Abstract: The invention relates to a device (1) for cleaning two-wheeled vehicles, in particular bicycles and/or electric bicycles. The device (1) has a wet cleaning device for cleaning the two-wheeled vehicle by means of a cleaning liquid and a splash guard housing (2) for retaining the cleaning liquid, wherein during cleaning a two-wheeled vehicle can be at least partially accommodated in the splash guard housing (2). The invention is characterized in that the device (1) comprises a drying means (3).

Abstract: In some embodiments, a system may enable autonomous reasoning in real-time communications by dynamically generating and executing DSLs based on context. The method includes determining a computational intent specification from messages exchanged in a communication session and accessing knowledge sources relevant to the computational intent specification. The method further includes generating a DSL using a generative language model based on the computational intent, the messages, and the knowledge sources, where the language defines constructs and syntax rules specifying allowable compositions of named entities and relationships. The method further includes executing the constructs to perform reasoning operations and generate an output message responsive to the messages. The method further includes presenting the output message within the real-time communication platform and storing an execution trace mapping the constructs to portions of the output message.

Abstract: A system for processing multi-modal data representing an environment to generate scene graphs of the environment is described. The system can obtain sensor data associated with a vehicle operating in the environment. In examples, the system can determine a set of features from the sensor data, including one or more objects and one or more agents present in the environment, and can generate a scene graph that represents the poses and velocities of these objects and agents relative to the environment. In some examples, based on generating the scene graph, the system can generate a knowledge graph by encoding the relationships among the identified objects and agents. In some examples, the system can generate a control signal, using attributes that represent the states of objects and agents in the knowledge graph, and provide this control signal to the vehicle in order to adjust or cause the operation of the vehicle.

Abstract: A system for processing multi-modal data representing an environment to generate scene graphs of the environment is described. The system can obtain sensor data associated with a vehicle operating in the environment. In examples, the system can determine a set of features from the sensor data, including one or more objects and one or more agents present in the environment, and can generate a scene graph that represents the poses and velocities of these objects and agents relative to the environment. In some examples, based on generating the scene graph, the system can generate a knowledge graph by encoding the relationships among the identified objects and agents. In some examples, the system can generate a control signal, using attributes that represent the states of objects and agents in the knowledge graph, and provide this control signal to the vehicle in order to adjust or cause the operation of the vehicle.

Abstract: A system for processing multi-modal data representing an environment to generate scene graphs of the environment is described. The system can obtain sensor data associated with a vehicle operating in the environment. In examples, the system can determine a set of features from the sensor data, including one or more objects and one or more agents present in the environment, and can generate a scene graph that represents the poses and velocities of these objects and agents relative to the environment. In some examples, based on generating the scene graph, the system can generate a knowledge graph by encoding the relationships among the identified objects and agents. In some examples, the system can generate a control signal, using attributes that represent the states of objects and agents in the knowledge graph, and provide this control signal to the vehicle in order to adjust or cause the operation of the vehicle.

Abstract: An artificial intelligence (AI) agent is configured to automatically generate agent-based model simulations based on the tasks. The AI agent receives an inbound task representing a hypothesis or other question indicating a use for an agent-based model. The AI agent selects from a plurality of model agents for the simulation. Model agent selection may include a semantic comparison between metadata for a number of candidate agents and the inbound task. The AI agent can execute the simulation and determine other scenarios to investigate in order to enhance its response. The AI agent can perform a number of actions responsive to the inbound task that depend on the results of the simulations. The AI agent may update a user interface or generate a notification with a recommendation based on the results. The AI agent may interact with an API to effect a change in a physical system represented by the model.

Abstract: Embodiments of the present disclosure include techniques for automatically generating enterprise application test scripts. In one embodiment, process flows are retrieved from a software system. Task data for the process flows is extracted and converted into one or more JSON objects. The JSON objects are sent to an LLM to autogenerate test scripts. The test scripts are executed by a software test system to test the enterprise application.

Abstract: Systems and methods for dynamic error resolution in hybrid quantum-classical computing environments are disclosed. A system can obtain telemetry data corresponding to a processing job. The system can determine that an error resolution technique is to be applied to the quantum portion of the processing job. The system can select, for a quantum portion of the processing job, the error resolution technique from a plurality of error correction techniques and a plurality of error mitigation techniques. The system can update a hierarchical data structure representing the processing job as at least a set of nodes. The hierarchical data structure can be updated to include the error resolution technique in association with a respective node of the hierarchical data structure representing the quantum portion of the processing job.

Abstract: A system for providing and displaying visually interactive bonus features in electronic wagering games may include a display device and/or circuitry. The circuitry may be configured to lock, as part of a bonus feature in an electronic wagering game presented via the display device, a set of blocks on reels of the electronic wagering game. The circuitry may also be configured to move, during implementation of the bonus feature, a slider window in at least one direction over the reels in connection with a reel spin and to then unlock one or more symbols rendered in a subset of the blocks due at least in part to the slider window landing over the subset of blocks. The circuitry may be further configured to perform a collection of one or more values represented by the symbols rendered in the subset of blocks. Various other systems and methods are also disclosed.

Abstract: The present invention discloses a composition and method for treating arthritis. The composition comprises a binary blend of molecules including citral, methyl cinnamate, and epicurzerenone. The binary blend exhibits synergistic efficacy in modulating inflammatory cytokines. The citral, methyl cinnamate, and epicurzerenone, are derived from essential oils of Cymbopogon citratus, Hedychium spicatum, and Zanthoxylum armatum, respectively. Both individual and binary blend exhibits downregulation of pro-inflammatory cytokines IL-2, IL-6, and TNF-?, and upregulation of anti-inflammatory cytokine IL-10.

