Abstract: Aspects of the present disclosure provide techniques and apparatus for power savings for control channel monitoring for enhanced machine type communications (eMTC). In one aspect, a method is provided which may be performed by a wireless device such as a low cost wireless device, which may be user equipment (UE) or an eMTC UE. The method generally includes determining whether a downlink channel is present in a subframe; and causing the UE to enter a low power mode for a duration based on a determination that the downlink channel is not present in the subframe.

Abstract: Modular transfer units are configured to transport bins or other storage units of standard shapes and sizes between locations. The modular transfer units may be loaded with bins or other storage units having items disposed therein at origins of the items, or at locations where the items are stored, such as fulfillment centers. The modular transfer units may then be mounted to one or more vehicles, such as trailers or rail cars, and transported to another location, where the modular transfer units may be removed from the vehicle, or transferred to another vehicle. The bins or other storage units may be loaded with items that are intended for delivery to a common location. After a bin or storage unit has been unloaded from a modular transfer unit, one or more other bins or storage units may be loaded thereon.

Abstract: A system processes audio data to detect when it includes a representation of a wakeword or of an acoustic event. The system may receive or determine acoustic features for the audio data, such as log-filterbank energy (LFBE). The acoustic features may be used by a first, wakeword-detection model to detect the wakeword; the output of this model may be further processed using a softmax function, to smooth it, and to detect spikes. The same acoustic features may be also be used by a second, acoustic-event-detection model to detect the acoustic event; the output of this model may be further processed using a sigmoid function and a classifier. Another model may be used to extract additional features from the LFBE data; these additional features may be used by the other models.

Abstract: The present invention discloses a cobalt compound of formula (I), a process for the preparation and use thereof. The present invention further relates to a pharmaceutical composition and a method inhibition of Tau Aggregation in a subject in need thereof using compound of formula (I).

Abstract: Certain aspects of the present disclosure provide techniques for hierarchical communication for device-to-device (D2D) communications. In certain aspects, a method generally includes determining user equipment (UE) data comprising at least one of one or more parameters about the UE, one or more parameters about objects near the UE, or raw sensor data. The method further includes determining a first level for transmitting a first portion of the UE data based on content of the first portion of the UE data. The method further includes determining a first modulation coding scheme associated with the first level based on a mapping of a plurality of levels to a plurality of modulation coding schemes. The method further includes encoding the first portion of the UE data using the first modulation coding scheme and transmitting the first portion of the UE data from the UE to at least one second UE directly.

Abstract: In one embodiment, change handling in mobile client applications may be facilitated by intermediate storage of changes using a data-provider-agnostic change object schema. An input on a mobile device that indicates a create, update, or delete action on a data object stored in a remote datastore is received. In response to receiving the input, a description of the action on the data object in a syntax that is agnostic as to type of remote service provider used for interacting with the remote datastore is created. The description of the action to a syntax of the first remote service provider is converted to compose a command configured to cause a first remote service provider to execute the action. The command is transmitted over a network to the first remote service provider to cause the action to be performed on the data object in the remote datastore.

Abstract: A method of associating multiple user endpoints (UEs) with a single IMS session in an IMS network having a serving node for controlling at least one IMS session for a user and at least a first access network for providing access to UEs. The method involves associating a first UE with the user and with an IMS session; discovering a second UE in a proximity of the first UE; discovering information about the second UE; communicating the information about the second UE to the serving node; the serving node utilizing computer-implemented policy logic to determine whether to associate the second UE with the user and the IMS session; and if the policy logic determines that the second UE is to be associated, the serving node associating the second UE with the IMS session while retaining the association with the first UE.

Abstract: An intelligent tracking system generally includes one or more tracking devices, some of which may be passive tracking devices. Each passive tracking device includes one or more transceivers and is energized by an energizing signal. Some of these passive tracking devices may operate in a first communication mode or a second communication mode based on the energizing signal. Some tracking devices may include encryption modules or authentication modules. Some of these devices may incorporate a bulk acoustic wave oscillator.

Abstract: In some embodiments, a first device may generate a data block for an ordered set of data blocks such that the data block is cryptographically chained to a given data block preceding the data block in the ordered set. The first device may obtain an encryption key used to encrypt information related to the data block, and use group members' keys to encrypt the encryption key to generate a group key. As an example, the group's members may include a first member associated with the first device and other members. The keys used to encrypt the encryption key may include the other members' keys. The first device may transmit the ordered set and the group key to a communication resource (e.g., accessible by the members). Other devices (associated with the other members) may use the ordered set and the group key to obtain content related to the ordered set.

Abstract: There is provided a method and apparatus for calibrating measurements made using a medical monitoring device. A conversion factor may be obtained including a first cross correlation that describes the correlation between measurements made using a first medical monitoring device and measurements made using a second medical monitoring device. The first conversion factor may then be used to convert measurements from the first medical monitoring device onto the same scale as measurements from the second medical monitoring device.

