2509results about How to "Improve extraction efficiency" patented technology

The invention discloses a terrain-level real-scene three-dimensional entity and element dynamic updating method, which comprises the following steps: S1, data acquisition and preprocessing: acquiring data of a target area by an acquisition mechanism based on entity and element type priorities, and preprocessing the acquired data to obtain model data of the target area; s2, change detection: comparing newly collected model data with historical model data, and identifying a change region and type; s3, entities and elements are extracted and updated, wherein the entities and the elements of the change area are processed to obtain updated models; s4, model fusion and optimization: fusing the updated entity and element model with the original model, and realizing efficient acquisition and preprocessing of target area data by using the multi-source surveying and mapping equipment and an acquisition mechanism based on entity and element type priorities; by dividing the small regions according to the region characteristics and correcting the acquisition frequency, the resource allocation is optimized, and the pertinence and efficiency of data acquisition are improved.

The invention discloses a tunnel wall surface deformation monitoring method and system based on computer image recognition. The method comprises the following steps: acquiring a tunnel area image and a tunnel wall surface image of each image acquisition point; tunnel wall surface deformation identification and wall surface deformation prediction are carried out on the tunnel area image and each tunnel wall surface image, and deformation image identification data and a wall surface deformation prediction result are correspondingly obtained; obtaining deformation image identification data and spatial position data corresponding to a wall surface deformation prediction result, and generating a plurality of deformation monitoring units in a deformation monitoring area of the tunnel; taking each deformation monitoring unit as a basic unit, acquiring sensor monitoring data and a corresponding monitoring threshold interval, and comparing the sensor monitoring data and the corresponding monitoring threshold interval to obtain a sensor monitoring judgment result; based on all sensor monitoring judgment results, the corresponding deformation image recognition data and the wall surface deformation prediction result, space matching analysis is carried out, and a tunnel wall surface deformation monitoring result is correspondingly obtained; according to the invention, the monitoring effect of tunnel wall surface deformation monitoring is improved.

The invention discloses a lightweight eye fundus blood vessel image segmentation model based on Mama. The model comprises the following steps: an encoder and a decoder comprise at least four layers of SlimPVM Blocks; gradually downsampling the input feature map through maximum pooling operation; the CCA Bottleneck module is used for calculating the self-attention of the cross-channel in the height dimension and the width dimension of the feature map; the encoder and the decoder carry out feature fusion through selective jump connection, and the selective jump connection carries out weighted selection on features through a channel attention mechanism; the decoder uses SlimPVM Block to refine the features after up-sampling, the model recovers lost spatial dimensions through convolution transpose operation, and coding features from selective jump connection are combined; and the decoder finally outputs a final segmentation mask generated through a 1 * 1 convolution layer, and the segmentation mask can accurately describe the boundary of the target area in the medical image. The method is specially used for retinal vessel segmentation tasks, model parameters are reduced, calculation overhead is reduced, and meanwhile segmentation performance is kept and even improved.

The invention discloses a thin mutual coal seam fracturing, gasification and carbon sequestration integrated method. The method comprises the steps of geological exploration and coal seam refined evaluation; a middle horizontal well is drilled downwards from the ground; top and bottom horizontal wells are planned and drilled in the uppermost and lower sandstone stratums of the thin mutual coal seam; a plurality of top and bottom fishbone wells are drilled obliquely downwards and upwards in the top and bottom horizontal wells; oxygen-enriched water vapor is injected into the middle horizontal well through a continuous oil pipe, the oxygen-enriched water vapor is squeezed into the reservoir under the action of high pressure, and fracturing operation is conducted; initiating an underground gasification process of the coal seam, and synchronously performing extraction operation of the coal seam gas; supercritical CO2 fracturing operation is conducted on the top horizontal well and the bottom horizontal well; injecting water-based fracturing fluid into the top horizontal well and the bottom horizontal well; gasified materials generated by coal seam combustion gasification and desorbed methane gas are extracted through the middle horizontal well, and supercritical carbon dioxide injected before is sealed for a long time. According to the method, the limitation of a traditional hydraulic fracturing technology can be solved, and the transformation effect of the reservoir can be improved.

