Abstract: Methods for stabilizing laser-induced graphene (LIG) through composite formation and compositions thereof. Using infiltration methods and/or lamination methods, LIG composites (LIGCs) with physical properties can be engineered on various substrate materials. The physical properties include surface properties, such as superhydrophobicity and antibiofouling; the LIGCs are also useful in antibacterial applications, Joule-heating applications, and as resistive memory device substrates. Further, methods for fabricating and using LIG for flexible and embeddable gas sensors.

Abstract: The present disclosure relates to machine learning (ML) models, and more particularly to novel techniques for computing performance metrics for Multioutput-Multilabel ML models. Novel techniques are described for computing the performance metrics in a parallel and distributed without having to store the entire dataset for which metrics are to be computed in the memory of a data processing system. Novel data structures are provided for performing the computations.

Abstract: An example system includes a memory device and a processing device, operatively coupled with the memory device. The processing device is configured to perform operations including: determining that a write request references a partially aligned translation unit; identifying a first entry in a translation map, such that the first entry identifies a first physical block of the memory device, such that the first physical block is mapped to the partially aligned translation unit; creating a second entry in the translation map, wherein the second entry identifies a second physical block of the memory device, wherein the second physical block is mapped to the partially aligned translation unit; linking, in the translation map, the first entry and the second entry; and writing a subset of data corresponding to the partially aligned translation unit to a first portion of the second physical block.

Abstract: Methods, systems, and devices for wireless communication are described. A user equipment may transmit, to a serving network entity, a message requesting a quantity of transmission layers scheduled to be used by one or more neighbor network entities for communication within a communication resource. In response, the user equipment may receive, from the serving network entity, an indication of the quantity of transmission layers scheduled to be used by one or more neighbor network entities for communication within the communication resource. The user equipment may apply the quantity of transmission layers for the communication resource to a rank-aware interference rejection algorithm and may use the rank-aware interference rejection algorithm to improve a noise covariance matrix estimation. When receiving a downlink message, from the serving network entity via the communication resource, the improved noise covariance matrix estimation may be used to mitigate interference at the communication resource.

Abstract: Vehicle corner modules (VCMs) connectable to a VCM-connection interface of a reference-frame of a vehicle platform, for regulating motion of a vehicle. When a wheel is mounted on a wheel-hub assembly of the VCM, a vehicle-connection interface of the VCM is disposed within a cylindrical footprint of the wheel. At least one of the at least one subsystem of the VCM is accommodated between the wheel-hub assembly and the vehicle-connection interface. Vehicle platforms are connectable to the VCMs. The connection of the vehicle platform to the VCM may include connection of subsystems of the VCM to electronic or flow subsystems mounted on the vehicle platform by connection of two portions of a multi-interface connection-element.

Abstract: A host can write data to and/or read data from a memory in a data storage device. In addition to writing host data in the memory, the data storage device can perform internal data movement/relocation (e.g. for wear leveling). The data storage device and method provided herein can balance host writes and relocation operations in multiple meta die systems by reducing the number of open blocks across the system.

Abstract: Arrangements for machine learning-based dynamic learning are provided. In some examples, audio data associated with a plurality of calls may be received and analyzed to identify a topic and sub-topic of each call and metadata of each call. Feedback data may also be received. A machine learning model may be executed by inputting, to the model, the identified topic and sub-topic and metadata of each call, and the feedback data, to output one or more topics or sub-topics of concern. A plurality of ongoing calls may be monitored to identify an ongoing call related to one of: a topic or sub-topic of concern. A plurality of agents who are not subject matter experts in the identified topic or sub-topic of concern and are available may be identified and joined, via respective computing devices, to the ongoing call in a dynamic learning session.

Abstract: Systems, computer program products, and methods are described herein for detecting data leaks via a distributed data orchestration apparatus and transmitted fabricated data responses. The present disclosure is configured to: create a plurality of fabricated data accounts within a set of network servers, where the plurality of fabricated data accounts are connected to an account monitoring engine; collect a set of transmitted fabricated data responses from the plurality of fabricated data accounts; analyze the collected set of transmitted fabricated data responses via an orchestration apparatus; determine the root cause of the data leak associated with the plurality of fabricated data accounts via the orchestration apparatus; and locate a geographic source of the data leak associated with the plurality of fabricated data accounts via a breach engine, where the geographic source of the data leak is located through the root cause of the data leak.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of master data for an entity from a master data system. The set of master data for the entity comprises a master data entity ID for uniquely identifying the entity. The program further receives a set of data associated with the entity from a set of applications configured to generate data associated with the entity and reference the entity using the master data entity ID when generating the of set data associated with the entity. The program also sends the set of master and the set of data associated with the entity to a search system for the search system to aggregate the set of master data for the entity and the set of data associated with the entity into a single record of data for the entity.

Abstract: Physical therapy assistant-as-a-service (PTaaS) enables the automatic evaluation of a patient's performance of physical therapy exercises and the automatic provision of feedback to the patient on their exercise performance in real-time. A patient device can provide real-time patient exercise video to a PTaaS backend that performs checks prior to the patient performing the exercise (pre-checks) and checks during patient performance of the exercise (live checks). If any of the checks fail, the PTaaS can provide feedback to the patient, such as if the patient is in an incorrect starting pose or has a body part at an incorrect angle before beginning the exercise or if the patient's form or posture during performance of the exercise needs to be adjusted. The PTaaS can automatically generate exercise metrics, reports, and physical therapy insights that a physical therapy clinician can access from a clinician portal.

