The invention discloses a biological water-quality detection method using said obstructive multi-module biological water-quality detection device. This device includes an obstruction index-selecting device and a water-quality testing device, wherein the obstruction index-selecting device is used to select a qualified or valid stepped obstruction level combination, the water-quality testing device detects the water-quality of the water body to be tested depending on the behavior at each obstruction in the valid obstruction level combination after injecting indicator organisms into the water body to be tested. The relationship between the degree of water pollution and the distribution area of indicator organisms is established and the distribution area of indicator organisms is counted in this method based on the difference between the behaviors of indicator organisms in the clean water body and the polluted water body count, so as to determine the degree of water pollution.

A system and method for the detection and elimination of microorganisms in a water flow is provided. The method includes arranging at least one light emission element at a water flow point, arranging of at least one light capture element at the water flow point, detecting the presence of the microorganism through the first light emission event and eliminating the microorganism through the realization of a second light emission event. A detection module is also provided which can be positioned at a water flow point.

A system and method for the detection and elimination of microorganisms in a water flow is provided. The method includes arranging at least one light emission element at a water flow point, arranging of at least one light capture element at the water flow point, detecting the presence of the microorganism through the first light emission event and eliminating the microorganism through the realization of a second light emission event. A detection module is also provided which can be positioned at a water flow point.

A sensor for gas species in water includes two membranes separating first, second and third chambers. The first and second chambers are separated by an ion exchange membrane, and the second and third chambers are separated by a gas permeable membrane. Water electrolysis in the first and second chambers provides analyte-ions corresponding to an analyte being detected that pass through the ion exchange membrane from the first chamber to the second chamber. Within the second chamber, these analyte-ions generate analyte via the electrolysis. Analyte in the second chamber passes through the gas permeable membrane to arrive at the third chamber. Within the third chamber, the analyte-ion is generated chemically from the analyte. Electrical detection of the analyte-ion in the third chamber provides sensing of the analyte present in the first chamber.

An imaging flow cytometer device includes a housing holding a multi-color illumination source configured for pulsed or continuous wave operation. A microfluidic channel is disposed in the housing and is fluidically coupled to a source of fluid containing objects that flow through the microfluidic channel. A color image sensor is disposed adjacent to the microfluidic channel and receives light from the illumination source that passes through the microfluidic channel. The image sensor captures image frames containing raw hologram images of the moving objects passing through the microfluidic channel. The image frames are subject to image processing to reconstruct phase and/or intensity images of the moving objects for each color. The reconstructed phase and/or intensity images are then input to a trained deep neural network that outputs a phase recovered image of the moving objects. The trained deep neural network may also be trained to classify object types.

Kits and systems for isolating microorganisms from a sample, the sample including sample matrix and microorganisms, the kit including concentration agent; and a system for isolating microorganisms from a sample.

We describe a method of determining a food-to-biomass ratio in an aqueous fluid the method comprising: providing an aqueous fluid comprising viable biomass and food for said biomass, and wherein there is insufficient available food to sustain all said viable biomass; using a sensor (for example a respirometer or a sensor for sensing an amount of ammonia, ammonium, nitrates or nitrites) to determine an amount of food in said aqueous fluid available to said biomass; determining a measure of viable biomass in said aqueous fluid by measuring polarisability of viable biomass cells in an AC electric field; and determining a food-to-biomass ratio from said amount of food and said measure of viable biomass.

Apparatus for controlling algae and bio-organisms in bodies of fluids, such as water. The algae control system includes a power unit and a transducer unit that includes a sonic head that radiates in multiple directions. The power unit connects to various power sources, including a mains supply connection, a solar panel array, and/or a battery. The power unit is electrically connected to the transducer unit. The sonic head includes a driver and a transducer subassembly. The driver excites the transducer subassembly to emit ultrasonic waves at various frequencies in the water surrounding the sonic head. Emissions at a high density of frequencies are enabled by the transducers. The frequencies include the critical structural resonant frequency for each microorganism to be controlled. The power unit and driver each include a processor in communication with each other. The processors store and execute a program for a selected application configuration.

A computer of a prediction-rule generating system includes an input unit configured to input time series data of an abundance proportion of microorganisms or nucleotide sequences included in activated sludge in which a water treatment is performed and water quality information indicating water quality after a water treatment associated with data at each time constituting the time series data, a principal component analyzing unit configured to perform principal component analysis on the input time series data and calculate principal component scores of data at each time constituting time series data, and a prediction rule generating unit configured to generate a prediction rule for predicting water quality after a water treatment from an abundance proportion of microorganisms or nucleotide sequences on the basis of the calculated principal component scores and the input water quality information indicating water quality after a water treatment.

A system and method for the detection and elimination of microorganisms in a water flow is provided. The method includes arranging at least one light emission element at a water flow point, arranging of at least one light capture element at the water flow point, detecting the presence of the microorganism through the first light emission event and eliminating the microorganism through the realization of a second light emission event. A detection module is also provided which can be positioned at a water flow point.