A data processing method for separating peaks of a plurality of components overlapping on a chromatogram from each other using actual data of a three-dimensional chromatogram including a chromatogram and a spectrum acquired by chromatographic analysis on a sample. The data processing method includes an adjustment target peak acquisition step of obtaining a plurality of adjustment target peaks by applying, to the chromatogram, a peak model function prepared in advance to approximate a waveform of the chromatogram, and an adjustment target peak adjustment step of setting a plurality of the adjustment target peaks obtained in the adjustment target peak acquisition step as initial values before adjustment, and repeating adjustment of the adjustment target peaks until pseudo data of a three-dimensional chromatogram on the sample obtained by combining the adjustment target peaks after adjustment is similar to the actual data.

An analysis assistance device includes an estimator that estimates a distribution of measurement quality indicator data using a regression analysis by using a plurality of analysis condition data pieces provided to an analysis device and a plurality of measurement data pieces obtained by the analysis device based on the plurality of analysis condition data pieces, an analysis assistance information displayer that displays the distribution on a display, and a saver that saves an analysis condition data piece of a point of interest designated in the distribution in a storage device in response to a saving operation.

A first analysis step of acquiring a three-dimensional chromatogram of at least one sample by executing, for the sample, first chromatography analysis using a photodiode array under a condition that a plurality of components contained in the sample can be separated from each other, and extracting spectrum data of each of a plurality of the components contained in the sample from the three-dimensional chromatogram of the sample, a second analysis step of executing second chromatography analysis using a photodiode array on another sample whose main component is the same as that of the sample under a condition that a three-dimensional chromatogram can be obtained in a shorter time than the first chromatography analysis to acquire a three-dimensional chromatogram of the another sample, and a peak separation step of acquiring peak separated data for the another sample in which peaks of a plurality of components contained in the another sample are separated from each other are included by applying peak separation processing based on the spectrum data extracted in the first analysis step to the three-dimensional chromatogram of the another sample acquired in the second analysis step.

The invention specifies an apparatus for evaluating sensor measured values (1.1), having: —a sensor (1), wherein a model function that is suitable for a least squares regression and definable by a parameter vector is provided for evaluating the sensor measured values (1.1) of the sensor (1), wherein at least one parameter of the parameter vector forms a sensor output signal (3), and —a computing and evaluation unit (2) that has a neural network (2.1), which estimates the parameter vector on the basis of actually ascertained sensor measured values (1.1), and a least squares regression module (2.2), wherein the neural network (2.1) is trained with parameter vectors and the associated sensor measured values, and that is set up: .sup.∘—to use the trained neural network (2.1) to ascertain at least one parameter estimate vector for sensor measured values (1.1) measured using the sensor (1) as an input variable for the least squares regression module (2.2), .sup.∘—if a convergence criterion is satisfied for the performance of the least squares regression, to terminate the least squares regression and .sup.∘—to output the at least one parameter of the most recently ascertained parameter vector as sensor output signal (3). An associated automated method for evaluating sensor measured values and a use of the apparatus are likewise specified.

The present solution describes an automated system for analyzing analytical gels or blots, such as electrophoresis gels. The system can automatically detect the lanes within the gel and convert the lane into a feature vector that can be compared to reference datasets. Based on a comparison of the feature vector to the reference datasets, the system can automatically classify the feature vector (and the test sample in the lane) into a phenotype group.

A system and method for determining an efficiency of gas extraction. A chamber allows inflow and outflow of the drilling fluid. An amount of gas extracted from a drilling fluid flowing through the chamber at a constant rate during a dynamic process is measured. A dissolution curve is obtained indicative of a gas remaining in the chamber after the dynamic process. An amount drawn from the chamber during a static process subsequent to the dynamic process is measured. An amount of gas from the drilling fluid during the static process is determined from a difference between the amount of gas drawn from the chamber during the static process and an amount of gas indicated by the dissolution curve. The gas extraction efficiency is determined from a ratio of the amount of gas extracted during the static process and the amount of gas extracted during the dynamic process.

A system and a method are provided for calculating one or more indicative properties, e.g., one or more of the cetane number, octane number, pour point, cloud point and aniline point of oil fractions, from the density and high pressure liquid chromatography (HPLC) data of a sample of the crude oil.

An analytical system comprises a chromatography column configured to separate a sample into one or more analytes; an ion removal device configured to remove at least ions of one charge from the mobile phase, the ion removal device fluidly coupled to an output of the chromatography column; an ion selective sensor configured to measure a signal corresponding to an activity of the ions of one charge in the mobile phase, the ion selective sensor fluidly coupled to an output of the ion removal device; an optional diverter valve that can interrupt the flow of the mobile phase; and a microprocessor configured to monitor the signal of the ion selective sensor and to either switch the optional diverter valve to interrupt the flow of the mobile phase or turn off the pump when the signal is greater than a predetermined threshold.

An analysis data processing method for processing analysis data collected with an analyzing device for each of a plurality of samples, by applying an analytical technique using statistical machine learning to multidimensional analysis data formed by output values obtained from a plurality of channels of a multichannel detector provided in the analyzing device, the method including: acquiring a non-linear regression or non-linear discrimination function expressing analysis data obtained for known samples; calculating a contribution value of each of the output values obtained from the plurality of channels forming the analysis data of the known samples, to the acquired non-linear regression or non-linear discrimination function, based on a differential value of the non-linear regression function or non-linear discrimination function; and identifying one or more of the plurality of channels of the detector, which are to be used for processing analysis data obtained for an unknown sample, based on the contribution value.

As a technique for separating odorous compounds by using a supercritical fluid chromatograph, a method for separating an odorous compound is provided which includes a process of carrying a sample containing an odorous compound into a column filled with a packing material made of a polymer having an unsaturated hydrocarbon structure, by a flow of a mobile phase which is a supercritical fluid of a predetermined substance.