Abstract: Various embodiments relate generally to computer science, data science, software, and computer program and platform architectures, including processing data received at an adaptive distribution platform to identify a point of time, initiating automatic replenishment of the item by the adaptive distribution platform if the point of time is substantially within the date range, transmitting a message to a client, the message including a characteristic of the item and a control user input, receiving a response to the message, processing the response to determine whether to adjust the scheduled delivery to replenish the item, generating a confirmation message to the client, transmitting a control signal from the adaptive distribution platform to a system, and adapting a predicted distribution event associated with the item.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to facilitate adaptive scheduling automatically to optimally distribute items, such as shipping an item in accordance with an adapted frequency for a subscription. In some examples, a method may include identifying item characteristics associated with an item, determining a frequency based on at least an item characteristic in association with a subset of subscriber accounts, generating data representing a frequency and a subset of the item characteristics to integrate with a web page generated for a merchant computing system, and transmitting the formatted data to a user interface to display a display portion based on the formatted data as an integrated portion of an integrated web page including the web page.

Abstract: Various embodiments relate generally to computer science, software, and computer program and platform architectures, including receiving input data configured to identify one or more items, the input data being converted from a first data format to a second data format, parsing the input data in the second data format to extract event data associated with the one or more items, evaluating the event data to determine shipment data configured to identify a location, an account, and a first option associated with the one or more items, comparing the input data in the second data format to a threshold to determine a statistical probability associated with the one or more items, calling a data service to retrieve other data associated with the one or more items, and generating a retrieval option associated with other items if the statistical probability is greater than the threshold and the other data indicates the device is within a numerical range of a location at which the item is stored.

Abstract: Various embodiments relate generally to computer science, software, and computer program and platform architectures, including receiving input data configured to identify one or more items, the input data being converted from a first data format to a second data format, parsing the input data in the second data format to extract event data associated with the one or more items, evaluating the event data to determine shipment data configured to identify a location, an account, and a first option associated with the one or more items, comparing the input data in the second data format to a threshold to determine a statistical probability associated with the one or more items, calling a data service to retrieve other data associated with the one or more items, and generating a retrieval option associated with other items if the statistical probability is greater than the threshold and the other data indicates the device is within a numerical range of a location at which the item is stored.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface and one or more sensors, and, more specifically, to one or more sensors that implements specialized logic to facilitate in-situ monitoring of inventories of consumables and automatic reordering of a consumable. In some examples, a method may include receiving sensor data representing usage of a device configured to process a consumable, characterizing the usage to form a characterized value, correlating data representing a unit of the consumable processed via the device to a characterized value of the usage, adjusting an amount representing an inventory of the consumable, detecting an amount of the inventory of the consumable is associated with one or more ranges of threshold values, and generating data representing a request to replenish the inventory of the consumable.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface and one or more sensors, and, more specifically, to one or more sensors that implements specialized logic to facilitate in-situ monitoring of inventories of consumables and automatic reordering of a consumable. In some examples, a method may include receiving sensor data representing usage of a device configured to process a consumable, characterizing the usage to form a characterized value, correlating data representing a unit of the consumable processed via the device to a characterized value of the usage, adjusting an amount representing an inventory of the consumable, detecting an amount of the inventory of the consumable is associated with one or more ranges of threshold values, and generating data representing a request to replenish the inventory of the consumable.

Abstract: Various embodiments relate generally to computer science, software, and computer program and platform architectures, including receiving input data configured to identify one or more items, the input data being converted from a first data format to a second data format, parsing the input data in the second data format to extract event data associated with the one or more items, evaluating the event data to determine shipment data configured to identify a location, an account, and a first option associated with the one or more items, comparing the input data in the second data format to a threshold to determine a statistical probability associated with the one or more items, calling a data service to retrieve other data associated with the one or more items, and generating a retrieval option associated with other items if the statistical probability is greater than the threshold and the other data indicates the device is within a numerical range of a location at which the item is stored.

