Abstract: An online system evaluates different item assortments for a physical warehouse having limited capacity to stock items. Each item assortment is stocked at the physical warehouse in proportion to an assortment split weight. The items at the warehouse are available for users to order, for example to be gathered by a picker and physically delivered to users near the warehouse. Rather than display all items actually stocked at the physical warehouse to all users, the different item assortments are displayed to different users. Users may order items from the assigned item assortment and, because both item assortments are actually stocked at the physical warehouse, orders from either item assortment may be successfully fulfilled for delivery. The different user interfaces thus permit evaluation of the preferred item assortment by users while maintaining expected delivery capability and while using the same storage capacity of the physical warehouse.

Abstract: An inventory interaction model predicts user interactions with items to be included in an item assortment in a warehouse. The item is described with features that include the co-located items and the respective user interactions, so that the item interactions for the evaluated item incorporate item-item effects in its predictions. To train the model effectively in the absence of prior interaction data for an item, training examples are generated from existing item and user interaction data of co-located items by selecting a portion of the items for the examples and including co-located item data, labeling the training example output with item interactions for the item. The trained model is then applied for an item assortment by describing co-located item features of the item assortment in evaluating candidate items.

Abstract: An inventory interaction model predicts user interactions with items of a location for a physical warehouse included with other warehouses in a region. The location is described with features that include the nearby locations and the respective user interactions with the respective item assortments, so that the item interactions for the evaluated location incorporate location-location effects in model predictions. To effectively train the model in the absence of prior interaction data for a location, training examples are generated from existing locations and user interaction data of item assortments by selecting a portion of the locations for the training examples and including nearby location interaction data, labeling the training example output with item interactions for the location. The trained model is then applied for an item assortment at a location by describing nearby locations in evaluating candidate locations and item assortments.

Abstract: A composite antenna mount includes a polymer matrix, a plurality of particles dispersed through the polymer matrix, at least some of the particles including a ferromagnetic coating, and a plurality of electrically conductive filaments electrically connecting the ferromagnetic coatings of the particles. The ferromagnetic coating each coated particle is configured to absorb electromagnetic radiation in a specified frequency range.

Abstract: An online concierge system facilitates creation of shopping lists of items for ordering from a physical retail store and at least partial self-service fulfillment of orders by the customer. To support fulfillment by the customer, the online concierge system may intelligently select one or more items of the order to be picked by a third-party picker and prepopulated to a shopping cart reserved for the customer in advance of the customer arriving at the retail location. The items for prepopulating may be selected based on various factors that optimize prepopulation decisions on an item-by-item basis in accordance with various machine learning models. The online concierge system may furthermore facilitate procurement of the remaining items by the customer through a customer client device that may track item procurement and/or provide guidance for locating items.

Abstract: An architecture is disclosed for an Implantable Pulse Generator having improved compliance voltage monitoring and adjustment software and hardware. Software specifies which stimulation pulses are to be measured as relevant to monitoring and adjusting the compliance voltage. Preferably, specifying such pulses occurs by setting a compliance monitoring instruction (e.g., a bit) in the program that defines the pulse, and the compliance monitor bit instruction may be set at a memory location defining a particular pulse phase during which the compliance voltage should be monitored. When a compliance monitor instruction issues, the active electrode node voltages are monitored and compared to desired ranges to determine whether they are high or low. Compliance logic operates on these high/low signals and processes them to decide whether to issue a compliance voltage interrupt to the microcontroller, which can then command the compliance voltage generator to increase or decrease the compliance voltage.

Abstract: An online concierge system facilitates ordering of items by customers, procurement of the items from physical retailers by pickers assigned to the orders, and delivery of the orders to customers. To enable efficient procurement, the online concierge system may facilitate preemptive picking of items for staging at a rapid fulfillment area of the physical retailer, and pickers may selectively pick items from the rapid fulfillment area instead of their standard storage locations. Decisions on which items to preemptively pick may be based on a predictive optimization model that scores and ranks items for predictive picking in accordance with various optimization criteria. In the course of fulfilling orders, pickers may furthermore be assigned to replenish items from the standard storage locations to the rapid fulfillment area to satisfy future predicted or actual orders in a manner that optimizes a cost metric.

Abstract: An online concierge system facilitates ordering of items by customers, procurement of the items from physical retailers by pickers assigned to the orders, and delivery of the orders to customers. To enable efficient procurement, the online concierge system may facilitate preemptive picking of items for staging at a rapid fulfillment area of the physical retailer, and pickers may selectively pick items from the rapid fulfillment area instead of their standard storage locations. Decisions on which items to preemptively pick may be based on a predictive optimization model that scores and ranks items for predictive picking in accordance with various optimization criteria. In the course of fulfilling orders, pickers may furthermore be assigned to replenish items from the standard storage locations to the rapid fulfillment area to satisfy future predicted or actual orders in a manner that optimizes a cost metric.

