145 results about "Environmental agent" patented technology

The invention discloses lysozyme, antibacterial peptide derived from the lysozyme and application of the lysozyme in preparation of antibacterial drugs. According to the invention, 1, 640 protein sequences recorded in a ruminant rumen caterpillars genome database are systematically predicted based on a lysozyme prediction model, and finally, the lysozyme with the amino acid sequence as shown in SEQ ID No.1 is relatively strong in antibacterial activity and stable in antibacterial activity, and is slightly influenced by environmental factors. According to the invention, an antibacterial peptide region of the lysozyme is analyzed and determined, three peptide fragments with clear antibacterial activity are identified, and the amino acid sequences of the peptide fragments are respectively shown as SEQ ID No.2, SEQ ID No.3 or SEQ ID No.4. The antibacterial peptide provided by the invention has relatively strong membrane destroying ability and broad-spectrum antibacterial activity, and compared with integral protein, the antibacterial peptide is simpler in structure and more flexible in synthesis and modification, and is easier to break through a bacterial drug-resistant mechanism.

The invention belongs to the technical field of novel pesticides, and particularly provides a bactericide suspending agent and a preparation method thereof.The effective component of the bactericide suspending agent is prothioconazole, and on the basis of the effective component of the bactericide suspending agent, microencapsulated oxidized vegetable oil accounting for 5-15% of the weight of the whole bactericide is added to serve as a synergistic auxiliary agent. The prothioconazole bactericide has the advantages that the adhesion capacity of the prothioconazole bactericide on the surfaces of crops can be obviously improved, the adverse effects caused by environmental factors such as rain wash are reduced, and the absorption of the bactericide is facilitated, so that the synergistic effect is achieved.

The invention relates to the technical field of smart breeding and big data analysis, and discloses a smart breeding monitoring method and system based on big data analysis. The method comprises the following steps: periodically acquiring original data of a farm sensing network, and constructing a multi-dimensional state image through time-space synchronization and normalization processing; inputting the image into a pre-trained behavior-environment decoupling analysis network, and stripping an independent behavior feature tensor and an independent environment background field tensor in parallel; and based on the two, calculating a coupling degree index through a cross impact evaluation matrix and generating a comprehensive anomaly scoring graph. According to the graph, a strategy generation engine dynamically synthesizes a regulation and control instruction set containing directional airflow guide, refined feeding and temperature and humidity coordinated regulation. According to the method, deep separation and correlation analysis of animal behaviors and breeding environment factors are realized, an abnormal root can be accurately traced, and early warning and systematic precise regulation and control are realized.

The invention belongs to the technical field of data processing, and relates to a disinfectant verification method based on Jerlin codes. The invention aims to solve the problem of biological potential safety hazards that the identity and the state are separated in the anti-counterfeiting verification of the existing disinfectant, and the titer of the liquid medicine falls off the threshold value due to environmental factors cannot be identified. The method comprises the following steps: in response to a code scanning operation, analyzing a Jerlin code to obtain a factory fingerprint, and splicing cloud logistics and terminal storage data to form a full-link environment monitoring sequence; calculating an environment pressure acceleration coefficient of each time slice by using a nonlinear kinetic model, and evaluating the damage degree of the environment to chemical properties; calculating accumulated chemical loss and residual titer based on the coefficient; and comparing the residual titer with a threshold value, and if the residual titer reaches the standard, generating a dynamic hash token containing titer information for cloud verification. According to the invention, deep combination of physical efficacy and digital verification is realized, and the use safety and reliability of the disinfectant are greatly improved under the condition that an expensive sensor is not needed.

The invention relates to the technical field of medicine management, in particular to an intelligent medicine expiration date management method and system, and the method comprises the steps: collecting environment parameters of medicine storage in real time; constructing a characteristic database of drug stability, and constructing a degradation rate model of the corresponding drug based on the characteristic database; based on the environmental parameters and a degradation rate model, calculating an accumulated value of the current storage condition to the drug quality, and generating a quality risk level; and generating a medicine optimization management instruction based on the quality risk level and the remaining time of the medicine fixed effective period. By means of the method, the problem that the medicine effect fails in advance due to the fact that dynamic environment factors are neglected in a traditional method is effectively solved, accurate early warning of quality deterioration is achieved through dynamic monitoring and degradation modeling, supervision blind areas are eliminated, and the risk of medical resource waste is reduced.