The invention relates to the technical field of plant extraction, in particular to an intelligent plant extraction control method and system, and the method comprises the following steps: based on historic plant extraction data, including temperature, pressure and pH value during extraction, analyzing the long-term trend of parameters, predicting the requirements of plant extraction conditions by simulating parameter reactions under various conditions, and obtaining a plant extraction result; and obtaining a parameter prediction result. According to the method, long-term trend prediction of parameters such as temperature, pressure and pH value is realized through analysis of historically recorded plant extraction data, so that the parameters of extraction equipment are adjusted in advance, changes of different plant materials and environmental conditions are effectively adapted, the extraction efficiency is optimized, and by dynamically simulating the expression of the extraction efficiency in various time periods, the extraction efficiency is improved. According to the innovative scheme, an optimal extraction time window is mined, resource consumption and extraction time in the extraction process are reduced, and meanwhile the quality and consistency of extracts are kept.

The invention relates to the technical field of intelligent scene recognition, and discloses an intelligent scene recognition method and equipment for an intelligent interaction control unit, and the method comprises the steps: carrying out the collection and preprocessing of an operation sequence, video content and audio data of the intelligent interaction control unit in a digital set-top box, and obtaining a standard multi-mode data set; inputting the standard multi-modal data set into a multi-branch deep neural network model, and extracting time sequence, visual and audio features through parallel processing to obtain a fusion scene feature vector; carrying out dimensionality reduction and semantic mapping on the fused scene feature vector to obtain a compressed semantic feature vector; performing similarity calculation on the compressed semantic feature vector and a predefined scene query vector to obtain a scene matching score; and based on the scene matching score, integrating the output of the plurality of sub-classifiers to obtain a target scene classification result, and the method can be efficiently operated on the digital set top box with limited resources to realize real-time scene recognition.

The invention belongs to but not limited to the technical field of text extraction, and particularly relates to an automatic construction method and system for a process industry text knowledge extraction dataset. Firstly, based on a word segmentation tool and a TF-IDF algorithm, an unlabeled text in the process industry field is converted into a large language model fine tuning dataset, and a large language model is subjected to fine tuning; the system has specific knowledge of the field; then, generating an initial knowledge extraction sample set with confidence through multi-stage exploration-utilization ratio adjustment based on the fine-tuned large language model; and finally, through a confidence-based large-scale sample set error detection and correction method, obtaining a sample data set which is finally used for domain knowledge extraction model training. Through the low-cost and high-efficiency industrial text knowledge extraction sample set construction and application method, the input-output ratio of resources is increased to the maximum extent, and the construction and application efficiency of an industrial safety knowledge extraction algorithm is improved.

The invention discloses a power system protocol analysis method and system based on association rule analysis and sequence alignment, particularly relates to the field of private protocol analysis, is used for solving the problems of dynamic field feature extraction and boundary recognition, and aims at extracting features of dynamic fields through separation of static fields and the dynamic fields. Then, hidden frequent items and associated features are mined by using an association rule algorithm, so that dynamic fields are displayed in a structured manner in a feature matrix, which becomes the basis of subsequent clustering and inference. The feature matrix is clustered through a DBSCAN algorithm, protocol formats are classified, noise and abnormal data are processed, and a preliminary format is provided for field boundary recognition. According to the method, the Nedleman-Wunsch sequence comparison and information entropy verification technology is combined, the boundary position is accurately identified, the fuzzy field is dynamically adjusted by using the field boundary ambiguity index and the sequence alignment error correction index, and finally, the boundary division precision is enhanced through mutual information correction, so that the accuracy and processing efficiency of protocol analysis are improved, and the method is suitable for popularization and application. And automatic analysis of a complex protocol is realized.

The invention discloses an active learning-based electric power knowledge graph construction method and system, and relates to the technical field of electric power market transaction data analysis, and the method comprises the steps: collecting data, cleaning the collected data, generating word prediction task data of an electric power transaction scene, and training an electric power field word embedding model; generating an entity relationship training sample, inputting a word embedding model, performing entity relationship label prediction through an entity relationship joint extraction model, extracting a high-quality sample based on active learning to perform part-of-speech tagging, and training the model based on a tagged sample; and applying the trained entity relationship joint extraction model to power transaction data to construct a knowledge graph, performing manual correction and entity unification, and storing the knowledge graph into a Neo4j database. According to the method, active learning and deep learning are combined, so that the sample labeling cost is effectively reduced, and meanwhile, the model performance is ensured.

