Abstract: An all-solid-state battery comprises a lithium anode, a cathode, solid electrolyte and a protective layer between the solid electrolyte and the lithium anode. The protective layer comprises an ion-conducting material having an electrochemical stability window against lithium of at least 1.0 V, a lowest electrochemical stability being 0.0 V and a highest electrochemical stability being greater than 1.0 V. More particularly, when the solid electrolyte is LiSiCON, the electrochemical stability window is at least 1.5 V, the lowest electrochemical stability is 0.0 V and the highest electrochemical stability is greater than 1.5 V. When the solid electrolyte is sulfide-based, the electrochemical stability window is at least 2.0 V, the lowest electrochemical stability is 0.0 V and the highest electrochemical stability is greater than 2.0 V.

Abstract: A bonusing system for gaming devices provides a bonus award eligible to be won via participating gaming devices. A messaging application programming interface (API) receives wagering event messages in a first message format from third-party servers. A message queue receives wagering event messages from the messaging API in a second message format. A bonusing system server manages award determination for the bonus award.

Abstract: One or more computing devices, systems, and/or methods for controlling a graphical user interface using a presentation of messages based upon predicted interactions with the messages are provided. For example, a plurality of messages associated with the messaging account may be received. Interactions with the plurality of messages may be tracked to generate sets of message interactions. The plurality of messages may be analyzed to identify sets of attributes. An expected action model may be generated based upon the sets of message interactions and the sets of attributes. A set of messages associated with the messaging account may be analyzed based upon the expected action model to predict one or more interactions corresponding to one or more potential presentations of the set of messages. A presentation may be selected from the one or more potential presentations. A graphical user interface may be controlled using the presentation.

Abstract: Inter-device communication with a pulse-amplitude modulation (PAM) signal can have at least two data eyes with different Vref levels. A physical interface (PHY) can be trained for the PAM signal by training a first data eye separately from the second data eye. The training can include adjusting the first Vref level separately from the second Vref level to center each reference voltage on its respective data eye.

Abstract: Methods and devices are provided for allowing a mobile device (e.g., a key fob or a consumer electronic device, such as a mobile phone, watch, or other wearable device) to interact with a vehicle such that a location of the mobile device can be determined by the vehicle, thereby enabling certain functionality of the vehicle. A device may include both RF antenna(s) and magnetic antenna(s) for determining a location of a mobile device relative to the vehicle. Such a hybrid approach can provide various advantages. Existing magnetic coils on a mobile device (e.g., for charging or communication) may be re-used for distance measurements that are supplemented by the RF measurements. Any device antenna may provide measurements to a machine learning model that determines a region in which the mobile device resides, based on training measurements in the regions.

Abstract: Transportable storage devices are communicatively coupled behind one or more dedicated “edge” data servers to take advantage of the benefits of the data servers and transportable storage devices while limiting their disadvantages. Each edge data server ingests data from one or more client devices and copies the data to one or more of the transportable storage devices for eventual transport to a cloud data center for upload to a cloud storage system. Multiple versions of a segment of data (e.g., of a file or a blob) are maintained at various points in the disclosed system and the disclosed technology ensures that the most recent version is the version ultimately stored on the cloud storage system.

Abstract: Versions of the disclosure relate to methods of imaging and detecting germinated seeds on a soilless growth medium.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving a new application programming interface (API) specification and extracting one or more keywords from the new API specification. The method also includes identifying, using a trained machine learning (ML) model, one or more existing API specifications that are similar to the new API specification based on the one or more keywords from the new API specification and, responsive to the identification, outputting information regarding the one or more existing API specifications that are similar to the new API specification.

Abstract: Systems and related methods providing for dynamic message creation are discussed herein. Circuitry may be configured receive generic configuration data that references work chunks for message generation and time data indicating a message send time. The work chunks may include references to message data, but not the actual message data. Based on the time data, the work chunks may be placed in a message queue. Circuitry may also be configured to retrieve a work chunk from the message queue and to generate one or more messages based on the retrieved work chunk. The references to message data in the work chunk may be used to retrieve the message data at the time of message generation.

Abstract: Systems, devices, and methods for automating network account transfers based on predicted inactivity are disclosed.

Abstract: In accordance with some embodiments, systems, methods, and media for high dynamic range imaging using single-photon and conventional image sensor data are provided. In some embodiments, the system comprises: first detectors configured to detect a level of photons proportional to incident photon flux; second detectors configured to detect arrival of individual photons; a processor programmed to: receive, from the first detectors, first values indicative of photon flux from a scene with a first resolution; receive, from the second detectors, second values indicative of photon flux from the scene with a lower resolution; provide a first encoder of a trained machine learning model first flux values based on the first values, provide the second encoder of the model second flux values; receive, as output, values indicative of photon flux from the scene; and generate a high dynamic range image based on the third plurality of values.