The invention discloses antistatic medical gauze and a preparation method thereof, and relates to the technical field of medical gauze. The antistatic medical gauze comprises the following raw materials in parts by mass: 60-80 parts of cotton fibers, 1-5 parts of an antistatic agent, 5-15 parts of a water-soluble polymer and 0.5-1 part of an antibacterial agent. Compared with the traditional technology that the antistatic effect is transient and is easily influenced by environmental factors, the invention realizes long-acting and stable charge neutralization capability by introducing a specific micromolecule antistatic agent (such as a compound shown in the formula 1) and combining a moisture absorption conductive mechanism, an ionization effect and surface energy regulation. The trend shows that the static dissipation is faster and the effect is lasting, the problems of potential safety hazards and dust adsorption caused by charge accumulation are effectively avoided, and the defect that the effect of an antistatic agent in the prior art is not lasting is overcome.

The invention discloses a garden disease and pest identification method and system based on computer image processing, and belongs to the technical field of disease and pest monitoring, and the method specifically comprises the steps: collecting a visible light image, an infrared image and environment parameters of vegetation; performing space-time registration on the visible light image and the infrared image and generating a three-dimensional temperature field model; the three-dimensional space is divided into grid units, and the temperature statistical characteristics and the vertical direction temperature gradient of each unit are extracted; obtaining an expected temperature gradient direction through a preset standard three-dimensional radiation field reference model; and when the actual gradient direction is consistent with the expected gradient direction, calculating a gradient direction deviation value of each grid unit, calibrating the grid unit with the deviation exceeding a threshold value as an abnormal region, and extracting a corresponding visible light image to carry out pest recognition. According to the invention, early-stage accurate identification of diseases and insect pests is realized, systematic diseases and local insect pests are effectively distinguished, interference of environmental factors is overcome, and the reliability of insect pest monitoring is improved.

The invention discloses a sea-land interaction zone underground water pollution source tracing method based on multi-pollutant fingerprints, and the method comprises the steps: constructing a fingerprint feature library of eight key pollutants including cadmium, arsenic, nitrate nitrogen, ammonium nitrogen, phosphate, total petroleum hydrocarbon, sulfamethoxazole, pH value and the like; statistical characteristic models of four pollution sources of industrial emission, agricultural non-point sources, oil exploitation and aquaculture are established, Z-Score standardization and a similarity calculation method based on a standard normal distribution probability density function are adopted, comprehensive similarity evaluation is performed in combination with a risk weight distribution mechanism, a similarity threshold value of 0.7 is set to perform pollution source identification and sorting, and the pollution sources are identified and sorted according to the similarity threshold value. And correction is performed by considering environmental factors such as tide, season and geology of a sea-land interaction zone. The method can quickly and accurately recognize the groundwater pollution source of the sea-land interaction zone, the traceability accuracy rate reaches 80% or above, and scientific and technical support is provided for prevention and control of groundwater pollution of the sea-land interaction zone and formulation of an environmental protection policy.

The invention provides a deep learning-based dangerous rock mass collapse landslide monitoring and early warning method and system, and relates to the technical field of geological disaster monitoring and early warning, and the method comprises the steps: obtaining rock mass monitoring data; according to the rock mass monitoring data, carrying out dangerous rock mass collapse landslide risk preliminary identification; when it is preliminarily recognized that the dangerous rock body does not have the collapse landslide risk, rock body monitoring data are obtained again; when the collapse landslide risk of the dangerous rock body is preliminarily identified, acquiring environment monitoring data; according to the rock mass monitoring data and the environment monitoring data, through a deep learning algorithm, carrying out dangerous rock mass collapse landslide risk fine identification; when it is finely recognized that the dangerous rock body does not have the collapse landslide risk, rock body monitoring data are obtained again; and when the collapse landslide risk of the dangerous rock body is finely identified, an early warning signal is sent out. According to the invention, environmental factors are considered, and timely and accurate early warning information can be provided in the face of complex and changeable natural environments.

