Systems and methods are provided for Quantitative Phase Microscopes (QPM) having laser systems including one or more of laser scissors and laser tweezers. In one embodiment, the system includes one or more structural elements, such as a stage and dichroic plate for operation of a QPM with laser scissors/tweezers. Another embodiment is directed to a method of operating a QPM system having laser scissors/tweezers. One or more solutions are provided for biodmedical applications of a QPM system including simulation and analysis of trauma on cellular structures and organelles. Processes are also provided for simulation and analysis of traumatic injury, including imaging and analysis of astrocytes.

Holographic Video Microscopy analysis of non-spherical particles is disclosed herein. Properties of the particles are determined by application of light scattering theory to holography data. Effective sphere theory is applied to provide information regarding the reflective index of a sphere that includes a target particle. Known particles may be co-dispersed with unknown particles in a medium and the holographic video microscopy is used to determine properties, such as porosity, of the unknown particles.

A system for measuring mechanical properties of rock cuttings includes a vibration platform with an upper surface configured to vibrate a plurality of rock cuttings thereon. A sensor system is operatively connected to the vibration platform to monitor the rock cuttings vibrating on the upper surface of the vibration platform. A calculation module is operatively connected to the vibration platform and the sensor system to calculate mechanical properties of the rock cuttings based on applied vibrational force frequency of the vibration platform and measurements of the rock cuttings from the sensor system.

Holographic Video Microscopy analysis of non-spherical particles is disclosed herein. Properties of the particles are determined by application of light scattering theory to holography data. Effective sphere theory is applied to provide information regarding the reflective index of a sphere that includes a target particle. Known particles may be co-dispersed with unknown particles in a medium and the holographic video microscopy is used to determine properties, such as porosity, of the unknown particles.

An experimental device and method for testing foam fluid properties and defoaming separation effects, the experimental device including a foam generation module configured to generate a foam fluid, an experimental loop configured to transport the foam fluid and enable the foam fluid to sufficiently develop in a loop, a foam property test module configured to test foam fluid properties, a foam separation processing module configured to separate foam from fluid and gas, and a defoaming result evaluation module configured to test and evaluate defoaming results. In the method, different foam fluids are generated in the foam generation module and are transported to the foam property test module and different foam separation processing modules through the experimental loop, and the foam properties of the foam fluids and defoaming separation effects are measured by the foam property test module and the defoaming result evaluation module connected to the foam separation processing module.

A TBM-mounted system and method for quickly predicting compressive strength of rocks based on rock mineral composition and fabric characteristics. The system is mounted on gripper shoe's side surface of an open-type TBM, and includes a protective device, hydraulic device, servo motor, detection device, control system and a data comprehensive analysis platform. The hydraulic device is mounted on the protective device's side wall, for controlling movement of detection device horizontally. The servo motor controls rotation of detection device. The detection device collects a variety of geological parameters of target surrounding rock affecting compressive strength of rock and providing basic data for compressive strength prediction of rock. The control system controls work of hydraulic device, servo motor and each detection device. The data comprehensive analysis platform is connected to each detection instrument, receives geological parameters collected, processes and analyzes each parameter, and gives a prediction of compressive strength of rock.

In example implementations, an apparatus is provided. The apparatus includes a channel, a camera, and a processor. The channel contains a fluid and an object. The fluid is to move the object through the channel. The camera system is to capture video images of the object in the channel. The processor is to track movement of the object in the channel via the video images based on known flow dynamics of the channel.

A system for analysing drops capable of being ejected by a coating product applicator, includes a light source configured to illuminate a drop ejection zone, designated observation zone; a first image acquisition device configured to acquire an image of the observation zone; and an image analyser configured to determine, from the image of the observation zone, the presence of drops at a given distance from the applicator, the size of the drops and the absence of satellite; the light source and the first image acquisition device being situated on a same side of the observation zone.

The present invention relates to a hazardous material measuring apparatus capable of analyzing concentration and components of various hazardous materials. The hazardous material measuring apparatus analyzes an optical spectrum obtained by a spectrometer or a hyperspectral image obtained by a hyperspectral camera, thereby analyzing concentration and components of the hazardous materials to be measured.

A method and a system for determining an indicator of processing quality of an agricultural harvested material using a mobile device is disclosed. A computing unit analyzes image data of a prepared sample of harvested material containing grain components and non-grain components in an analytical routine to determine the indicator of the processing quality of the agricultural harvested material. Further, the computing unit uses a trained machine learning model in the analytical routine to perform at least one step of determining the indicator of the processing quality of the agricultural harvested material and that the computing unit adjusts at least one machine parameter of the forage harvester based on the indicator of processing quality.