58789 results about "Environmental chemistry" patented technology

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

The embodiment of the invention provides an environment monitoring method and system based on 5G. According to the method, a dynamic coupling sensing field is constructed in a 5G network coverage domain, an adaptive topology with nonlinear interaction of parameters is established, and when parameter abnormity is detected, differential geometric reconstruction of a 5G network slice control surface is triggered based on Riemannian curvature change. And constructing a space-time manifold space at the 5G edge computing node, decomposing and extracting a diffusion principal curvature direction, and iteratively solving a propagation rate of an abnormal parameter in combination with a geodesic equation to generate a diffusion leading edge envelope surface. And according to the main curvature distribution characteristics of the diffusion leading edge envelope surface, constructing a dynamic sampling optimizer, generating an exponential decay sampling function, and deploying a directional sensing wavefront. And carrying out conformal tightening processing on the sampling function and the geographic grid to generate an interactive holographic manifold, establishing an aging judgment criterion of an abnormal level based on curvature 2-form characteristics, and triggering a graded early warning pulse wave packet. According to the technical scheme provided by the embodiment of the invention, the real-time performance and precision of environment monitoring are improved.

The invention provides a marine pollution tracing and monitoring method based on satellite remote sensing and an unmanned aerial vehicle, and relates to the technical field of marine pollution tracing and monitoring, and the method comprises the steps: configuring a pollution diffusion path prediction model and a data driving model based on range pollution data, precise pollution data and deepwater data after multi-modal data fusion, and obtaining a pollution prediction result and pollution error data, carrying out hybrid drive fusion based on the pollution prediction result and the pollution error data, and tracking an initial source of pollutants to obtain pollution source tracing data. Through preprocessing and fusion of multi-modal data, in combination with range pollution data, precise pollution data and deep water data, a pollution diffusion path prediction model and a data driving model are dynamically adjusted, so that a more precise pollution prediction result and pollution error data are generated, and meanwhile, through reverse diffusion simulation and pollution traceability analysis, a more precise pollution prediction result is obtained. The high efficiency of pollution source positioning and decision support is improved, and an accurate and decision basis is provided for coping with marine pollution events.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

The invention discloses a land degradation supervision method based on remote sensing monitoring, and relates to the technical field of land degradation monitoring. The method is used for solving the problems of hidden degradation risk identification and dynamic propagation simulation. According to a multi-temporal thermal infrared remote sensing image, daily variation characteristics of surface temperature are extracted through spectral analysis, a recessive salinization risk distribution map is constructed by combining measured data of soil salinity, and interference of vegetation coverage is overcome. And multi-source remote sensing and geographic data are fused, dominant driving factors significantly associated with the salting risk are screened, and the degeneration cause is clarified. And in combination with ecological restoration potential and treatment resource constraints, calculating an antagonism index of a driving factor and the restoration potential, and dividing degradation threat levels. And a natural hydrology and human activity dual-path propagation model is constructed, a risk space-time evolution process is simulated, and a future hotspot migration path and an optimal blocking window are predicted. According to the method, accurate early warning and active prevention and control of land degradation are realized through a technical chain of risk identification, driving analysis, threat grading and dynamic simulation.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

A method for inversing a depth of a subsurface chlorophyll-a maxima (SCM) of an oceanic water body based on remote sensing reflectance is provided. The method includes: band selection, R value calculation, data collection, model construction, and ZSCM calculation. This method can not only reduce the dependence of machine learning on sea surface chlorophyll-a concentrations, sea surface temperature data and sea surface height data, and reduce the calculation resource consumption of running machine learning, but also effectively improve the inversion accuracy, and effectively reduce the calculation resource consumption and inversion difficulty of inversing the SCM.

