618 results about "Standard curve" patented technology

The invention provides an HCG and LH test paper identification method and system based on optical characteristics and a storage medium. The method comprises the following steps: firstly, collecting and generating a reflectivity curve of a test paper detection area and a quality control area; secondly, extracting a reflection characteristic value of a curve in a detection area for test paper validity verification, and entering a core identification stage if the test paper is qualified; preliminary judgment is carried out by calculating a similarity deviation value of a quality control area curve and an HCG / LH standard curve, when the deviation is significant, a preliminary recognition result is generated and enters a cross validation link, and a result is confirmed by comparing a reflection characteristic value with a dynamic threshold range; when the similarity deviation is not obvious or the cross validation is not passed, starting a pre-trained discrimination model to perform final arbitration; by constructing a quadruple judgment mechanism of validity verification, preliminary recognition, cross validation and model arbitration, the operation complexity and misjudgment risk of manual test paper type selection are overcome, and the automation degree of the detection process and the accuracy and reliability of the recognition result are improved.

The invention provides an aviation nacelle part waviness automatic detection and evaluation method, and belongs to the field of product production detection, and the method comprises the steps: carrying out the protocol scanning of part surface contour features, and obtaining the undistorted coordinate point discrete point cloud data of the actual surface contour; filtering the point cloud data; obtaining a piece of flattened deviation value discrete point cloud data; obtaining a flattened deviation value continuous curve by adopting a general standard curve reduction method; extracting waviness components, and obtaining a curve center line; obtaining a crest value and a trough value participating in calculation; and calculating the maximum wave amplitude, the waviness and the slope for evaluating the waviness by using the wave peak value and the wave trough value. According to the method, the relation between the minimum cut-off wavelength of the waviness and the sampling interval is stipulated, the undistorted reduction of the surface profile curve is ensured, the influence of non-waviness profile components in the digital evaluation of the waviness is eliminated through a combined calculation method, and the evaluation accuracy of the waviness of the aviation nacelle part is improved.

The invention relates to the technical field of new material detection, in particular to a copper foil coating content detection method. The method comprises the following steps: preparing a plurality of mixed standard solutions; the mixed standard solution comprises copper ions and at least one to-be-detected element ion; in the plurality of mixed standard solutions, the copper ion concentrations are the same and are first preset concentration values; measuring a plurality of mixed standard solutions, and establishing a standard curve between a theoretical value and a measured value of the ion concentration of each to-be-measured element; dissolving a plating layer on the surface of the to-be-detected copper foil by using nitric acid, and filtering to obtain a to-be-detected sample solution; adding copper salt into the to-be-detected sample solution to obtain a to-be-detected analysis solution; measuring the to-be-measured analysis solution to obtain the measurement concentration of each to-be-measured element ion; according to the measured concentration of each to-be-measured element ion and the corresponding standard curve, the corrected content of each to-be-measured element ion is obtained. The problem that an existing copper foil coating content detection method is low in detection accuracy is solved.

The invention relates to a method for detecting activity of gamma-polyglutamic acid hydrolase and application. The method comprises the following steps: (1) preparing an enzymolysis reaction solution and a blank reaction solution; (2) preparing an NAC / OPA mixed solution; (3) adding an NAC / OPA mixed solution into the enzymatic hydrolysis reaction solution to obtain a reaction solution to be detected; (4) drawing a standard curve by taking L-glutamic acid as a standard substance; and (5) detecting the fluorescence intensity of the blank reaction solution and the reaction solution to be detected by using a microplate reader, and then calculating the activity of the gamma-polyglutamic acid hydrolase according to the fluorescence intensity and the standard curve. The method for detecting the activity of the gamma-polyglutamic acid hydrolase is high in detection speed, detection of a single sample can be completed within 25 min, and nearly real-time process monitoring is achieved. And the method has the advantages of reliable detection result and high accuracy, can be used for monitoring the enzyme activity of the gamma-polyglutamic acid hydrolase in the gamma-polyglutamic acid preparation process in real time and guiding the optimization of the fermentation process, and has extremely high industrial application value.

