Abstract: With a forever incremental snapshot configuration and a typical caching policy (e.g., least recently used), a storage appliance may evict stable data blocks of an older snapshot, perhaps unchanged data blocks of the snapshot baseline. If stable data blocks have been evicted, restore of a recent snapshot will suffer the time penalty of downloading the stable blocks for restoring the recent snapshot. Creating synthetic baseline snapshots and refreshing eviction data of stable data blocks can avoid eviction of stable data blocks and reduce the risk of violating a recovery time objective.

Abstract: A software developer can use a local browser, running on a local machine of the developer in a first location to access a real device (e.g., a smart phone) at a second location, such as a datacenter. The developer can select and control the remote device, in the second location. A mirrored display of the remote device can be generated on the local machine by transmitting a video feed of the screen of the remote device to the local machine. The developer can interact with the mirrored display, and the interactions can be transmitted to the remote device. The developer can activate an accessibility mode via the local machine to test accessibility features of a program.

Abstract: The use of a megastigmane derivative to enhance the sweetness of a sweetness modifier and to decrease the amount of a sweetness modifier used in a consumable is provided.

Abstract: The subject disclosure provides for a mechanism implemented with neural networks through machine learning to predict wear and relative performance metrics for performing repairs on drill bits in a next repair cycle, which can improve decision making by drill bit repair model engines, drill bit design, and help reduce the cost of drill bit repairs. The machine learning mechanism includes obtaining drill bit data from different data sources and integrating the drill bit data from each of the data sources into an integrated dataset. The integrated dataset is pre-processed to filter out outliers. The filtered dataset is applied to a neural network to build a machine learning based model and extract features that indicate significant parameters affecting wear. A repair type prediction is determined with the applied machine learning based model and is provided as a signal for facilitating a drill bit operation on a cutter of the drill bit.

Abstract: A software developer can use a local browser, running on a local machine of the developer in a first location to access a real device (e.g., a smart phone) at a second location, such as a datacenter. The developer can select and control the remote device, in the second location. A mirrored display of the remote device can be generated on the local machine by transmitting a video feed of the screen of the remote device to the local machine. The developer can interact with the mirrored display, and the interactions can be transmitted to the remote device. The developer can activate an accessibility mode via the local machine to test accessibility features of a program.

Abstract: System and methods for tuning equation of state (EOS) characterizations are presented. Pressure-volume-temperature (PVT) data is obtained for downhole fluids within a reservoir formation. A component grouping for an EOS model of the downhole fluids is determined, based on the obtained PVT data. The component grouping is used to estimate properties of the downhole fluids for a current stage of a downhole operation within the formation. A machine learning model is trained to minimize an error between the estimated properties and actual fluid properties measured during the current stage of the operation, where the component grouping for the EOS model is iteratively adjusted by the machine learning model until the error is minimized. The EOS model is tuned using the adjusted component grouping. Fluid properties are estimated for one or more subsequent stages of the downhole operation to be performed along the wellbore, based on the tuned EOS model.

Abstract: A storage tier manager efficiently creates different representations of a dataset backup for different retention periods. Each of the representations of the dataset backup is distinctly identifiable despite initially representing a same dataset backup. The representations are structured metadata corresponding to the dataset backup. One representation is a cached backup version of the dataset backup (“cached backup” or “cached representation”) provided for low latency access while residing at a storage tier of the backup appliance for a relatively short retention period according to a lifecycle management policy. The other representation is a cloud backup version of the dataset backup (“cloud backup” or “cloud representation”) provided for persisting into cloud storage for a longer retention period according to the lifecycle management policy.

Abstract: A Lepidium meyenii extract, as well as aromatic alkamides thereof are described for use in compositions and methods for improving the taste of a consumable containing a component having an astringent, bitter or off-taste.

Abstract: With a forever incremental snapshot configuration and a typical caching policy (e.g., least recently used), a storage appliance may evict stable data blocks of an older snapshot, perhaps unchanged data blocks of the snapshot baseline. If stable data blocks have been evicted, restore of a recent snapshot will suffer the time penalty of downloading the stable blocks for restoring the recent snapshot. Creating synthetic baseline snapshots and refreshing eviction data of stable data blocks can avoid eviction of stable data blocks and reduce the risk of violating a recovery time objective.

