Inline classification of a biological specimen including mammalian cells can include generating an alternating current (AC) electrical stimulus to an electrode structure. The electrode structure can be electrically coupled with a flow cell. A response, elicited by the electrical stimulus, can be received when a model specimen class traverses the flow cell. Using the received response, a corresponding impedance parameter value can be determined, the value indicative of a specified biophysical characteristic corresponding to the model specimen class. The first impedance parameter can be translated to a value corresponding to the specified biophysical characteristic.

To enable evaluation of a shape of a fine particle and a fine particle type, a substrate is set as a substrate on which an isolated fine particle to be measured and an isolated standard fine particle in the vicinity of the isolated fine particle to be measured are disposed, and a scanning electron microscope body including a detector configured to detect secondary charged particles obtained by scanning a surface of the substrate with an electron beam probe, and a computer that processes a detection signal and generates an image of the isolated fine particle to be measured and the isolated standard fine particle are provided. The computer corrects a shape of the isolated fine particle to be measured by using a measurement result of the isolated standard fine particle disposed in the vicinity of the isolated fine particle to be measured. Further, by attaching a fine particle spreading tank equipped with a fine particle suspension dropping device inside the microscope body, automatic measurement including dropping of fine particle suspension onto a surface of a surface-modified substrate is possible.

A method (10) utilizes first, second, and third image data originating from first, second, and third digital image frames, respectively, captured sequentially in time of a sample volume containing a fluid possibly comprising moving microscopic objects comprising moving microscopic objects while illuminating the sample volume by coherent light, each image data comprising, for a moving microscopic object of foreign object present in the sample volume, a hologram pattern (11); and comprises automatically generating first differential image data comprising the difference of the first and the second image data, (13a); automatically generating second differential image data comprising the difference of the second and the third image data (13b); automatically generating product of difference (POD) image data comprising the product of the first and the second differential image data, (14); and automatically detecting the presence of moving microscopic object(s) in the sample volume on the basis of product pattern(s) present in the POD image data (17).

A particle counter and classification system and method wherein a first stage magnetometer sensor subsystem for the fluid is tuned to detect and determine the size of ferrous and/or conducting particles in the fluid above a predetermined size. A pump is configured to drive a volume of the fluid through the first stage magnetometer sensor subsystem. A processing subsystem is responsive to the first stage magnetometer sensor subsystem and is configured to count the number of ferrous and/or conducting particles above the predetermined size based on the output of the first stage magnetometer sensor subsystem and to determine and report the concentration of the ferrous and/or conducting particles above the predetermined size as a function of the size of the particles, their number, and the volume of the fluid.

An example system includes an input channel having a first end and a second end to receive particles through the first end, a sensor to categorize particles in the input channel into one of at least two categories, and at least two output channels Each output channel is coupled to the second end of the input channel to receive particles from the input channel, and each output channel is associated with at least one category of the at least two categories. Each output channel has a corresponding pump operable, based on the categorization of a detected particle in a category associated with a different output channel, to selectively slow, stop, or reverse a flow of particles into the output channel from the input channel.

Systems and methods for predicting engine performance are provided herein. A fluid sample having particles suspended therein is received from a first engine. A plurality of particles are extracted from the fluid sample. Features of the plurality of particles extracted from the fluid sample and features of particles of reference fluid samples from a plurality of reference engines are obtained. A plurality of correlation indices indicative of a level of correlation between the first engine and each one of the plurality of reference engines is determined. The correlation indices are compared to a threshold to determine a subset of the plurality of reference engines. Performance history for the engines in the subset is obtained. From the performance history, the first engine is determined as having a similarity in performance with the engines in the subset. An output is generated indicating a predicted performance for the first engine.

The present invention provides a classification analysis method, a classification analysis device, and a storage medium for classification analysis, which enable, with high accuracy, the classification analysis of particulate or molecular analytes. As a means for solving the problem, a data group of particle-passage detection signals is based which are detected by a nanopore device 8 in accordance with passage of subject particles through a through-hole 12. A feature value is obtained in advance which indicates the feature of the waveform of the pulse signals corresponding to the passage of the predetermined analyte and the feature value obtained in advance is set as the learning data for the machine learning. The feature value obtained from the pulse signals of said analyzed data is set as a variable and the classification analysis on the predetermined analytes in the analyzed data can be performed by executing a classification analysis program due to the machine learning.

The invention provides methods for evaluating disease, such as cancer, by way of performing multiple assays involving single-cell analysis on live cells isolated from a sample of a patient. The data obtained from the multiple assays is analyzed and linked to thereby provide a characterization of any given cell having undergone analysis, which, in turn, allows for evaluation of the sample either known to be, or suspected of being, cancerous. A report may be generated based on the data analysis, wherein the report provides information related to the cancer evaluation, including, but not limited to, whether the sample tested positive for cancer, a determination of a stage or progression of cancer, and a customized treatment plan tailored to an individual patient's cancer diagnosis.

A microfluidic device that reads a colloidal mixture and separates the colloids based upon size and shape. and in the case of polymer colloids such as DNA, it reads patterns of markers attached to DNA. The combination of different separated fractions and DNA markers (it mapping) constitutes the physical code.

A sensing system comprises at least one fluidic channel (104) for providing at least one analyte (105) into at least one region of interest; at least one radiation transport system (501), for providing excitation radiation (103) for exciting analytes traversing the at least one region of interest; and a radiation collection system (301) for collecting any radiation signal emitted from the at least one region of interest. The at least one radiation transport system is adapted for providing excitation radiation comprising a plurality of excitation radiation intensity peaks (101, 102), whereby the distance between the excitation radiation intensity peaks is known. The sensing system comprises means (302, 303) for measurement of the speed of the at least one analyte within the fluidic channel (104), the means for measurement of speed comprising timing means (303) for obtaining the time between maxima in radiation signals emitted by the at least one analyte.