216 results about "Quantitative determination" patented technology

The invention belongs to the technical field of geophysical exploration, and particularly relates to a method and a system for quantitatively measuring intrinsic parameters of bedrock fractures based on all-angle domain amplitude and phase joint inversion. The method comprises the following steps: acquiring geological radar reflection data of a target fracture at a plurality of incident angles; synchronously extracting data sequences of amplitude change along with angles and phase change along with angles; establishing a fracture reflection theoretical model; constructing a target function jointly constrained by the amplitude residual and the phase residual; and adopting a global optimization algorithm to minimize the target function, and synchronously inverting to obtain the fracture opening, the filler dielectric constant and the occurrence parameter. According to the invention, through the combined constraint of the amplitude and the phase, the inversion multiplicity is effectively inhibited; accurate system effect correction is adopted, so that the reliability of large-angle data is ensured; according to the method, multi-parameter synchronous inversion without prior hypothesis is realized, the inversion precision is small in relative error, the method is obviously superior to a traditional method, and the method has important engineering application value.

The invention relates to the technical field of giant salamander by-product quality evaluation, and discloses a giant salamander by-product source functional factor quality evaluation system and method, and the method comprises the steps: obtaining a giant salamander by-product sample, carrying out the pretreatment, and extracting a functional factor to obtain a to-be-detected sample; identifying and quantitatively determining specific markers based on biochemical analysis and molecular detection means to generate a marker data set; inputting the marker data into a multi-modal feature fusion module, extracting activity and stability features, and performing time sequence dynamic modeling; activity and stability independent evaluation branches are set, and corresponding score values are generated; dividing functional domains according to functional factor categories, constructing an evaluation curve based on historical data, substituting a target sample into each functional domain and an adjacent functional domain to generate functional domain evaluation results, and performing weighted fusion; and finally, carrying out weighted integration on the activity score, the stability score and the comprehensive evaluation value, and determining a final quality evaluation result.

The invention provides a pepsinogen II determination kit and a quantitative determination method, the kit comprises a reagent R1 and a reagent R2, the reagent R1 comprises a luminous donor molecule labeled pepsinogen II first antibody and a reaction buffer solution; and the R2 reagent comprises a light-emitting receptor molecule labeled pepsinogen II second antibody and a reaction buffer solution. A double-antibody sandwich structure marked by a luminescent donor and a luminescent receptor respectively is adopted, binding and luminescence can be completed in a liquid phase, solid phase coating and subsequent multi-step washing are not needed, real homogeneous detection and one-step incubation are achieved, the operation process is simplified, the detection time is shortened, and a full-automatic platform is adapted; and an improved buffer system can inhibit non-specific adsorption and reduce heterotropism interference such as RF / HAMA, so that the detection accuracy and repeatability are improved.

The invention relates to the technical field of biological detection signal analysis, and discloses a method for rapidly detecting the content of active collagen. The method comprises the following steps: collecting an original optical response signal of a reaction between a to-be-detected solution and a specific reagent, and constructing a time-space continuous primary reaction track through multi-level slicing and cross-domain splicing of a time domain, a frequency domain and a time-frequency domain; a signal mode set related to activity is separated through convolution kernel group depth scanning. A graph association network between signal modes is constructed based on the set, and a steady-state feature graph representing reaction kinetics is generated through iterative calculation. The feature map is mapped to a virtual reaction space defined by standard data, and quantitative judgment is achieved by calculating the distance between a projection vector and a preset concentration anchor point. According to the method, the sensitivity and the anti-interference performance of detection are enhanced through deep analysis reaction dynamic signals and correlation network modeling.

