53 results about "Quantitative methodology" patented technology

The invention relates to novel expiration detection equipment based on the quantitative analysis method, and the novel expiration detection equipment is applied to the fields of human health assessment, disease screening, clinical diagnosis and the like. The expiration diagnosis is an emerging in-vitro diagnosis method, the clinical application range of the expiration diagnosis is gradually expanded, real-time and on-line detection of human expiration is achieved, a quantitative method for markers in expiration is established, reliable endogenous marker experimental data is obtained, a human expiration marker data model is constructed, and the real-time detection of the human expiration is achieved. Powerful support can be provided for exhaled air physiology research, clinical application of exhaled air diagnosis and environmental exposure research. And quantitative analysis is carried out on healthy people and sick people in different areas, and hit rules of different people are set according to weight values, so that the accuracy of quantitative analysis is improved, and the requirement on the computing power of data analysis is reduced.

The invention belongs to the technical field of traditional Chinese medicine quality control, and particularly relates to a phyllanthus emblica quality grading method based on pharmacodynamic theory, which comprises the following steps: S1, identifying a phyllanthus emblica liver protection quality marker group; s2, performing one-time quantitative analysis on the phyllanthus emblica quality marker group; s3, constructing an emblic leafflower fruit quality grading model; and S4, application of the emblic leafflower fruit quality grading model. According to the invention, by combining mass spectrometry and network analysis, six mass markers with liver protection activity in phyllanthus emblica are excavated for the first time; the established quality marker quantitative method is good in specificity and high in accuracy; the obtained grading model is excellent in effect, the phyllanthus emblica medicinal material can be divided into three grades according to the liver protection activity of the phyllanthus emblica, the problems of high subjectivity and poor traceability of an existing shape-distinguishing and quality-discovering evaluation standard are solved, establishment of a high-quality and high-price system of the phyllanthus emblica medicinal material is promoted, and high-quality development of the traditional Chinese medicine industry is promoted.

The invention relates to a high-coverage quantitative analysis method of lipidome and a quantitative kit, the method adopts a mobile phase A and a mobile phase B with different pH values for elution, the pH value of the mobile phase B is 2.5-5, and the pH value of the mobile phase A is 2.5-3.0. According to the method, good separation of acid-sensitive lipid compounds such as PA, S1P and PS can be realized, ionization inhibition of lipid compounds such as free fatty acid and free cholesterol can be reduced, and the quantitative sensitivity of the lipid compounds can be improved. According to the method, 104 lipid subclasses can be covered, 2375 lipid compounds can be quantified, and the number of the lipid compounds is more than two times that of the lipid compounds in the existing lipidomics quantitative method. The lipidome quantitative kit can be used for quantitatively analyzing lipidomes of seven biological samples such as plasma, urine, cells, liver and excrement of human or animal sources as well as escherichia coli and arabidopsis rosette leaves, and can meet quantitative analysis requirements of lipidomes in different biological samples.

The invention discloses a drug mixture trace impurity identification and quantification method based on deep learning, and the method comprises the steps: collecting the spectral data of a target drug mixture, and carrying out the preprocessing of the spectral data; training the spectral data through an improved YOLOv8 deep learning algorithm which performs dynamic adjustment according to the spectral data through a convolution kernel, and evaluating a deep learning model obtained according to the improved YOLOv8 deep learning algorithm through a cross validation method. And performing impurity identification and quantitative analysis on the to-be-detected sample by using a deep learning model of which the evaluation result meets a preset condition, and performing dynamic convolution adjustment by aiming at a convolution layer according to a drug feature corresponding to input spectral data in the training and detection process. The deep learning model can better adapt to different morphological characteristics of drugs, and the recognition and quantification precision of trace impurities is improved.

This disclosure provides methods and apparatus for generating training data, training machine learning models, and analyzing biological samples. Generating training data includes: acquiring a first image of a biological sample; generating a first set of annotations for the first image based on a second image of the biological sample stained by a quantitative method that converts antibody / antigen complexes into dots; and outputting the first image and a benchmark truth including the first set of annotations as data for training a first machine learning model (“ML”) to analyze the biological sample. Furthermore, the generated (output) training data can then be used to train the ML model, and the trained ML model can be used to analyze the biological sample.