The invention discloses a multi-parameter in-situ detection data analysis system for a marine ranch, and relates to the technical field of data analysis, the multi-parameter in-situ detection data analysis system comprises a multi-parameter sensor group and a self-adaptive multi-dimensional trigger type sampling control module, the multi-parameter sensor group comprises an environmental parameter sensor and a biological behavior sensor, the environmental parameter sensor is used for measuring real-time environmental parameters of the marine ranch, the biological behavior sensor is used for monitoring biological behavior parameters of the marine ranch in real time, and the self-adaptive multi-dimensional trigger type sampling control module comprises a data preprocessing unit and a dynamic sampling strategy unit. The self-adaptive multi-dimensional trigger type sampling control module is designed, so that sampling modes are dynamically switched according to real-time dual-mode data, environment sudden changes are effectively captured, data redundancy or key change sampling leakage caused by traditional fixed sampling frequency is avoided, monitoring precision is improved, energy optimization is achieved, the service life of equipment is prolonged, and the system is suitable for large-scale popularization and application. And high quality and real-time performance of data are ensured.

The invention relates to the technical field of water treatment intelligent control, in particular to an AI-based intelligent urban water purification and sewage treatment process optimization system and method, and the method comprises the steps: obtaining related sensor data information, and monitoring and recording the change of key data in real time; establishing a water quality change prediction model by using a multiple linear regression model, wherein the water quality change prediction model predicts the water quality change according to the key data change acquired in real time; the dynamic agent AI model adjusts the dosage, and the water treatment chemical / biological reaction kinetics AI model predicts the pollutant degradation condition; a local lightweight AI model optimizer and a multi-target genetic algorithm are combined with energy consumption, medicament cost, processing efficiency and carbon emission to obtain an optimal control model; the optimal control model optimizes the operation parameters of the sewage treatment process according to the pollutant degradation condition. According to the method, the operation parameters of the sewage treatment process are optimized through the optimal control model, the energy consumption, the agent cost and the carbon emission are reduced, and the treatment efficiency is improved.

The invention relates to a facility for producing liquid CO2 and biomethane, comprising: —a unit for producing biogas; —at least one unit for the membrane separation of biogas to produce biomethane and a gaseous mixture M1 mainly comprising carbon dioxide; —a unit for cryogenically distilling the gaseous mixture M1 to produce liquid CO2 and a gaseous mixture M2 comprising carbon dioxide, methane, oxygen and hydrogen; —one or more membranes located in the flow of the gaseous mixture M2 to separate the methane from the oxygen-hydrogen mixture

The invention relates to the technical field of remote sensing image recognition, in particular to a remote sensing sewage area recognition method and system based on a graph structure and multi-stage enhancement. The method comprises the steps of performing data preprocessing and representation enhancement on an acquired remote sensing image; performing sewage salient region preliminary screening on the enhanced remote sensing image, including abnormal enhancement mapping construction based on local statistical distribution; pollution candidate graph extraction based on spatial structure prior driving; enhancing the response of the stable region based on a structure consistency enhancing mechanism of the polluted region; high-precision segmentation and identification of the sewage area comprises the following steps: constructing a multi-resolution residual pyramid structure; carrying out fine-grained boundary structure modeling and uncertainty suppression; generating a sewage distribution probability graph and optimizing structural consistency; according to the method, the multi-resolution residual pyramid structure is constructed, image context information under different perception scales is fully mined, and the sensitivity and edge integrity of the model to a sewage area under a complex texture background are remarkably enhanced.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

A system and method for maintaining an oxygen concentration of a biological sample. The oxygen concentration can be maintained by measuring the oxygen concentration within the biological sample and adjusting a rate of an oxygen supplier in response to this measurement. For example, when the oxygen concentration is below a threshold, oxygen can be delivered to the biological sample at a higher rate.

