Abstract: A failure recommendation system for a command line interface (CLI) uses machine learning to predict the most likely command to correct an unsuccessful or failed attempt to perform an intended operation using the CLI. The failure recommendation system is based on a conditional probability model trained on failure-success pairs of commands from CLI telemetry data to learn the most likely command to remediate a failure. The conditional probability model predicts the most likely command based on a failure type and the failed command. The failure type is identified through a failure type classifier and is used to select the most likely command to remediate a failure from the different events that may lead to a failure.

Abstract: A failure recommendation system for a command line interface (CLI) uses machine learning to predict the most likely command to correct an unsuccessful or failed attempt to perform an intended operation using the CLI. The failure recommendation system is based on a conditional probability model trained on failure-success pairs of commands from CLI telemetry data to learn the most likely command to remediate a failure. The conditional probability model predicts the most likely command based on a failure type and the failed command. The failure type is identified through a failure type classifier and is used to select the most likely command to remediate a failure from the different events that may lead to a failure.

Abstract: An apparatus for atomic scale processing is provided. The apparatus may include a reactor and an inductively coupled plasma source. The reactor may have inner and outer surfaces such that a portion of the inner surfaces define an internal volume of the reactor. The internal volume of the reactor may contain a fixture assembly to support a substrate wherein the partial pressure of each background impurity within the internal volume may be below 10?6 Torr to reduce the role of said impurities in surface reactions during atomic scale processing.

Abstract: An apparatus for atomic scale processing is provided. The apparatus may include a reactor (100) and an inductively coupled plasma source (10). The reactor may have inner (154) and outer surfaces (152) such that a portion of the inner surfaces define an internal volume (156) of the reactor. The internal volume of the reactor may contain a fixture assembly (158) to support a substrate (118) wherein the partial pressure of each background impurity within the internal volume may be below 10?6 Torr to reduce the role of said impurities in surface reactions during atomic scale processing.

Abstract: An apparatus for atomic scale processing includes: a reactor having inner and outer surfaces; where at least a portion of the inner surfaces define an internal volume of the reactor; a fixture assembly positioned within the internal volume of the reactor having a surface configured to hold a substrate within the internal volume of the reactor; a vacuum pump in communication with the reactor; at least one reactor pressure control device; and a controller in communication with the at least one reactor pressure control device, where the controller is configured to activate and deactivate the at least one reactor pressure control device to increase and decrease the pressure within the internal volume of the reactor, where the increase in the pressure within the internal volume of the reactor increases the temperature of the substrate from an initial temperature.

Abstract: A failure recommendation system for a command line interface (CLI) uses machine learning to predict the most likely command to correct an unsuccessful or failed attempt to perform an intended operation using the CLI. The failure recommendation system is based on a conditional probability model trained on failure-success pairs of commands from CLI telemetry data to learn the most likely command to remediate a failure. The conditional probability model predicts the most likely command based on a failure type and the failed command. The failure type is identified through a failure type classifier and is used to select the most likely command to remediate a failure from the different events that may lead to a failure.

Abstract: An apparatus for atomic scale processing is provided. The apparatus may include a reactor (100) and an inductively coupled plasma source (10). The reactor may have inner (154) and outer surfaces (152) such that a portion of the inner surfaces define an internal volume (156) of the reactor. The internal volume of the reactor may contain a fixture assembly (158) to support a substrate (118) wherein the partial pressure of each background impurity within the internal volume may be below 10?6 Torr to reduce the role of said impurities in surface reactions during atomic scale processing.

Abstract: An apparatus for providing solitary bees for pollination, comprising a bee nest and a portable on-site incubator. The bee nest can comprise a plurality of corrugated sheets, each sheet comprising a plurality of flutes. When the sheets are stacked together, the flutes form cavities arranged in a tessellating pattern. The portable incubator can comprise a chamber for holding dormant adult bees, an opening providing access to the chamber, a passage for exiting of bees from the chamber, means for heating the chamber, means for controlling chamber temperature, and a power supply. Dormant adult bees placed in the incubator are stimulated into activity and leave the incubator. Female bees that leave later lay eggs in the bee nest.

Abstract: An aquatic harvester for use with an aquatic craft, the aquatic craft including sides, a bow and a stern, the aquatic harvester including a frame which includes one or more arms, the or each arm having a forward end portion and the or each arm being pivotally connected to the aquatic craft at a position spaced from the forward end, said forward end of the or each arm being adapted for connection with an implement, the apparatus further including means for controlling the pivotal position of the or each arm relative to the aquatic craft.