Abstract: Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period; access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs; and determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Abstract: Sensor logs corresponding to a first machine are accessed. Each sensor log spans at least a first period. First computer readable logs corresponding to the first machine are accessed. Each computer readable log spans at least the first period, the computer readable logs include a maintenance log including maintenance task objects, each maintenance task object includes a time and a maintenance task type. A set of statistical metrics are derived from the sensor logs. A set of log metrics are derived from the computer readable logs. Using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period are determined.

Abstract: Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period; access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs; and determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Abstract: Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period; access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs; and determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Abstract: The present disclosure describes the engineering of microbial cells for fermentative production of L-homocysteine and provides novel engineered microbial cells and cultures, as well as related L-homocysteine production methods.

Abstract: Systems, methods, non-transitory computer readable media can be configured to accessing a target sensor log corresponding to a first machine; accessing one or more prior sensor logs corresponding to the first machine and one or more prior sensor logs corresponding to a plurality of second machines which are of the same type as the first machine; accessing a plurality of computer readable logs corresponding to the first machine and the second machines, the computer readable logs for each second machine comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determining a set of statistical metrics characterising a difference between the target sensor log and each prior sensor log; selecting a sub-set of the prior sensor logs in dependence upon the statistical metrics; analysing the maintenance logs to correlate each prior sensor log included in the subset to one or more correlated maintenance tasks; selecting a

Abstract: Systems, methods, non-transitory computer readable media can be configured to accessing a target sensor log corresponding to a first machine; accessing one or more prior sensor logs corresponding to the first machine and one or more prior sensor logs corresponding to a plurality of second machines which are of the same type as the first machine; accessing a plurality of computer readable logs corresponding to the first machine and the second machines, the computer readable logs for each second machine comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determining a set of statistical metrics characterising a difference between the target sensor log and each prior sensor log; selecting a sub-set of the prior sensor logs in dependence upon the statistical metrics; analysing the maintenance logs to correlate each prior sensor log included in the subset to one or more correlated maintenance tasks; selecting a

Abstract: Systems, methods, non-transitory computer readable media can be configured to accessing a target sensor log corresponding to a first machine; accessing one or more prior sensor logs corresponding to the first machine and one or more prior sensor logs corresponding to a plurality of second machines which are of the same type as the first machine; accessing a plurality of computer readable logs corresponding to the first machine and the second machines, the computer readable logs for each second machine comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determining a set of statistical metrics characterising a difference between the target sensor log and each prior sensor log; selecting a sub-set of the prior sensor logs in dependence upon the statistical metrics; analysing the maintenance logs to correlate each prior sensor log included in the subset to one or more correlated maintenance tasks; selecting a

Abstract: Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period; access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs; and determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Abstract: Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period. Access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type. Determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs. Determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Abstract: Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period; access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs; and determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Abstract: Systems, methods, non-transitory computer readable media can be configured to accessing a target sensor log corresponding to a first machine; accessing one or more prior sensor logs corresponding to the first machine and one or more prior sensor logs corresponding to a plurality of second machines which are of the same type as the first machine; accessing a plurality of computer readable logs corresponding to the first machine and the second machines, the computer readable logs for each second machine comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determining a set of statistical metrics characterising a difference between the target sensor log and each prior sensor log; selecting a sub-set of the prior sensor logs in dependence upon the statistical metrics; analysing the maintenance logs to correlate each prior sensor log included in the subset to one or more correlated maintenance tasks; selecting a

Abstract: A diaper is adapted for capturing and isolating bodily waste of a wearer. The diaper is constructed of a fabric blank folded to form front and rear waistlines of the diaper, a crotch region located between the front and rear waistlines, and a pair of leg openings. The fabric blank includes an outside shell and an adjustable inside panel. The inside panel is movable during wear from a normal wear position, wherein the crotch region is substantially uncovered by the panel, to a waste-isolating position, wherein the crotch region is substantially covered by the panel.

Abstract: A utility hand-piece is adapted for being worn on a hand of a user. The hand-piece includes a body portion adapted for covering at least a portion of the hand, and incorporating at least one fluid channel. A fluid inlet is formed with the body portion and communicates with the fluid channel. A fluid outlet is formed with the body portion and communicates with the fluid channel downstream of the fluid inlet. Upon connecting a fluid source to the hand-piece, fluid is transferred from the fluid inlet through the fluid channel and dispensed from the body portion through the fluid outlet.

Abstract: A utility hand-piece is adapted for being worn on a hand of a user. The hand-piece includes a body portion adapted for covering at least a portion of the hand, and incorporating at least one fluid channel. A fluid inlet is formed with the body portion and communicates with the fluid channel. A fluid outlet is formed with the body portion and communicates with the fluid channel downstream of the fluid inlet. Upon connecting a fluid source to the hand-piece, fluid is transferred from the fluid inlet through the fluid channel and dispensed from the body portion through the fluid outlet.

Abstract: A utility hand-piece is adapted for being worn on a hand of a user. The hand-piece includes a body portion adapted for covering at least a portion of the hand, and incorporating at least one fluid channel. A fluid inlet is formed with the body portion and communicates with the fluid channel. A fluid outlet is formed with the body portion and communicates with the fluid channel downstream of the fluid inlet. Upon connecting a fluid source to the hand-piece, fluid is transferred from the fluid inlet through the fluid channel and dispensed from the body portion through the fluid outlet.

Abstract: A utility hand-piece is adapted for being worn on a hand of a user. The hand-piece includes a body portion adapted for covering at least a portion of the hand, and incorporating at least one fluid channel. A fluid inlet is formed with the body portion and communicates with the fluid channel. A fluid outlet is formed with the body portion and communicates with the fluid channel downstream of the fluid inlet. Upon connecting a fluid source to the hand-piece, fluid is transferred from the fluid inlet through the fluid channel and dispensed from the body portion through the fluid outlet.

Abstract: A utility hand-piece is designed for being worn on a hand of a user to hold an elongated object. The hand-piece includes a wrist wrap adapted for extending around a wrist of the user. A finger wrap is formed with the wrist wrap. The finger wrap is adapted for residing adjacent a back side of the hand, and extends along at least one finger of the user. A fastener tab secures the elongated object to the finger wrap. The finger wrap defines a passage for receiving and positioning a distal end of the object, such that the distal end projects from the passage on a palm side of the hand.