The invention discloses a bridge cable force real-time tracking method based on peak value automatic extraction, and aims to solve the problem that the manual extraction of real-time and batch power spectral density map peak values is tedious and difficult, and the method comprises the steps: firstly converting an acceleration signal collected by a sensor into frequency domain information through fast Fourier transform; then performing data preprocessing on the power spectral density map to ensure the peak value extraction accuracy; peak values in the power spectral density map are preliminarily extracted based on a data maximum value searching method, then the minimum saliency, the minimum height and the minimum spacing of the peak values are limited to eliminate false peaks, and resonance peaks in the power spectral density map and corresponding frequencies and frequency intervals of the resonance peaks are recognized; on the basis of a modal analysis method and a vibration string theory, cable force tracking is finally realized and is used for guiding subsequent bridge structure evaluation work.

The invention belongs to the technical field of biology, and particularly relates to an extraction method of polydeoxyribonucleotide, which comprises the following steps: carrying out homogenate treatment on pretreated in-vitro testis tissue, filtering the obtained homogenate, adding a pancreas extract into the filtrate, and stirring to obtain enzymatic hydrolysate; and precipitating protein in the enzymatic hydrolysate, removing the protein, adding sodium acetate for treatment, adding absolute ethyl alcohol for precipitation, centrifuging, washing the obtained precipitate, and drying to obtain the product. Common trypsin and lipase in fish pancreas are beneficial to release of DNA, the fish pancreas extract is applied to extraction of the polydeoxyribonucleotide, the extraction time can be remarkably shortened, the yield can be increased, meanwhile, nuclease in the fish pancreas extract can effectively degrade DNA, and small-fragment polydeoxyribonucleotide is obtained.

The invention discloses an ultrasonic excitation and acid fracturing integrated permeability-increasing coal seam enhanced extraction system which comprises an ultrasonic excitation and acid fracturing integrated drilling and feeding device, an ultrasonic control box and a liquid mixing box, and further discloses an ultrasonic excitation and acid fracturing integrated permeability-increasing coal seam enhanced extraction method. Comprising the following steps: S1, collecting a sample in a coal seam; s2, four extraction drill holes with unequal distances are constructed in the coal seam; s3, gas concentration detection is conducted on the extraction drill hole; s4, an ultrasonic transducer is started, and a fracturing pump is started for fracturing; the ultrasonic transducer is started again; s5, after the step S4 is repeated five times, the fracturing pump is closed, and then the ultrasonic transducer is started; and S6, gas concentration detection is conducted on all the extraction drill holes. The method has the advantages that ultrasonic excitation and the acid fracturing effect are mutually coupled, the pore structure of the coal body is improved, the connectivity of pore fractures is improved, gas desorption is promoted, and the coal seam gas extraction efficiency is improved.

The invention relates to the technical field of intelligent control, in particular to a traditional Chinese medicinal material extraction intelligent control system which comprises a heat energy distribution control module, a pressure environment optimization module, a solvent dynamic adjustment module, an extraction abnormity intervention module and a component extraction quality improvement module. According to the invention, by dynamically adjusting heat energy output, pressure distribution and solvent flow velocity, accurate control of key parameters in the extraction process of traditional Chinese medicinal materials is realized, uniform distribution of heat energy is ensured, extraction efficiency and quality are optimized, the system is adjusted according to the change of pressure gradient, the adaptive capacity to the fluctuation of extraction conditions is enhanced, and the extraction efficiency is improved. The flexibility and overall stability of the system are improved, the use efficiency of the solvent is improved through fine solvent adsorption and diffusion regulation and control, the solvent is promoted to uniformly act on the traditional Chinese medicinal materials, the extraction rate and uniformity of effective components are improved, the solvent distribution and concentration are rapidly adjusted when temperature fluctuation or pressure deviation occurs, and the abnormal response capability is enhanced. And the continuity of the extraction process and the product consistency are ensured.