The invention discloses a small and medium-sized enterprise digital transformation method based on SEM and fsQCA. The method comprises the following steps: obtaining samples and data of a target industry; a quantitative method is adopted through questionnaire survey, and variables are quantified by adopting a Like five-point scale; symmetrical and asymmetrical modeling is carried out on the measuring scale; carrying out comprehensive inspection and evaluation analysis on the proposed model; the enterprise digital transformation method has the beneficial effects that the organization phenomenon is understood in detail by integrating symmetric and asymmetric statistical tools, that is, SEM and fsQCA methods are integrated, so that small and medium-sized enterprises are helped to realize digital transformation, the possibility and interaction of organizations can be deeply informed, and the transformation efficiency is improved. The inherent limitation related to a symmetric method is solved, small and medium-sized enterprises, policy formulators and employees are guided to promote sustainable development practice by using digital technology, dynamic ability and a digital platform, and transition of the small and medium-sized enterprises from a simulation process to a digital process is promoted.

The invention provides an automatic migration rate quantification method for a mesenchymal stem cell scratch experiment. In order to solve the problems of fuzzy cell scratch boundary, low contrast, irregular form and difficulty in automatic migration rate quantification, the method comprises the following steps: firstly, constructing a mesenchymal stem cell (MSCs) scratch microscopic image data set, and carrying out gray scale and contrast enhancement on an original RGB image; and then, automatic segmentation of the scratch and the cell region is realized by utilizing a high-low frequency feature decoupling network, and quantitative analysis of the end-to-end mobility is realized by combining time sequence mask alignment, initial scratch region identification and scratch area measurement at each time point. The method supports batch processing of images at multiple time points, provides a high-precision, automatic and visual mobility analysis means, and can be widely applied to mesenchymal stem cell migration behavior research and regenerative medicine experiments.

The invention discloses a quantitative method of a high-concentration target compound and belongs to the technical field of sample detection. The quantitative method comprises the following steps: (S.1) obtaining a corresponding relation between the concentration of a target analyte and the ion signal response intensity for fitting to obtain a quantitative model; (S.2) fitting signal response intensity data obtained by the target compound with gradient concentration according to primary reaction kinetics to obtain a quantitative model; and (S.3) through detection, substituting the sum of ion signal intensities of all products obtained by ionization of a target compound into the quantitative model to obtain a concentration parameter so as to realize quantification. The quantitative method provides a chemical kinetics modeling method for fitting a nonlinear quantitative curve in a wide analyte concentration range for various analytical instruments. The method is not only suitable for a target compound which only generates monomer product ions, but also suitable for a target compound which simultaneously generates monomer product ions and polymer product ions, so that the quantitative capability of an analytical instrument on a target analyte with unknown concentration is greatly improved.

The application discloses a kind of based on multi-feature fusion and model learning's electromagnetic detection defect qualitative and quantitative method, builds multi-modal electromagnetic detection system, acquires the multi-frequency eddy current of measured component / multi-channel magnetic flux leakage signal and lift-off data, after adaptive denoising, interference suppression and normalization preprocessing, extract four categories 44-dimensional multidimensional features, obtain optimal feature subset by three-level screening strategy;Adopt channel attention and cross attention mechanism to realize multi-feature adaptive fusion, build "shared backbone+double branch" dual-task joint learning model, complete transfer pre-training, fine-tuning and lightweight compression;Finally output defect qualitative and quantitative results, support dual-technology result fusion and risk rating.The application realizes the full-depth coverage detection of special equipment metal components from surface to middle-deep defects, qualitative classification accuracy is greater than or equal to 98%, depth quantitative average relative error is less than or equal to 5%, single-frame inference time is less than or equal to 10ms, which can be directly deployed on handheld devices to realize real-time detection on site.