The invention discloses a cast-in-place pile integrity detection method based on a heat conduction model, and relates to the technical field of cast-in-place pile detection. The method comprises the following steps: firstly, constructing a cast-in-place pile heat conduction characteristic template library comprising standard heat conduction curves corresponding to various integrity states, wherein each standard curve comprises a plurality of key temperature nodes; generating a comprehensive heat conduction curve by fusing the standard curves of the same type of integrity states; acquiring actual temperature monitoring data of the to-be-detected cast-in-place pile, selecting a corresponding comprehensive heat conduction curve, and extracting a reference heat conduction curve; marking abnormal conduction nodes in the reference conduction curve to obtain a corrected conduction curve; and establishing a heat conduction anomaly analysis model to verify and correct key temperature nodes of the conduction curve, determining defect nodes, generating an integrity report containing position information of the defect nodes, and completing detection. Various quality conditions of the cast-in-place pile can be covered, advantages and characteristics of curves are integrated, and detection errors and unnecessary links are reduced.

The invention discloses a microfluidic nitration reaction platform based on in-situ Raman and a reaction optimization method. The platform integrates a microreactor, an in-situ Raman detection module, a spectrogram processing and quantifying module, an experimental optimization module and a central control module, and is suitable for monitoring and optimizing complex reactions under a non-mutual solution phase plunger flow system. According to the method, an indirect hard modeling (IHM) method is used for processing an overlapped Raman spectrogram, a standard curve is combined for establishing a multi-component concentration prediction model, and high-precision quantification of reactants and products is realized. According to the platform, a Gaussian process model is combined with dynamics prior, a multi-target Bayesian optimization process based on expected hypervolume improvement (EHVI) is driven, and Pareto optimal conditions in a temperature and residence time space are effectively explored. The system has the functions of automatic focusing sampling, spectrogram real-time decoupling, concentration inversion and experimental condition decision making, and is suitable for intelligent reaction development and optimization in the fields of fine chemical engineering, high-throughput reaction screening and the like.

The invention discloses an AI-based press-fitting curve intelligent analysis and standard curve generation method and system, and relates to the field of press-fitting curve analysis, and the method comprises the steps: constructing an AI classification model and a training set; training an AI classification model by using the training set to obtain a trained AI classification model; performing quality classification on the training set by using the trained AI classification model to obtain a quality classification result; performing standard curve fitting on the press-fitting curve samples with normal quality classification results to obtain a standard curve; and performing quality classification on the to-be-analyzed press fitting curve by using the trained AI classification model to obtain a quality classification result of the to-be-analyzed press fitting curve. The AI intelligent classification diagnosis of the press-fitting curve to be analyzed is automatically realized, manual intervention is reduced, the judgment consistency is improved, and the classification accuracy is improved.

The invention discloses an online pre-column derivatization coupled liquid chromatography-mass spectrometry amino acid detection method, and relates to the technical field of analysis and detection, and the method comprises the following steps: obtaining a to-be-detected sample, and carrying out protein hydrolysis treatment to obtain hydrolysate; mixing the hydrolysate with a derivatization reagent, carrying out on-line derivatization reaction through multiple sections of reaction zones which are connected in series, and maintaining different pH environments in the reaction zones; an online detection unit is arranged at an outlet of the reaction zone to monitor the concentration of derivative products and adjust reaction conditions in real time; performing chromatographic separation on the derivative reaction liquid; switching an ion source ionization polarity mode according to an elution time window to carry out mass spectrometry detection; and substituting the mass spectrum response signal into the standard curve to calculate the amino acid concentration value. The method realizes automatic derivation and high-sensitivity detection of amino acid, and has the advantages of simplicity and convenience in operation, controllable reaction conditions and high detection efficiency.

The invention relates to the technical field of fluorescence detection, in particular to a three-dimensional fluorescence detection correction method based on double light sources, and the correction method comprises the following steps: obtaining double light source optical parameters, sample cell geometric parameters and original fluorescence intensity data, the geometric parameters of the sample pool comprise the length, width, height, pool wall reflection coefficient and sample attenuation coefficient of the sample pool; and constructing a light intensity distribution model in a three-dimensional space of the sample cell based on the optical parameters of the double light sources and the geometric parameters of the sample cell. According to the invention, accurate characterization of the light intensity of any spatial point in the sample cell is realized, light intensity deviation caused by various factors is quantified from the source, personalized correction is carried out on each spatial point, the influence caused by optical path difference at different positions, light source fluctuation and element error is effectively offset, and the accuracy and accuracy of the detection result are improved. The consistency of detection values of standard substances with the same concentration in different areas of the sample pool is greatly improved, and the linearity of a standard curve is remarkably optimized.

