Abstract: An interactive monitoring and control system for a mineral extraction system includes one or more processors configured to receive sensor data indicative of properties of components of the mineral extraction system and to provide a user interface for display via a display screen. The user interface includes a representation of the components of the mineral extraction system, includes the sensor data indicative of the properties of the components of the mineral extraction system, and enables a user to provide inputs to adjust the components of the mineral extraction system.

Abstract: The present invention relates to a stable pharmaceutical composition of tetrofosmin or pharmaceutically acceptable salts thereof. It also relates to a lyophilized non-radioactive kit which upon reconstitution with 99mTc-pertechnetate solution gives a stable 99mTc-tetrofosmin radiopharmaceutical composition. It also provides process for the preparation of said radiopharmaceutical compositions and their use in diagnostic imaging procedures. The compositions provide desirable technical attributes such as stability, high radiochemical purity (RCP) and desired bio-distribution.

Abstract: Storage devices and systems are capable of dynamically managing QoS requirements associated with host applications via a management interface. The management interface may the enable storage devices to: (i) decide which data needs to be transferred back to the hosts, (ii) choose to skip portions of the data transferred back to the hosts to improve throughput and maintain low cost, and (iii) operate contention resolutions with host applications. Furthermore, storage devices and systems may achieve a virtual throughput that may be greater than its actual physical throughput. The management interface may also be operated at an application level, which advantageously allows the devices and systems the capabilities of managing contention resolutions of host applications, and managing (changing, observing, fetching, etc.) one or more QoS requirements for each host application.

Abstract: Aspects directed towards configuring new storage devices in a storage device pool are provided. In one aspect, a storage management device receives optimization information that includes at least one optimization learned by at least one source data storage device while part of a data storage system. A new data storage device for the data storage system is then configured with the at least one device optimization. In another aspect, a data storage device receives optimization information from a storage management device coupled to a plurality of pooled data storage devices, which includes the data storage device and at least one source data storage device. For this aspect, the optimization information includes at least one optimization learned by the at least one source data storage device while coupled to the storage management device. The data storage device is then configured to include the at least one device optimization.

Abstract: Methods, systems, and apparatuses for storage device pool management based on storage device logical to physical (L2P) table information are provided. One such data storage system includes data storage devices each including a non-volatile memory; and a storage management device configured to receive L2P table information from at least two of the data storage devices; receive host data from a host device to be stored in one or more of the data storage devices; select, based on the L2P table information from the at plurality of data storage devices and the size of the host data, a target data storage device from the plurality of data storage devices; and send the host data to the target data storage device.

Abstract: Aspects directed towards data storage management are provided. In one aspect, a data storage system receives fragmentation level information from data storage devices, and host data from a host device to be stored in the data storage devices. Based on the received fragmentation level information, a target data storage device is selected from the data storage devices, and the host data is sent to the target data storage device. In another aspect, a data storage device determines threshold conditions that trigger a defragmentation process. For this aspect, a fragmentation level metric indicating a proximity of the data storage device to initiating the defragmentation process is calculated based on the threshold conditions and a current amount of data stored in a non-volatile memory (NVM). The fragmentation level metric is then sent to a storage management device.

Abstract: Example methods and systems are directed to a managed inventory. A database may store information regarding items owned by a user. The information regarding an item may include a quantity owned and one or more triggering events. Based on the occurrence of a triggering event, an order for the item may be placed without user intervention. Data to the database may be provided by one or more sensors. Triggering events may be defined in terms of sensor data. The triggering event may be defined by a user or through machine learning. The order may be placed using a predetermined modality or a dynamically-determined modality based on one or more criteria, such as price, shipping speed, and the urgency of the order.

Abstract: A method of performing convolution in a neural network with variable dilation rate is provided. The method includes receiving a size of a first kernel and a dilation rate, determining at least one of size of one or more disintegrated kernels based on the size of the first kernel, a baseline architecture of a memory and the dilation rate, determining an address of one or more blocks of an input image based on the dilation rate, and one or more parameters associated with a size of the input image and the memory. Thereafter, the one or more blocks of the input image and the one or more disintegrated kernels are fetched from the memory, and an output image is obtained based on convolution of each of the one or more disintegrated kernels and the one or more blocks of the input image.

Abstract: Example methods and systems are directed to a managed inventory. A database may store information regarding items owned by a user. The information regarding an item may include a quantity owned and one or more triggering events. Based on the occurrence of a triggering event, an order for the item may be placed without user intervention. Data to the database may be provided by one or more sensors. Triggering events may be defined in terms of sensor data. The triggering event may be defined by a user or through machine learning. The order may be placed using a predetermined modality or a dynamically-determined modality based on one or more criteria, such as price, shipping speed, and the urgency of the order.

Abstract: A data storage device and method are provided for host multi-command queue grouping based on write-size alignment in a multi-queue-depth environment. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to provide a host with an indication of a required amount of data needed to program a set of multi-level cell blocks in the memory; receive an assurance from the host that the host will be providing the data storage device with the required amount of data; and based on the assurance received from the host, program the set of multi-level cell blocks as data is received from the host but before the required amount of data is received from the host. Other embodiments are possible, and each of the embodiments can be used alone or together in combination.

Abstract: An electrical connector assembly includes an electrical terminal defining a pair of retaining ridges, a connector housing having a terminal cavity extending therethrough from a first opening to a second opening and a fixed terminal lock nib that projects inwardly into the terminal cavity from a rigid first wall to engage a first ridge of the pair of retaining ridges of the electrical terminal, and a terminal retainer inserted within the connector housing proximate the first opening and removably retained to the connector housing by a flexible retaining arm. The terminal retainer further includes a flexible terminal lock arm having a moveable terminal lock nib that projects inwardly into the terminal cavity from the flexible terminal lock arm to engage a second ridge of the pair of retaining ridges of the electrical terminal, thereby inhibiting removal of the electrical terminal from the terminal cavity through the second opening.