The invention discloses a light-emitting diode epitaxial wafer and a preparation method thereof, and relates to the field of semiconductor photoelectric devices. The light-emitting diode epitaxial wafer sequentially comprises a substrate, a buffer layer, an N-type GaN layer, a multi-quantum well layer, an electron blocking layer and a P-type GaN layer. The buffer layer sequentially comprises a first AlN layer, a second AlN layer, a third AlN layer, a first superlattice layer, a first AlGaN layer, a second superlattice layer and a first GaN layer; the first superlattice layer comprises a fourth AlN layer and a second AlGaN layer which are alternately stacked, and the second superlattice layer comprises a third AlGaN layer and a second GaN layer which are alternately stacked; a first V-shaped pit extending to the second superlattice layer is formed in the third AlN layer, a second V-shaped pit is formed in the first superlattice layer, and the second V-shaped pit is filled and leveled up by the first AlGaN layer; the second superlattice layer forms a third V-shaped pit, and the first V-shaped pit and the third V-shaped pit are filled and leveled up by the first GaN layer. By implementing the invention, the luminous efficiency can be improved.

The invention discloses a green processing technology of sea cucumber powder capable of realizing directional enrichment and improving polysaccharide release rate, and belongs to the field of food processing. The sea cucumber powder is prepared by the following steps: S1, pretreating sea cucumbers; s2, enrichment of nutrient substances of the sea cucumbers; s3, regulating and controlling the particle size of the sea cucumber powder; s4, performing'single 'supercritical treatment; s5, carrying out in-situ ultramicro physical crushing; and S6, performing'dual 'supercritical treatment. Through the design of the gas disperser and the additional arrangement of the second hole disc, the supercritical extraction instrument can perform effective supercritical carbon dioxide extraction on the ultramicro sea cucumber powder, the deodorization of the ultramicro sea cucumber powder is realized, and the eating quality of the ultramicro sea cucumber powder is improved. Moreover, by detecting and regulating the stacking density and the tap density, optimal processing parameters for the ultramicro sea cucumber powder are found, so that the prepared ultramicro sea cucumber powder is high in polysaccharide release rate, good in eating quality and easy for subsequent processing.

The invention provides a preparation method of a general flavone extract in abelmoschus manihot flowers, which comprises the following steps: A) crushing the abelmoschus manihot flowers, extracting with an alcohol solvent, filtering, and concentrating to obtain an extracting solution; b) purifying the extracting solution by adopting macroporous resin to obtain an eluent; and C) concentrating the eluent, and drying to obtain the traditional Chinese medicine composition. According to the method, diluted alcohol extraction and a high-speed homogenization-ultrasonic-assisted liquid phase extraction method (HSH-UAE) are adopted, so that the contact area of a solvent and the abelmoschus manihot flowers is increased, full contact of medicinal materials and the solvent is guaranteed, and flavonoid substances are dissolved more sufficiently, so that the extraction speed is increased, and the extraction efficiency is improved. Macroporous adsorption resin is selected for separation and purification, the purification effect is good, operation is easy, safety, no toxicity and no pollution are achieved, reuse can be achieved after slight treatment, and the production cost is effectively reduced. Compared with a traditional method, the method has the technical advantages that the extraction speed is high, the extraction yield is high, effective components are fully extracted and reserved, and the process is simple.

The invention discloses a hole making process parameter recommendation method based on a knowledge graph, which uses an optimized seven-step method, and provides an ontology evaluation system and an ontology updating method, so that a hole making process ontology can be updated and iterated according to different processing requirements; according to the method, the fine-tuning UIE model is adopted to perform knowledge extraction on the hole-making process text data, good extraction accuracy can be obtained only by performing fine-tuning on the UIE model by using small sample data, the marking cost of knowledge extraction of the hole-making process text data is reduced, and the extraction efficiency is improved; according to the method, an entity alignment algorithm and a processing case filtering algorithm based on text similarity and word list mapping are designed, so that the repetition rate of knowledge in the knowledge graph is reduced, and the retrieval efficiency is improved.