Abstract: An architecture is disclosed for an Implantable Pulse Generator having improved compliance voltage monitoring and adjustment software and hardware. Software specifies which stimulation pulses are to be measured as relevant to monitoring and adjusting the compliance voltage. Preferably, specifying such pulses occurs by setting a compliance monitoring instruction (e.g., a bit) in the program that defines the pulse, and the compliance monitor bit instruction may be set at a memory location defining a particular pulse phase during which the compliance voltage should be monitored. When a compliance monitor instruction issues, the active electrode node voltages are monitored and compared to desired ranges to determine whether they are high or low. Compliance logic operates on these high/low signals and processes them to decide whether to issue a compliance voltage interrupt to the microcontroller, which can then command the compliance voltage generator to increase or decrease the compliance voltage.

Abstract: A compliance voltage management algorithm is disclosed for managing the compliance voltage, VH, that powers the DAC circuitry in a stimulator device. A user can use a user interface associated with an external programming device to define a time-varying stimulation waveform to be programmed into the stimulator device. The algorithm analyzes the prescribed waveform and determines a number of groups of pulses that will be treated similarly from a VH management standpoint. Optimal compliance voltages are determined for each group, as are the rise and fall rates at which VH is able to change at transitions between groups. These rise or fall rates in VH are then used to set when the compliance voltage should increase or decrease. For example, the algorithm will automatically set VH to start rising in advance of a transition so that it is at the proper higher value when the transition occurs.

Abstract: An architecture is disclosed for an Implantable Pulse Generator having improved compliance voltage monitoring and adjustment software and hardware. Software specifies which stimulation pulses are to be measured as relevant to monitoring and adjusting the compliance voltage. Preferably, specifying such pulses occurs by setting a compliance monitoring instruction (e.g., a bit) in the program that defines the pulse, and the compliance monitor bit instruction may be set at a memory location defining a particular pulse phase during which the compliance voltage should be monitored. When a compliance monitor instruction issues, the active electrode node voltages are monitored and compared to desired ranges to determine whether they are high or low. Compliance logic operates on these high/low signals and processes them to decide whether to issue a compliance voltage interrupt to the microcontroller, which can then command the compliance voltage generator to increase or decrease the compliance voltage.

Abstract: An architecture is disclosed for an Implantable Pulse Generator having improved compliance voltage monitoring and adjustment software and hardware. Software specifies which stimulation pulses are to be measured as relevant to monitoring and adjusting the compliance voltage. Preferably, specifying such pulses occurs by setting a compliance monitoring instruction (e.g., a bit) in the program that defines the pulse, and the compliance monitor bit instruction may be set at a memory location defining a particular pulse phase during which the compliance voltage should be monitored. When a compliance monitor instruction issues, the active electrode node voltages are monitored and compared to desired ranges to determine whether they are high or low. Compliance logic operates on these high/low signals and processes them to decide whether to issue a compliance voltage interrupt to the microcontroller, which can then command the compliance voltage generator to increase or decrease the compliance voltage.

Abstract: An architecture is disclosed for an Implantable Pulse Generator having improved compliance voltage monitoring and adjustment software and hardware. Software specifies which stimulation pulses are to be measured as relevant to monitoring and adjusting the compliance voltage. Preferably, specifying such pulses occurs by setting a compliance monitoring instruction (e.g., a bit) in the program that defines the pulse, and the compliance monitor bit instruction may be set at a memory location defining a particular pulse phase during which the compliance voltage should be monitored. When a compliance monitor instruction issues, the active electrode node voltages are monitored and compared to desired ranges to determine whether they are high or low. Compliance logic operates on these high/low signals and processes them to decide whether to issue a compliance voltage interrupt to the microcontroller, which can then command the compliance voltage generator to increase or decrease the compliance voltage.

Abstract: An architecture is disclosed for an Implantable Pulse Generator having improved compliance voltage monitoring and adjustment software and hardware. Software specifies which stimulation pulses are to be measured as relevant to monitoring and adjusting the compliance voltage. Preferably, specifying such pulses occurs by setting a compliance monitoring instruction (e.g., a bit) in the program that defines the pulse, and the compliance monitor bit instruction may be set at a memory location defining a particular pulse phase during which the compliance voltage should be monitored. When a compliance monitor instruction issues, the active electrode node voltages are monitored and compared to desired ranges to determine whether they are high or low. Compliance logic operates on these high/low signals and processes them to decide whether to issue a compliance voltage interrupt to the microcontroller, which can then command the compliance voltage generator to increase or decrease the compliance voltage.

Abstract: An architecture is disclosed for an Implantable Pulse Generator having improved compliance voltage monitoring and adjustment software and hardware. Software specifies which stimulation pulses are to be measured as relevant to monitoring and adjusting the compliance voltage. Preferably, specifying such pulses occurs by setting a compliance monitoring instruction (e.g., a bit) in the program that defines the pulse, and the compliance monitor bit instruction may be set at a memory location defining a particular pulse phase during which the compliance voltage should be monitored. When a compliance monitor instruction issues, the active electrode node voltages are monitored and compared to desired ranges to determine whether they are high or low. Compliance logic operates on these high/low signals and processes them to decide whether to issue a compliance voltage interrupt to the microcontroller, which can then command the compliance voltage generator to increase or decrease the compliance voltage.