The present invention describes a fluidic device for measuring at least one of corpuscle mass density and weight. The fluidic device comprises a sedimentation chamber fluidly connected to an inlet channel configured to be immersed in a liquid. The fluidic device further comprises a pumping system connected to the sedimentation chamber. The pumping system is adapted to control the flow of liquid in the sedimentation chamber. A processor of the fluidic device is configured to obtain corpuscle data related to a corpuscle in at least one region of the sedimentation chamber; and calculate at least one of corpuscle mass density and weight based on the data received.

In some examples, a system including a fluid stream monitoring system. The monitoring system includes an illumination device configured to illuminate at least some of particles suspended in a fluid stream; and an imaging device configured to image the illuminated particles at a first image plane that intersects a longitudinal axis of the fluid stream, wherein the illumination device and the imaging device are registered to the fluid stream delivery device in the first image plane, where the first image plane is substantially orthogonal to the longitudinal axis. The system includes processing circuitry configured to determine one or more physical characteristics of the fluid particles.

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.

A method including selecting image data of a mechanical mud separation machines (“MMSM”) to detect objects in an object flow and other operational conditions at the MMSM. The image data may be processed by a Deep Neural Network to identify objects in the object flow, operational parameters of the MMSM, and environmental conditions. Additional image data may be selected for additional processing based on the results of the analysis.

A computer-implemented method for data analysis comprises obtaining a plurality of first observations, each one of the plurality of first observations including one or more values of one or more first parameters, the plurality of first observations grouped into a plurality of groups; constructing a first histogram using the values of at least one of the one or more first parameters, included in the plurality of first observations; constructing, for each one of the plurality of groups, a second histogram having bins corresponding to bins of the first histogram, wherein each one of the bins of the second histogram includes a count of the first observations, among the first observations that belong to the one of the plurality of groups, having one or more values corresponding to the one of the bins for the at least one of the one or more first parameters; and outputting the second histograms.

A stream including at least one of solid CO.sub.2 particles or CO.sub.2 droplets is directed toward an article including surface particles. The stream causes at least a portion of the surface particles on the article to dislodge from a surface of the article. A purge cycle to transport at least a portion of the dislodged surface particles away from the surface of the article is initiated. The purge cycle includes generating a laminar flow at a first velocity for a first time period and subsequently generating a laminar flow at a second velocity for a second time period. A determination is made of whether a number of particles transported away from the surface of the article satisfies a particle criterion. In response to a determination that the number of particles transported away from the article does not satisfy the criterion, the purge cycle is re-initiated.

Disclosed is a method for detecting an antigen-specific activated T cell comprising: acquiring first information on a particle size and second information on a T cell activation marker for a first measurement sample prepared by mixing in vitro a first specimen separated from a biological sample containing a T cell and an antigen-presenting cell and an antigen reagent containing a predetermined antigen, by measuring the first measurement sample with a flow cytometer; acquiring the first information and the second information for a second measurement sample prepared from a second specimen separated from the biological sample and not containing the antigen reagent, by measuring the second measurement sample with the flow cytometer; detecting a target particle in the first measurement sample based on the first information and the second information on the first measurement sample, and detecting a background particle in the second measurement sample based on the first information and the second information on the second measurement sample; and detecting a cell complex in which the T cell and the antigen-presenting cell adhere to each other in the first measurement sample, the cell complex including a T cell activated by the predetermined antigen, based on a detection result of the target particle and a detection result of the background particle.

Disclosed is a method of measuring red blood cell membrane fluctuations based on dynamic cell parameters using a digital holographic microscope; the method including a step of modeling the three-dimensional images of red blood cells to be measured, and a step of measuring red blood cell membrane fluctuations based on the three-dimensional images. According to this method, since the three-dimensional images of red blood cells to be measured are modeled and red blood cell membrane fluctuations are measured based on the three-dimensional images, red blood cell membrane fluctuations can be measured more easily.

The apparati, methods, and computer program products disclosed herein can be used to nondestructively detect undissolved particles, such as glass flakes and/or protein aggregates, in a fluid in a vessel, such as, but not limited to, a fluid that contains a drug.

An analysis device includes an acquisition unit configured to acquire an image of a cell and an identification unit configured to identify elements that are identifiable on the basis of the image of cell acquired by the acquisition unit. Characteristic quantities of the elements identified by the identification unit are calculated, a correlation between the characteristic quantities is calculated on the basis of the calculated characteristic quantities of the elements, and a correlation between the elements is calculated on the basis of the calculated correlation between the characteristic quantities.