14200 results about "Nutrition" patented technology

A system can process an indication of user data, wherein the user data comprises a food item including at least one recipe having one or more ingredients, and a query, wherein the query is associated with at least one ingredient, and generate, based at least in part on the query, nutrition data associated with the at least one ingredient, wherein the nutrition data comprises preparation data, sourcing data, delivery data, and a list of nutrients for the at least one ingredient. The system can further estimate, based at least in part on the nutrition data associated with the least one ingredient, a nutritional score, then compare the estimated nutritional score to a threshold, and based on the compared nutritional score, generate one or more instructions to cause an indication of the nutritional score on a user device.

The invention relates to the technical field of medical rehabilitation, in particular to an artificial intelligence-based orthopedic full-cycle rehabilitation management system, which comprises a rehabilitation demand evaluation module, a three-dimensional pathological modeling module, a multi-modal training generation module, a rehabilitation effect prediction module, a dynamic parameter adjustment module and a full-cycle management module. Multi-dimensional data such as bone mineral density, joint motion range, gait mechanics and psychological state of a patient are collected, an artificial intelligence algorithm is combined for analysis, a personalized rehabilitation scheme is generated, and rehabilitation parameters are predicted and adjusted in real time. The system can dynamically correct the training intensity, the nutritional supplement dosage, the psychological intervention mode and the rehabilitation schedule, and the safety and reliability of data are guaranteed through the block chain technology; according to the system, biomechanics, nutriology, psychology and environmental factors are comprehensively fused, the system has strong adaptive ability and full-period management ability, real-time optimization can be performed according to the rehabilitation process of a patient, and the rehabilitation effect of the orthopedics department and the satisfaction degree of the patient are remarkably improved.

The invention relates to the technical field of agricultural planting management, and discloses an intelligent agricultural planting method and system. The method comprises the following steps: analyzing nutritional requirements based on environment sensing and plant image data, and generating nutrition allocation data; carrying out growth prediction through seedling image features and formulating a cultivation standard; spectral parameters are extracted according to environment condition analysis and canopy images, and an environment regulation and control scheme is formed; combining growth state evaluation and pest and disease damage characteristics to calculate health indexes; a management strategy is optimized through growth parameter time sequence analysis; and determining the harvesting opportunity and grade evaluation according to the plant maturity and quality characteristics. According to the application, environment monitoring, growth diagnosis, quality evaluation and market analysis are organically combined, so that more accurate and intelligent agricultural planting decision support is provided.

The invention discloses a sheep flock accurate nutrition supply method based on an intelligent feeding algorithm, and the method comprises the following steps: collecting the body type, physiology, movement and environment data of sheep through a multi-modal sensing device, and constructing individual three-dimensional representation based on a neural radiation field model, historical growth data and a real-time health state are analyzed by utilizing an individual nutritional requirement calculation model, an optimal feed distribution strategy is determined by combining an intelligent sheep flock optimization algorithm, a feeding scheme is dynamically adjusted by adopting deep reinforcement learning, and through a cloud-side collaborative calculation architecture, the calculation efficiency is improved and a feeding decision is optimized. A non-intrusive health monitoring technology is combined, a group health evaluation model is constructed, the feed ratio is adjusted in real time, accurate matching of individual and group nutritional requirements is achieved, and through prediction of the individual and group nutritional requirements, self-adaptive adjustment is conducted on feeding parameters, and a dynamic nutrition supply strategy is optimized. The system effectively improves the feeding precision, reduces the feed waste, and optimizes the health management of the sheep flock.