The invention discloses a cibotium barometz sporophyte transformation method and system based on multi-factor coupling regulation, and relates to the technical field of biology. The method comprises the following steps: synchronously acquiring environment data and sporophyte image data; preprocessing the environment data, performing feature extraction on the image data, and splicing the processed data into a comprehensive feature vector; quantifying the weight, correlation degree and interaction level among the environmental factors through an entropy method, grey correlation analysis and a coupling coordination degree model; constructing an improved CNN-LSTM neural network, extracting features through a double-branch structure, fusing a coupling analysis result to carry out cross-modal fusion, and training to obtain a prediction model; when the predicted conversion rate is lower than a threshold value, environment parameters are automatically adjusted until conversion is completed; according to the method, the problems of environmental factor data isolation and regulation lag in the prior art are solved, accurate prediction and intelligent regulation of the sporophyte transformation process are realized, and the transformation success rate and the production efficiency are remarkably improved.

The invention relates to the technical field of animal behavioral experiments, and discloses an animal behavioral experiment multi-scene simulation system. According to the invention, through cooperative control of multiple environment modules and seamless switching of a dynamic scene, continuous switching of natural scenes such as illumination, sound, smell, terrain and the like is accurately simulated; on the basis of real-time biological signal detection and intelligent feedback, environment adjustment or scene switching is automatically triggered according to animal behaviors / physiological states, and closed-loop self-adaptive adjustment is formed; in combination with an intelligent decision and an AI scene generation engine, self-definition and iterative optimization of a complex script are supported; the parameter coupling controller simulates the interaction effect between environmental factors, the fault-tolerant mechanism and the effect evaluator guarantee the data reliability, the closed-loop verification loop efficiently establishes a causal model of environmental parameters and behavior response, and a high-authenticity, self-adaptive and reproducible experimental platform is provided for animal behavior research.

The invention provides a nano lipid carrier system with photo-thermal stability as well as a preparation method and application thereof, and relates to the technical field of nano preparations. The lipid carrier comprises the following components: an active substance, hydrogenated lecithin, simmondsia chinensis seed oil, SpectrastHCP, an emulsifier and a chelating agent, wherein the active substance is resveratrol. The lipid carrier has better stability, is stable under the conditions of dilution, centrifugation and the like, and can be stored for a long time in a severe environment. Indissolvable substances such as resveratrol are wrapped by the lipid carrier, so that the water solubility of the substances can be remarkably improved, and the problem of difficult dissolution is solved. In addition, the wrapping of the lipid carrier can effectively isolate the influence of oxygen, illumination and other environmental factors, the stability of the active matter can be improved, and meanwhile, the discoloration problem is effectively improved. When the nano-scale lipid carrier is applied to a preparation, the nano-scale lipid carrier can more easily penetrate through the skin barrier and deeply penetrate into the deep layer of the skin, and the effect of transferring active matters is more facilitated.

The invention discloses a composite microcapsule of bacillus subtilis and trichoderma asperellum, which is prepared by the following steps: embedding bacillus subtilis Pn1 and trichoderma asperellum Ta1 by adopting sodium alginate, and carrying out microencapsulation treatment, so that the controllable release of the bacillus subtilis Pn1 and the trichoderma asperellum Ta1 is realized; therefore, the stability of the composite biocontrol bacterium under adverse environmental factors is improved, meanwhile, the inhibition effect on root rot bacteria is enhanced, and the sodium alginate embedded bacillus subtilis Pn1 and trichoderma asperellum Ta1 have important application value in prevention and treatment of panax notoginseng biological root rot.

The invention discloses an XGBoost chlorophyll a concentration aerial remote sensing inversion method based on characteristic wave band selection, and relates to the technical field of environmental monitoring. By constructing an integrated input characteristic vector, an optimal characteristic wave band most relevant to the chlorophyll a concentration, an enhanced chlorophyll a index and specially designed correction characteristics are fused; and more targeted information is provided for the model. Moreover, correction features obtained through calculation of spectral difference values of adjacent shadow regions and non-shadow regions are introduced, and training data containing samples of the two regions are utilized to train an XGBoost model, so that the XGBoost model can autonomously learn and quantify a composite interference effect brought by illumination and suspended matter concentration change. Therefore, according to the technology, inversion noise caused by complex environmental factors can be effectively inhibited, high-precision and full-coverage inversion of the chlorophyll a concentration under different illumination and turbidity conditions is realized, and the robustness and the practical application value of the method are remarkably improved.