The invention relates to the technical field of process control, in particular to an injection molding process optimization method and device, computer equipment and a storage medium, and the method comprises the following steps: obtaining stress signals of four tie bars of an injection molding machine, calculating a total mold locking force, and preprocessing the stress signals through temperature compensation and moving average filtering; real-time mold cavity pressure is calculated based on a mold filling stage linear model, a pressure maintaining stage quadratic function model and a cooling stage exponential attenuation model triggered by an injection molding machine control signal; generating a standard curve template with a confidence interval according to the characteristic parameters of the qualified sample, and dynamically updating the standard curve template; and comparing the current pressure curve with a standard template output quality judgment result in real time, and triggering automatic parameter adjustment to form closed-loop control. The device and the method have the effect of solving the problems of high cost, poor compatibility and difficulty in maintenance when the pressure of the die cavity is directly measured.

The invention relates to the field of compound qualitative analysis, and provides an SERS statistical quantitative analysis method and system based on signal-to-noise ratio regulation, and the method comprises the following steps: carrying out SERS spectrum collection on target molecules with different concentrations on a reference batch SERS substrate through a point-by-point measurement method to obtain an original spectrum data set; on the basis of a multi-signal-to-noise-ratio standard, identifying characteristic peaks of the original spectrum data set to obtain a quantitative standard curve set; carrying out recovery rate verification on the quantitative standard curve set to obtain a verified standard curve set; and through the verification standard curve set, carrying out reverse derivation on the SERS detection rate of the target molecule with unknown concentration on the batch of SERS substrates to be detected to obtain a predicted concentration value of the target molecule. According to the invention, the dynamic range and precision of detection are expanded.

The invention provides a method for detecting the content of elements in carbonized resin. The method comprises the steps of resin pretreatment, instrument tuning, standard curve drawing, sample detection and the like. The method comprises the following steps: firstly, transferring a certain amount of dry carbonized resin into a cleaned PFA digestion tank, adding high-purity mixed acid, setting a segmented heating program to start microwave digestion, cooling to room temperature after digestion is completed, adding a proper amount of ultrapure water to dilute a digestion solution, and adding an internal standard solution and a chemical additive to obtain a to-be-detected sample solution; preparing a multi-element mixed standard solution according to the sample element types, adding the standard solution into the sample solution, and measuring the signal intensity ratio R of the to-be-measured element to the internal standard in each solution; and drawing a standard curve by taking the labeling concentration as a horizontal coordinate and R as a vertical coordinate, correcting the standard curve, and detecting the sample to be detected. The method is used for detecting the content of elements in carbonized resin, the carbonized resin is digested through microwaves, and the obtained solution is clear and can be directly subjected to ICP-OES (Inductively Coupled Plasma-Optical Emission Spectrometer) detection.

The invention relates to the technical field of organic fertilizer detection, and discloses a method for continuously detecting nitrogen and phosphorus in an organic fertilizer. The method comprises the following steps: acquiring an organic fertilizer sample to be detected, and crushing, homogenizing and filtering the sample through a pretreatment device to obtain a standard detection solution; introducing the standard detection liquid into a trace detection channel, and respectively determining absorbance values of the characteristic wavelength of the nitrogen element and the characteristic wavelength of the phosphorus element by adopting a spectral absorption method; generating an initial detection data set based on the absorbance value, and performing time sequence alignment processing on nitrogen element data and phosphorus element data in the set to form a synchronous detection data sequence; according to the synchronous detection data sequence, a standard curve database is called to match nitrogen and phosphorus concentration conversion parameters in the current detection environment, and a preliminary concentration calculation result is generated; environment temperature and humidity, reagent batches and equipment loss data in the historical detection records are extracted to serve as compensation coefficient input, and corrected nitrogen and phosphorus concentration values are output.

The invention discloses a primer and a method for quantitatively monitoring the biomass of sargassum hemiphyllum based on an environmental DNA technology, and belongs to the technical field of molecular ecology. The primer probe group comprises an upstream primer, a downstream primer and a fluorescent probe which are specifically targeted to the sargassum hemiphyllum mitochondria COX1 gene, and the sequence is shown as SEQ ID NO.1-3. The kit comprises the primer probe group, a qPCR (quantitative polymerase chain reaction) premixed solution, nuclease-free water and a sargassum hemiphyllum plasmid positive control. The method comprises the following steps: collecting a water sample, enriching eDNA, performing qPCR detection by using the primer probe group after extraction and purification, and realizing qualitative detection and quantitative evaluation of sargassum hemiphyllum through a Cq value or a standard curve. The method disclosed by the invention has the advantages of high sensitivity, strong specificity, no damage to the environment and target organisms, capability of realizing large-scale rapid general survey and the like, and is suitable for early warning of gulfweed blooms, investigation of population distribution and evaluation of ecological influence.

