Abstract: Disclosed herein are system, method, and computer program product embodiments for rapid identification and access to relevant regulatory documents. A data model relating regulatory mandates and requirements to citations appearing within an enforcement document is used to rapidly access specific citations within an enforcement document. In the case of image-based enforcement documents, the originality of these documents is preserved while allowing a user to see where the relevant citations appear in the document images. The relevant citations are further compared to business policies to identify potential impacts of regulatory mandates and requirements.

Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for processing a perspective view range image generated from sensor measurements of an environment. The perspective view range image includes a plurality of pixels arranged in a two-dimensional grid and including, for each pixel, (i) features of one or more sensor measurements at a location in the environment corresponding to the pixel and (ii) geometry information comprising range features characterizing a range of the location in the environment corresponding to the pixel relative to the one or more sensors. The system processes the perspective view range image using a first neural network to generate an output feature representation. The first neural network comprises a first perspective point-set aggregation layer comprising a geometry-dependent kernel.

Abstract: Systems, apparatuses, and methods related to bit string accumulation are described. A method for bit string accumulation can include performing an iteration of a recursive operation using a first bit string and a second bit string and modifying a quantity of bits of a result of the iteration of the recursive operation, wherein the modified quantity of bits is less than a threshold quantity of bits. The method can further include writing a first value comprising the modified bits indicative of the result of the iteration of the recursive operation to a first register and writing a second value indicative of the factor corresponding to the result of the iteration of the recursive operation to a second register.

Abstract: The present invention provides a retroviral or lentiviral vector having a viral envelope which comprises a mitogenic T-cell activating transmembrane protein which comprises: (i) a mitogenic domain which binds a mitogenic tetraspanin, and (ii) a transmembrane domain; wherein the mitogenic T-cell activating transmembrane protein is not part of a viral envelope glycoprotein. When cells such as T-cells or Natural Killer cells are transduced by such a viral vector, they are activated by the mitogenic T-cell activating transmembrane protein.

Abstract: Systems and methods for producing heat and an oxidant for an endothermic chemical production process are disclosed. At least some process heat is recovered from (1) a hot gas including hot gas from a waste air vent of an MTBE production unit and/or (2) a catalyst regeneration process into a combustion gas stream. The combustion gas stream is further used in a steam reformer and/or a cracker for providing an oxidant and at least some heat.

Abstract: Apparatus and method for a scalable pricing engine. A scalable pricing engine is operable in a low-scale mode and a high-scale or scalable mode to process pricing data in response to pricing requests. The pricing engine operates in a first runtime environment in the low-scale mode in which it can service pricing requests up to a threshold number and in which the pricing data can be updated and tested. The pricing engine also operates in a second runtime environment which is a scalable runtime supporting pricing requests above the specified threshold. The scalable runtime and pricing engine rely on a scalable read-only data service which distributes a read-only copy of at least a portion of the pricing data from the primary database, a high-scale cache to reduce access latency, data processing and network resource allocations, and data reduction techniques when processing requests and responses.

Abstract: Apparatus and method for asynchronous pricing. For example, some implementations include an asynchronous pricing service in addition to the pricing service. When performing a first pricing operation on a first set of pricing data, the pricing service performs operations on a pricing engine. In response to a second pricing request at the asynchronous pricing service with a second set of pricing data, the second set of pricing data is subdivided into a plurality of portions and a corresponding plurality of pricing jobs are specified, which are independently executed by the pricing engine to produce a corresponding plurality of partial pricing results. The asynchronous pricing service aggregates the partial pricing results to generate a second pricing result.

Abstract: An embodiment includes analyzing text content of a user query to identify via natural language processing (NLP) a query topic. The embodiment maps the query topic to a topic cluster at a node of a hierarchical model of a text database. The embodiment generates query demand data indicative of demand for the topic cluster based on user queries. The embodiment identifies the topic cluster as a topic-cache candidate based on the query demand data. The embodiment compares an amount of memory required for storing text associated with the first topic cluster to available cache memory. The embodiment caches the text of the topic cluster candidate upon determining that there is sufficient available cache memory space.

Abstract: A system and method for a protocol to identify patterns among caregivers and predict the root cause of burnout, whereby the system leverages proprietary data and data collected form third party sources to assess the risk of caregivers and then adjusts accordingly based on previous data of the caregivers as well as other similar caregivers.

Abstract: Certain aspects of the present disclosure provide a method of wireless communications by a user equipment (UE), generally including detecting one or more synchronization signal blocks (SSBs) transmitted from a network entity, identifying a channel scattering type based on the detecting, and selecting one or more parameters for beam management, based on the identified channel scattering type.

Abstract: A server system receives an electronic document from a client system to be stored at a content management system. The server system generates multiple copies of the electronic document that are stored in parallel at respective multiple instances of the content management system. The server system receives a request to retrieve a copy of the electronic document. In response to the request, the server system checks, by a load balancer, whether the respective multiple instances of the content management system are operational to retrieve the copy of the electronic document. The server system then performs load balancing by the load balancer in accordance with a round-robin process to select a particular instance and retrieves the copy of the electronic document from the particular instance of the content management system.