The invention relates to the field of nutrition and health management, and discloses a nutrition evaluation and prediction method and system based on big data, and the method comprises the following steps: firstly collecting the physiological data, diet record and activity data of a user, and carrying out the preprocessing of the data, and guaranteeing the data quality; dimensionality reduction is carried out through feature extraction and principal component analysis, and key features are extracted; the method comprises the following steps: evaluating daily nutritional requirements of a user by using a multivariable linear regression model, a Bayesian network and causal inference, predicting a nutritional requirement change trend of the user in a future period of time based on a long-short-term memory network, and optimizing daily diet selection of the user by using a Markov decision process; and finally, generating a personalized nutrition scheme by adopting linear programming and a genetic algorithm, and ensuring that the nutritional requirements and health targets of the user are met. According to the method, personalized and scientific diet suggestions can be provided, and the quality and effectiveness of individual nutrition management are improved.

The present disclosure provides non-intergeneric remodeled microbes that are able to fix atmospheric nitrogen and deliver such to plants in a targeted, efficient, and environmentally sustainable manner. The utilization of the taught microbial products will enable farmers to realize more productive and predictable crop yields without the nutrient degradation, leaching, or toxic runoff associated with traditional synthetically derived nitrogen fertilizer. The remodeled microbes taught herein are able to be combined with leading agricultural chemistry and elite germplasm. Furthermore, the disclosure provides seed treatments comprising remodeled microbes.

Systems for plant culture include a chamber featuring one or more walls enclosing a spatial volume internal to the chamber, where the one or more walls include a surface for supporting a plant within the enclosed spatial volume, a gas delivery apparatus with at least one gas source, a nutrient delivery apparatus with a reservoir, a sampling apparatus connected to a port formed in the one or more walls, and a controller configured so that during operation of the system, the controller activates the nutrient delivery apparatus to deliver an aqueous growth medium to the plant, and activates the gas delivery apparatus to deliver into the enclosed spatial volume a mixture of isotopically-substituted gases. Also provided are methods of use of the system for measuring nitrogen in a plant and for identifying microbes capable of providing fixed nitrogen to a plant.

The invention provides a composition beneficial to improvement of brain cognition, memory and sleep and prevention and improvement of Alzheimer's disease, and belongs to the technical field of health food. The composition comprises L-alpha-glycerophosphorylcholine (GPC), phosphatidylserine (PS), docosahexaenoic acid (DHA), tea leaf theanine (L-theanine), vitamin B groups, vitamin D3 and the like, and is prepared into a health care product, a dietary supplement, a functional food, a medical food or a nutritional supplement by adopting the existing technology. The traditional Chinese medicine composition has the effects of effectively nourishing nerve cells, improving the brain sensitivity and improving the cognitive function. The composition is particularly directed at age-related cognitive decline and neurodegenerative diseases. Repair and regeneration of nerve cells can be promoted, the transmission efficiency of neural signals is enhanced, and the overall working efficiency of the brain is improved. Daily life challenges caused by cognitive decline can be relieved, and individual life quality can be improved.

The invention relates to the field of preparation and application of biological peptides, in particular to a hippocampal swelling peptide and application thereof in preparation of functional products for repairing male reproductive system injury. A green controllable enzymolysis technology is utilized to obtain protein polypeptide with nutritional, health-care and medicinal values, five active peptide sequences with high biological activity are obtained through further research on the basis, the high-purity active peptide is obtained through a chemical synthesis mode, and the biological activity of the peptide is verified through mouse spermatogonium.

The invention relates to bacillus, a biocontrol inoculant prepared from the bacillus and application of the biocontrol inoculant, and belongs to the technical field of biological inoculants. The bacillus provided by the invention is bacillus subtilis and is named as ZZ1, the preservation unit is China General Microbiological Culture Collection Center, the preservation address is Institute of Microbiology, Chinese Academy of Sciences, No.3, No.1 Yard, Beichen West Road, Chaoyang District, Beijing, the preservation center is numbered as CGMCC No.31374, and the preservation time is July 19, 2024. The bacillus ZZ1 disclosed by the invention has a certain bacteriostatic effect on different pathogenic bacteria regardless of living bacteria, supernate or cell lysis solution. The bacillus ZZ1 is high in living ability and wide in application range of nutrient sources, temperature, humidity and pH value. The compound has no pathogenicity to fruits and vegetables, has good tolerance to broad-spectrum bactericides, and has a great application prospect.