The invention discloses a water body new pollutant risk assessment method and system. Belongs to the technical field of environmental science. Comprising the steps of collecting multi-source heterogeneous data to generate an initial data set; performing data fusion in the initial data set by using a weighted Bayesian fusion algorithm and a space-time interpolation method to generate a target data set; importing the target data set into a deep learning model for prediction and obtaining a prediction result; and obtaining a preset early warning condition and combining with the prediction result to judge whether risk early warning needs to be carried out. Through constructing a pollutant data acquisition system and data fusion, the monitoring precision of the new pollutants in the water body is improved. The fusion algorithm is used for data preprocessing, and pollutant detection is comprehensive. And the space-time diffusion process of the pollutants can be accurately modeled.

The invention discloses a landslide prediction and early warning system and method based on a remote sensing technology, and is applied to the technical field of landslide early warning. Comprising a data acquisition module for acquiring multi-source data in a monitoring area; the cloud computing module is used for large-range landslide risk assessment and deformation monitoring; the edge calculation module is used for landslide risk assessment and deformation monitoring of a specific area; the end-cloud cooperative communication module is used for realizing data interaction between the cloud computing module and the edge computing module; the federal learning module is used for realizing cooperative training under data privacy protection of different areas; and the landslide early warning module is used for carrying out early warning based on landslide risk assessment and deformation monitoring results of the cloud computing module and the edge computing module. According to the invention, by using the deep learning model, the end-cloud collaborative architecture and the federal learning driven data fusion framework, efficient, low-cost and high-precision landslide risk prediction is realized.

Carbon Capture, Utilization, and Storage (CCUS) is a relatively new technology directed to mitigating climate change by reducing greenhouse gas emissions. Current and new government requirements require proof that carbon dioxide (CO2) is either sequestered in a stable form or safely stored for long periods of time. In instances when the CO2 is sequestered through mineral formation, the need for long-term monitoring can be reduced, as the stability of the sequestered CO2 is inherent based on a chemical change in subterranean rocks. The reactions between CO2 and rock formations are influenced by numerous factors, including temperature, pressure, fluid composition, and the mineralogy of the formation. Furthermore, these reactions occur over large spatial areas and long timescales, making them difficult to monitor directly. Methods and systems of the present disclosure, therefore, may use a combination of laboratory experiments, field monitoring, and modeling to provide convincing evidence of CO2 mineral sequestration.

A system and method for maintaining an oxygen concentration of a biological sample. The oxygen concentration can be maintained by measuring the oxygen concentration within the biological sample and adjusting a rate of an oxygen supplier in response to this measurement. For example, when the oxygen concentration is below a threshold, oxygen can be delivered to the biological sample at a higher rate.

The invention relates to the technical field of soil pollution identification, and discloses a soil heavy metal pollution identification system. A multispectral remote sensing sensing module of the system obtains surface reflectance data and soil in-situ spectral data through a satellite load and a vehicle-mounted mobile platform respectively, and the surface reflectance data and the soil in-situ spectral data are processed by a heterogeneous data fusion gateway to generate multiband spectral response signals. In the pollution risk assessment module, a spatial distribution analysis unit outputs a heavy metal spatial distribution map, a migration risk prediction unit generates a pollution migration probability cloud map in combination with meteorological and hydrological data, and a pollution threshold defining unit outputs a soil remediation safety threshold. In the treatment decision execution module, an in-situ remediation execution unit adjusts passivator injection parameters, a pollution source management and control unit regulates pollution source blocking equipment and collects monitoring signals, and a three-dimensional dynamic early warning platform generates a comprehensive pollution risk index. According to the system, the cooperative operation of soil heavy metal pollution identification, evaluation and treatment is realized.