Abstract: A system for processing multi-modal data representing an environment to generate scene graphs of the environment is described. The system can obtain sensor data associated with a vehicle operating in the environment. In examples, the system can determine a set of features from the sensor data, including one or more objects and one or more agents present in the environment, and can generate a scene graph that represents the poses and velocities of these objects and agents relative to the environment. In some examples, based on generating the scene graph, the system can generate a knowledge graph by encoding the relationships among the identified objects and agents. In some examples, the system can generate a control signal, using attributes that represent the states of objects and agents in the knowledge graph, and provide this control signal to the vehicle in order to adjust or cause the operation of the vehicle.

Abstract: Aspects of the disclosure are directed to batch memory prefetching. In accordance with one aspect, the disclosure includes examining a current cache line from a plurality of cache lines; determining if a conditional branch opcode or an unconditional branch opcode is present; sending an anticipatory address to a bulk memory to fetch one or more anticipatory program instructions; and depositing the one or more anticipatory program instructions into a prefetch cache memory to augment an initial set of program instructions.

Abstract: A method receiving a dataset including a plurality of images, executing an embedding model using the plurality of images to generate a plurality of image embeddings, clustering the plurality of image embeddings into a plurality of clusters based on similarities between the plurality of image embeddings, determining a density for each cluster based on an aggregate similarity of image embeddings of the cluster, based on the density for each of the plurality of clusters satisfying a criterion, for each cluster: receiving a first set of annotations for one or more pixels of each of a first subset of the images included in the cluster, inputting the annotated first subset of images into a vision transformer with a remaining unannotated subset of images not included in the annotated first subset, and generating a second plurality of annotations for the remaining unannotated subset of images not included in the annotated first subset.

Abstract: A method and a system for performing real-time fraud detection by proactively identifying fraudulent activity before executing a transaction are provided. The method includes: receiving, from a user, first information that relates to a proposed transaction; providing the first information as an input to a machine learning model; using the machine learning model to generate an output that relates to potentially fraudulent activity associated with the first information; generating, based on the first output, an alert message that includes second information that relates to notifying the user about the potentially fraudulent activity; and transmitting the alert message to the user. The output may include a score that relates to a likelihood that the first information is associated with actual fraudulent activity, and the score may be normalized to fall in a range of between zero and ten.

Abstract: A network device may receive a hash key from a control plane of the network device, and may sort the hash key based on a next hop address field and to generate a sorted hash key. The network device may store the sorted hash key locally in a data plane of the network device, and may generate a sorted hash table based on the sorted hash key. The network device may utilize the sorted hash table to symmetrically route traffic with another network device.

Abstract: Systems and methods for optimizing the placement of experts in a mixture-of-experts (MoE) model are disclosed. A system can include one or more processors coupled to non-transitory memory. The system can obtain a set of attributes of a plurality of hardware components of a distributed computing environment. The system can determine a set of co-activation metrics for a plurality of experts of a mixture-of-experts model according to inference or training operations executed using the mixture-of-experts model. The system can generate a quadratic unconstrained binary optimization (QUBO) data structure based at least on the set of attributes and the set of co-activation metrics. The system can assign the plurality of experts of the mixture-of-experts model to the plurality of hardware components of the distributed computing environment according to the QUBO data structure. The system can execute the mixture-of-experts model using the plurality of hardware components according to the assignment.

Abstract: Systems and method are provided that include a standard cell with multiple input and output storage elements, such as flip flops, latches, etc., with some combination logic interconnected between them. In embodiments, the slave latches on input flip flops are replaced with a fewer number latches at a downstream node(s) of the combination logic resulting in improved performance, area and power, while maintaining functionality at the interface pins of the standard cell. The process of inferring such a standard cell from a behavioral description, such as RTL, of a design or remapping equivalent sub-circuits from a netlist to such a standard cell is also described.

Abstract: A method and a system for displaying a response to at least one natural language query are disclosed. The method includes receiving the at least one natural language query. The method further includes analyzing, using a trained model, the at least one natural language query to identify an intent and entities associated with the at least one natural language query. The method further includes composing a database-specific query using the identified intent and entities associated with the at least one natural language query. The method includes executing the database-specific query to retrieve the response to the at least one natural language query from at least one database. The method further includes displaying, via a display, the response that is retrieved from the at least one database.

Abstract: The present invention provides a carbon-free electrocatalyst for oxygen reduction reaction (ORR) in polymer electrolyte membrane fuel cells (PEMFCs). Described herein is a Pt decorated carbon-free catalyst with solid-state proton conducting zirconium phosphate (ZrP) as support material for PEMFC. The invention further describes the process for obtaining said Pt decorated conducting zirconium phosphate (ZrP) as support material as proton conductor. Also, the present invention relates to an efficient proton conductor which optimizes utilization of Pt- catalyst thereby improving the performance of the PEMFC. The carbon-free system alleviates the problem of carbon-corrosion leading to detachment of Pt-nanoparticles.

Abstract: A mirror assembly can include a housing, a mirror, and a light source. In certain embodiments, the mirror is rotatable within a support portion of the mirror assembly. In some embodiments, the mirror assembly includes a light pipe configured to emit a substantially constant amount of light along a periphery of the mirror. In some embodiments, the mirror assembly includes a sensor assembly. The sensor assembly can be configured to adjust the amount of emitted light based on the position of a user in relation to the mirror.