A high-nutrient and high-activity chemical fertilizer-biological compound fertilizer, and a preparation method and application thereof are provided. The high-nutrient and high-activity chemical fertilizer-biological compound fertilizer includes an inorganic chemical fertilizer and a microbial agent. The chemical fertilizer-biological compound fertilizer has nutrient contents of nitrogen, phosphorus, and potassium of greater than 40% and a viable number of microorganisms of 200 million cfu / g or more. The chemical fertilizer-biological compound fertilizer further includes a microbial protectant, and a mass ratio of the microbial protectant to the microbial agent is ≥1.

A programmatically generated AI avatar includes a customizable personality module, acting as the embodied interface for a powerful AI “mind” that delivers personalized coaching to improve user health, well-being, and longevity. The system uses machine learning, large language models, and biometric modeling to synthesize real-time, multi-modal health data—including sleep, nutrition, glucose, mood, and activity—and generate forward-prescribed KHAs. Unlike human coaches, it continuously adapts based on context and behavior, targeting the root cause: metabolic dysfunction—namely by restoring healthy, sustainable body composition through the preservation or building of lean muscle mass and reduction of excess fat. KHAs can also be shared with friends or programmatically generated AI avatars, allowing for coordinated action, emotional support, and accountability through social connection—further reinforcing positive behavior and adherence. The system's reinforcement learning engine incorporates both individual response data and anonymized population-level insights to optimize recommendations over time, learning which interventions are most effective for users with similar physiological and behavioral profiles. First validated with Olympic athletes—resulting in measurable improvements and medal-winning outcomes—this system offers a scalable, emotionally intelligent coaching engine that exceeds human capability, designed for the ultimate purpose of supporting sustainable health, resilience, and human thriving.

The invention relates to the technical field of microorganisms, and discloses burkholderia gladioli as well as a bacterial agent and application of the burkholderia gladioli. The Burkholderia gladioli (Burkholderia gladioli) CCTCC (China Center For Type Culture Collection) NO: M20242288 provided by the invention has good capacities of fixing nitrogen, dissolving phosphorus, dissolving zinc, producing siderophores and oxidizing sulfur, and can be used for regulating the nutrient structure of soil and converting substances which are difficult to utilize by plants in the soil, so that the growth of the plants is promoted, and the stress resistance of the plants is improved; the strain also can be used for antagonizing Fusarium solani, Fusarium equiseti, Fusarium verticillium, Fusarium verticillium and Rosellinia necatrix, can be used for antagonizing Fusarium solani, Fusarium equiseti, Fusarium verticillium and Rosellinia necatrix, and can also be used for antagonizing Fusarium solani, Fusarium equiseti, Fusarium verticillium, Rosellinia necatrix, Fusarium moniliforme and Rosellinia necatrix, Fusarium moniliforme and Rosellinia necatrix. Besides, the burkholderia gladioli provided by the invention is a strain separated from rape farmland soil, and compared with a strain screened by extreme environment and laboratory mutagenesis, the burkholderia gladioli has better adaptability when being applied to a planting environment, and can be stably colonized in plant rhizosphere and soil, so that the burkholderia gladioli stably plays a growth promoting role for a long time, is safe and environment-friendly, and has a wide application prospect. Wide application prospects are realized.