The invention provides a nano enzyme as well as a preparation method and application thereof. The preparation method of the nano enzyme comprises the following steps: adding a stabilizer into a preheated solvent, and carrying out ultrasonic treatment; then adding ferric salt and cobalt salt, and adding alkali to adjust the pH value of the solution; then transferring the solution into a reaction kettle for reaction; and after the reaction, washing and separating to obtain the product. The obtained nano-enzyme is appropriate and uniform in particle size and good in dispersity, the enzyme activity is as high as 9.56 U / mg, and the application of the nano-enzyme in immunochromatography detection and plant canker prevention and treatment is widened. When the immunochromatography detection card prepared from the nano enzyme is used for detecting human hemoglobin, the detection limit can reach 0.05 ng / mL and is at least 10 times lower than that of a commercially available kit. When the nano-enzyme suspension is used for preventing and treating the kiwifruit canker, the nano-enzyme suspension with the concentration larger than or equal to 0.1 mg / mL is used, and the plant canker can be well controlled.

The invention relates to a waste lithium iron phosphate battery recycling method, in particular to a graded recycling method for lithium, iron, phosphorus and graphite in a waste lithium iron phosphate battery, and belongs to the technical field of lithium ion batteries and resource recycling of the lithium ion batteries. According to the method, the mode that oxidizing roasting and selective leaching are combined is adopted, the leaching rate and selectivity of lithium are effectively improved, the leaching rate of the lithium element is close to 100% under the optimized condition, and limit recovery of the lithium element is achieved; meanwhile, aiming at the problem that iron and phosphorus in the leaching residues are difficult to utilize, a wet ball milling and secondary acid leaching method is combined, phosphorus and iron elements are separated from negative electrode graphite firstly, and graded recovery of iron, phosphorus and graphite is achieved. According to the method, the high recovery rate of lithium is realized, and meanwhile, high-added-value products such as ferric oxide and sodium phosphate are prepared by efficiently recovering ferric phosphate.

The present disclosure provides water-soluble film packages composed of a water-soluble film, where the packages include: one or more compartment(s) including dehydrated microbes. The disclosure further provides methods of production of the water-soluble film packages, and methods of application thereof. The water-soluble packages of the disclosure enable convenient and accurate application of microbial dry powders to plants, promote uniform dispersion of powdered microbes, enhance microbial shelf life, and enhance the survival of microbes on seed, while being environmentally sustainable.

The invention relates to the field of landfill methane emission remote sensing monitoring, and discloses a landfill methane emission flux measuring and calculating method and device and a medium, and the method comprises the following steps: based on regional satellite TROPOMI observation data, carrying out qualitative analysis on annual average methane emission signals of a landfill, and determining a target landfill according to a qualitative analysis result; based on data of a satellite-borne hyperspectral imager, the methane emission flux of the target landfill is quantitatively measured and calculated, and the position of a methane emission hot spot area in the target landfill is determined; and positioning the position of an emission source in the target landfill through an active methane laser detection lens carried by an unmanned aerial vehicle platform, and independently calculating the methane emission flux of the target landfill by adopting an upper and lower section method. Based on the method, the annual average methane emission condition of the landfill can be rapidly and accurately evaluated, the methane emission flux of the whole landfill is obtained, and the internal emission hot spot area of the landfill is positioned.

The invention provides a refuse landfill methane emission monitoring method and system for air-ground combined monitoring, ground sampling points are selected by combining topographic features, possible emission hot spot areas and historical operation information of a refuse landfill, and areas which are difficult to reach by ground sampling can be realized through aerial survey air sampling; by integrating ground sampling and aerial survey, high-resolution methane concentration data can be obtained, and meanwhile interference of flowing wind on hot spot area recognition is reduced; by combining ground surface sampling data and aerial survey data, a Getis-Ord Gi * statistical method and a nuclear density estimation method are adopted to carry out bimodal hot spot area identification, a methane emission source area can be positioned more accurately, the precision and efficiency of methane emission monitoring of the refuse landfill are remarkably improved, and the method is suitable for popularization and application. The methane emission source of the refuse landfill is accurately and efficiently found, the emission amount of the methane emission source is evaluated, targeted suggestions are provided for operation of the landfill, and the method has important environmental protection and economic values.