The invention discloses a metagenome activity quantification method based on an exogenous artificially synthesized endogenous reference gene and application of the metagenome activity quantification method, and relates to the technical field of biology. According to the invention, an endogenous reference gene as shown in SEQ ID NO.1 is firstly designed, and the endogenous reference gene has no homology with an existing organism and can realize homology interference. On the basis, a metagenome activity quantitative method is further designed, and the core thought of the metagenome activity quantitative method comprises the following steps: providing an artificially synthesized vector containing an endogenous reference gene, setting the artificially synthesized vector as a standard system with gradient concentration, and adding the standard system into a sample to be detected; before addition, a to-be-detected sample is pretreated through light-sensitive DNA combined with dye so as to shield dead bacteria DNA interference, then nucleic acid extraction, library construction and sequencing are carried out, and metagenome activity quantification is obtained through bioinformatics analysis and calculation. According to the method, homology interference is eliminated from the source, absolute quantification of microbial activity is realized, the stability and standardization degree of an internal standard are improved, and the method is suitable for quantitative analysis of metagenomes in various scenes.

The invention discloses a polyunsaturated lipid carbon-carbon double bond isomer quantification method and system, and relates to the technical field of quantitative analysis, and the method comprises the following steps: collecting a lipid sample, and identifying the diagnosis ion strength of C = C in polyunsaturated lipid; according to a dynamic association algorithm, establishing a relationship between the C = C isomer of the polyunsaturated lipid and the diagnostic ion strength; using a polyunsaturated lipid standard substance to obtain a diagnostic ion strength deviation coefficient caused by a liquid chromatography-mass spectrometry method at different positions C = C; and based on the deviation coefficient and a dynamic association algorithm result, carrying out deconvolution on the diagnosis ion strength to obtain the C = C isomer strength of the polyunsaturated lipid. According to the method, a C = C isomer quantification method based on C = C diagnosis ions is optimized, the strength deviation caused by a derivation method or secondary mass spectrometry fragmentation efficiency is calibrated by associating the strength of a plurality of C = C diagnosis ions and performing deconvolution calculation, and accurate quantification of the polyunsaturated lipid C = C isomer is realized.

The application discloses a large-scale mass spectrometry queue-oriented joint alignment and quantification method, relates to the cross field of bioinformatics, artificial intelligence and high-performance computing, and outputs a quantitative feature matrix through an end-to-end deep learning network; wherein, in a unified back propagation process, the end-to-end deep learning network synchronously optimizes the retention time alignment, the cross-batch intensity drift correction and the quantitative regression based on a joint loss function, the application regards the retention time alignment, the cross-batch intensity drift correction and the quantitative regression as a whole joint operation instead of linearly performing the operations one by one, and overcomes the defects of the step-by-step strategy in the prior art.

The present application relates to the technical field of elemental analysis detection, and particularly relates to an accurate non-calibration quantitative method based on automatic recognition and matching of different substrates, comprising: detection; acquiring actual fluorescence intensity and an actual spectrum diagram, and determining the type of main dark matter; determining the corresponding diagram of the current detection sample and selecting a corresponding non-calibration quantitative model; acquiring a simulation diagram; calculating the similarity of the simulation diagram and the actual spectrum diagram, if the similarity is greater than a similarity threshold value, outputting each content in the sample, if the similarity is less than or equal to the similarity threshold value, outputting new each element content, and re-performing full spectrum matching of the simulation diagram and the actual spectrum diagram until the matching result converges. By constructing a diagram library, the change trend of the actual measurement diagram and the simulation diagram is compared, so that the condition that the same matter is determined as different matters due to the pure comparison of the similarity is avoided, the error caused by the wrong model is avoided, and the accuracy of the non-calibration quantification is increased.

The application relates to the technical field of SCGD-OES online detection, and specifically provides a multi-element online quantitative method, system, equipment and medium of a high-salt matrix solution, which comprises the following steps: synchronously collecting multi-modal data; constructing a state vector according to the multi-modal data; calculating a stability index through robust principal component analysis and Mahalanobis distance; combining with working condition parameters to distinguish the working condition and the stability state; and adaptively selecting a quantitative analysis mode; under the working condition constraint, inputting spectral line characteristics into a segmented weighted least square regression model which is fused with monotonicity constraint, multi-spectral line consistency and self-absorption / quenching penalty term, compensating for the matrix effect and calculating the concentration; and finally, fusing the stability index, spectral line consistency deviation and model residual error to calculate the comprehensive confidence, and outputting the concentration and the confidence. The application improves the accuracy, robustness and result reliability of multi-element online analysis under high-salt, dynamic and nonlinear complex working conditions.