The invention discloses a cardiovascular disease risk prediction method and system based on dietary multi-modal data and ensemble learning, and the method comprises the steps: constructing a multi-modal set through integrating multi-source heterogeneous data such as demographic statistics, dietary nutrition, clinical physiological and biochemical indexes and lifestyles; data cleaning is completed based on a box plot method and missing value processing, and key features are screened through Pearson's correlation coefficients, variance expansion factors and feature importance evaluation; a plurality of heterogeneous base models are fused by adopting a Stacking integration framework, a meta-feature matrix is generated through five-fold layered cross validation, and multi-level decision fusion is realized through a logistic regression meta-model; and quantifying the contribution weight of the dietary characteristics to the risk in combination with an SHAP method, and generating a visual interpretation chart and personalized intervention suggestions. According to the method, the accuracy and the stability of a prediction result are remarkably improved, the contribution degree and the action mechanism of dietary factors and other characteristics to the prediction result can be deeply analyzed, powerful support is provided for accurate prevention and personalized treatment of cardiovascular diseases, and the method has good practical value.

The invention provides an animal feeding plan generation method and system based on ingestion monitoring data. The method comprises the following steps: obtaining ingestion time sequence data of each animal in a feeding space for a feed storage box; acquiring health index sampling data of each animal; nutritional ingredients corresponding to the feed types of the feed storage boxes are obtained, so that a feed nutrition relation graph is constructed; processing the feed nutrition relation graph on the basis of a graph neural network to obtain updated node features of each feed type graph node; and defining an input state of a feeding plan generation model by using the acquired data, so as to determine an animal feeding plan corresponding to the target action through reinforcement learning. Therefore, through data driving and in combination with an advanced graph neural network and reinforcement learning technology, the feeding amount and the feeding time of the feed can be accurately calculated, and intelligent management of the animal feeding process is realized.

The invention discloses a cooking robot control method and system based on a knowledge graph, and relates to the technical field of cooking robot control, and the method comprises the steps: collecting multi-source cooking data, constructing the knowledge graph, receiving user demands, recommending dishes based on the graph, determining cooking parameters according to the recommended dishes, and controlling the cooking robot according to the cooking parameters. Comprise time, temperature, seasoning dosage and the like. The parameters are sent to a cooking robot controller, data are collected by a sensor during cooking, the data are compared with standard data, and the parameters are adjusted by a feedback algorithm to ensure that cooking meets the expectation. According to the method, personalized dish recommendation and cooking parameter adaptive adjustment can be realized, dish quality and taste are ensured, user health is considered, nutrition balance is promoted, the intelligent degree of the cooking robot is improved, the market competitiveness of the cooking robot is enhanced, and the requirement of people for high-quality cooking experience is met.

Techniques disclosed herein relate to nutritional content determination based on gesture detection data. In some embodiments, the techniques involve obtaining gesture detection data corresponding to consumption of a food item or a drink; determining, based on the gesture detection data, nutritional content of the food item or the drink; and causing delivery of insulin in accordance with the nutritional content of the food item or the drink.

The present invention relates to a novel association or combination of active ingredients useful in the prevention and repair of neuronal damage, both centrally and peripherally. In greater detail, the present invention relates to an association or combination of i) an extract of Gastrodia elata and ii) at least one ingredient selected from the group comprising or, alternatively, consisting of citicoline, L-acetylcarnitine and, preferably, at least one vitamin of group D, and / or mixtures thereof, and / or at least one vitamin of group B, and / or mixtures thereof. Furthermore, the invention also relates to the pharmaceutical compositions and / or compositions for medical devices (Regulation (EU) 2017 / 745) and / or nutraceutical and / or food compositions comprising that association and to their use in therapy, in particular in the protection of the functionality of the nervous system and in the prevention and / or treatment of central and peripheral neuropathies.

The invention relates to the technical field of agricultural information, discloses a corn precise topdressing prescription map generation method based on unmanned aerial vehicle multispectral remote sensing, and effectively solves the key problems of insufficient monitoring precision, poor environmental adaptability, low decision intelligent level and the like in the traditional fertilization technology. Through the unmanned aerial vehicle multispectral imaging technology, efficient and accurate monitoring of the corn nitrogen nutrition condition is achieved; in combination with a machine learning algorithm, an intelligent fertilization decision model adapted to different environmental conditions is established, and the fertilization precision in a complex farmland scene is remarkably improved; and a multi-source data fusion technology is adopted, and crop growth, soil characteristics and meteorological factors are comprehensively considered, so that the fertilization scheme is more scientific and reasonable. Compared with a traditional method, the method has the advantages that accurate variable fertilization can be realized according to actual needs of crops, the utilization rate of the fertilizer is increased, environmental pollution is reduced, and reliable technical support is provided for sustainable development of modern agriculture.