The invention discloses a multi-source operation exception association analysis and grading disposal method and system. The method comprises the steps of telemetry data collection and caching, non-blocking sending and self-adaptive readaptation, sliding time window and matrix construction, exception association clustering and comprehensive scoring, exception type judgment and grading alarm and self-healing disposal. The method comprises the following steps: continuously sensing a program execution state and an abnormal behavior, realizing data peak clipping storage by local cache, introducing a self-adaptive backoff retry mechanism, decentralizing transmission of abnormal data on the premise of not blocking a main service, and identifying and distinguishing anomalies in combination with abnormal propagation characteristics and an influence coupling relationship. And after quantitative judgment, automatically outputting a matched grading treatment strategy and an operation recovery measure. The closed-loop operation treatment mechanism of coverage sensing, transmission, aggregation, judgment and disposal constructed by the invention can realize rapid sensing, accurate attribution and adaptive response of the abnormity in a complex industrial load environment, and the stability and reliability of the operation of an industrial system are remarkably improved.

The invention belongs to the technical field of medicine detection, and particularly relates to a method for determining the content of impurities in OAB-14 by using high performance liquid chromatography. The method comprises the following steps: preparing a test sample labeling solution, a test sample solution and a contrast solution of OAB-14, respectively injecting the test sample labeling solution, the blank solution, the contrast solution and the test sample solution into a liquid chromatograph, recording chromatograms, and calculating according to a main component self-contrast method to obtain the content of impurities in the test sample solution; wherein the impurities are one or more of an impurity A, an impurity B, an impurity C, an impurity D, an impurity E or an impurity F. According to the method, the impurities in the OAB-14 can be qualitatively and quantitatively measured at the same time, the stability and the reproducibility are good, the separation degree between a main peak and each impurity peak is good, the precision is high, and an analysis means is provided for quality control of the OAB-14.

The present application relates to the technical field of cell function detection, and particularly relates to a method for evaluating cell function of HL-60 in monocyte activation test. The method comprises the following steps: (1) preparing HL-60 cell suspension; (2) stimulating with pyrogen; (3) quantifying total protein; (4) detecting by Western blotting; and (5) evaluating cell function. The method is based on Western blotting technology, and combines statistical analysis to realize objective and quantitative determination of the core functional index of the ability of synthesizing IL-6 protein under pyrogen stimulation, can accurately identify cells with pyrogen response function defects, provides clear experimental reference for selection of HL-60 cell generations, can pre-screen qualified cells, reduces pyrogen detection deviation caused by unqualified cell function and improper generations from the source, and effectively improves the reliability and repeatability of pyrogen detection results.

This invention discloses a method and system for data fusion of multi-platform commercial outlets based on multi-source heterogeneous data. It relates to the field of data processing technology. The method involves acquiring commercial outlet data from multiple platforms and performing validity verification to generate an initial data foundation for each platform; extracting outlet coordinate information and performing a unified format conversion to obtain a coordinate-standardized commercial outlet dataset; constructing a multi-industry knowledge graph and an industry-wide common affix library; using algorithms to remove common name affixes and retain core feature identifiers to generate a feature-identified dataset; constructing a similarity algorithm to extract multiple features of outlets, calculate their similarity separately, and fuse them to obtain an overall similarity, generating a similarity matching result set; and identifying and removing duplicate data from multiple platforms based on the matching results to generate a full dataset of multi-source fused commercial outlets. Compared to traditional fusion methods, this method achieves accurate feature identification and quantitative determination of duplicate data, improving the completeness and accuracy of the fused data and making more efficient use of computing power.

The application discloses a kind of coal rock nonlinear fracture propagation length quantitative determination method based on multiple parameters, comprising: preparation of coal rock sample containing notch;Spray black and white speckle on the surface of sample, install acoustic emission sensor, clip type extensometer and displacement sensor;Carry out three-point bending peak after cycle loading and unloading fracture experiment, record load, crack opening, force point displacement, acoustic emission waveform and DIC image;Through COD-P and LPD-P curve calculation mechanics flexibility, back calculation to solve stress constraint crack length;From acoustic emission positioning, obtain the spatial distribution histogram of breakage dissipation energy, combined with DIC horizontal displacement gradient threshold cloud picture, determine equivalent crack tip and length;Further calculate coal rock fracture process zone length, and intuitively show nonlinear fracture propagation path.The application provides a kind of crack dynamic change quantitative determination method based on mechanics flexibility-displacement gradient-energy dissipation distribution multiple physical parameters, reduce the influence of human subjective consciousness, and the measurement result is accurate and reliable.