Select substituted lysine and branched amino acid salts, compositions containing the same and the use of the foregoing in treating the adverse physiological effects of various diseases, especially skin diseases; in mitigating the effects of aging and environmental factors on skin; and in improving and rejuvenating skin.

METHODS FOR GEOLOCATION-BASED SKIN SCIENCE-BASED ENVIRONMENTAL EXPOSURE METRICS Methods for communicating the risk of skin conditions due to exposure to sunlight and environmental conditions to individuals. These methods leverage geolocation and environmental data to provide guidance and enable consumers to make informed decisions regarding outdoor activities, healthcare, and skincare. A photopollution metric is a function of the ultraviolet index (UVI) and the level of a pollutant such as particulate matter (PM) and allows for the communication of an individual's risk of exposome-induced skin conditions based on environmental exposure. Figure for abstract: none

The present application relates to a kind of ship hull fouling detection method and system that can accurately remove environmental interference, the method includes the storage and pre-processing of multi-source data, the reference effective power under the prediction of unblocked state, the effective power required by the actual output and the effective power required by the environmental additional resistance, the effective power required by the consumption, the quantification and identification of fouling state and the output and visualization of result.The method can realize the high-precision quantitative evaluation of the degree of ship fouling, and accurately removes the interference of wind, wave, seawater temperature, salinity and other environmental factors.The above multi-source data can be collected synchronously in millisecond level to ensure the consistency of data space-time, in addition, the method is matched by resistance decomposition and fouling database, the fouling coverage area, thickness and type are accurately calculated, and the accuracy and reliability of fouling detection are significantly improved.

The invention belongs to the technical field of cultural relic protection and building information models, and discloses an ancient city wall daily management and disease management and control system and method based on BIM scene construction. An existing disease management and control system has the problems that the urban wall occurrence environment and the repair history are difficult to comprehensively consider, and multi-disease collaborative analysis is lacked. According to the method, non-structural nodes are introduced, environmental factors such as a drainage system, vegetation coverage, underground facilities and an internal space are incorporated into a city wall management system, and collaborative expression of a city wall structure and an occurrence environment is realized on the basis of structural partitioning. According to the system, urban wall block numbers serve as a unified index, monitoring data, disease information and repair records are fused, spatial visualization and information linkage are achieved based on a BIM scene, meanwhile, a threshold value management mechanism is set, when state parameters of non-structural nodes reach a threshold value, a corresponding maintenance protection scheme is triggered, and the maintenance and protection efficiency is improved. And urban wall information management, disease dynamic monitoring and scientific repair decision making are realized.

The invention discloses a strawberry gray mold early warning system and method based on multi-physiological index collaboration, belongs to the technical field of strawberry gray mold early warning, and solves the problems that in the prior art, due to dependence on a single data source, a model is easily interfered by environmental factors, early abnormal performance of gray mold in multiple physiological levels cannot be comprehensively captured, and the early warning effect is poor. Therefore, the recognition accuracy of the strawberry gray mold asymptomatic latency period is reduced. The data acquisition layer is used for acquiring fluorescence indexes, spectral indexes and photosynthetic indexes of strawberry plants; the feature processing layer is used for respectively calculating feature indexes corresponding to the fluorescence index, the spectrum index and the photosynthetic index acquired by the data acquisition layer; the alarm judgment layer is used for judging alarm levels corresponding to the feature indexes output by the feature processing layer; and the decision fusion layer is used for performing fusion decision according to the alarm level output by the alarm judgment layer to obtain an early warning state. The strawberry gray mold early warning method is used for realizing accurate and effective strawberry gray mold early warning.

The invention relates to water eutrophication detection equipment based on an intelligent sensing system, in particular to the technical field of environment detection and Internet of Things. The equipment comprises a data acquisition, processing, evaluation, output and maintenance module, water quality detection data is obtained through an online detection equipment probe, after abnormity processing, missing value filling and classified storage, an embedded algorithm model is adopted for water quality category and eutrophication evaluation, data are uploaded in real time and early warning is carried out, algorithm model updating and parameter configuration are supported, and the online detection equipment is used for online detection. The equipment realizes multi-parameter real-time monitoring and intelligent analysis, supports automatic early warning and remote maintenance, improves the detection efficiency and accuracy, effectively reduces the influence of environmental factors on a detection result, improves the equipment stability in combination with a nano protection technology, and provides reliable technical support for water pollution prevention and control.