The invention provides a three-dimensional gesture estimation method fusing hand and object features, and relates to the technical field of gesture recognition. The method specifically comprises the following steps: acquiring a plurality of different hand and object images containing 3D postures of a hand and an object, constructing an image data set, and dividing a training set from the image data set according to a preset proportion; constructing a hand occlusion estimation joint model fusing the hand object features; inputting the training set into a hand occlusion estimation joint model fused with the hand and object features for training to obtain a trained hand occlusion estimation joint model fused with the hand and object features; and acquiring a hand and object image containing 3D postures of a hand and an object, and inputting the hand and object image into the trained hand occlusion estimation joint model fusing the hand and object features for gesture estimation to obtain a three-dimensional gesture estimation result. According to the method, the hand feature information can be better extracted under the severe shielding condition by designing the hand shielding estimation joint model fusing the hand feature.

The invention relates to a process for gradient extraction of seaweed protein, algin and fucoidin in brown algae. The invention relates to a process for extracting seaweed protein, algin and fucoidin in brown algae, which comprises the following steps: carrying out superfine grinding on seaweed, adding water for extraction, filtering and separating to obtain water extraction filtrate, repeatedly dissolving the water extraction filtrate in the next batch of superfine ground seaweed, and circulating for 7 times to obtain saturated or supersaturated water extraction filtrate; adjusting the pH value of the water extraction filtrate to be acidic, and filtering and separating through a micro-filtration membrane to obtain seaweed protein and first filtrate; adding calcium chloride into the first filtrate, and settling to obtain algin and supernate; filtering the supernate through a polyethersulfone composite membrane to obtain a fucoidin concentrated solution; and carrying out spray drying on the concentrated solution to obtain fucoidin powder. The method solves the problem that other functional components are wasted due to the fact that only a single component can be extracted in an existing brown algae functional component extraction method, and also solves the problems of secondary pollution, poor product quality and high cost in an existing extraction method.

The invention discloses a multi-modal large model automatic evaluation method and system based on Agentic Workflow, relates to the technical field of artificial intelligence model evaluation, and solves the technical problems that an existing large model evaluation method lacks image-text evaluation, is relatively high in subjectivity and is easy to cause illusion. The method comprises the following steps that S1, an input task is analyzed, and a structured task template is generated; s2, generating a multi-round multi-modal task flow chart based on the task template generated in the step S1; s3, based on the flow chart in the step S2, distributing the multi-modal large model component to each task node, executing a task and obtaining an intermediate result; s4, performing multi-dimensional scoring on the intermediate and final results in the step S3 by a plurality of scoring Agents, and fusing to generate an evaluation result; and S5, generating a feedback report based on the process data in the steps S1 to S4, identifying a model short plate, and providing an optimization suggestion. The method has the advantages of comprehensive evaluation of multiple modes, real-time feedback optimization and the like.

The invention discloses a method for fracturing a low-permeability coal seam by linkage of CO2 and high-pressure water, which comprises the following steps of: performing hydraulic fracturing to form a part of fractures, forming a weak acid environment by utilizing the characteristic that a CO2 medium is easily dissolved in high-pressure water in a high-pressure environment, and promoting chemical reaction between acid water and mineral components on the surfaces of the fractures under the driving of concentration gradient and high-pressure injection, the fractures are pressed by high-pressure water at the same time, so that cooperative work of high-pressure fracturing and CO2 acidification anti-reflection is achieved, and a complex fracture network is formed in the coal seam; after permeability increasing, the pressure is relieved, the normal pressure environment is recovered, at the moment, CO2 media dissolved in the high-pressure water in the layer penetrating drill holes are partially recovered to be in the gas state, CO2 gas and gas can form competitive adsorption in the coal seam, a large amount of gas is displaced and desorbed from the interior of the coal seam, in the whole process, the permeability increasing effect on the coal seam can be effectively achieved, and the coal seam permeability increasing effect is achieved. And no extra damage is caused to the coal seam, finally, on the premise that more energy is not consumed, effective transformation of the pore structure volume of the coal body is achieved to the maximum extent, and the gas extraction efficiency is improved.