The application discloses a method for determining 15 new psychoactive substances in saliva by solid phase supported liquid-liquid extraction (SLE) combined with ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS / MS), which specifically uses a mixed solution of methyl tert-butyl ether and n-hexane as an elution solvent, adopts solid phase supported liquid-liquid extraction to pretreat saliva samples, and then adopts UPLC-MS / MS to detect the collected eluent, so as to realize qualitative and quantitative determination of the new psychoactive substances in saliva. The method has the advantages of rapidness, accuracy, high sensitivity and simple operation, the detection limit of the method is 0.2-0.5 ng / mL, can meet the domestic and foreign limit requirements, and provides technical support for monitoring and investigation of the new psychoactive substances in saliva.

A quantitative detection method of thallium content in converter graphite ball, steps include: 1) the pretreatment of converter graphite ball; 2) the preparation of standard solution series; 3) the detection of thallium content in converter graphite ball.The application finds that the suitable pretreatment method of converter graphite ball is carbon removal by burning, and then high-chloric acid and dilute nitric acid are used to dissolve salt, by which the converter graphite ball can be completely dissolved, thereby the stability of quantitative determination of thallium content in converter graphite ball is improved, the pretreatment method is simple, fast and operable; the method is suitable for the quantitative detection of thallium content in converter graphite ball with thallium content not less than 0.0062 μg / L, the recovery rate of thallium is as high as 99.1%, the analysis accuracy is high, the detection lower limit is as low as ppb level, the sensitivity is high, and the method has the advantages of simple operation, simple analysis condition and low labor intensity.Therefore, the application has significant economic benefits and the advantages of simplicity and economy.

The invention discloses a quantitative detection method for a mixture of bis (2-hydroxyethyl) disulfide and mercaptoethanol, and relates to the field of analysis and detection. The testing method comprises the following steps: respectively preparing a bis (2-ethoxyl) disulfide standard solution and a mercaptoethanol standard solution with different concentrations; and quantitatively measuring the standard solution and the detection sample through gas chromatography equipment, optimizing chromatographic conditions, drawing a standard curve according to the detection result of the standard solution, and quantitatively analyzing the detection sample by combining the standard curve and the spectrum of the standard solution. According to the present invention, the gas chromatography conditions are optimized, the phenyl functional group-containing polysiloxane is selected as the filler of the chromatographic column, and the detection temperature and the temperature rising program are controlled so as to ensure the separation and the detector sensitivity, and the split ratio is controlled to avoid the non-linear response and the peak overlapping; the detection accuracy of the bi-component bis (2-ethoxyl) disulfide and mercaptoethanol is high, the chromatographic peak separation degree is good, and the product quality detection requirement can be met.

The invention discloses a deep surrounding rock anchor rod spacing quantitative determination method based on fracture toughness parameters. The method comprises the following steps: obtaining the fracture toughness and uniaxial compressive strength of rock through an indoor test; determining a uniaxial compression parameter and an elastic modulus of the rock mass by combining a geological strength index GSI, a damage factor D and a Hoek-Brown criterion; calculating a brittleness index B4 by using the fracture toughness of the surrounding rock, the uniaxial compressive parameter of the rock mass and the elastic modulus; and based on the brittleness index B4, the rock mass elasticity modulus, the engineering burial depth and the rock mass volume weight, a quantitative calculation formula of the anchor rod spacing is established, an empirical coefficient is solved in combination with the spacing range of the corresponding surrounding rock grade in the specification, and finally quantitative determination of the anchor rod spacing is achieved. The method overcomes the defect that quantitative basis is lacked in spacing adjustment in existing specifications, and is particularly suitable for anchor rod support design for controlling brittle failure of surrounding rocks under the deep high-stress condition.