The invention discloses a rainwater centralized treatment device for gardens, and relates to the technical field of rainwater treatment.The rainwater centralized treatment device comprises a box body, a water inlet pipe installed on the outer wall of one side of the box body and a water drainage pipe installed at the bottom of the box body, and further comprises a filtering mechanism used for filtering rainwater drained into the box body through the water inlet pipe; the transposition cleaning mechanism is used for cleaning different positions of the filtering mechanism; the quantitative mixing mechanism is used for automatically obtaining the filtered quantitative rainwater, mixing the filtered quantitative rainwater with the nutritional agent and discharging the mixture; according to the rainwater centralized treatment device for the garden, by continuously filtering rainwater, the problem that the filtering continuity is influenced by blockage when the rainwater is filtered is avoided, and by automatically and quantitatively extracting the filtered rainwater, mixing the filtered rainwater with quantitative nutritional agents and automatically discharging the mixed rainwater, comprehensive treatment of the rainwater is achieved; the purpose of automatically filtering and mixing the rainwater is achieved without manually adding nutritional agents, and automatic centralized treatment of the rainwater is achieved.

The invention relates to the technical field of water treatment, in particular to a denitrification slow-release composite carbon source as well as a preparation method and application thereof. Comprising the following components in percentage by weight: 2-10% of hydroxy acrylic acid, 2-10% of saccharides, 5-15% of straw waste liquid, 5-15% of kitchen waste liquid, 2-10% of saccharides, 3-15% of porous volcanic ash, 5-15% of polyvinyl alcohol, 0.2-1% of inorganic salt, 1-2% of polypeptide, 0.5-1% of growth factors, 0.2-1.5% of MFC agar, 0.1-0.5% of cellulase, 0.1-0.5% of protease, 0.1-0.5% of denitrifying bacteria and the balance of water. The sum of the percentages of the raw materials is 100%. The invention has the advantages that: each nutrient component is balanced, the nutrition is comprehensive, the activity of denitrifying bacteria is improved, the number of species and community layers of a biological system of a sewage treatment plant are increased, the growth of various microorganisms is facilitated, nutrient substances can be fully utilized, and the denitrification effect is far higher than that of related carbon sources such as single methanol, glucose and the like.

The invention discloses a soilless culture nutrient solution containing a solid hydrogen supply material and an irrigation method and system. Raw materials of the soilless culture nutrient solution comprise the solid hydrogen supply material, a nutrient solution and a pH regulator. The use amount of the solid hydrogen supply material is 0.05-5 mmol / L; the dosage of the pH regulator is 0.01 to 50 mmol; all the raw materials are mixed, and the soilless culture nutrient solution with the irrigation hydrogen concentration larger than or equal to 500 ppb / L and the pH value of 5-8 is provided. On the basis of applying the soilless culture nutrient solution, the pH value and the hydrogen concentration of the soilless culture nutrient solution are monitored in real time, and the pH value and the hydrogen concentration of the soilless culture nutrient solution are adjusted and controlled by adjusting and controlling at least one of the applying amount of the soilless culture nutrient solution, the applying speed of the soilless culture nutrient solution, the using amount of a solid hydrogen supply material and the using amount of a pH adjusting agent. The hydrogen-rich nutrient solution can be controllably provided for soilless culture plants, stable release of hydrogen and proper adjustment of the pH value and nutritional ingredients are achieved, and the requirements of different crops and different growth stages are met.