Abstract: Various embodiments relate generally to computer science, software, and computer program and platform architectures, including receiving input data configured to identify one or more items, the input data being converted from a first data format to a second data format, parsing the input data in the second data format to extract event data associated with the one or more items, evaluating the event data to determine shipment data configured to identify a location, an account, and a first option associated with the one or more items, comparing the input data in the second data format to a threshold to determine a statistical probability associated with the one or more items, calling a data service to retrieve other data associated with the one or more items, and generating a retrieval option associated with other items if the statistical probability is greater than the threshold and the other data indicates the device is within a numerical range of a location at which the item is stored.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface and one or more sensors, and, more specifically, to one or more sensors that implements specialized logic to facilitate in-situ monitoring of inventories of consumables and automatic reordering of a consumable. In some examples, a method may include receiving sensor data representing usage of a device configured to process a consumable, characterizing the usage to form a characterized value, correlating data representing a unit of the consumable processed via the device to a characterized value of the usage, adjusting an amount representing an inventory of the consumable, detecting an amount of the inventory of the consumable is associated with one or more ranges of threshold values, and generating data representing a request to replenish the inventory of the consumable.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface and one or more sensors, and, more specifically, to one or more sensors and/or computing algorithms that implement specialized logic to facilitate in-situ monitoring and characterization of resource usage and/or device usage to determine usage of one or more consumables to updates inventories of consumables for automated replenishment of a consumable. In at least one example, sensors and/or computing algorithms facilitate formation of an automated home inventory replenishment network. In some examples, a method may include accessing sensor data if a consumable is processed, determining multiple modes of operation for a device, correlating a type of consumable associated with a mode of operation, and updating an amount of inventory for a consumable responsive to an amount consumed and a modified consumption rate.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to facilitate distribution of items in accordance with an automatically adaptive schedule, for example, via an interface. In some examples, a method may include predicting data representing, for example, a zone of time in which depletion of an item is predicted. The method may monitor whether to replenish the item, and transmit via a network an electronic message including one or more item characteristics associated with the item to be replenished. The method may also include receiving another electronic message, and transmitting a control message to a merchant computing system to initiate adaptive distribution to replenish the item, among other things.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to facilitate adaptive scheduling automatically to optimally distribute items, such as shipping an item in accordance with an adapted frequency for a subscription. In some examples, a method may include identifying item characteristics associated with an item, determining a frequency based on at least an item characteristic in association with a subset of subscriber accounts, generating data representing a frequency and a subset of the item characteristics to integrate with a web page generated for a merchant computing system, and transmitting the formatted data to a user interface to display a display portion based on the formatted data as an integrated portion of an integrated web page including the web page.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to facilitate predictive consumption of a sample of an item in accordance with an automatically adaptive schedule, for example, via an interface. In some examples, a method may include identifying data representing a replica of an item for transmission to a location associated with an electronic account, identifying a characteristic associated with a user or an item, predicting a date of consumption of the replica, and generating a subset of data included in an electronic message to initiate executable instructions to generate feedback regarding the replica relative to the date of consumption, among other things.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface and one or more sensors, and, more specifically, to one or more sensors that implements specialized logic to facilitate in-situ monitoring of inventories of consumables and automatic reordering of a consumable. In some examples, a method may include receiving sensor data representing usage of a device configured to process a consumable, characterizing the usage to form a characterized value, correlating data representing a unit of the consumable processed via the device to a characterized value of the usage, adjusting an amount representing an inventory of the consumable, detecting an amount of the inventory of the consumable is associated with one or more ranges of threshold values, and generating data representing a request to replenish the inventory of the consumable.

Abstract: A laser based tunable high resolution ESCA (Electron Spectroscopy for Chemical Analysis) system in which harmonics of a subpicosecond laser source are used to carry out core level photoemission is provided wherein photon energies tunable to 80 eV have been achieved and energies up to 150 eV or more are possible. The harmonic light is of extremely narrow bandwidth and spectrally bright which can be focussed by using reflective optics of gratings to an extremely small spot of well below one micron to permit high spatial resolution. When used in conjunction with appropriate electron objects, high resolution chemically sensitive mapping of device-size features is possible.