Systems, devices, and methods including a processor having addressable memory, where the processor is configured to: collect, via a set of sensors, biological signals related to patient status; collect, via an environmental monitoring device, environmental data associated with an environment of the patient; store, locally via a secure encrypted local database, the collected biological signals and the collected environmental data; detect an abnormality in the collected biological signals; increase measurement frequency of the biological signals by the set of sensors based on the detected abnormality; detect an error in the collected biological signals; determine whether the detected error in the collected biological signals of the current reading is due to environmental factors; correct the determined error in the collected biological signals; and transmit the error corrected collected biological signals as encrypted data.

The application provides a metal nanomaterial toxicity prediction method and device, the method comprises the following steps: collecting related data affecting the toxicity of the metal nanomaterial, wherein the related data comprises the physical and chemical properties of the metal nanomaterial, the interaction mode between the metal nanomaterial and organisms, the influence data of external environmental factors on the metal nanomaterial, and the selective reaction data of the metal nanomaterial between different organisms; screening target indexes from the related data and calculating the weights of the target indexes; inputting the target indexes and the weights corresponding to each target index into a pre-trained toxicity prediction model to obtain a metal nanomaterial toxicity prediction result. It can be seen that the application considers multiple dimensions and calculates the weights of the indexes, the indexes considered are more comprehensive, and the index weights can better reflect the influence degree of each index on the toxicity of the metal nanomaterial, thereby improving the accuracy of the model toxicity prediction.

This invention discloses a time-series causal analysis method, computer device, and storage medium for environmental change and infectious disease incidence risk. The invention can process environmental data time series and infectious disease incidence time series using convergent cross-mapping algorithms, Peter-Clark instantaneous conditional independence tests, and causal forest algorithms, respectively. The obtained first, second, and third causal relationship information represent the causal relationship between the environmental data time series and the infectious disease incidence time series from different perspectives. This allows multiple causal relationship algorithms to complement each other and strengthen the causal relationships identified by each algorithm. It can more effectively explain the causal patterns of environmental change represented by environmental data time series and infectious disease incidence time series represented by infectious disease incidence time series, aiming to provide a more reliable answer to the driving effect of environmental factors on infectious diseases. This invention has wide applications in the field of environmental health technology.

The invention relates to the technical field of paliperidone metabolic efficiency evaluation, in particular to a paliperidone metabolic efficiency evaluation system based on a CYP2D6 gene and environmental factors. According to the system, the obtained historical data information is preprocessed, so that more effective data information can be obtained, and a model can be trained more effectively by using the data information; meanwhile, a dynamic metabolism prediction module formed by weighting output of each network in a multi-modal feature fusion module by utilizing a gating attention mechanism is trained based on the preprocessed data, so that a gene-environment-PK / PD multi-dimensional model is obtained, various factors of the environment and the gene can be quantified, and multi-modal data are fused; the dynamic evaluation of the metabolic efficiency is further realized; according to the method, the current data information is scored by using the gene-environment-PK / PD multi-dimensional model, and the score is compared with the preset score, so that whether the model evaluation is qualified or not can be quickly judged, and the model evaluation is adjusted when the model evaluation is unqualified, thereby further improving the evaluation accuracy.

This invention discloses a method for evaluating the interfacial reinforcement effect of a road interfacial reinforcing agent, comprising the following steps: S1, specimen preparation: asphalt, aggregate, and the interfacial reinforcing agent to be evaluated are compounded to prepare a standard specimen; S2, environmental and load simulation: the standard specimen is treated to simulate actual road environmental conditions to simulate cumulative damage; S3, mechanical property testing: mechanical tests are performed on the standard specimen after simulation treatment to obtain its interfacial mechanical property parameters; S4, comprehensive evaluation: based on the interfacial mechanical property parameters, an interfacial performance index is calculated to evaluate the reinforcing effect of the interfacial reinforcing agent. This invention simulates the complex environment during actual road use and conducts various environmental factor tests on the interfacial layer after treatment with the interfacial reinforcing agent to more realistically and accurately reflect the reinforcing effect of the interfacial reinforcing agent.

