculated by means of effect room concentration and body temperature corrected half effect concentration, credible weight is given to a channel in combination with multi-source sign sequence residual errors and uncertainty, and anesthesia depth estimation after confidence weighting is output; finally, a cost function is jointly constructed according to anesthesia depth estimation and the core body temperature track, and the infusion rate or the injection dosage is optimized and generated under the safety constraint of a circulation system. According to the invention, the universality of individualized anesthesia management based on the physical sign data of the patient can be improved.

The application discloses a kind of based on digital twinning egg chicken type breeding simulation system, it is related to intelligent breeding technical field, including data acquisition unit, for obtaining multidimensional state parameters, and output to biological state quantification unit;Biological state quantification unit is used to solve out individual metabolic rate index and group aggregation entropy;Time lag characteristic analysis unit is used to quantify and generate biological response time lag complexity index;Regulation and control instruction generation unit is used to calculate temperature demand reference value, and further generate final temperature setting target value;Model self-optimization unit is used to predict the biological state of next time, and compare with the actual observation state after regulation and control execution, generate prediction error, and the weight and coefficient preset in system are iterated and updated.The application quantifies egg chicken biological state and response characteristics accurately, realizes accurate, flexible and can continuously self-improve intelligent environmental regulation and control by combining model self-optimization, significantly improves breeding efficiency and animal welfare.

Compositions consist essentially of trigonelline or consist of trigonelline. The compositions can be used in food or beverage applications, pharmaceutical formulations, or as a dietary supplement. The compositions can be administered to a mammal to treat or prevent a mitochondria-related disease or a condition associated with altered mitochondrial function in an individual in need thereof or at risk thereof. The mitochondria-related disease or condition is selected from the group consisting of deleterious effects of aging, stress (e.g., oxidative stress), obesity, overweight, reduced metabolic rate, metabolic syndrome, diabetes mellitus, complications from diabetes, hyperlipidemia, neurodegenerative disease, cognitive disorder, stress-induced or stress-related cognitive dysfunction, mood disorder, anxiety disorder, age-related neuronal death or dysfunction, chronic kidney disease, kidney failure, trauma, infection, cancer, hearing loss, macular degeneration, myopathies and dystrophies, and combinations thereof.

Disclosed are a novel camptothecin compound, a linker-camptothecin compound, and a use thereof in a ligand-drug conjugate. Specifically, the involved camptothecin compound and an antibody-drug conjugate prepared therefrom can produce relatively good inhibitory activity on tumors in vivo and in vitro and exhibit significant toxicity and efficacy; in addition, a suitable metabolic rate also provides sufficient safety guarantee. These advantages are of great value for the development of antibody-drug conjugates in clinical treatment.

Systems and methods for perfusing the target tissue are provided. The system can include a processor and a bioreactor. The bioreactor includes a media reservoir for storing media, a peristaltic pump for transferring the media, a perfusion chamber for culturing the target tissue with the media, and a plurality of sensors. The perfusion chamber, the peristaltic pump, and the media reservoir are coupled through the tubing. The processor includes an artificial intelligence (AI) module and is configured to generate periodic reports on the metabolic rate of the target tissue through the plurality of sensors and control an operation of the bioreactor for extending a perfusion period.