A fluid sampling unit includes a housing and a shutoff valve adapted to selectively permit and restrict fluid flow to a fluid line disposed within an internal cavity of the housing. An electrically-actuated valve is disposed within the housing downstream from, and in fluid communication with, the shutoff valve. A first metallic line including copper is disposed within the housing in fluid communication with and between the shutoff valve and the electrically-actuated valve. A second metallic line including lead is disposed within the housing in fluid communication with and between the shutoff valve and the electrically-actuated valve. A control unit includes a controller adapted to selectively actuate the electrically-actuated valve.

A fluid sampling unit includes a housing and a shutoff valve adapted to selectively permit and restrict fluid flow to a fluid line disposed within an internal cavity of the housing. An electrically-actuated valve is disposed within the housing downstream from, and in fluid communication with, the shutoff valve. A first metallic line including copper is disposed within the housing in fluid communication with and between the shutoff valve and the electrically-actuated valve. A second metallic line including lead is disposed within the housing in fluid communication with and between the shutoff valve and the electrically-actuated valve. A control unit includes a controller adapted to selectively actuate the electrically-actuated valve.

The present invention provides a method and a device for estimating a value to be estimated associated with a specimen, by performing machine learning of a relationship between a value of an estimation object and an output corresponding thereto, based on an output from a chemical sensor with regard to a plurality of specimens for which specific values to be estimated are known, and using the result of the mechanical learning to estimate a specific value to be estimated on the basis of an output from the chemical sensor with regard to a given unknown specimen.

The present invention provides a method and a device for estimating a value to be estimated associated with a specimen, by performing machine learning of a relationship between a value of an estimation object and an output corresponding thereto, based on an output from a chemical sensor with regard to a plurality of specimens for which specific values to be estimated are known, and using the result of the mechanical learning to estimate a specific value to be estimated on the basis of an output from the chemical sensor with regard to a given unknown specimen.

The present disclosure provides a sensor assembly for a target analyte. The sensor assembly comprises plural sensing sites, each of the sensing sites comprising one or more through holes. Each of the sensing sites has a different through hole configuration corresponding to a different property of the one or more through holes.

The present disclosure provides a sensor assembly for a target analyte. The sensor assembly comprises plural sensing sites, each of the sensing sites comprising one or more through holes. Each of the sensing sites has a different through hole configuration corresponding to a different property of the one or more through holes.