The invention relates to the technical field of biological sewage treatment, in particular to a device and a method for improving the autotrophic nitrogen removal performance of an MABR (Membrane Ammonia Baffled Reactor). Coupling of partial nitrosation reaction and anaerobic ammonia oxidation reaction is completed; through a circular reaction zone and a membrane reaction zone in the reaction tank, nitrate nitrogen generated by anaerobic ammonia oxidation and excessive nitrite nitrogen during instability regulation are circularly removed, and the purpose of improving the total nitrogen removal effect of the reactor is achieved; a proper amount of a sodium nitrite solution is added at proper time, the concentration of free nitrous acid in a mixed solution of the reactor is increased, and the intermittent proportion of MABR intermittent aeration is synchronously regulated and controlled, so that the activity of nitrite oxidizing bacteria is synergistically inhibited by low dissolved oxygen and high free nitrous acid, and the unstable short-cut nitrification reaction is recovered again; the autotrophic nitrogen removal performance of the reactor is improved.

The invention relates to the technical field of environment monitoring, solves the problem that a monitoring system and method cannot meet the requirements for accuracy and real-time performance of animal behavior research and climate environment research in a plateau area at the same time, and particularly discloses a monitoring system and method integrating environment monitoring and animal monitoring recognition. Comprising a sensing system, a data transmission system and a data processing system, the sensing system is used for collecting environment and animal data of a monitoring site, and the data processing system is used for receiving and processing the data and analyzing the change trend and the correlation influence degree of the environment data and the animal data; the monitoring method comprises the following steps: acquiring environment and animal data through the environment monitoring network and the animal behavior sensing network; data is transmitted to the data processing system in real time through the data transmission system; the data processing system analyzes the dynamic change trend of the environment data and the animal data; and generating early warning information and triggering a protection measure execution instruction. The method can be used for monitoring the plateau environment and animals, and is high in accuracy and high in real-time performance.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

The invention relates to the technical field of water environment risk monitoring, in particular to a method for evaluating the algal bloom risk of a water body. The method comprises the following steps: collecting historical monitoring data of a to-be-evaluated water body, wherein the historical monitoring data comprises blue-green algae abundance data, water quality data and hydrological data; analyzing the correlation between the cyanobacteria abundance or chlorophyll a concentration and the water quality and hydrological data of the to-be-evaluated water body; hydrological and water quality parameters with the highest correlation with the cyanobacteria abundance or chlorophyll a concentration are screened out; hydrology and water quality parameters of a water body to be evaluated are taken as predictive variables, and cyanobacteria abundance or chlorophyll a concentration is taken as a response variable to construct a Bayesian network model; the weight of each parameter in the Bayesian network model is calculated, and the algal bloom risk probability that the cyanobacteria abundance exceeds a specific threshold value under the given parameter condition is calculated according to the weights. According to the invention, the scene-based probability deduction of the stable period and the dynamic period is realized through the double-branch Bayesian network model, so that the accuracy and timeliness of algal bloom risk assessment are improved.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

The invention discloses a cleaning control method and system based on an electronic cleaning agent, and the method comprises the steps: obtaining the distribution characteristics of pollutants and a material sensitivity judgment result through obtaining the micron-sized particle distribution data, chemical residue concentration data and surface roughness parameters of the pollutants on the surface of an electronic workpiece; according to the pollutant distribution characteristics and the material sensitivity judgment result, matching a candidate formula from a preset cleaning agent formula database, calculating pollutant removal rate predicted values of different concentration and time combinations through a linear regression algorithm, and determining optimized cleaning agent formula parameters and cleaning strength control parameters; and in the cleaning process, the residual quantity of pollutants and the surface damage degree are collected in real time, if the residual quantity of the pollutants exceeds a preset threshold value T1 or the surface damage degree exceeds a preset threshold value T2, cleaning agent injection pressure and cleaning time parameters are dynamically adjusted, and updated cleaning execution parameters are generated. Accurate and efficient cleaning of the surface of the electronic workpiece is achieved.