Abstract: The present disclosure relates to compounds according to Formula (I), Formula (I) or a pharmaceutically acceptable salt and/or solvate thereof, compositions including such compounds, and methods useful for treating, preventing, and/or ameliorating a CDK4 and/or CDK6-mediated disorder, disease, or condition (e.g., cancer such as breast cancer) in a subject.

Abstract: Multiple predictions about the position of an object during a time period may each indicate the position of the object at a respective time during the time period. Respective validity indications corresponding to the multiple predictions may each indicate an accuracy of the corresponding prediction. Whether a change has occurred in a distribution of the predictions from a first subset of predictions to a second subset of predictions during the time period may be determined. If the change has occurred, a prediction from the first subset of predictions or the second subset of predictions may be selected, based on the validity of the predictions and/or the detection of a motion, as a best indication of the position of the object.

Abstract: Three-dimensional (3D) DRAM integrated in the same package as compute logic enable forming high-density caches. In one example, an integrated 3D DRAM includes a large on-de cache (such as a level 4 (L4) cache), a large on-die memory-side cache, or both an L4 cache and a memory-side cache. One or more tag caches cache recently accessed tags from the L4 cache, the memory-side cache, or both. A cache controller in the compute logic is to receive a request from one of the processor cores to access an address and compare tags in the tag cache with the address. In response to a hit in the tag cache, the cache controller accesses data from the cache at a location indicated by an entry in the tag cache, without performing a tag lookup in the cache.

Abstract: The embodiments herein provide a system and method for personalized cartoon image generation. The method (100) comprises launching a keyboard interface (101), capturing a digital picture (102), face segmentation using neural network (103), normalization of segmented face (104), face cartoonification (105), which generates bobble head, facial landmark extraction (106), facial expression feature transfer (109) and customization of the generated plurality of cartoon images (110). Hence, the embodiments herein helps in creation of personalized plurality of cartoon images to make the user part of the conversations and the graphics or content shared look similar to the user input face and more aesthetically pleasing instead of using any reference stickers to convey the messages.

Abstract: The present invention discloses a multi-agent robotic system for scrap collection and segregation is disclosed, featuring a foldable chassis with dynamic mechanical assemblies and integrated intelligence for precise waste management. The system includes articulated robotic arms equipped with grippers to collect and categorize materials, powered by dual-piston hydraulic actuators that drive telescopic folding segments with positional encoders for synchronized deployment. A control interface module, mounted on shock-dampening supports, comprises a multi-core CPU to process real-time data from sensors and actuators, ensuring precise operations. A wireless communication module enables encrypted coordination between multiple systems in the ecosystem. The mobility assembly integrates omnidirectional wheels with foldable axles and gyroscopic stabilization for seamless movement.

Abstract: An air transferring system is disclosed. The air transferring system includes an enclosure, a faceplate, and a blower assembly attached to the faceplate. The enclosure includes a base, a lid having an air exhaust, and a shroud. The shroud has an open shroud top, an open shroud bottom, and an opening in the shroud defined between a first shroud edge and a second shroud edge. Each of the shroud edges extends between the open shroud top and the shroud bottom. The faceplate includes a faceplate opening that extends between the first and second shroud edges. The blower assembly includes a blower exhaust proximate to all of the faceplate opening, an exhaust opening, and an impeller for drawing air through the air exhaust, faceplate opening, and blower exhaust and urging the air out the exhaust.

Abstract: A computer includes a processor and a memory, the memory storing instructions executable by the processor to receive sensor data indicating an obstacle, formulate a control barrier function for a vehicle based on the sensor data, determine a control input based on the control barrier function, and actuate a component of the vehicle according to the control input. The control barrier function is defined with respect to a reference point that is spaced from a centroid of the vehicle.

Abstract: Approaches for controlling operations of a sucker rod pump system of a production well that produces reservoir fluids from a reservoir, which employs a gateway device disposed at a wellsite corresponding to the well and a cloud-computing system operably coupled to the gateway device. The gateway device may communicate time-series operational data characterizing operation of the sucker rod pump system to the cloud-computing system. The cloud-computing system can receive and store the time-series operational data communicated from the gateway device and repeatedly perform operations that i) process the time-series operational data to train a machine learning model that predicts run time of the sucker rod pump system given feature data extracted the time-series operational data and ii) use the resultant machine learning model to determine new operating parameter data for use in controlling the sucker rod pump system, wherein the new operating parameter data maximizes production from the well.

Abstract: A method can include implementing a control scheme for a plurality of wells; using the control scheme, classifying each of the wells; based on the classifying, identifying one or more of the wells as experiencing liquid loading; and issuing a control instruction to perform an unloading operation for the one or more of the wells.