Abstract: Methods, systems, and devices for wireless communications are described. Techniques described herein provide for a user equipment (UE) to determine a channel estimation associated with a downlink channel. In some examples, a network entity may determine a projection matrix and may transmit, to the UE, control signaling indicating the projection matrix. The UE may determine the channel estimation associated with the downlink channel based on the projection matrix. The UE may receive data signaling from the network entity, and the UE may demodulate the data signaling according to the channel estimation that is based at least in part on the projection matrix.

Abstract: Provided are defined culture media for culturing pluripotent stem cells in a suspension culture devoid of substrate adherence, the defined culture media comprising an effective amount of a protease inhibitor; a GSK3? inhibitor and at least one agent selected from the group consisting of a protease inhibitor and a WNT3A polypeptide; a WNT3A polypeptide and a stabilizing agent thereof with the proviso that said stabilizing agent is not a lipid vesicle; and/or a GSK3? inhibitor, with the proviso that the medium is devoid of an ERK1/2 inhibitor. Also provided are cell cultures and methods of suing same.

Abstract: Described herein are techniques for genotyping a family trio by constructing a family genomic reference graph and analyzing sequence reads from members of the family trio using the family genomic reference graph, the family trio comprising a child and biological parents of the child. In some embodiments, the techniques include obtaining the sequence reads; aligning the sequence reads to an initial genomic reference; identifying, based on results of the aligning, an initial plurality of variants; generating the family genomic reference graph using the initial plurality of variants; aligning at least some of the sequence reads to the family genomic reference graph; and identifying, based on results of aligning the at least some of the sequence reads to the family genomic reference graph, an updated plurality of variants comprising a respective updated set of variants for each of the members of the family trio.

Abstract: Arrangements for intelligent call routing are provided. Audio data from a call between an agent device and a user device may be received and a topic of the call and metadata may be extracted from the audio data. The extracted topic and metadata may be compared to an alert signals database to output whether an alert will be attached to the call. Agent parameters associated with the agent who is part of the call may be identified. A machine learning model may be executed by inputting, to the model, the extracted topic, extracted metadata, the output of whether the alert will be attached to the call, and the agent parameters, to output a routing signal. Based on the routing signal, a second call communication session may be initiated between the agent computing device and a computing device of at least one of another agent or a supervisor.

Abstract: A topside platform for a voltage source converter high voltage direct current, VSC HVDC, symmetrical monopole converter station. The topside platform including a first floor and a second floor, an incoming AC switchgear module, and first and second transformer modules, wherein the incoming AC switchgear module is configured to distribute a first alternating current, AC, signal from an AC grid to the first and second transformer modules, wherein the first and second transformer modules are arranged on the first floor of the topside platform and are configured to transform the first AC signal into a second AC signal; and first and second converter modules configured to convert the second AC signal into a direct current, DC, signal for a DC circuit, wherein the first and second converter modules are positioned on the second floor of the topside platform, wherein the incoming AC switchgear module is positioned between the converter modules.

Abstract: A system for generating an expandable pool of virtual agents to provide solutions in a virtual environment comprises a call center server in communication with a metaverse server. The call center server generates the virtual agents with corresponding skills of each real-world agent using a machine learning model based on historical observation operations performed by each particular real-world agent and a historical rule set to address the service issue. The metaverse server identifies the virtual agents in the virtual environment. The call center server routes a service inquiry with a service issue from a user equipment of a user to the metaverse server. The metaverse server identifies a first virtual agent with a first skill and conducts a first interaction between the first virtual agent and a user avatar to generate the customized solution to address the service issue.

Abstract: A planning and scheduling system, which handles generation of a global workflow sequence for multiple workflow stages of a workflow unit, determines a first workflow sequence for a primary workflow stage of the workflow unit for a plurality of product items. The one or more second workflow sequences are generated for one or more secondary workflow stages of the workflow unit concurrently based on a transformation of the determined first workflow sequence. A global workflow sequence is obtained for the primary workflow stage and the one or more secondary workflow stages based on at least the determined first workflow sequence for the primary workflow stage and the generated one or more second workflow sequences. A set of operations are executed on the plurality of machines based on the obtained global workflow sequence to produce the plurality of product items.

Abstract: Systems and methods for deep learning model development for data extraction using a feedback loop. A system generates an interactive graphical user interface (GUI) on one or more user devices for displaying a document with data extracted from the document by a data extraction model together with a user interaction tool allowing the user to correct the extracted data. The system receives, via the interactive GUI, correction information for the extracted data and monitoring performance characteristics of the extraction model in real-time based on the user correction information. The system automatically updates and trains the extraction model using the correction information responsive to detecting that the performance characteristics meet a predetermined performance reduction condition.

Abstract: A security device maintenance system is provided. The aspects include one or more processors configured to assess security data quality by conducting one or more tests that compare the security data to one or more predetermined thresholds, assign one or more anomaly indicators to security devices if the security data quality fails to meet the one or more predetermined thresholds, and generate an automated maintenance report for the one or more security devices including the one or more anomaly indicators. The aspects can also include periodically retrieving one or more security data from the one or more security devices, utilizing an artificial intelligence (AI) model to detect one or more anomalies, and generating one or more predictive maintenance suggestions.

Abstract: This invention relates to the treatment of a psychiatric or neurological disorder in a patient in need thereof who has anhedonia (lack of pleasure or motivation to pursue rewarding activities) by administering irdabisant or a pharmaceutically acceptable salt thereof, either as a monotherapy, or in combination with an antipsychotic agent. Examples of such psychiatric or neurological disorder include major depressive disorder, bipolar depression (such as bipolar I or bipolar II disorders), post-traumatic stress disorder, substance use disorder, anhedonia-related aspects of schizophrenia (e.g., negative symptoms) and schizoaffective disorder (e.g., with mood and/or negative symptoms).