The invention discloses a quantitative analysis method suitable for black sesame melanin in a complex matrix sample, and belongs to the technical field of food quality control and chemical analysis. According to the invention, black sesame melanin is subjected to oxidative cracking, so that four characteristic degradation products, namely 2-oxo-2, 3-dihydrobenzo [d] oxazole-6, 7-dicarboxylic acid, 4-hydroxyphthalic acid, 3-methoxy-4-hydroxyphthalic acid and 4-hydroxy-5-methoxyphthalic acid, are confirmed for the first time. The invention expands the new application of the four chemical components in the quantitative analysis of the black sesame melanin, and also develops a quantitative analysis method of the black sesame melanin. The method is accurate and good in repeatability, solves the problems that a traditional quantitative method is large in matrix interference and insufficient in specificity, can be applied to a complex food matrix system, and has good application prospects and value in the technical fields of food quality control and chemical analysis.

The invention discloses a method for establishing andrographis paniculata quality control by using a QAMS (quantitative analysis of multi-components by single marker) method. Comprising the following steps: preparing a test sample solution, preparing a reference solution, determining chromatographic conditions and mass spectrum conditions, determining main components of a test sample, establishing a standard curve, performing methodological investigation by using an external standard method, determining an internal reference and a relative correction factor of the quantitative analysis of multi-components by single marker, and investigating the durability of the relative correction factor and positioning of a chromatographic peak. And comparing and verifying the content of the measured sample. The invention further discloses an andrographis paniculata quality control method. According to the method, relative correction factors of an internal reference substance and other to-be-detected components are established on the basis of an ultra-high performance liquid chromatography-tandem mass spectrometry-based quantitative analysis of multi-components by single marker, and the contents of four components including desoxidized andrographolide, andrographolide, dehydroandrographolide and andrographolide in andrographis paniculata are determined as a quality control method of the andrographis paniculata medicinal material, so that the quality of the andrographis paniculata medicinal material is improved. The calculated value and the measured value meet the requirements of quantitative methodology, the requirements of reference substances are reduced, and the quality control level of andrographis paniculata is improved.

The invention discloses a stage-by-stage dynamic flood control water level regulation and control method suitable for a hydropower station, and the method comprises the steps: obtaining watershed hydro meteorology, engineering operation and topographic geology multi-source basic data, and carrying out the Spark distributed cleaning, wavelet denoising and GAN missing value complementation preprocessing, thereby forming a standardized data set; an optimal flood season staging scheme is screened through coupling of qualitative analysis and a quantitative method; then, the safe pre-discharge amount and the effective pre-discharge time serve as sensitive factors, a flood control water level dynamic control model is built in combination with fuzzy mathematics and Copula joint distribution, and flood control water level process lines and regulation and control domain values of all flood season stages are generated; the safety of a regulation and control threshold value is verified through finite element simulation and a two-dimensional hydrodynamic model, a regulation and control scheme meeting flood control safety and efficient utilization of water resources is output, dynamic and accurate regulation and control of the flood control water level of the hydropower station are achieved, and the problems that in traditional static flood control water level dispatching, the contradiction between flood control and benefit making is prominent, the staging precision is low, and safety verification is insufficient are solved.

This invention provides a method for quantitative analysis of intracellular lipid content based on the Bodipy 493 / 503 fluorescent probe, relating to the field of lipid metabolism detection technology. The method includes: (1) determining the absorption spectrum and excitation / emission spectrum of Bodipy 493 / 503 in isopropanol, and determining the maximum absorption wavelength and maximum excitation / emission wavelength of the fluorescent probe in isopropanol based on the spectral results; (2) staining the target cells with the Bodipy 493 / 503 probe after treatment with the compound, observing the changes in fluorescence signal in the field of view before and after isopropanol extraction, and taking pictures; (3) measuring the absorbance and fluorescence intensity of the isopropanol extract, analyzing the experimental results, and comparing them with the results of triglyceride content detection. This quantitative method is simple, fast, sensitive, effective, and has good experimental controllability and repeatability. The analytical results obtained are consistent with those obtained using other lipid content analysis methods, and it can be of great application in the field of research on the lipid metabolism interference effects of chemicals or environmental pollutants.