The invention discloses an intelligent decision-making method for environmental governance based on collaborative metric learning and reinforcement learning, belongs to the technical field of air pollution prevention and artificial intelligence crossing, and particularly relates to an intelligent decision-making method for environmental governance. The objective of the invention is to solve the problems that the existing traditional environment treatment technology is difficult to meet increasingly complicated pollution treatment requirements due to the disadvantages of static rule stiffness, high cross-domain cost and multi-target imbalance. The method comprises the following steps: obtaining preprocessed pollution source, environment state and treatment measure data; obtaining a pre-trained fusion collaborative measurement learning model; outputting an embedded vector of the environmental factor; outputting an embedded vector of the pollution source; obtaining the state representation of the embedding space; obtaining a pre-trained cross-regional migration model and an initial parameter corresponding to the model; obtaining a pre-trained reinforcement learning dynamic decision model; and obtaining to-be-detected pollution source data and environment data of the new region, and generating a treatment action of the new region.

The present invention relates to a spinal needle that clearly identifies the presence of cerebrospinal fluid (CFS) to dispense a drug or anaesthetic in the correct direction and site of the meninges. The response of the sensor to the presence of CFS does not depend on environmental factors and is performed quickly to prevent excessive loss of CFS in the patient. The spinal needle comprises a hub having a proximal end and a distal end, said hub comprising a transparent tank arranged at the proximal end of the hub that is configured to receive CFS, an expandable CFS sensor arranged inside the transparent tank and a connection port arranged at the distal end of the hub configured to couple to a device for medical fluids, and a cannula comprising a tip fluidically connected to the proximal end of the hub.

The invention discloses a chronic obstructive pulmonary disease acute exacerbation risk early warning method and system based on home monitoring data and environmental factors, and belongs to the technical field of medical health monitoring and risk early warning. The method comprises the following steps: acquiring multi-dimensional data (symptom score, FEV1 trend, night blood oxygen saturation, medication compliance and weather data) of a user; pre-processing the multi-dimensional data and inputting the pre-processed multi-dimensional data into the trained machine learning prediction model; the model outputs an acute exacerbation risk probability value in the future 7 days; when the risk probability exceeds a preset threshold value, graded early warning information and personalized intervention suggestions are sent. The system comprises a data acquisition module, a data preprocessing module, a model prediction module, an early warning pushing module and a terminal interaction module. Multi-source data are integrated, through targeted feature extraction and model training, early-stage accurate early warning of chronic obstructive pulmonary acute exacerbation is achieved, meanwhile, personalized intervention suggestions are provided, early warning-intervention-feedback closed-loop management is supported, operation is convenient, cost is controllable, the acute exacerbation occurrence rate and the hospitalization rate of patients can be effectively reduced, and the patient experience is improved. The method is suitable for popularization and application in family and basic medical scenes.

This invention discloses a composition that can effectively soothe and repair sensitive skin, its preparation method, and its application, relating to the field of skincare products. The composition of this invention, by weight, comprises 5-18 parts β-glucan, 1-10 parts mannan, 8-15 parts yeast polypeptides, 1-10 parts sodium hyaluronate, 2-5 parts magnesium ascorbate phosphate, and 8-15 parts Scutellaria baicalensis root extract. This composition is mild and non-irritating, can quickly and effectively relieve skin sensitivity reactions, protect the skin barrier, and has good storage stability, not easily affected by environmental factors such as temperature and oxygen.

This invention relates to the fields of smart aquaculture and big data analysis technology, and discloses a smart aquaculture monitoring method and system based on big data analysis. The method includes periodically acquiring raw data from the farm's sensor network, and constructing a multi-dimensional state image through spatiotemporal synchronization and normalization processing. This image is input into a pre-trained behavior-environment decoupling analysis network, and independent behavioral feature tensors and independent environmental background field tensors are extracted in parallel. Based on these two, a coupling degree index is calculated through a cross-influence evaluation matrix to generate a comprehensive anomaly score map. According to this map, a strategy generation engine dynamically synthesizes a set of control instructions including directional airflow guidance, refined feeding, and coordinated temperature and humidity regulation. This method achieves deep separation and correlation analysis between animal behavior and aquaculture environmental factors, accurately tracing the root cause of anomalies and realizing early warning and precise systemic control.