The invention discloses a laterite nickel ore leachate extraction tower which comprises an extraction tower body, a heavy phase feeding mechanism, a light phase feeding mechanism, a baffle mechanism and a gas distribution device, the extraction tower body comprises a tower body, a containing cavity is formed in the tower body, and an upper clarifying groove is formed in the top of the tower body; the baffle mechanism comprises at least one movable baffle arranged in the tower body and a lifting driving piece, and through holes are densely distributed in the movable baffles. A heavy phase and a light phase are promoted to be mixed in an air floatation mode, and meanwhile, the lifting driving part drives the movable baffle to move up and down, so that the movable baffle is always located in the light phase in the tower body and located in a preset height range above an interface of the light phase and the heavy phase. When a heavy phase upwards penetrates through each through hole in the movable baffle, the heavy phase is dispersed into small liquid beads, so that the heavy phase is in full contact with a light phase above, the mixing effect is improved, and the extraction efficiency is improved.

The invention discloses a social network public opinion monitoring method and system based on artificial intelligence. The method comprises the following steps of obtaining public opinion data from a social network platform and performing data preprocessing; hot events are automatically extracted from the public opinion data, and a density peak clustering algorithm is utilized to identify a high-density area and determine the popularity of the hot events. A BERT model is adopted to carry out sentiment classification on a text, context features are extracted in combination with bidirectional LSTM, and sentiment tendency is output through a Softmax classifier. For a specific target event, a multi-head attention mechanism and a convolutional neural network are used for specific target emotion classification. And performing noise reduction and decomposition on the time sequence data, constructing a plurality of basic prediction models, generating a combined prediction model in combination with weighted average, and monitoring and predicting the public opinion development trend in real time. Accurate public opinion analysis and decision support are provided for governments and enterprises, public opinion risks are reduced, social stability is maintained, and social construction is promoted.

The invention provides a road surface coring device based on road detection, which belongs to the technical field of road surface detection coring equipment and comprises a movable support frame, a vertical movable seat, a rotary drill bit, a first adjusting mechanism and a second adjusting mechanism. The movable supporting frame is provided with two guide sliding rods. And the vertical moving seat is arranged on the two guide sliding rods in a sliding manner. And the rotary drill bit is in power connection with a driving structure arranged on the vertical moving seat through a transmission mechanism. The rotary drill bit is provided with a cylindrical cavity with an open bottom end. The clamping assembly is provided with a plurality of abutting parts arranged around the inner wall of the barrel cavity. The first adjusting mechanism can drive the vertical moving seat to move up and down. The second adjusting mechanism can drive the clamping assembly to act after the core sample is separated from the road, so that the abutting parts move towards the interior of the barrel cavity and clamp the core sample. According to the road surface coring device based on road detection, it is guaranteed that a core sample is clamped and taken out along with the drill bit in the process that the drill bit leaves a drill hole, and the core sample can be effectively prevented from falling into the drill hole.

The invention discloses a preparation method of efficient antioxidant sturgeon protein peptide. The preparation method comprises the following steps: S1, extracting a sturgeon skin crude protein solution; s2, extracting sturgeon swimming bladder crude protein; s3, extracting crude protein liquid of the sturgeon meat; s4, performing mixed enzymolysis; and S5, carrying out enzyme deactivation treatment on the obtained enzymatic hydrolysate to obtain enzymatic hydrolysate, and sequentially carrying out ultrafiltration and vacuum drying on the enzymatic hydrolysate to obtain the efficient antioxidant sturgeon protein peptide. Proteins extracted from different parts of sturgeons are mixed according to a specific proportion and then subjected to enzymolysis, the added neutral protease and papain can achieve a synergistic effect, protein is hydrolyzed more comprehensively, small molecule peptides with specific functions are generated, meanwhile, glutathione added during enzymolysis can protect sulfydryl of enzymes, and the enzymolysis effect of the sturgeons is improved. The enzyme activity is maintained, so that the finally obtained sturgeon protein peptide has good oxidation resistance.

The invention discloses a green deodorization method suitable for ultramicro sea cucumber powder, and belongs to the field of food processing. The method comprises the following steps: S1, putting sea cucumber coarse powder into an extraction kettle of a supercritical extraction instrument, and deodorizing the sea cucumber powder; s2, crushing the sea cucumber powder subjected to fishy smell removal in the step S1 by using an ultrafine crusher to obtain sea cucumber powder, and controlling the bulk density of the powder to be 0.65-0.7 g / mL and the tap density to be 0.70-0.80 g / mL; and S3, putting the sea cucumber powder subjected to superfine grinding in the step S2 into an extraction kettle of a supercritical extraction instrument for deodorization. According to the invention, the second hole disc is additionally arranged on the gas distributor in the supercritical extraction instrument, so that carbon dioxide fluid flows back during extraction, the pressure of the carbon dioxide fluid discharged from the material basket is reduced, and the material is prevented from being taken out, thereby solving the problem of pipeline blockage of ultra-micro powder and improving the extraction efficiency and the production efficiency.