The invention relates to the technical field of land improvement, in particular to an alginic acid type multifunctional long-acting soil conditioner and a preparation method and application of the alginic acid type multifunctional long-acting soil conditioner. The core particle layer comprises an organic material, nano silicon, calcium magnesium polyphosphate, magnesium hydride, ammonium borate, rhamnose and an adhesive, and the slow release layer comprises clay minerals and alginate; the mass ratio of the clay mineral to the alginate to the organic material to the calcium magnesium polyphosphate to the nano silicon to the magnesium hydride to the ammonium borate to the rhamnose to the binder is controlled within a certain range. The soil conditioner provided by the invention is good in slow release performance, can release effective components durably and slowly, and has multiple effects of improving soil quality, providing nutrition, promoting crop growth, improving resistance and the like; the problems of soil acidification, heavy metal pollution, micro-plastic pollution, pesticide pollution, antibiotic pollution and the like in agricultural production can be effectively solved.

The invention relates to the technical field of livestock breeding, in particular to a cow manure automatic scoring system and method.The cow manure automatic scoring system comprises an image acquisition unit, a physical property sensor, a chemical component detection module and a data processing unit.The image acquisition unit is used for capturing the form, color and fiber residue of manure; the physical property sensor is used for measuring the water content of excrement and evaluating the viscosity and hardness of the excrement; the chemical component detection module comprises a near infrared spectrum analysis unit and an electrochemical sensor unit; and the data processing unit is used for integrating an AI algorithm, realizing multi-source data fusion and scoring, and uploading the data to the cloud management platform through the communication module. Therefore, the problems that in the prior art, manual scoring is subjective, low in efficiency and difficult to quantify, diseases are difficult to find early due to the lack of rapid component detection means, and accurate nutrition regulation and control are difficult to achieve due to the fact that scoring data are difficult to integrate into a breeding system are solved.

The invention relates to the technical field of intelligent control, in particular to a monopotassium phosphate intelligent control method and system.The method comprises the following steps that rhizosphere phosphorus and potassium concentration changes are obtained, whether the rhizosphere phosphorus and potassium concentration changes are in a critical rate interval or not is judged, an effective absorption time period identifier is generated, and an organ amplification ratio is analyzed to judge a cooperation period; and extracting a stalk concentration ratio, comparing the stalk concentration ratio with a reference interval to generate an application inhibition identifier, fusing information to judge a fertilization window, adjusting the concentration according to the root hair amplification and the water consumption rate, and generating a control instruction set. According to the method, the effective time period of phosphorus and potassium nutrient absorption of the crops is determined through crop rhizosphere phosphorus and potassium ion concentration difference calculation and average treatment, the objective interval of crop nutrient absorption rate indexes is defined, blind fertilization is avoided, the pertinence and accuracy of nutrient absorption and utilization of the crops are enhanced, the excessive application state of nutrient elements is dynamically identified, and the crop quality is improved. The risk of excessive nutrients caused by nutrient enrichment of crops is prevented, and resource waste and environmental burden are effectively reduced.

The invention provides a microbial agent for promoting growth of medicago sativa and application of the microbial agent, and relates to the technical field of agriculture, the microbial agent is prepared from sinorhizobium meliloti MCSWL1, sinorhizobium meliloti MCSD1 and nitrogen-fixing rhizobium sp. MCDC3 according to the mass ratio of 1: 1: 2, and the mass ratio of the sinorhizobium meliloti MCSWL1, the sinorhizobium meliloti MCSD1 to the nitrogen-fixing rhizobium sp. MCDC3 to the nitrogen-fixing rhizobium sp. MCDC3 to the nitrogen-fixing rhizobium sp. MCDC3 is 1: 1: 2. The microbial agent for promoting the growth of the medicago sativa, provided by the invention, can form a close symbiotic relationship with the medicago sativa (particularly grassland No.3), and provides sufficient nitrogen nutrition for the growth of the medicago sativa, so that the soil fertility is effectively improved, and the healthy growth of plants is promoted.

