The present disclosure describes a method in which a sample is passed through a fluid flow path of a sensor assembly such that the sample intersects at least one sensor comprising at least three electrodes arranged such that two or more electrodes are opposing and two or more electrodes are beside one another. The sensor is read by a reader monitoring changes to the sensor due to the presence of the sample. The reader measures the presence and/or concentration of one or more analytes within the sample based upon data obtained by the reader.

An automatic analysis device has a plurality of types of photometers having different quantitative ranges, and an analysis control unit for quantifying the desired component in specimens based on measurement values of one or more photometers selected from among the plurality of types of photometers. The analysis control unit: sets a switching region in an overlap region of respective quantitative ranges of the plurality of types of photometers, said switching region having a greater width than does the variation in quantitative values of the desired component based on the measurement values of photometers having the same specimen; compares the quantitative value of a quantitative range portion that corresponds to the switching region and the quantitative values of the desired component based on the measurement values of the photometers; and selects a photometer to be used in quantitative output of the desired component from among the plurality of types of photometers.

An object recognition apparatus includes a first spectrometer configured to obtain a first type of spectrum data from light scattered, emitted, or reflected from an object; a second spectrometer configured to obtain a second type of spectrum data from the light scattered, emitted, or reflected from the object, the second type of spectrum data being different from the first type of spectrum data; an image sensor configured to obtain image data of the object; and a processor configured to identify the object using data obtained from at least two from among the first spectrometer, the second spectrometer, and the image sensor and using at least two pattern recognition algorithms.

An apparatus includes a reactive species source, a spectral measurement volume, a light source to emit a light beam into the spectral measurement volume, a spectrometer to receive the light beam from the spectral measurement volume. The apparatus includes an a controller configured to, when a reactive species is present in the spectral measurement volume, control the light source to emit the light beam into the spectral measurement volume and the spectrometer to determine an environment spectrum using the light beam, and when the reactive species is not present in the spectral measurement volume, control the light source to emit the light beam into the spectral measurement volume and the spectrometer to determine a baseline spectrum using the light beam, calculate a net spectrum based on a difference between the environment spectrum and the baseline spectrum, and estimate a concentration of the reactive species based on the net spectrum.

A system and method for classifying a sample are provided. The system includes a housing containing the sample, a sensing element to measure at least one physical parameter of the same, and a processor configured to receive and analyze the physical parameter measurement, and to determine if the sample can be classified based on the measurement. If the sample cannot be classified, the processor selects and applies other analytical techniques until the sample is classified. The method includes selecting an analytical technique to apply to a sample, applying the technique to the sample, obtaining the results of the analytical technique, and determining if the sample can be classified based on the analytical technique. The method further includes selecting and applying further analytical techniques if the sample was not classified, until the sample is able to be classified.

Systems and methods for analyzing an unknown geological sample are disclosed. The system may include at least two analytical subsystems, and each of the at least two analytical subsystems provides different information about the geological sample. The data sets from various analytic subsystems are combined for further analysis, and the system includes a chemometric calibration model that relates geological attributes from analytical data previously obtained from at least two analytical techniques. A prediction engine applies the chemometric calibration model to the combined analytical information from the geological sample to predict specific geological attributes in the unknown geological sample.

A system and method for determining impurities in a beverage grade gas such as CO.sub.2 or N.sub.2 relies on a coupling of FTIR analysis and UV fluorescence detection. Conversion of reduced sulphur present in some impurities to SO.sub.2 can be conducted using a furnace. In some cases, CO.sub.2 % also is determined.

To show a highly accurate cell measurement method. A cell measurement method comprises: a step of staining a cultured target cell with a dye; a step of obtaining a first image and a second image which are transmission images for a first light and a second light to which the dye has different absorbance; a step of dividing each of the first image and the second image into a plurality of divided regions and comparing the first image and the second image for each of the divided regions so as to eliminate noises; and a step of integrating an indicator of a cell amount in each of the divided regions in the images from which the noises were eliminated so as to evaluate a target cell amount.

Disclosed herein are characterization systems. A characterization system may comprise a stationary unit. The characterization system may comprise a rotary unit. optically connected to the stationary unit (e.g., via a FORJ) if present. The rotary unit may comprise a first optical channel, a second optical channel, and a light detector for detecting light for a first characterization modality. The light detector may be a camera, interferometer, or spectrometer. The first optical channel and/or the second optical channel may comprise a single mode optical fiber, a multimode optical fiber, or multiple waveguides. The first optical channel may be optically connected to the light detector. The stationary unit, if present, may be optically connected to the rotary unit at least in part with the second optical channel. The second optical channel may be used to detect light for a second characterization modality, with a detector in the stationary unit.

A sample analysis system is provided with: a reference substance database including measurement results and component classification information of reference substances obtained by each analysis device on information of each reference substance; a reference substance designation unit; a measurement result collation unit to obtain the commonality of the components, the difference between the physical quantities of the respective components, and the degree of coincidence of the measurement results for each analysis device for the designated reference substance; an integration coincidence degree calculation unit to obtain an integration degree of coincidence; and a judgment unit to judge whether or not the difference between the contents of contained components is within an allowable range and classify the corresponding component based on the component classification information.