The invention discloses a quantitative method of SRBSDV based on rice infected tissue transcriptome sequencing. The quantitative method comprises the following steps: 1) acquiring genome assembly and gene annotation files of SRBSDV virus and high-throughput transcriptome sequencing original data of rice infected virus tissue; (2) constructing an SRBSDV virus genome index module; 3) obtaining the non-redundant length of each gene in the SRBSDV virus genome annotation file; 4) obtaining high-quality transcriptome sequencing data; 5) obtaining the total number of short reading lengths of each sample in the step 4); 6) obtaining a BAM file of an individual level; (7) obtaining the original expression quantity of different genes of the virus in each sample; and 8) obtaining a gene expression quantity standardization function FPKB. By means of a standardized bioinformatics analysis framework, the virus infection level can be evaluated more accurately; and more virology information can be mined, the maximization of data utilization is realized, support is provided for virus research and prevention and control, and the accuracy of virus quantification is improved.

This application discloses a quantitative method for evaluating the data quality of a disease registration database, the method comprising: obtaining a data dictionary and a backup data set of a disease registration database; referring to the description and method of the medical database data quality evaluation in previous literature, this patent defines at least five dimensions to quantitatively evaluate the data quality of the disease registration database, the dimensions at least including: the corrected disease registration database case volume, the number of variables collected by the disease registration database data, the case data integrity, the case data reliability, and the annual follow-up completion rate; based on the combination of the five dimensions, a data quality evaluation index and its calculation formula are defined, and the data quality of the disease registration database is comprehensively evaluated based on the data quality index. This application is beneficial to cancer research based on databases, and can systematically and flexibly evaluate different databases, improve the effectiveness and comparability of databases, and promote their optimal use.

The invention discloses a quantitative internal reference combination system in a multiple amplification system, a detection method and application. The quantitative internal reference combination system comprises a plurality of internal reference genes, each internal reference gene comprises an upstream primer binding region, a variable sequence, a fixed sequence and a downstream primer binding region, the internal reference genes have different copy number gradients, and the variable sequences of the internal reference genes are different. The method is used for quantitatively detecting pathogenic microorganisms in a multiple amplification system, has double functions of quantifying and monitoring the amplification system, and ensures that the amplification efficiency of different internal reference sequences is consistent by designing and screening internal reference; the quantitative method is accurate in quantification, overcomes the defect that different amplification systems have different amplification coefficient differences, and ensures the quantitative accuracy.

The invention relates to the technical field of elemental analysis and detection, in particular to an accurate non-standard quantification method based on automatic identification and matching of different matrixes. Acquiring actual fluorescence intensity and an actual spectrogram, and determining the types of main dark substances; determining a map corresponding to the current detection sample and selecting a corresponding non-standard quantitative model; acquiring a simulation map; and calculating the similarity between the simulated spectrum and the actual spectrum, if the similarity is greater than a similarity threshold value, outputting each content in the sample, if the similarity is less than or equal to the similarity threshold value, outputting new content of each element, and carrying out full-spectrum matching on the simulated spectrum and the actual spectrum again until a matching result is converged. By constructing the atlas database and comparing the change trend of the actually measured atlas and the change trend of the simulated atlas, the situation that the substances are judged to be different substances when the same substances and different contents are caused by pure similarity comparison is avoided, errors caused by using wrong models can be avoided, and therefore the accuracy of non-standard quantification is improved.

The invention discloses a rapid nondestructive component quantitative analysis method and system for an aqueous film-forming foam extinguishing agent, and relates to the technical field of near-infrared spectroscopic analysis, and the method comprises the following steps: obtaining near-infrared original spectrograms of an aqueous film-forming foam extinguishing agent standard sample, deionized water and a sample to be detected, and carrying out smooth pretreatment; pre-treatment spectrograms of the standard sample, the deionized water and the sample to be detected are obtained; performing variance correction on the basis of the preprocessed spectrogram of the standard sample and the preprocessed spectrogram of the deionized water to obtain a new standard sample near-infrared absorption spectrogram, spectrograms of the aqueous film-forming foam extinguishing agents with different fluorocarbon surfactant contents and a corrected spectrum of the sample to be detected; and establishing a component quantitative analysis model according to the aqueous film-forming foam extinguishing agent spectrogram, and inputting the corrected spectrum of the sample to be detected into the component quantitative analysis model to obtain the content of each component in the sample to be detected. The method for quantifying the components of the foam extinguishing agent provided by the invention has the characteristics of rapidness, simplicity, convenience and low cost.