Abstract: A method for creating product compatibility rules for an enterprise resource planning system. The method includes obtaining, by a processor, product compatibility rules defined for a plurality of products in a first standard format. The product compatibility rules define, for each product, a plurality of parameters and one or more configurations associated with each of the plurality of parameters which are at least one of compatible and non-compatible with the corresponding product. The method further includes generating, by the processor, a plurality of unique combinations of configurations for each product and identifying, by the processor, one or more products of the plurality of products for each unique combination of configurations. Further, the method includes creating, by the processor, product compatibility rules for the enterprise resource planning system by defining a relationship between the one or more products and each unique combination of configurations in a second standard format.

Abstract: A battery energy storage system is disclosed that receives energy from an electrical grid and supplies electrical energy to one or more microgrids. The battery energy storage system comprises a power conversion system arranged to charge a battery with the energy from the electrical grid and discharge the battery to supply electrical energy to the one or more microgrids. An energy control system controller communicatively coupled to the power conversion system manages the energy drawn from the electrical grid to charge the battery and to manage the energy discharged from the battery to supply electrical energy to the one or more microgrids.

Abstract: Example methods and systems are directed to a managed inventory. A database may store information regarding items owned by a user. The information regarding an item may include a quantity owned and one or more triggering events. Based on the occurrence of a triggering event, an order for the item may be placed without user intervention. Data to the database may be provided by one or more sensors. Triggering events may be defined in terms of sensor data. The triggering event may be defined by a user or through machine learning. The order may be placed using a predetermined modality or a dynamically-determined modality based on one or more criteria, such as price, shipping speed, and the urgency of the order.

Abstract: Providing constant fixed commands to memory dies within a data storage device may result in hardware and firmware overheads impacting the performance at a flash interface module (FIM) because the FIM has to handle both the constant fixed commands and the overheads associated with the constant fixed commands. To avoid the impact on performance at the FIM, multiple fixed commands may be combined into individual multi-commands that may be provided to the memory dies. The use of multi-commands reduces hardware and firmware overheads at the FIM relative to the constant fixed commands, which improves performance of the data storage device because the saturation of the FIM is decreased.

Abstract: Various devices, such as storage devices or systems are configured to efficiently process and update logical mappings within control table sets. Control table sets are often groupings of logical mapping corresponding to the logical locations of data requested by a host-computing device and the physical locations of the data within the memory array. As data is written and erased, these mappings must be updated within the control table set. Received changes to these mappings are typically stored and updated in two locations: a cache memory and a control table update list. By tracking and marking various control table sets as dirty or having undergone multiple changes, additional received updates can be stored and updated in only the cache memory, bypassing the second control table change list. By only utilizing one method of updating control table sets, processing overhead is reduced and various read or write activities are more efficiently done.

Abstract: In an embodiment, a UE receives a first uplink grant for a first RAT (e.g., 5G NR) and a second uplink grant for a second RAT (e.g., LTE). In one embodiment, the UE schedules an uplink transmission on the first RAT (e.g., by selectively dropping the uplink transmission on particular resource blocks) so as to manage an amount of time that is based on concurrent uplink transmissions on both the first and second RATs are performed. In another embodiment, the UE establishes a first period of time where a BSR transmitted by the UE on the first RAT is adjusted based on scheduling of concurrent uplink multi-RAT transmissions, and a second period of time where no BSR is transmitted by the UE on the first RAT based where concurrent uplink transmissions on both the first and second RATs are not permitted to be scheduled.

Abstract: An embodiment may involve persistent storage containing a machine learning trainer application configured to apply one or more learning algorithms. One or more processors may be configured to: obtain alert data from one or more computing systems; generate training vectors from the alert data, wherein elements within each of the training vectors include: results of a set of statistics applied to the alert data for a particular computing system of the one or more computing systems, and an indication of whether the particular computing system is expected to fail given its alert data; train, using the machine learning trainer application and the training vectors, a machine learning model, wherein the machine learning model is configured to predict failure of a further computing system based on operational alert data obtained from the further computing system; and deploy the machine learning model for production use.

Abstract: Non-volatile memory (NVM) dies of a data storage device, wherein on-chip latches of the dies are made available to a host device for use as volatile memory. In some examples, a data storage controller dynamically determines when the latches of a particular NVM die of an NVM array are available for use as volatile memory and exports those particular latches to the host device for use as random access memory (RAM). In other examples, the data storage controller dynamically determines when particular dies of the NVM array of dies are available and exports all latches of those dies to the host device for use as RAM. The data storage controller may rotate NVM die usage so that, over time, different dies are used for latch-based volatile memory while other dies are used for NVM storage. Usage profiles are described that allow the host device to select particular latch usage configurations.

Abstract: Storage devices can be configured to desirably reduce the number of times a zone reset or erasure occur via the use of one or more paired overwrite memory blocks. These storage devices can include a plurality of memory devices with some of these memory devices designated as overwrite memory devices. A controller within the storage device can be configured to direct the storage device to generate one or more subsets within the memory devices such as zones, pair each of subsets with at least one or more overwrite memory devices, store data sequentially within the subset of memory devices, and store any received overwrite data in the overwrite memory devices in chronological order. Data stored within the subsets of memory devices are not erased and instead of being overwritten directly, are instead pointed via a control table to a location in the overwrite memory devices storing the corresponding overwrite data.