Abstract: Disclosed herein is a nanovesicles from adult stem cells containing iron nanoparticles and its use. The nanovesicle according to the present disclosure provides effects of maximizing the efficacy of treating mesenchymal stem cells by pretreating cells with iron nanoparticles; reconstituting the cells in a nano-sized form to facilitate intravenous injection; and increasing the efficiency of targeting disease areas through magnet induction. In particular, the present disclosure can replace mesenchymal stem cells as a cell therapeutic agent, and it can be applied to various diseases as a novel biopharmaceutical drug because it can increase the function and efficiency of an exosome-based therapeutic agent.

Abstract: The vehicle comprises a Gearbox Position Sensor (GPS). The controller is adapted to receive input signals from the GPS, compare a value of the input signal with a predetermined threshold value, and activate a shift assist functionality based on the comparison. The value of the input signal is any one selected from a group comprising voltage and an angle. Further, the shift assist functionality comprises adjustment of engine operation by at least one of Electronic Throttle Control, a fuel injection control, ignition control. The controller is in connection with the Electronic Throttle Body, a fuel injector and an ignition system respectively for the adjustment/control of the engine operation. A robust solution of achieving quick shift functionality is achieved by using the existing GPS of the vehicle. The implementation cost of new and existing vehicle is reduced.

Abstract: A model-as-a-service (MaaS) platform performs cross-model resources allocation from a shared pool of GPU resources based on model-agnostic metrics generated by a metric standardizer. The metric standardizer receives, from model providers, model-specific benchmark metrics that define relationships between resource utilization and token processing according to the different model-specific tokenization schemes; receives, from one or more MaaS components, token-based job metrics pertaining to LLM processing tasks; and determines, based on the model-specific benchmark metrics and token-based job metrics, the model-agnostic metrics for multiple model pools executing instances of different large language models (LLMs) that generate and process text according to different model-specific tokenization schemes. The MaaS platform further includes one or more resource allocation components that dynamically reallocates resources of the shared pool based on the model-agnostic metric.

Abstract: A model-as-a-service (MaaS) platform performs cross-model resources allocation from a shared pool of GPU resources based on model-agnostic metrics generated by a metric standardizer. The metric standardizer receives, from model providers, model-specific benchmark metrics that define relationships between resource utilization and token processing according to the different model-specific tokenization schemes; receives, from one or more MaaS components, token-based job metrics pertaining to LLM processing tasks; and determines, based on the model-specific benchmark metrics and token-based job metrics, the model-agnostic metrics for multiple model pools executing instances of different large language models (LLMs) that generate and process text according to different model-specific tokenization schemes. The MaaS platform further includes one or more resource allocation components that dynamically reallocates resources of the shared pool based on the model-agnostic metric.

Abstract: A model-as-a-service (MaaS) platform performs cross-model resources allocation from a shared pool of GPU resources based on model-agnostic metrics generated by a metric standardizer. The metric standardizer receives, from model providers, model-specific benchmark metrics that define relationships between resource utilization and token processing according to the different model-specific tokenization schemes; receives, from one or more MaaS components, token-based job metrics pertaining to LLM processing tasks; and determines, based on the model-specific benchmark metrics and token-based job metrics, the model-agnostic metrics for multiple model pools executing instances of different large language models (LLMs) that generate and process text according to different model-specific tokenization schemes. The MaaS platform further includes one or more resource allocation components that dynamically reallocates resources of the shared pool based on the model-agnostic metric.

Abstract: A system and method for automated video generation for training machine and deep learning algorithms in aviation environments generates photorealistic digital human characters and an aviation environment according to a desired scenario, including fixtures, free objects, lighting and physics configurations, and camera views. Character actions in the desired scenario are mapped to pose sequences which may be manually generated or transferred from image sequences of human activities, including both main character activities specified by the scenario, characters responding to the main characters, and background character actions. A video automation pipeline animates character actions performed by the digital human characters into video datasets with annotation files incorporating detailed pixel and depth information for each frame. Video datasets may include variant video datasets differentiated from the primary dataset by changes in domain variants (e.g.

Abstract: An electrochemical impedance spectroscopy (EIS) measurement system to adjust for an alternating current (AC) signal of an electrochemical cell in an energy storage system can include a current measurement device and a voltage measurement device.

