Abstract: Pre-connected analyte sensors are provided. A pre-connected analyte sensor includes a sensor carrier attached to an analyte sensor. The sensor carrier includes a substrate configured for mechanical coupling of the sensor to testing, calibration, or wearable equipment. The sensor carrier also includes conductive contacts for electrically coupling sensor electrodes to the testing, calibration, or wearable equipment.

Abstract: A method is described of dynamically searching a search domain. A first result set of data objects is presented. The first result set is obtained from a first search of a search domain having active and inactive data objects for first search features obtained from a source data object. An update is detected in the search domain. Key features are extracted from the source data object to be included in second search features when the update in the search domain is in the source data object. A second search of the updated search domain is performed for data objects having the second search features.

Abstract: A method is described of dynamically searching a search domain. A first result set of data objects is presented. The first result set is obtained from a first search of a search domain having active and inactive data objects for first search features obtained from a source data object. An update is detected in the search domain. Key features are extracted from the source data object to be included in second search features when the update in the search domain is in the source data object. A second search of the updated search domain is performed for data objects having the second search features.

Abstract: A method is described of dynamically searching a search domain. A first result set of data objects is presented. The first result set is obtained from a first search of a search domain having active and inactive data objects for first search features obtained from a source data object. An update is detected in the search domain. Key features are extracted from the source data object to be included in second search features when the update in the search domain is in the source data object. A second search of the updated search domain is performed for data objects having the second search features.

Abstract: A method is described of dynamically searching a search domain. A first result set of data objects is presented. The first result set is obtained from a first search of a search domain having active and inactive data objects for first search features obtained from a source data object. An update is detected in the search domain. Key features are extracted from the source data object to be included in second search features when the update in the search domain is in the source data object. A second search of the updated search domain is performed for data objects having the second search features.

Abstract: The likelihood of a problem report being escalated to a critical status in a customer service environment is predicted by receiving historical Problem Management Records for which associated problems have been resolved and final criticality statuses have been determined, analyzing the historical Problem Management Records using at least one trainable data mining process to produce a prediction output for each historical Problem Management Record, validating the prediction output against the final criticality statuses, training the data mining process according to the validation, and, subsequently, analyzing an unresolved Problem Management Record by the trained analysis module to produce a prediction indicator and a confidence indicator for unresolved Problem Management Record to be re-classified as critical status. The unresolved Problem Management Record is escalated to critical status level responsive to the prediction indicator and the confidence indicator exceeding a predetermined threshold.