The invention belongs to the technical field of sewage heavy metal monitoring, and particularly relates to a sewage heavy metal concentration dynamic monitoring method and sensor based on image gray scale, and the monitoring method comprises the following steps: (1) establishing a database and a standard curve of image gray value and heavy metal concentration; (2) shooting a sewage sample image, synchronously collecting a standard color card during shooting, obtaining a sample-color card composite image, carrying out image recognition, and obtaining a sewage sample image gray value dynamically calibrated by the color card; and (3) substituting the image gray value into a standard curve of the image gray value and the heavy metal concentration or a database, and calculating the heavy metal concentration in the sewage. According to the invention, the cost is low, the heavy metal can be rapidly and dynamically monitored on line in real time by utilizing the image gray difference under different heavy metal concentrations and adopting machine vision correction, and the heavy metal pollution phenomenon can be found in time.

The invention discloses a method for detecting exogenous amylase derived from aspergillus in honey and application of the method. The method comprises the following steps: screening and determining a characteristic peptide fragment, pre-treating a sample, making a standard curve, separating by using liquid chromatography, detecting by using tandem mass spectrometry, and quantifying by using an internal standard method. The exogenous amylase characteristic peptide fragment derived from aspergillus is FASYTNDIALAK, and the specific peptide fragment derived from aspergillus is FASYTNDIALAK. The invention establishes a quantitative method for detecting the exogenous amylase derived from aspergillus in the honey by liquid chromatography-tandem mass spectrometry, and the quantitative method has better accuracy and sensitivity and is suitable for adulteration identification of the honey. The method has important practical significance for controlling the quality of honey and maintaining the healthy and sustainable development of the bee product industry.

The invention belongs to the field of antibiotic analysis and detection, and discloses a quinolone drug SERS (Surface Enhanced Raman Scattering) detection method based on an improved silver nano-substrate and a spectral angle matching model. An improved Lee-Meisel method is adopted to synthesize silver nano sol with precisely controlled particle size, molecular adsorption is realized by utilizing electrostatic interaction of a positively charged quinolone drug and negatively charged silver nano particles, and a high-density Raman enhanced hot spot is formed after an agglomeration agent is added; the SERS spectrum is collected at the excitation wavelength of 785 nm and the integral time of 10 s, qualitative distinguishing of drugs is achieved by combining a spectrum angle matching model, and quantitative detection is achieved by constructing a standard curve through the linear relation between the characteristic peak intensity and the drug concentration logarithm. The detection limit of the four drugs is as low as 1.03-1.16 ppb, the classification accuracy rate reaches 100%, the method is obviously superior to existing similar methods, the detection matrix range is wide, such as animal food and dairy products, and universality and high sensitivity are both considered.

The present application belongs to the technical field of copper foil oxidation resistance detection and analysis, and discloses a copper foil oxidation resistance detection method and system based on glossiness analysis, which comprises the following steps: obtaining a glossiness attenuation standard curve of copper foil samples with different oxidation resistance grades; dividing the glossiness attenuation standard curve according to the inflection point position to obtain different oxidation stages and glossiness change ranges; obtaining a to-be-detected glossiness attenuation curve of the to-be-detected copper foil; obtaining a glossiness attenuation standard curve with the highest similarity to the to-be-detected glossiness attenuation curve among all the glossiness attenuation standard curves, and calculating the first defect influence degree of the to-be-detected copper foil at different oxidation stages according to the glossiness change range of the to-be-detected glossiness attenuation curve at the same oxidation stage; correcting the first defect influence degree to obtain the second defect influence degree, so as to calculate the final similarity between the to-be-detected glossiness attenuation curve and all the glossiness attenuation standard curves; and dividing the oxidation resistance grade of the to-be-detected copper foil according to the final similarity.

The invention discloses a combined determination method for the tin content of iron ore, which is characterized by comprising the following steps: drawing a calibration curve; selecting measurement parameters of an instrument; weighing a sample; sample melting: uniformly mixing the weighed sample with a mixed flux in a certain proportion, and melting in a muffle furnace; extracting a sample: extracting the fused sample by using hydrochloric acid, and fixing the volume for detection; and sample determination: determining by using an inductively coupled plasma emission spectrometer, determining the intensity value of each element by drawing a standard curve method, and calculating the final content of the element according to a calibration curve made by a standard solution. The invention aims to provide the combined determination method for the tin content of the iron ore, through experiments, the accuracy of determining the standard substance and the tin element of the tin-containing iron ore can be guaranteed, and through standard recovery experiments, the recovery rate is 95% or above. The method is used for production practice, and is an effective and practical method.