The invention relates to the technical field of medicine crystal form quantification, in particular to a specific characterization method of a medicine crystal form quantification method, which is characterized in that a characteristic derivative spectrum is compared with a regression coefficient curve of a quantitative model, and near-infrared absorbance data is multiplied by a correlation multiple suitable for drawing when a graph is drawn. According to the technical scheme, the mode that the characteristic derivative spectrum is compared with the regression coefficient curve of the quantitative model is adopted, the near-infrared absorbance data is multiplied by the correlation multiple suitable for drawing when the graph is drawn, the characteristic wave number range can be accurately judged, and specificity judgment is visual and reliable.

Methods and systems are described of a stochastic quantitative approach (StochQuant) that uses molecular counts obtained from a testing measurement, an absolute anchoring measurement of a reference molecule, and possibly additional physical parameters such as quantitatively measurable amounts of a sample, to identify a probability distribution, a confidence interval and / or a confidence level in outcome of a testing measurement of a target molecule, thus improving reliability and accuracy of quantitative detection of the target molecule performed by the testing measurement.

The invention relates to a quantitative method for whey protein in milk and dairy products, which comprises the following steps: preparing samples including liquid dairy products and solid dairy products; quantitative detection is carried out, and analysis is carried out by combining a capillary electrophoresis system CEInfinite with an acrylamide derivative AD coating capillary column; according to the method verification, reproducibility on the same batch of AD and different batches of AD coating capillaries is compared, and then repeatability summary of isoelectric points and peak areas is obtained; and obtaining a result. According to the method disclosed by the invention, high-efficiency separation and simultaneous quantitative analysis of alpha-lactalbumin, beta-lactoglobulin A and beta-lactoglobulin B in whey protein in dairy products are rapidly realized by using full-column imaging capillary isoelectric focusing electrophoresis (icIEF) and acrylamide derivative AD coating capillary; the method has important significance in promoting scientific research, new product development and the like while guaranteeing the product quality, protecting the health of consumers and optimizing the production process.

The subject matter described herein includes computational methods, systems and non-transitory computer readable media for de-novo drug discovery, which is based on deep learning and reinforcement learning techniques. The subject matter described herein allows generating chemical compounds with desired properties. Two deep neural networks-generative and predictive, represent the general workflow. The process of training consists of two stages. During the first stage, both models are trained separately with supervised learning algorithms, and during the second stage, models are trained jointly with reinforcement learning approach. In this study, we conduct a computational experiment, which demonstrates the efficiency of proposed strategy to maximize, minimize or impose a desired range to a property. We also thoroughly evaluate our models with quantitative approaches and provide visualization and interpretation of internal representation vectors for both predictive and generative models.

The present invention is a quantifying method by which a sample containing an analyte is quantified for the analyte, the method including steps of: (1) measuring the same sample a plurality of times by using a measurement apparatus to obtain a plurality of quantitative values of the analyte in the sample; and (2) calculating an amount of change in the analyte derived from the measurement apparatus from the plurality of the quantitative values, and correcting at least one of the plurality of the quantitative values with the amount of change to obtain a true quantitative value of the analyte. This provides a method for more accurately quantifying an analyte in a measurement system in which an amount of the analyte increases or decreases in a measurement apparatus during measurement of the sample.

The present disclosure provides a quantification method, an analysis system, and a program product for quantifying a specific component contained in a measurement sample. The quantitative method comprises the steps of: acquiring a measurement spectrum at each of a plurality of time points by analyzing a measurement sample by chromatography; deriving an index value for each of the plurality of time points by applying a filter for extracting a specific component to the measurement spectrum for each of the plurality of time points; a chromatogram obtaining step for obtaining a chromatogram by arranging, in the time direction, the index values for each of the one or more time points; and quantifying the specific component from the peaks of the chromatogram.