The present application relates to the technical field of environmental monitoring and pollution tracing, and discloses a basin-scale perfluorinated compound tracing method and system based on artificial intelligence, which integrates multi-source data in a basin to construct a unified spatial and temporal granularity basin multi-source data cube, identifies perfluorinated compound structures through a virtual spectrum diagram enhanced deep learning model, simulates pollutant spatial and temporal concentration distribution by combining a graph neural network of a physical mechanism, and then inversely propagates and matches source characteristic fingerprints to invert potential emission source contribution, outputs a pollution source contribution heat map and a priority control enterprise list, solves the core problems of difficulty in joint analysis of multi-source data, difficulty in identification of unknown compounds and difficulty in quantitative determination of multi-source superposition contribution in basin-scale perfluorinated compound tracing, and provides support for precise pollution control.

The invention provides a method for quantitatively detecting arsenic element in ciliate desert-grass leaves, which comprises the following steps: preparing a sample tablet of the ciliate desert-grass leaves, collecting LIBS spectral data of the sample tablet, obtaining the true value of the arsenic element content of the sample tablet, and constructing an original spectral view angle, a first derivative view angle and a second derivative view angle of the LIBS spectral data. The method comprises the following steps: preliminarily establishing a ciliate desert-grass leaf arsenic element quantitative model by adopting a table priori data fitting network model, introducing spectral physical priori constraint for an original prediction result of the table priori data fitting network model at each view angle, establishing a multi-view prediction result fusion model, and generating a final arsenic element concentration prediction result. According to the method, the respective advantages of the three perspectives can be combined, the sensitivity and stability of arsenic content detection are remarkably improved, the method can be applied to rapid detection of arsenic elements in the leaves of the ciliate desert-grass, and an efficient and reliable technical means is provided for ciliate desert-grass arsenic element absorption mechanism research, pollution remediation efficiency evaluation and treatment strategy optimization.

In a first aspect, the present invention is directed to a magnetic particle having a saturation magnetization ≥ 15 Am2 / kg and having at least one azide group –N=N'-N- bonded to a polymer matrix of the magnetic particle. A second aspect of the invention relates to a process for preparing a magnetic particle, which comprises at least one magnetic core (M), a polymer matrix (P) comprising a crosslinked polymer at least partially surrounding the magnetic core (M), the polymer matrix (P) comprising on its surface at least a functional group reactive towards amine groups and / or hydroxyl groups. In a third aspect, the invention is directed to the magnetic particle obtained or obtainable from the process of the second aspect. A fourth aspect is related to a process for preparing a magnetic particle having a saturation magnetization ≥ 15 Am2 / kg of the first aspect, and a fifth aspect relates to the magnetic particle obtained or obtainable from the process of the fourth aspect. A sixth aspect is directed to the use of the magnetic particle having a saturation magnetization ≥ 15 Am2 / kg of the first aspect or of the fourth aspect for qualitative and / or quantitative determination of at least one analyte in a fluid or in a gas, and a seventh aspect relates to a method for determining at least one analyte in a fluid using said magnetic particle having a saturation magnetization ≥ 15 Am2 / kg.

The invention relates to the technical field of material testing and analysis, and discloses a quantitative determination method for effective components in a traditional Chinese medicine capsule, which comprises the following steps: mixing choline chloride and ethylene glycol to prepare a deep eutectic solvent system; the traditional Chinese medicine capsule is placed in the eutectic solvent system, a composite frequency ultrasonic field is applied, a sound pressure amplitude step is generated by alternately switching a first working frequency and a second working frequency, and the eutectic solvent system is driven to complete solvent exchange in the medicine powder micropores; according to the method, the diffusion equilibrium of a microscopic interface is broken through the physical suction effect generated by sound pressure step, a solvent saturation dead zone in the compact particles is eliminated, and on the basis of integration of extraction and purification, the extraction and purification efficiency is greatly improved. And the accuracy and the stability of quantitative response signals are improved.