Abstract: A correlation engine and policy manager (CPE) system includes: a persistent database, a cache database, an event gate, an event enricher, an event transformer, and an event dispatcher. The event gate obtains event data from at least one event source, and forwards the event data to the event enricher. The event enricher enriches the event data with additional data in the cached business layer data of the cache database, and forwards the enriched event data to the event transformer. The event transformer applies one or more policies in a cached business layer data of the cache database to the enriched event data to obtain transformed event data, and outputs the transformed event data to be stored in the persistent database. The event dispatcher dispatches output data to cause or prompt an action responsive to the transformed event data satisfying the at least one policy.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a generative neural network. One of the methods includes training a generative neural network by performing a sequence of a plurality training stages each generating an expanded training data set. The method also involves performing a sequence of improve steps, each comprising training the generative neural network on the training examples in a corresponding subset of the expanded training data set.

Abstract: Disclosed herein are deep-learning based systems, methods, and instrumentalities for medical decision-making. A system as described herein may implement an artificial neural network (ANN) that may include multiple encoder neural networks and a decoder neural network. The multiple encoder neural networks may be configured to receive multiple types of patient data (e.g., text and image based patient data) and generate respective encoded representations of the patient data. The decoder neural network (e.g., a transformer decoder) may be configured to receive the encoded representations and generate a medical decision, a medical summary, or a medical questionnaire based on the encoded representations. In examples, the decoder neural network may be configured to implement a large language model (LLM) that may be pre-trained for performing the aforementioned tasks.

Abstract: An apparatus for automated collision avoidance includes a sensor configured to detect an object of interest, predicting a representation of the object of interest at a future point in time, calculating an indication of a possibility of a collision with the object of interest based on the representation of the object of interest at the future point in time, and executing a collision avoidance action based on the indication.

Abstract: An interconnect structure is disclosed. The interconnect structure includes a first metal interconnect in a bottom dielectric layer, a via that extends through a top dielectric layer, a metal plate, an intermediate dielectric layer, and an etch stop layer, and a metal in the via to extend through the top dielectric layer, the metal plate, the intermediate dielectric layer and the etch stop layer to the top surface of the first metal interconnect. The metal plate is coupled to an MIM capacitor that is parallel to the via. The second metal interconnect is on top of the metal in the via.

Abstract: A system for detecting a road surface includes a processor and a memory. The memory stores instructions executable by the processor to determine a virtual boundary for a vehicle body based on a shape of the vehicle body, to identify one or more objects based on vehicle sensor data, based on the identified one or more objects, the determined virtual boundary, and an input to at least one of propulsion, steering, or braking, to determine at least one of a braking override or a steering override, and based on the determination, to perform at least one of adjusting a vehicle steering and a vehicle speed.

Abstract: A system for a smart building includes sensors configured to provide measurements using a plurality of communication protocols and an edge device, wherein the edge device provides a data bus, a plurality of protocol agents configured to ingest data from the plurality of sensors using the plurality of protocols and publish the data to the data bus, an analytics engine subscribed to the data on the data bus, and a plurality of containerized applications connected to the data bus.

Abstract: Methods, apparatus, and processor-readable storage media for automatically detecting data anomalies using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data pertaining to multiple tasks associated with at least one enterprise; detecting one or more data anomalies by predicting one or more values within the obtained data by processing at least a portion of the obtained data using one or more artificial intelligence techniques, and comparing the one or more predicted values to one or more corresponding portions of the obtained data; generating one or more data recommendations associated with at least a portion of the one or more detected data anomalies; and performing one or more automated actions based at least in part on at least one of the one or more detected data anomalies and the one or more generated data recommendations.

Abstract: Methods and systems are provided for monitoring the operation of a sucker rod pump (SRP), which involves a workflow that processes surface operational data and downhole operational data related to the operation of the SRP. The surface operational data is derived from real-time measurements performed by surface-located sensors, while the downhole operational data is derived from real-time measurements performed by downhole sensors. The surface operational data is processed to generate input data for supply to a first machine learning model (e.g., Surface Data Classifier) and the downhole operational data is processed to generate input data for supply to a second machine learning model (e.g., Downhole Data Classifier). The output of at least one of the first and second machine learning models is used to characterize an operational condition or status of the SRP.

Abstract: A method includes processing event data to detect a status of a network function. The event data is processed based on two or more conditions defined by a correlation policy. The correlation policy includes a non-deterministic finite automata tree (NFAT) structure correlation policy having a policy type and a logic-gate. The method additionally includes determining the policy type of the NFAT structure correlation policy. The method also includes determining whether a first value of the two or more conditions is indicative of whether a first condition is satisfied. The method further includes determining whether a second value of the two or more conditions is indicative of whether the second condition is satisfied. The method additionally includes determining whether the NFAT structure correlation policy is satisfied based on the first value, the second value, the logic-gate and the policy type.

Abstract: The physical characteristics of one or more anatomical structures of a person may change in accordance with conditions surrounding the determination of such physical characteristics. Machine learning based techniques may be used to determine a template representation of the one or more anatomical structures that may indicate the physical characteristics of the one or more anatomical structures free of the impact imposed by changing conditions. The template representation may then be used to predict the physical characteristics of the one or more anatomical structures under a new set of conditions, without subjecting the person to additional medical scans.