A control method based on an adaptive neural network model for dissolved oxygen of an aeration system includes: obtaining related water quality monitoring data of a sewage treatment plant, and performing data preprocessing on the related water quality monitoring data; performing principal component analysis on the preprocessed related water quality monitoring data and a dissolved oxygen concentration of the aeration system through a principal component analysis method, and determining a water quality parameter with a highest rate of contribution to a principal component; taking the water quality parameter with the highest rate of contribution to the principal component, and predicting a dissolved oxygen concentration of the aeration system; and optimizing a dissolved oxygen predictive value obtained by means of the adaptive neural network model to obtain an optimal regulation value, and performing online regulation on a fuzzy control system of the adaptive neural network model.

The present disclosure provides a color chart and a test kit for estimating chemical oxygen demand of water. The color chart includes a blue component, an indigo component, an umber component, and an orange component. The test kit includes an oxidant, a reductant, an indicator, and the color chart. The present disclosure also provides a method for estimating chemical oxygen demand of water. The method includes providing a water sample; adding an oxidant to the water sample; heating the water sample; adding a reductant to the water sample; adding an indicator to the water sample, such that the water sample develops a color; and matching the color of the water sample with the color components of the color chart to estimate the chemical oxygen demand of the water sample.

A control method based on an adaptive neural network model for dissolved oxygen of an aeration system includes: obtaining related water quality monitoring data of a sewage treatment plant, and performing data preprocessing on the related water quality monitoring data; performing principal component analysis on the preprocessed related water quality monitoring data and a dissolved oxygen concentration of the aeration system through a principal component analysis method, and determining a water quality parameter with a highest rate of contribution to a principal component; taking the water quality parameter with the highest rate of contribution to the principal component, and predicting a dissolved oxygen concentration of the aeration system; and optimizing a dissolved oxygen predictive value obtained by means of the adaptive neural network model to obtain an optimal regulation value, and performing online regulation on a fuzzy control system of the adaptive neural network model.

An apparatus, a system, sensor, and a method for determining dissolved oxygen content in air and aqueous medium are disclosed herein. The dissolved oxygen content may be determined by irradiating the sensor comprising at least a photo-oxidizable compound by a light irradiation source, wherein the irradiation enables the photo-oxidizable compound to change its luminescent properties based upon photo-oxidation thereby enabling the quantification of the dissolved oxygen content in the medium. The dissolved oxygen content may be captured via the impedance response generated by interdigitated conducting electrode patterns included in the sensor. The dissolved oxygen content registered by the interdigitated conducting electrode patterns may be transmitted to a user device via a short range or long-range communication via an electronic circuit embedded within the sensor.

The present disclosure provides a color chart and a test kit for estimating chemical oxygen demand of water. The color chart includes a blue component, an indigo component, an umber component, and an orange component. The test kit includes an oxidant, a reductant, an indicator, and the color chart. The present disclosure also provides a method for estimating chemical oxygen demand of water. The method includes providing a water sample; adding an oxidant to the water sample; heating the water sample; adding a reductant to the water sample; adding an indicator to the water sample, such that the water sample develops a color; and matching the color of the water sample with the color components of the color chart to estimate the chemical oxygen demand of the water sample.

The present invention relates to a method and a device for the chemical-free determination of the chemical oxygen demand (CODs) in aqueous samples. The object of the invention, to develop a method that compensates for the disadvantages of the standard method and at the same time is at least as good as this, in that it can determine the COD quickly and with a high measurement frequency without chemicals and is cheap and has a low personnel requirement and should be simple to automate, is achieved in that the chemical oxygen demand of aqueous samples is determined by non-specific oxidation of water components at an electrode (11), assisted by (ultra)sound from a sound source (15) in a frequency range in which no significant quantities of oxidative species are formed, i.e. below the cavitation threshold.

A water quality monitoring device and a monitoring method thereof are provided. The water quality monitoring device includes a water tank, a first and a second optical detection devices and a control circuit. The water tank has an accommodating space to carry a liquid. The first optical detection device provides a first light to detect and obtain a first reference light intensity, a first scattered light intensity, and a first penetrating light intensity. The second optical detection device provides a second light to detect and obtain a second reference light intensity, a second scattered light intensity, and a second penetrating light intensity. The control circuit calculates a water quality detection value of the liquid based on the first reference light intensity, the first scattered light intensity, the first penetrating light intensity, the second reference light intensity, the second scattered light intensity, and the second penetrating light intensity.

Apparatus (2) for sensing at least one parameter in water, which apparatus (2) comprises: (i) a conductivity sensor (6) for sensing conductivity in water; (ii) the conductivity sensor (6) is an electrode-based conductivity sensor having bare electrodes (12) which contact the water; (iii) there are at least four of the electrodes (12); (iv) the conductivity sensor (6) is fabricated on a substrate (14) using photolithography and etching; (v) the conductivity sensor (6) is an open cell sensor having a physically unconstrained electric field; (vi) the conductivity sensor (6) is of a dot construction comprising a dot and a surrounding formation; (vii) the conductivity sensor (6) has two electrodes which are for current stimulation and which geometrically bound and enclose another two electrodes which are for voltage sensing; and (viii) the conductivity sensor (6) is a laminar construction on the substrate (14).

Disclosed is an analysis system for analyzing water and wastewater, comprising an analysis device that includes a device housing which accommodates device components and which has an inlet on a housing surface, said inlet being designed as an injection port through which a substance to be analyzed can be introduced into a device component when the device housing is closed, and comprising a syringe that includes an injection needle outlet, the surface normal of which is congruent with the longitudinal axis; and/or the syringe includes an automatic ejection element for ejecting a predetermined amount of substance within a predetermined injection period.

Methods for identifying animals that are genetically superior, drugs, nutritional strategies, or physiological manipulations that improve feed efficiency or productivity of animals, e.g., selecting animals that are genetically superior for feed efficiency or productivity based on metabolic rates of particular tissues, wherein metabolic rates of certain tissues such as skeletal muscle are inversely proportional to feed efficiency, while metabolic rates of other tissues such as mammary gland are directly proportional to milk production. Thus, animals with low skeletal muscle metabolic rates are generally more feed efficient, e.g., gain more weight per unit of food. The methods herein may be used to improve the genetics, nutrition, and handling or animals more efficiently produced animal products, e.g., meat production, milk, production, egg production, wool production, etc. The methods herein may also be used to determine estimated breeding values of animals for feed efficiency, growth, or production.