Abstract: A lighting control system (1) comprising at least one lighting module (2) and a controller (3), the controller (3) being configured to cause the at least one lighting module to create a lighting scene for a lighting calendar event, the controller (3) further being configured to obtain first data by data mining social media content relating to the lighting calendar event, determine first lighting attributes from the first data, based on the first lighting attributes, control the at least one lighting module to generate at least one lighting scene and apply the at least one lighting scene for the lighting calendar event, obtain second data by data mining social media content relating to the applied at least one lighting scene, determine second lighting attributes from the second data, and based on the second lighting attributes control the at least one lighting module to generate at least one updated lighting scene and apply the at least one updated lighting scene for the lighting calendar event.

Abstract: A resource allocation engine distributes host resources, such as CPU cores, dynamically between a set of containers executing in the context of the host operating system. The resource allocation engine sets a lower limit on CPU allocation for each container to prevent the containers from being starved of CPU resources. The resource allocation engine monitors the utilization of the resources allocated to the containers, and redistributes the host resources dynamically among the containers based on the utilization values. Containers having high utilization values are assigned more resources correspondingly, and containers having low utilization values are assigned fewer resources. In some embodiments, the resource allocation engine assigns weights to the containers, and uses the weights to assign CPU resources for an upcoming assignment period. An operating system utility, such as C-groups, is used to implement the resource allocations to the containers for the assignment periods.

Abstract: A user equipment (UE) is configured to store information related to network slices. The UE receives network slice related information associated with a first public land mobile network (PLMN), stores the network slice related information in a database locally at the UE, identifies a predetermined condition and removes at least a portion of the network slice information associated with the first PLMN based on camping on a second PLMN and the predetermined condition.

Abstract: Embodiments disclosed herein determine when a sensor of an electronic device is being used, determine if a transmitter of the electronic device is transmitting a signal, determine whether the signal has a frequency in the certain frequency bands (e.g., that cause noise at the sensor), and reduce power (e.g., perform a power back-off operation) at the transmitter if so.

Abstract: Techniques described herein are directed toward smart external interference detection and avoidance. An example method includes determining a first received signal strength indicator (RSSI) value of a received first signal across a radio band, wherein the first RSSI value is based at least in part on a second signal transmitted by an interfering device. The first received RSSI value is compared with a threshold value. A first gain adjustment value is determined for a receiver chain of the first computing device and a second gain adjustment value of a transmitter chain based at least in part on the comparison. A first gain of a first amplifier of the receiver chain is adjusted based at least in part on the first gain adjustment value. A second gain of a second amplifier of the transmitter chain is adjusted based at least in part on the second gain adjustment value.

Abstract: Apparatuses, methods, and systems are disclosed for determining a precoder for wireless communications. An apparatus includes a processor that determines a precoder for a set of modulation symbols, the determined precoder comprising a plurality of codewords and configured to reduce an ensemble interference and a pairwise interference among the plurality of codewords. The processor precodes the set of modulation symbols based on the determined precoder. The processor maps the precoded set of modulation symbols to a set of physical transmission resources, wherein a number of modulation symbols in the set of modulation symbols is greater than a number of physical transmission resources in the set of physical transmission resources. The apparatus includes a transceiver that transmits, to a receiver node, an indication of the determined precoder and the set of physical transmission resources.

Abstract: A method includes segmenting point cloud data of an image into a plurality of input clusters, wherein each of the plurality of input clusters includes a given set of point cloud data from among the point cloud data. The method includes, for each of the plurality of input clusters: selectively filtering the given set of point cloud data to identify production component cloud data (PCCD), aligning the PCCD with a predefined axis to generate a rotated PCCD, classifying the given set of the plurality of production components into one or more asset types based on the rotated PCCD, generating a three-dimensional bounding box based on the rotated PCCD, segmenting the rotated PCCD into a plurality of production clusters, and determining one or more parameters associated with the given set of the plurality of production components based on the plurality of production clusters and the one or more asset types.

Abstract: Methods and systems are provided for providing an insights page. When data identifying a party of a call is received, a customer relationship management (CRM) application can be launched at a computing device without any further user input, and records that are potentially relevant to the call and that are to potentially be included as part of an insights page of the CRM application can be automatically determined. Some of the records are automatically determined by analyzing CRM information using artificial intelligence technologies. The records can then be ranked in a priority order according to relevance from most relevant to least relevant. The insights page can then be caused to be displayed at a user interface of the computing device without user input with at least some of the records displayed in the priority order as relevant records.

Abstract: A method or system for estimating delays in design under tests (DUTs) using machine learning. The system accesses multiple DUTs, each comprising various logic blocks. For each DUT, a combinatorial path is identified, connecting one or more logic blocks. A feature vector is generated, including values of orthogonal features representing the combinatorial path's characteristics. Each DUT is compiled for emulation, and the delay of its combinatorial path is measured. These measured delays, along with the corresponding feature vectors, are used to train a machine learning delay model. The trained model is designed to receive a combinatorial path of a DUT as input and generate an estimated wire delay as output. This approach leverages machine learning to predict delays in electronic designs, improving the efficiency and accuracy of delay estimations in complex circuits.