A chemical pattern recognition method for evaluating the quality of a traditional Chinese medicine based on medicine effect information, comprising: collecting chemical information of a traditional Chinese medicine sample, obtaining medicine effect information reflecting a clinical therapeutic effect thereof, performing spectrum-effect relationship analysis on the chemical information and the medicine effect information, and obtaining an index significantly related to the medicine effect as a feature chemical index; dividing the traditional Chinese medicine sample into a training set and a test set; using a pattern recognition method to extract a feature variable from samples of the training set by taking the feature chemical index as an input variable; building a pattern recognition model using the feature variable; and substituting feature variable values of samples of the test set into the model, and completing chemical pattern recognition evaluation of the quality of the traditional Chinese medicine. According to the method, chemical reference substances are not needed, the chemical pattern recognition model is built on the basis of the feature chemical index reflecting the medicine effect, the one-sidedness and the subjectivity of the existing standards are overcome, and a traditional Chinese medicine quality evaluation system capable of reflecting both the clinical therapeutic effect and overall chemical composition information is finally formed.

A method for measuring a proportion of sA1c (%), which includes, when a peak derived from abnormal hemoglobin D, abnormal hemoglobin S or abnormal hemoglobin C is identified, calculation of the peak area, and measurement of the proportion of sA1c (%) corrected by using the calculation results. Results of measurement are obtained, by cation exchange chromatography, of sA1c (%) with a subject who provided a blood sample containing abnormal hemoglobin D, abnormal hemoglobin S or abnormal hemoglobin C by eliminating influences by such abnormal hemoglobin.

Disclosed herein are chromatography instrument support systems, as well as related apparatuses, methods, computing devices, and computer-readable media. For example, in some embodiments, a chromatography instrument support apparatus may include: first logic to generate one or more peak locations for a chromatogram data set and to generate one or more baselines for the chromatogram data set, wherein an individual peak has an associated baseline, and wherein the first logic includes a machine-learning computational model that outputs estimated peak locations and estimated baselines; second logic to cause the display of the one or more peak locations and the one or more baselines concurrently with the display of the chromatogram data set; and third logic to, for individual peaks, generate an associated integrated value representing an area above the associated baseline and under a portion of the chromatogram data set corresponding to the individual peak.

A data processor (10) that performs data processing on a plurality of the chromatograms stored in the data storage part (8) is provided. The data processor (10) is capable of executing automatic identification for automatically performing identification processing. In the identification processing, one chromatogram among the plurality of the chromatograms is set as a reference chromatogram, a plurality of component peaks on the reference chromatogram is set as reference peaks, and it is identified which component peaks among component peaks on other chromatograms than the reference chromatogram among the plurality of the chromatograms corresponds to each of the plurality of the reference peaks. In the automatic identification, the data processor (10) is configured to identify component peaks corresponding to each of the reference peaks by executing filtering using a reference parameter for peak parameters of each of component peaks on the other chromatograms.

The present disclosure discusses a method of separating a sample (e.g., pharmaceutical drug, genotoxic impurity, biomarker, and/or biological metabolite) including coating a metallic flow path of a chromatographic system; injecting the sample into the chromatographic system; flowing the sample through the chromatographic system; separating the sample; and analyzing the separated sample using mass spectroscopy. In some examples, the coating applied to the surfaces defining the flow path is non-binding with respect to the sample—and the separated sample. Consequently, the sample does not bind to the low-binding surface of the coating of the flow path. The applied coating can increase the chromatographic peak area for the sample of the chromatographic system.

A method for scientific instrument support includes obtaining a chromatographic data. The method includes one of (a) calculating an intensity score for the chromatographic data and identifying an injection miss when the intensity score is below a score threshold or (b) applying a machine learning model to classify the chromatographic data. The method further includes notifying a user of an injection miss or injection error.

A composition comprising an ethylene/alpha-olefin interpolymer that comprises the following properties: a) a total unsaturation/1000C≥0.30; b) a molecular weight distribution (MWD)≤3.0; c) a TGIC broadness parameter B.sub.1/4≤8.0. A solution N polymerization process to prepare an ethylene/alpha-olefin/interpolymer, said process comprising polymerizing, in one reactor, at a reactor temperature ≥150° C., a reaction mixture comprising ethylene, an alpha-olefin, a solvent, and a metal complex as described herein. A method to determine the TGIC broadness parameter B.sub.1/x of a polymer composition comprising one or more olefin-based polymers.

A first liquid raw material and a second liquid raw material are reacted with each other by a reactor of a reaction device, so that a reaction product is produced. The reaction product is analyzed by an analyzer. In the controller, the reference value is acquired by the reference value acquirer from the chromatogram obtained from the result of the analysis by the analyzer. An upper limit value and a lower limit value with respect to the reference value are set by an allowable range setter. At least one of a residence time of the first liquid raw material, a residence time of the second liquid raw material, a reaction temperature, and a reaction pressure in the reactor is dynamically changed as a control target by a reaction controller such that the reference value falls between the upper limit value and the lower limit value.

A method for synchronizing data for gas samples with volatile organic compounds. The data includes chromatographic data indicative of molecule retention times. The method includes identifying or selecting marker molecules and clustering the plurality of gas samples into a plurality of clusters according to a clustering criterion. Next, a first correction of retention time deviations is performed on the data for the gas samples between clusters by using the marker molecules as anchor points to provide a coarse reduction of retention time deviations between the data. Finally, a second correction of retention time deviations is performed on the data, so as to further reduce retention time deviations between the data. The method reduces significant retention time deviations to allow, e.g., breath sample fingerprints obtained by different equipment at different times to be compared in one database for use on a digital platform.

An analysis method for analyzing a sample includes a first step of acquiring measurement data including a first signal based on the sample and a second signal based on noise added to the first signal as a result of analysis of the sample, a second step of assuming a shape representing the first signal and a shape representing the second signal and modeling the measurement data using Bayesian inference, and a third step of estimating a probability distribution of characteristics of the sample based on the modeled measurement data.