The invention relates to a livelihood public opinion big data-based territorial space planning implementation monitoring method, which comprises the following steps of: constructing a multi-level space unit and a territorial space information lexicon according to territorial space multi-source data, and matching livelihood public opinion big data in the territorial space information lexicon to obtain a spatial position; matching the obtained spatial position with a multi-level spatial unit to obtain a spatial unit corresponding to the spatial position; identifying an emotion label for each record in the livelihood public opinion big data, and calculating a livelihood emotion index planned and implemented in the spatial range of each hierarchical spatial unit according to the emotion label; and processing the livelihood public opinion big data to obtain a territorial space livelihood keyword library, updating the territorial space livelihood keyword library, and generating each level of space unit planning and implementing livelihood public opinion keywords in combination with the territorial space information word library and the updated territorial space livelihood keyword library. The method can dynamically monitor subjective feelings of the public on planning implementation conditions and key problems of social livelihood attention.

The invention discloses a water conservancy ecological engineering desilting device and a desilting method thereof, and relates to the technical field of river channel desilting, the water conservancy ecological engineering desilting device comprises a desilting frame and further comprises a crushing device, the top of the desilting frame is fixedly provided with a desilting pipe, the top of the desilting frame is fixedly provided with a connecting buckle, and the top of the desilting frame is fixedly provided with a servo motor, the crushing device comprises a rotating rod, a sleeve, an extrusion rod, a cambered surface block, a scattering rod, a cambered surface rod, an S-shaped rod and a linkage plate, the sleeve moves upwards to reset to drive the scattering rod and the S-shaped rod to move upwards, the scattering rod moves upwards to drive the cambered surface rod to move upwards, and the cambered surface rod and the scattering rod move in a reciprocating mode to scatter caked sludge at the dredging position; the arc-surface rod and the scattering rod reciprocate to uniformly apply force, so that caked sludge is effectively scattered, the dredging efficiency is improved, the crushed sludge is conveniently further treated and conveyed, and the overall treatment capacity of the equipment is improved.

The invention relates to a method for extracting high-purity astragalus polysaccharide. The method comprises the following specific steps: washing astragalus, drying and crushing into coarse powder; under a certain solid-liquid ratio, extracting astragalus polysaccharide by using ultrasonic waves; carrying out mixed enzymolysis on the extracting solution and cellulase, and terminating enzyme reaction through heating; and mixing the enzymatic hydrolysate with specific molecularly imprinted polymers (MIPs), specifically adsorbing the astragalus polysaccharide through a molecular recognition effect, and eluting and purifying by using a mixed solution of water and ethanol. In the preparation process of the MIPs, oligosaccharide fragments of astragalus polysaccharide, acrylamide, ethylene glycol dimethacrylate, potassium persulfate and lauryl sodium sulfate are dissolved in methanol, and free radical polymerization reaction is carried out under the protection of nitrogen. Experimental results show that the purity and the extraction rate of the astragalus polysaccharide extracted by the method are remarkably improved, and the method has the advantages of simplicity and convenience in operation, high efficiency, economy, environmental protection and the like.

The invention relates to the technical field of compound extraction, in particular to a control method and system for ultrasonic-assisted extraction of high-purity flavonoid compounds. According to the method, preparation conditions are optimized according to material characteristics, then ultrasonic treatment is carried out by adopting a segmented control strategy, meanwhile, the extraction process is tracked in real time through chromatographic detection, process parameters are adjusted in time based on the change trend of an efficiency curve, blindness of a traditional fixed parameter control mode is avoided, and the efficiency is improved. Through intelligent dynamic adjustment, the energy utilization efficiency is remarkably improved, excessive degradation of effective components is effectively prevented, and the control accuracy of the extraction process is improved.