Abstract: The use of verbascoside or a related compound thereof to enhance the sweetness of a sweetness modifier and to decrease the amount of a sweetness modifier used in a consumable is provided.

Abstract: The use of mucic acid gallate compounds in a non-sugar sweetener such as a steviol glycoside-containing consumable to provide lingering aftertaste specific masking effect is provided.

Abstract: With a forever incremental snapshot configuration and a typical caching policy (e.g., least recently used), a storage appliance may evict stable data blocks of an older snapshot, perhaps unchanged data blocks of the snapshot baseline. If stable data blocks have been evicted, restore of a recent snapshot will suffer the time penalty of downloading the stable blocks for restoring the recent snapshot. Creating synthetic baseline snapshots and refreshing eviction data of stable data blocks can avoid eviction of stable data blocks and reduce the risk of violating a recovery time objective.

Abstract: The use of ligustrosidic acid or a derivative thereof to enhance the sweetness of a sweetness modifier and to decrease the amount of a sweetness modifier used in a consumable is provided.

Abstract: The use of a secoiridoid glucoside or a polyphenol compound to enhance the sweetness, mask the bitter off-taste and/or improve the flavor perception of a sweetness modifier and to decrease the amount of a sweetness modifier used in a consumable is provided.

Abstract: A hydrocarbon field including thief zones can be modeled based on production history data and supplemental data constraining a thief-zone distribution across the field. In various embodiments, a numerical optimization approach involves creating a plurality of model thief-zone distributions with varying parameter values, parameterizing permeability maps obtained for the thief-zone distributions and aggregating across the thief-zone distributions to obtain distributions of coefficients associated with the parameterization, and then iteratively sampling the coefficient distributions, determining a permeability map of the model based on the selected coefficients, and measuring a deviation between the measured production history data and simulated production history data derived from the computational model until a match is achieved.

Abstract: The subject disclosure provides for a mechanism implemented with neural networks through machine learning to predict wear and relative performance metrics for performing repairs on drill bits in a next repair cycle, which can improve decision making by drill bit repair model engines, drill bit design, and help reduce the cost of drill bit repairs. The machine learning mechanism includes obtaining drill bit data from different data sources and integrating the drill bit data from each of the data sources into an integrated dataset. The integrated dataset is pre-processed to filter out outliers. The filtered dataset is applied to a neural network to build a machine learning based model and extract features that indicate significant parameters affecting wear. A repair type prediction is determined with the applied machine learning based model and is provided as a signal for facilitating a drill bit operation on a cutter of the drill bit.

Abstract: A storage appliance can be designed to facilitate efficient restore of multiple backed up files in a system that allows files to share data blocks. A data management application or storage OS names data blocks and communicates those names to the storage appliance when backing up to or through the storage appliance. The storage appliance can leverage the data block names when restoring a group of files by restoring at data block granularity instead of file granularity. Restoring at the granularity of the data blocks by their names allows the storage appliance to avoid repeatedly sending a same data block to the restore requestor (e.g., a storage OS or data management application) while still instructing the restore requestor how to reconstruct the corresponding file(s) with mappings between valid data ranges and the named data blocks.

Abstract: Systems and methods for a hybrid approach to assisted history matching in large reservoirs based on a reservoir model built using connectivity between each production well and each corresponding injection well, aquifer or gas cap.

Abstract: A storage tier manager creates different versions of a dataset backup for different retention periods. Each of the versions is distinctly identifiable despite initially representing a same dataset backup. One version can be referred to as a cached version of the dataset backup and another version can be referred to as a cloud version of the dataset backup. When the retention period expires for the cached version of the dataset backup, the storage tier manager migrates the cloud version of the dataset backup from the caching storage tier to the cloud storage tier. The storage tier manager can then recover storage space occupied by data that has been migrated, as long as that data is not shared with other cached versions of other dataset backups due to deduplication.

Abstract: The use of mucic acid gallate compounds in a non-sugar sweetener such as a steviol glycoside-containing consumable to provide lingering aftertaste specific masking effect is provided.