Abstract: A door includes an inner wall, an outer wall, and a window assembly including a window. The inner wall is configured to engage with a cab of a vehicle. The outer wall is coupled to the inner wall and spaced apart from the inner wall to form an interior cavity. The door is configured to move between a closed position in which the inner wall is engaged with the cab and an open position in which the inner wall is separated from the cab. In the closed position, at least a portion of the interior cavity is configured to be disposed outboard from the cab in a lateral direction. The window is slidably engaged to the door and configured to move between an extended position and a retracted position. In the retracted position, the window is at least partially disposed in the portion of the interior cavity.

Abstract: The present disclosure provides a method and system for evaluating a machine learning model using an evaluation dataset for the machine learning model. The evaluation dataset includes for each entity in a group of entities: (i) an ordered set of attribute values for the entity, each attribute value corresponding to a respective attribute in a set of attributes that is common for all of the entities in the group of entities, and (ii) an outcome prediction generated for the entity by the machine learning model based on the ordered set of attribute values for the entity, wherein the outcome prediction generated for each entity is either a first outcome or a second outcome. Based on the evaluation dataset, using an optimization process, respective importance values are computed for the attributes, the respective importance values indicating attributes that are most responsible for the machine learning model predicting a first outcome.

Abstract: A method, programming product, processor, and/or system for prefetching data is disclosed that includes: receiving a request for data at a cache; identifying whether the request for data received at the cache is a demand request or a prefetch request; and determining, in response to identifying that the request for data received at the cache is a prefetch request, whether to terminate the prefetch request, wherein determining whether to terminate the prefetch request comprises: determining how many hits have occurred for a prefetch stream corresponding to the prefetch request received at the cache; and determining, based upon the number of hits that have occurred for the prefetch stream corresponding to the prefetch request received by the cache, whether to terminate the prefetch request.

Abstract: The disclosure is directed to systems, methods, and computer storage media, for, among other things, generating, training, and tuning lexicon-based classifier models. The models may be employed in various compliance enforcement applications and/or tasks. The tradeoff between the model's false positive error rate (FPR) and the model's false negative rate (FNR) may be “tuned” via a balance parameter supplied by the user. The classifier model may classify content (e.g., text records) as either belonging to a “positive” class or a “negative” class. The positive class may be associated with non-compliance, while the negative class may be associated with compliance (or vice-versa). In some embodiments, the classifier model may be a probabilistic probability model that provides a probability (or degree of belief) that the content is associated with the positive and/or negative class.

Abstract: Solid forms comprising 2-(4-chlorophenyl)-N-((2-(2,6-dioxopiperidin-3-yl)-1-oxoisoindolin-5-yl)methyl)-2,2-difluoroacetamide, compositions comprising the solid forms, methods of making the solid forms and methods of their uses are disclosed.

Abstract: Described are a system, method, and computer program product for reconfiguring a data table for processing on a server cluster. The method includes extracting a data table from a relational database and determining whether the data table includes a column having a range of values with a uniform distribution. The method also includes, in response to determining that the data table includes the column, classifying the column as a candidate column for splitting the data table. The method further includes, in response to determining that the data table does not include the column, inserting an index column into the data table and classifying the index column as the candidate column. The method further includes splitting the data table based on the candidate column and distributing each subdivision to a node of the server cluster so as to cause the server cluster to collectively process the data table.

Abstract: Methods and devices useful in performing precise indoor localization and tracking are provided. By way of example, a method includes locating and tracking, via a first wireless electronic device, a plurality of other wireless electronic devices within an indoor environment. Location ambiguity mitigation is performed using characteristics of signals received by a reference node used to generate a radio frequency map of electronic devices.

Abstract: A processor may initialize a fetch of a first instruction. The processor may determine whether there is an icache miss for the first instruction. The processor may fetch the next instruction from a cache.

Abstract: A size associated with a content file is determined to be greater than a threshold size. Contents of the content file split across a plurality of component files are stored. Metadata, for the content file, is updated to reference a plurality of component file metadata structures for the component files. A node of the metadata is configured to track different sizes of portions of the content file stored in different component files of the plurality of component files. File metadata of the content file is split across the plurality of component file metadata structures and each component file metadata structure of the plurality of component file metadata structures specifies a corresponding structure organizing data components for a corresponding portion of the content file.