Abstract: Methods and systems for reclaiming disk space via consolidation and deletion of expired snapshots are described. The expired snapshots may comprise snapshots of a virtual machine that are no longer required to be stored within a data storage domain (e.g., a cluster of data storage nodes or a cloud-based data store). In some cases, rather than storing an incremental file corresponding with a particular snapshot of the virtual machine, a full image of the particular snapshot may be generated and stored within the data storage domain. The generation of the full image may allow a chain of dependencies supporting the expired snapshots to be broken and for the expired snapshots to be deleted or consolidated. The full image of the particular snapshot may be generated using compute capacity in the cloud or may be generated locally by a storage appliance and uploaded to the data storage domain.

Abstract: Systems, methods, and computer-readable media for providing throughput assurance in a virtual service chain. A virtual service chain formed by a plurality of stitched virtualized network functions running on a plurality of virtual nodes can be monitored. An inline statistics agent can generate inline statistics of the operation of the virtual service chain. Further, an actual throughput of the virtual service chain can be identified from the inline statistics. As follows, throughput assurance for the virtual service chain can be provided by comparing the actual throughput of the virtual service chain with an expected throughput of the virtual service chain.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Anomalous events may be classified based on the monitored network traffic and attack models such that the classification determines that targets of the anomalous events may be currently subject to attacks by entities communicating on the networks. A honeypot trap may be provided in the networks based on the classified events such that the honeypot trap mimics characteristics of the targets. The portions of the network traffic associated with the honeypot trap may be monitored. Characteristics of the attacks may be determined based on the monitored portions of network traffic. Reports that include information based on the characteristics of the attacks may be generated.

Abstract: Users receiving incoming messages may provide their preferences for how they wish to be notified of the incoming messages. A plurality of user devices may be caused to output indicators of the incoming messages, and at least one of the user devices may also provide an acknowledgement of the notification, and the indicators may be cleared.

Abstract: A self-managing database system includes a metrics collector to collect metrics data from one or more databases of a computing system and an anomaly detector to analyze the metrics data and detect one or more anomalies. The system includes a causal inference engine to mark one or more nodes in a knowledge representation corresponding to the metrics data for the one or more anomalies and to determine a root cause with a highest probability of causing the one or more anomalies using the knowledge representation. The system includes a self-healing engine, to take at least one remedial action for the one or more databases in response to determination of the root cause.

Abstract: The invention provides noble metal-free electro-catalyst compositions for use in acidic media, e.g., acidic electrolyte. The noble metal-free electro-catalyst compositions include non-noble metal absent of noble metal. The non-noble metal is non-noble metal oxide, and typically in the form of any configuration of a solid or hollow nano-material, e.g., nano-particles, a nanocrystalline thin film, nanorods, nanoshells, nanoflakes, nanotubes, nanoplates, nanospheres and nanowhiskers or combinations of myriad nanoscale architecture embodiments. Optionally, the noble metal-free electro-catalyst compositions include dopant, such as, but not limited to halogen. Acidic media includes oxygen reduction reaction (ORR) in proton exchange membrane (PEM) fuel cells, and direct methanol fuel cells and oxygen evolution reaction (OER) in PEM-based water electrolysis and metal air batteries, and hydrogen generation from solar energy and electricity-driven water splitting.

Abstract: A data analytics platform may determine whether a machine learning model is a regression model. The data analytics platform may perform, based on determining that the machine learning model is a regression model, a regression prescription method including acquiring a predicted value of a performance indicator determined by the machine learning model processing data associated with a plurality of features and the performance indicator, acquiring a target value of the performance indicator, determining a rate of change of the performance indicator with respect to each feature to generate first results, determining, based on the regression model and for each feature, a rate of change of each feature with respect to other features to generate second results, and determining, for each feature and based on the predicted value, the target value, the first results, and the second results, a change in each feature to achieve the target value.

Abstract: Provided are materials and methods for treating patients with hemoglobinopathies, either ex vivo or in vivo. Also provided are materials and methods for deleting and/or mutating a portion of a human beta globin locus on chromosome 11 and one or more of: a BCL11 A gene on chromosome 2, and a DNA sequence that encodes a transcriptional control region of the BCL11 A gene on chromosome 2, in a human cell by genome editing and thereby increasing the production of fetal hemoglobin (HbF) in the genome-edited human cells.

Abstract: Embodiments described herein relate to a system. The system may include a base configured to be removably coupled to an electrical component. The base may include a first plurality of crossbar alignment features arranged in a first pattern. The system may also include a crossbar configured to be removably coupled to the base using a portion of the first plurality of crossbar alignment features. The crossbar may include a first plurality of adapter plate alignment features arranged in a second pattern. The system may also include an adapter plate configured to be removably coupled to the crossbar using a subset of the first plurality of adapter plate alignment features. The adapter plate may include a plurality of measurement device mounting features.

Abstract: Systems and methods for training machine-learned models are provided. A method can include receiving a rasterized image associated with a training object and generating a predicted trajectory of the training object by inputting the rasterized image into a first machine-learned model. The method can include converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. The method can include utilizing a second machine-learned model to determine an accuracy of the predicted trajectory based on the rasterized trajectory. The method can include determining an overall loss for the first machine-learned model based on the accuracy of the predictive trajectory as determined by the second machine-learned model. The method can include training the first machine-learned model by minimizing the overall loss for the first machine-learned model.