The invention discloses a leaf nutrition state diagnosis and chemical fertilizer adjustment method based on image recognition. The method comprises the following steps: S1, collecting a leaf image; s2, performing denoising, enhancement and background removal on the image, extracting color, shape and texture features, and generating a leaf feature vector; s3, modeling by using a nonlinear dynamic chaotic system, detecting abnormal changes, and performing multi-scale chaotic analysis; s4, constructing a topological network for high-dimensional topological data analysis, and performing multi-modal data fusion in combination with a Bayesian network; s5, dynamically adjusting algorithm parameters according to a fusion result; s6, generating a diagnosis result through a generative adversarial network, image fusion and a deep artifact removal algorithm; and S7, constructing a cognitive intelligent agent and group intelligence optimization algorithm, and carrying out dynamic environment adaptation and closed-loop feedback regulation and control. According to the invention, the efficiency and accuracy of nutrition state diagnosis are improved, the fertilizer application is optimized, and the environmental pollution is reduced.

The invention relates to the technical field of medical equipment, and discloses a nutrient canal anti-blocking control system based on pipeline resistance monitoring, and the system comprises a data collection module which collects the real-time pressure difference, flow and fluid temperature in a pipeline; the data processing module is used for calculating a real-time resistance value in the pipeline; the resistance prediction module is used for establishing a resistance model based on the historical resistance value and the real-time resistance value and predicting the trend of the resistance value; the water injection control module generates an adjusting instruction for dynamically adjusting the water injection flow; the water injection execution module injects water into the pipeline according to the adjusting instruction of the water injection control module to prevent the pipeline from being blocked; and the feedback module adjusts water injection parameters of the water injection control module. A resistance model is established through the data acquisition module and the data processing module, the resistance trend is predicted, a water injection anti-blocking strategy is automatically generated, and accurate monitoring, intelligent prediction and efficient anti-blocking are achieved. And human intervention is not needed, the problems of slow blocking response and high maintenance cost are solved, manpower is greatly saved, and the anti-blocking efficiency is improved.

The invention relates to the cross technical field of computers and livestock breeding, and discloses an intelligent nutrition mode management method and system based on HAP multi-modal data, and the method comprises the steps: obtaining the multi-source heterogeneous HAP data of livestock, and carrying out the feature extraction and feature fusion of the multi-source heterogeneous HAP data; utilizing a controllable generative adversarial network to generate enhanced HAP feature data and an HAP feature data sequence simulating a physiological process; early abnormal signals are detected through an abnormal detection algorithm, and multi-modal attribution analysis is carried out; continuously optimizing the nutrition demand prediction model and the feeding strategy optimization model; according to the method, by effectively utilizing the neglected unstructured information in the past and combining the multi-modal fusion analysis, the early-stage discovery capability of the weak signal for indicating the physiological abnormality or nutritional imbalance of the livestock and poultry is improved.

The invention relates to an integrated management system for diabetic patients, which comprises the following steps of: constructing a high-dimensional metabolic data model, performing multi-modal fusion on genome information, metabolome data and life behavior data, and mining a potential mode of metabolic characteristics of the patients; carrying out patient typing by utilizing a clustering algorithm comprising a self-organizing mapping network, and identifying different metabolism types comprising an insulin resistance type and an insulin secretion insufficiency type; developing a hierarchical management strategy based on a typing result, wherein the hierarchical management strategy comprises diet, exercise and medicine intervention schemes for different types; collecting dynamic quantitative indexes of the metabolic load, and integrating the blood glucose fluctuation amplitude, insulin sensitivity and daily nutrition intake of the patient; constructing a metabolic load prediction model, and combining a time sequence deep learning algorithm with real-time data, including blood glucose, diet and exercise, of a patient to measure a future metabolic load; and establishing a causal relationship model between patient behaviors and metabolic reactions, and analyzing an interaction mode of diet, exercise and metabolic loads by adopting a causal inference technology.