This invention relates to a fully automated rapid silicate concentration detection method, comprising: S1, establishing a standard curve based on a silicate standard solution; S2, performing fully automated rapid silicate concentration detection based on the standard curve; S1 includes: S11, preparing the standard solution; S12, performing automatic sample injection and detection; S13, signal acquisition and processing; S14, fitting the standard curve; S15, verifying and storing the standard curve; S16, performing anti-interference verification, including: adding interfering substances to the standard solution to verify the reliability of the curve; S2 includes: S21, performing range calibration using the standard solution before sample measurement, setting the photomultiplier tube's high voltage value to V1 to achieve the standard measurement range; S22, preparing reagent A (2% ammonium molybdate), reagent B (4% dilute sulfuric acid), and reagent C (basic luminescent agent) required for fully automated rapid silicate concentration detection; S23, performing fully automated rapid silicate concentration detection based on the standard curve. A corresponding fully automated rapid silicate detector is also disclosed.

This invention discloses an online pre-column derivatization coupled with liquid chromatography-mass spectrometry (LC-MS) for amino acid detection, relating to the field of analytical detection technology. The method includes: obtaining a sample for protein hydrolysis to obtain a hydrolysate; mixing the hydrolysate with a derivatizing reagent and performing an online derivatization reaction through multiple reaction zones arranged in series, each zone maintaining a different pH environment; setting an online detection unit at the reaction zone outlet to monitor the concentration of the derivatized product and adjust the reaction conditions in real time; performing chromatographic separation of the derivatized reaction solution; switching the ionization polarity mode of the ion source according to the elution time window for mass spectrometry detection; and substituting the mass spectrometry response signal into a standard curve to calculate the amino acid concentration value. This invention achieves automated derivatization and high-sensitivity detection of amino acids, with advantages such as simple operation, controllable reaction conditions, and high detection efficiency.

The application discloses a method for determining unbound concentration of lenvatinib, which comprises the following steps: sending standard curve working solution and quality control working solution into a liquid chromatography tandem mass spectrometry detection system to obtain a standard curve; adding a plasma sample into an ultrafiltration tube, centrifuging under the condition of a centrifugal force of 3000g for 15 min, and collecting an ultrafiltrate of the plasma sample; adding the ultrafiltrate of the plasma sample into blank plasma ultrafiltrate, mixing uniformly, taking supernatant into a collection plate, sending the collection plate into the liquid chromatography tandem mass spectrometry detection system to obtain a ratio of a peak area of lenvatinib to a peak area of an internal standard, and then bringing the area ratio into the standard curve to obtain the unbound concentration of lenvatinib in the plasma sample. The method for determining the unbound concentration of lenvatinib can accurately determine the unbound concentration of lenvatinib in plasma and overcome the prejudice of the prior art.

This invention belongs to the field of cable testing technology, specifically a method and system for testing cable cross-linking byproducts. The method includes: taking a structurally intact original sample of the cable and weighing its insulation layer; sealing the sample in an inert gas bladder to establish an inert environment; heating the sample at a constant temperature for an extended period to allow methane within the insulation layer to fully diffuse into the gas bladder; measuring the total volume of the gas bladder after heating and performing gas chromatography analysis to obtain the methane peak intensity; calculating the total methane mass in the gas bladder based on this intensity and a standard curve, and then calculating the cumulative methane release per unit mass of insulation material; finally, evaluating the cable degassing effect by comparing this release amount with a preset threshold. This invention, by simulating real diffusion kinetics, can effectively evaluate the thoroughness of deep degassing, providing a reliable means for process optimization and high-quality control.

The invention belongs to the technical field of medicine detection, and particularly relates to an ICPMS (Inductively Coupled Plasma Mass Spectrometry) detection method for element impurities in theophylline. The linear test solution, the blank solution and the theophylline test solution are subjected to ICPMS detection, the content of element impurities in the theophylline test solution is calculated according to an internal standard curve method, and the element impurities are one or more of cadmium, lead, arsenic, mercury, cobalt, vanadium, nickel, lithium, antimony or copper. The method is good in reproducibility and stability, high in accuracy and high in precision.