A micro-crack crushing state monitoring method, a monitoring system, a medium and a product, relate to the technical field of data processing. In the implementation of the method, the monitoring system obtains the acceleration sequence of the falling hammer of the intelligent rammer at the impact point and the coordinate information of the impact point, calculates the acceleration peak value and compares it with the impact acceleration threshold interval, realizes the quantitative determination of the crushing effect of the impact point, can accurately identify the points of excessive crushing and insufficient crushing, and output the corresponding coordinates and generate targeted treatment prompts and instructions, change the traditional manual experience judgment mode, realize the automatic and accurate monitoring of the micro-crack crushing effect, effectively avoid the subjectivity and error of manual judgment, and improve the efficiency and accuracy of the crushing effect monitoring in old road reconstruction and other engineering.

The invention discloses a multi-level-based high-precision safety modeling method and system for a hybrid power system of an aviation aircraft, and relates to the technical field of aviation aircrafts. Comprising the following steps: constructing a multi-level modeling framework of the hybrid aircraft, and dividing modeling levels; the method comprises the following steps: constructing a high-precision component-level model in a mathematical description manner for components of a hybrid power system; according to the established high-precision component-level model, identifying a data interaction mechanism among the component models; simulation calculation is conducted on the hybrid power system model, and the change rule of performance parameters of the hybrid power system model along with engine operation is obtained; according to a test verification result, correcting model parameters of the hybrid power system; and based on the verified rated boundary of the hybrid power system model, a system time-varying limit state function is constructed, a whole machine safety model is formed, and quantitative determination of the system safety state is realized. According to the method, more comprehensive security analysis on a complex system is finally realized.

This invention relates to the field of analytical chemistry, and in particular to a method for the quantitative determination of total phosphate in aquatic products using acid hydrolysis combined with liquid chromatography-tandem mass spectrometry. The method exhibits good linearity for orthophosphate in the range of 0.1–20.0 mg / L, with a correlation coefficient of 0.9991, a limit of detection of 0.03 g / kg, a limit of quantitation of 0.10 g / kg, and low matrix effect. At spiking levels of 1.0–10.0 g / kg, the intra-day recoveries for shrimp and fish are 89.8%–102.8% and 88.7%–105.8%, respectively; the inter-day recoveries are 90.9%–106.4% and 90.2%–105.8%, respectively; the intra-day RSD is ≤10.0%, and the inter-day RSD is ≤9.6%. This method features simple pretreatment, strong anti-interference capabilities, high sensitivity, and excellent accuracy and precision. It is suitable for the detection of total phosphate in aquatic products, providing a reliable technical means for the supervision of total phosphate in aquatic products, and is highly practical.

The invention discloses a glue filling information determination method and system based on laser detection and visual identification, and the method comprises the steps: obtaining the position data of a mechanical arm in real time in the gluing process of the mechanical arm, and collecting and generating laser detection data through a visual identification assembly and a laser detection head disposed at the tail end of the mechanical arm; generating a colloid point cloud image under a mechanical arm coordinate system based on the laser detection data and the mechanical arm position data, and generating a standard colloid model based on the colloid point cloud image; and based on the colloid point cloud image and the standard colloid model, determining colloid height missing information, and based on the colloid height missing information, generating a glue supplementing path track of the mechanical arm and the glue discharging speed corresponding to each glue supplementing position on the glue supplementing path track. According to the technical scheme, the glue height missing information is accurately obtained through the laser and vision fusion technology, accurate quantitative determination of glue supplementing information is achieved, and the problems that traditional glue supplementing is inaccurate in positioning and unbalanced in quantity control are solved.

