A method includes: performing a time-frequency analysis on measurement data to obtain waveform data representing a temporal change in the intensity of each of a plurality of frequency components; dividing the waveform data of each of a plurality of predetermined frequencies into a plurality of segments so that each section where positive values successively occur and each section where negative values successively occur in a time-axis direction are defined as one segment; calculating the area of each of the segments to obtain segment values; creating, for the waveform data of each of the predetermined frequency components, a selected segment group by excluding a segment whose segment value exceeds a predetermined reference value from the segments in the waveform data; and determining a noise level of each of the predetermined frequency components based on the average value of the segment values of the segments included in the selected segment group.

A method includes: performing a time-frequency analysis on measurement data to obtain waveform data representing a temporal change in the intensity of each of a plurality of frequency components; dividing the waveform data of each of a plurality of predetermined frequencies into a plurality of segments so that each section where positive values successively occur and each section where negative values successively occur in a time-axis direction are defined as one segment; calculating the area of each of the segments to obtain segment values; creating, for the waveform data of each of the predetermined frequency components, a selected segment group by excluding a segment whose segment value exceeds a predetermined reference value from the segments in the waveform data; and determining a noise level of each of the predetermined frequency components based on the average value of the segment values of the segments included in the selected segment group.

In a method for estimating a noise level representing the magnitude of a noise component from measurement data, first waveform data composed of high frequency noise components extracted from assumed noise data are divided into segments so that each section where positive values successively occur or each section where negative values successively occur in the first waveform data is defined as one segment. A segment-width threshold is determined based on the distribution of the widths of the segments. Second waveform data composed of high frequency noise components extracted from measurement data are divided into segments in the same manner. Each segment having a width larger than the threshold is excluded from the segments in the second waveform data, to create a first segment group. The noise level is determined based on the heights or areas of the plurality of segments included in the first segment group.

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 computer implemented method for identifying at least one peak in a mass spectrometry response curve is provided comprising: a) providing at least one mass spectrometry response curve by using at least one mass spectrometry device; b) evaluating the mass spectrometry response curve by using at least one trained model thereby identifying a start point and an end point of at least one peak of the mass spectrometry response curve, wherein the model was trained using a deep learning regression architecture.

The present disclosure relates to a method for determining a carry over of an analyte from a previous sample into a sample of interest on a liquid chromatography mass spectrometer (LC-MS) device, the method comprising the following steps: (a) determining at least one chromatogram of said sample of interest on said LC-MS device; (b) determining a background height of the chromatogram; and (c) determining the carry over of the analyte from said previous sample into the sample of interest based on the background height. The present disclosure also relates to methods, systems, and computer program products related to the aforesaid method.

A chromatograph mass spectrometer includes a measurement unit including a mass spectrometry unit capable of MS.sup.n analysis, and to separate sample components and repeatedly perform mass spectrometry, a chromatogram display processing unit to create a chromatogram at a specific m/z and display it, a time designation unit to designate a retention time according to a user operation, a spectrum display processing unit to create an MS spectrum corresponding to the retention time and an MS.sup.n spectrum, as an MS.sup.n analysis result corresponding to the retention time, targeting an m/z of a peak in the MS spectrum or an m/z range including the m/z, and display the MS spectrum and the MS.sup.n spectrum on the same screen, the time designation section designating a retention time by a user moving a pointer, and the spectrum display processing unit, updating the display corresponding to the retention time corresponding to the pointer position.

A chromatograph mass spectrometer includes a measurement unit including a mass spectrometry unit capable of MS.sup.n analysis, and to separate sample components and repeatedly perform mass spectrometry, a chromatogram display processing unit to create a chromatogram at a specific m/z and display it, a time designation unit to designate a retention time according to a user operation, a spectrum display processing unit to create an MS spectrum corresponding to the retention time and an MS.sup.n spectrum, as an MS.sup.n analysis result corresponding to the retention time, targeting an m/z of a peak in the MS spectrum or an m/z range including the m/z, and display the MS spectrum and the MS.sup.n spectrum on the same screen, the time designation section designating a retention time by a user moving a pointer, and the spectrum display processing unit, updating the display corresponding to the retention time corresponding to the pointer position.

A gas chromatograph is provided with: a sample gas generator; a separation column; a detector; a plurality of gas supply sources; a switching unit; a regulator-; and an out-of-gas determination unit. After the out of gas determination unit has determined that the out of gas has occurred in the gas supply source supplying the carrier gas to the sample gas generator, it is configured to perform a column protection operation for changing the gas supply source fluidly connected to the sample gas generator by the switching unit.

A methodology scales supercritical fluid chromatography (SFC) and/or carbon dioxide based chromatography methods between different system and/or column configurations. The methodology includes measuring an average mobile phase density during a first separation utilizing C02 as a mobile phase component and substantially duplicating the average density profile for a second separation. Substantial duplication of the average mobile phase density (e.g., within about 10%, 5%, 2.5%, 1%, 0.5%, 0.1 %, 0.05%) results in chromatography for both system and/or column configurations having similar selectivity and retention factors. Average mobile phase density may be, either measured directly, calculated, or approximated using average pressure or density measurements. The average pressure profile may be used as a close approximation to duplicate average density profiles between separations.