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 magnetic stimulation signal output method and device of magnetic stimulation equipment, a magnetic stimulation system and a computer readable storage medium, and the method comprises the steps: receiving a magnetic pulse output instruction, and at least obtaining a standard curve, a magnetic pulse output mode and a pulse set value according to the magnetic pulse output instruction; sampling the standard curve according to set sampling times to obtain sampling data; according to a magnetic pulse output mode, multiplying the pulse set value by each piece of sampling data to obtain pulse data of each magnetic pulse in the string magnetic pulse signal; wherein the pulse data is pulse frequency and / or pulse amplitude; and outputting each magnetic pulse of the string magnetic pulse signal according to the pulse data. According to the technical scheme, flexible and diversified change adjustment of the magnetic pulse signal can be realized, the problem of adaptive fatigue of human muscles and the like is effectively avoided, and the physiotherapy effect of the magnetic stimulation equipment is ensured.

The application relates to the technical field of zinc-aluminum coating detection, in particular to a method for rapidly detecting the contents of Zn, Al and Si elements in a zinc-aluminum coating; the method comprises the following steps: ultrasonic cleaning of the zinc-aluminum coating to be detected to obtain a pretreated sample; glow surface analysis of the pretreated sample by using a glow spectrum method, drawing of a horizontal and vertical coordinate graph, and obtaining of an Fe-h curve graph, a Zn-h curve graph, an Al-h curve graph and a Si-h curve graph; according to the curve graphs, the total mass of Zn, Al and Si is respectively calculated; the thickness of the zinc-aluminum coating to be detected is calculated by taking the Fe-h curve graph as a standard curve; according to the curve graphs and the thickness of the zinc-aluminum coating to be detected, the average mass of Zn, Al and Si is respectively obtained; and according to the average mass and the total mass, the average mass fraction of Zn, Al and Si is obtained. The method can avoid the substrate effect of the zinc-aluminum coating in the detection process, so that the accuracy of the zinc-aluminum coating detection is improved.

This invention discloses a method for determining the arsenic content in ores, belonging to the field of ore element detection technology, comprising the following steps: (1) weighing the ore sample, adding hydrochloric acid-nitric acid mixed acid for acid hydrolysis, then adding hydrofluoric acid and perchloric acid for auxiliary digestion, evaporating to near dryness, and dissolving the residue with hydrochloric acid; (2) adding a thiourea-ascorbic acid-citric acid mixed reducing masking agent to reduce and mask interfering ions; (3) using an atomic fluorescence spectrometer to determine the fluorescence intensity of arsenic in the sample solution, and calculating the arsenic content according to the standard curve. This method achieves accurate and stable determination of arsenic in various ores such as phosphate rock and iron ore by optimizing sample pretreatment conditions, improving the reduction system and matrix interference suppression strategy.

The invention relates to a separation qualitative and quantitative detection method for L-lactide, D-lactide and Meso-lactide, and belongs to the field of lactide optical purity detection.The separation qualitative and quantitative detection method comprises the following steps that firstly, various lactide standard curves of different configurations are established respectively, the concentration range of the standard curves is 10-1000 mg / L, and the concentration range of the standard curves is 10-1000 mg / L; the plurality of lactides with different configurations comprise one or more of L-lactide, D-lactide and Meso-lactide; and the lactide with different configurations comprises one or more of the L-lactide, the D-lactide and the Meso-lactide. 2, detecting by using a gas chromatograph-mass spectrometer, and quantitatively calculating a lactide substance to be detected, wherein the concentration range of the lactide substance to be detected is 200-1000mg / L; according to the invention, separation and quantitative detection of three lactide optical isomers are realized by using an analysis method; the influence of impurities in the to-be-detected substance of lactide on the accuracy of the quantitative result of lactide is reduced; qualitative and semi-quantitative information of the impurities in the to-be-detected substance is provided.

The invention relates to the technical field of biological analysis and detection, and particularly discloses a streptococcus mutans detection kit based on an anchored CRISPR-Cas12a enhanced paper-based micro-fluidic chip and a detection method. The detection kit comprises an RAA solution or RAA freeze-dried powder, magnesium acetate or a magnesium acetate solution, TMB or a TMB solution, an RAA forward primer, an RAA reverse primer, a cell lysis buffer, a buffer system and a paper-based micro-fluidic chip. The detection method comprises the following steps: establishing a standard curve and detecting a sample. The detection kit is used for detecting the content of streptococcus mutans and has the characteristics of high efficiency, rapidness, specificity, sensitivity, portability and the like, and the method is simple and convenient to operate, low in detection cost and capable of being applied to on-site detection of streptococcus mutans.