The application belongs to the field of asphalt mixture performance analysis, and specifically discloses a fatigue performance analysis method for asphalt mixture of asphalt pavement. The method fuses embedded sensors to synchronously collect dynamic strain field and temperature field inside the material in the paving and rolling construction process, and combines a temperature-strain coupled fatigue damage evolution model to construct an online fatigue performance analysis system for the whole construction process, effectively restores the complex thermal-mechanical coupling environment and non-uniform compaction process in the actual paving operation, significantly reduces the scale effect deviation and boundary condition distortion caused by the difference between the laboratory specimen preparation and the field working condition, and at the same time, in the online detection process of the fatigue performance of the asphalt mixture, the abnormal accumulation process of the strain before the micro-crack initiation can be captured by positioning the damage significantly exceeding the limit area, realizing the instant quantitative determination of the pavement structure performance state, fully embodying the in-situ monitoring capability of the fatigue damage initiation.

The invention relates to the technical field of coal mine fully mechanized mining, in particular to a hydraulic support peak value checking and staged type selection parameter determining method under the dynamic load effect, which comprises the following steps: S1, acquiring and preprocessing support, wall caving and micro-seismic monitoring data before pressure relief or treatment; s2, the support resistance and the valve opening rate are counted according to a fixed time window, and the rib spalling depth and the microseismic strength are fused to form a statistical table; s3, calculating a dynamic load coefficient and constructing a dynamic load strength index, identifying a weighting dynamic load event and extracting a peak value; s4, staged according to the propulsion distance and statistics of resistance peak values and dynamic load coefficient peak values of all stages are carried out; s5, calculating stage rated working resistance according to the stage resistance peak value and the safety coefficient; and S6, screening the candidate stent which meets the condition and has the minimum rated resistance as a recommended model. According to the method, the dynamic load peak value checking of the hydraulic support and the quantitative determination of the staged model selection parameters are realized, and the safety and the economy of the model selection of the support are improved.

The application provides a PVC film preparation system and method based on industrial intelligent vision. In a stable production process of an extruder, an extruder screw torque signal and a melt temperature signal are collected, and a PVC film surface image sequence is obtained in real time. A black point density change rate per unit area in the PVC film surface image sequence is counted, and an area distribution feature of the black points in the PVC film surface image is extracted. A torque fluctuation amplitude in the screw torque signal and an over-threshold integral quantity of the melt temperature signal are calculated. The area distribution feature, the torque fluctuation amplitude and the over-threshold integral quantity are used to determine the causes of the black points in the PVC film preparation, and a determination result of the causes of the black points is obtained. Based on the black point density change rate and the cause category of the determination result, a parameter adjustment amount is calculated, and a speed adjustment amount and a maintenance time required to reduce the black point density to a target value are output. Based on the above scheme, cause category quantitative determination based on multi-source signal fusion can be realized.

The invention discloses a blade damage quantitative determination method and system, and belongs to the technical field of image processing and fault diagnosis. The method comprises the following steps: performing multi-scale feature extraction on a leaf image; generating a damage candidate area and performing mask segmentation; carrying out statistics on damaged pixel areas and carrying out cross-category sorting; dividing damage grades based on quartile; and outputting a combined result of the category and the grade. The system comprises corresponding modules. Through pixel-level segmentation and quantitative evaluation, the problems that a traditional method is insensitive to weak damage and lacks a unified quantitative standard are solved, and the method has the advantages of being high in detection precision, high in adaptability and the like and is suitable for leaf health monitoring and maintenance.

The invention belongs to the technical field of unconventional oil and gas development, and particularly relates to a gas-water-rock reaction and particle dissolution-migration in-situ visual quantitative determination method and device based on a micro-fluidic chip. The quantitative determination method comprises the following steps: firstly, designing a chip model containing a real rock core, wherein factors such as a strong heterogeneous structure of the compact conglomerate oil reservoir and strong difference of a pore throat structure are considered at the same time; then, the gas-water-rock reaction and the particle dissolution-migration process are recorded through an optical camera; and finally, analyzing contribution degrees of different minerals to a gas-water-rock reaction and judging different corrosion modes of the conglomerate by combining image processing software and a mathematical model. The method can be used for carrying out in-situ visual quantitative determination on gas-water-rock three-phase reaction, particle corrosion and a secondary migration process in the conglomerate reservoir under the conditions of oil reservoir temperature pressure and fluid chemistry.

