Abstract: A multi-analyte sensor device is disclosed. The multi-analyte device is a handheld device that includes a replaceable sensor. In one embodiment, the replaceable sensor includes a plurality of electrodes coated with one or more different molecular imprinted polymer (MIP) coatings for measuring concentrations of target analytes. The replaceable sensor is configured to be attached or detached from the device one or more times.

Abstract: A multi-analyte sensor includes a body having a proximal end and a distal end. A plurality of strips is connected to one end of the body and a plurality of electrical conductors run through the body and into the plurality of strips. Exposed portions of first and second electrical conductors running through first and second strips are coated with analyte-responsive materials, such as a first molecular imprinted polymer (MIP) and a second MIP, respectively. The first MIP has binding sites for a first target analyte and the second MIP has binding sites for a second target analyte. The multi-analyte sensor may be part of a sensing device that also includes a controller and a data store.

Abstract: A multi-analyte sensor includes a body having a proximal end and a distal end. A plurality of strips is connected to one end of the body and a plurality of electrical conductors run through the body and into the plurality of strips. Exposed portions of first and second electrical conductors running through first and second strips are coated with analyte-responsive materials, such as a first molecular imprinted polymer (MIP) and a second MIP, respectively. The first MIP has binding sites for a first target analyte and the second MIP has binding sites for a second target analyte. The multi-analyte sensor may be part of a sensing device that also includes a controller and a data store.

Abstract: A system and method for machine translation are disclosed. Source sentences are received. For each source sentence, a target sentence comprising target words is generated. A plurality of translation neighbors of the target sentence is generated. Phrase alignments are computed between the source sentence and the translation neighbor. Translation neighbors are scored with a translation scoring model, based on the phrase alignment. Translation neighbors are ranked, based on the scores. In training the model, parameters of the model are updated based on an external ranking of the ranked translation neighbors. The generating of translation neighbors, scoring, ranking, and, in the case of training, updating the parameters, are iterated with one of the translation neighbors as the target sentence. In the case of decoding, one of the translation neighbors is output as a translation. The system and method may be at least partially implemented with a computer processor.

Abstract: A system and method for machine translation are disclosed. Source sentences are received. For each source sentence, a target sentence comprising target words is generated. A plurality of translation neighbors of the target sentence is generated. Phrase alignments are computed between the source sentence and the translation neighbor. Translation neighbors are scored with a translation scoring model, based on the phrase alignment. Translation neighbors are ranked, based on the scores. In training the model, parameters of the model are updated based on an external ranking of the ranked translation neighbors. The generating of translation neighbors, scoring, ranking, and, in the case of training, updating the parameters, are iterated with one of the translation neighbors as the target sentence. In the case of decoding, one of the translation neighbors is output as a translation. The system and method may be at least partially implemented with a computer processor.