The invention discloses a new energy automobile charging pile layout optimization method based on big data analysis, and relates to the technical field of charging pile layout management. The method comprises the following steps of layout response judgment, layout test verification and layout decision training optimization. According to the method, the peak load response capability in the prediction process is quantitatively judged, so that the condition of charging pile overload or resource waste in the peak period can be effectively reduced, and the balance and adaptability of charging facility configuration are remarkably improved. Through layout decision response optimization, the response precision and timeliness of the model to peak load sudden change can be improved, and meanwhile, through obtaining a layout test verification result, the layout accuracy and the use efficiency of charging pile resources can be further improved. On the basis, charging pile planning layout decision training optimization is introduced, so that the charging pile layout decision is more accurate and higher in adaptability, and the actual effect and reliability of the layout decision are improved.

This application discloses a method and system for assessing extreme environmental conditions in coastal engineering, relating to the fields of marine and coastal engineering technology. The method includes: establishing wave propagation deformation conversion relationships; performing quality control on multi-source wave-tide data; performing tidal level decomposition on the total water level time series; identifying multiple independent extreme wave-tide coupling events, extracting characteristic parameters to form a multi-dimensional extreme sample set, and establishing a joint distribution model; determining the target probability level and constructing an environmental profile with equal exceedance probabilities; selecting representative combined operating conditions, and using the wave propagation deformation conversion relationships to convert the representative combined operating conditions to nearshore control points to obtain design wave elements. This application, driven by multi-source wave-tide data, establishes a joint distribution model of wave height, period, and tidal level and constructs an environmental profile with equal exceedance probabilities, achieving quantitative determination of extreme design wave conditions with clear joint probability meanings, thus improving the scientific and economical nature of coastal engineering design.

The embodiment of the invention discloses an intelligent recognition and grading method for gastric intestinal metaplasia, and the method comprises the steps: collecting a gastric mucosa HE staining digital pathological image, and building a universal part recognition model through a convolutional neural network according to the pathological classification standards of different parts of a stomach body, gastric antrum and gastric horn. In order to reduce judgment errors caused by other glands, a semantic segmentation model is trained, and the gastric mucosa is accurately found out. On the basis, a developed high-precision detection and recognition algorithm is used for recognizing the enteric glands, and quantitative determination is carried out on the enteric glands in the gastric mucosa of the stomach body, the antrum and the corner of the stomach. And the identified target glands are automatically counted, and intelligent OLGIM grading is carried out.

The application belongs to the technical field of oil and gas field development, and discloses a method and device for measuring the thickness of a soft rock area after long-term fracture diversion, which comprises the following steps: obtaining a core sample to be measured; performing layer-by-layer scratch at equal depth on the fracture diversion surface of the core sample to be measured; collecting discrete horizontal displacement data in real time during the process of each layer of scratch, and determining the corresponding discrete fracture toughness value; for each layer of scratch, determining the curve of the change of fracture toughness with scratch displacement based on the discrete horizontal displacement data and the discrete fracture toughness value, and calculating the average fracture toughness of all discrete points within the range of each layer of scratch; calculating the difference between the average fracture toughness of two adjacent layers, and determining that the soft and hard rock interface has been reached when the difference between the average fracture toughness of two adjacent layers is not greater than a first preset threshold; and calculating the thickness of the soft rock area according to the total number of scratches and the single-layer scratch depth when the soft and hard rock interface is reached. The application can realize efficient and high-precision quantitative measurement of the thickness of the soft rock area.