Abstract: An electrochemical impedance spectroscopy (EIS) measurement system to adjust for a change in a direct current (DC) voltage value of an electrochemical cell in an energy storage system can include a current measurement device, which can be arranged for measuring a current through the electrochemical cell. The EIS measurement system can also include a voltage measurement device, which can be arranged to be coupled across the electrochemical cell, for measuring a voltage across the electrochemical cell. The EIS measurement system can also include processing circuitry, which can be coupled to the current measurement device and the voltage measurement device and which can be configured to determine a representation of the DC voltage across the electrochemical cell. The processing circuitry can also be configured to determine an EIS voltage at a specified EIS frequency using the representation of the DC voltage across the electrochemical cell and the measured voltage across the electrochemical cell.

Abstract: The technology disclosed herein may establish a data representation of the physical geometry of a battery assembly, the battery assembly comprising a plurality of cells, one or more power connections, an electrochemical impedance spectroscopy (EIS) controller, EIS force conductors, and EIS sense conductors. The technology may define simulation port positions at each connection between EIS force/sense conductors and each cell, and at each connection of EIS sense conductors to the EIS controller. The technology may model the EIS sense circuitry and the EIS force circuitry. The technology may simulate EIS response across a frequency range using the established data representation, established simulation port positions, and the modeled EIS sense circuitry and force circuitry, producing S-parameters corresponding to each established simulation port. The technology may adjust the complex impedance of the particular cell as a function of the S-parameters.

Abstract: Systems and methods are disclosed herein for providing fair allocation of resources in a multi-tenant environment. Systems and methods are configured for identifying a plurality of tenants participating in the multi-tenant environment. For each tenant of the plurality of tenants, systems determine a tenant status as a donating tenant, a fairly borrowing tenant, or an unfairly borrowing tenant and apply a different borrowing algorithm to each tenant of the plurality of tenants based on a corresponding tenant status determined for each tenant. Different borrowing algorithms are configured to determine different resource borrowing limits from a common pool of resources for each tenant.

Abstract: A disclosed method facilitates an increase in utilization with respect to a resource quota allocated to a tenant from a shared resource pool. The method includes transmitting a lease request to a quota service on behalf of the tenant, where the lease request identifies a processing task and specifies quantity of cloud-based resources requested from the shared resource pool for execution of the processing task. The method further provides for determining, based on a feedback signal received from the quota service, whether grant of the lease request would cause the tenant to exceed a resource quota allocated to the tenant and dynamically decreasing parallelism of active tasks being processed by the cloud-based resources on behalf of the tenant in response to determining that grant of the lease request would cause the tenant to exceed the resource quota limit.

Abstract: A system provides capacity-based load balancing across model endpoints of a cloud-based artificial intelligence (AI) model. The system includes a consumption determination engine executable to determine a net resource consumption for processing tasks in a workload generated by a client application for input to the trained machine learning model. The system also includes a load balancer that determines a distribution of available resource capacity in a shared resource pool comprising compute resources at each of the multiple model endpoints. The load balancer allocates parallelizable tasks of the workload among the compute resources at the multiple model endpoints based on the net resource consumption of the tasks and on the distribution of available resource capacity in the shared resource pool.

Abstract: A disclosed method reduces memory consumption of a trained sequential model. The method includes receiving, from a client application, an initial processing request identifying an input sequence to be processed by the trained sequential model and an initial value for an output size parameter specifying a requested size of output from the trained sequential model. The method further includes sequentially transmitting, to the trained sequential model, multiple partial processing requests based on the initial processing request that each specify a fraction of the initial value as the output size parameter and receiving a sequence of output responses from the trained sequential model generated in response to processing the multiple partial processing requests. The method further provides for returning, to the client application, a final merged response that includes the sequence of output responses.

Abstract: A similarity matrix is generated for different descriptions of one or more things. The similarity matrix includes values that indicate the extent of similarity between different pairs of descriptions. The values of the similarity matrix are clustered to generate a clustered similarity matrix, which include groupings of pair-wise similarities between the different descriptions. Commonalities between the different descriptions are identified using the groupings of pair-wise similarities.

Abstract: Web-based opinion survey method, apparatus, and computer-readable media operable to cause propositional function responses to be provided to a survey server from a client device. The propositional functions are P(x), where P and x are the predicate and subject. Each P(x) is evaluated in the client device for subjects, each with a different x. Preferably, the client device displays the subjects within a Web Single Page Application (SPA) running on the client device. Preferably, the SPA displays a nonnumerical scale, the granularity of which is directly proportional to the number of pixels spanned by the scale. For each P(x), the client device displays labeled markers along the scale, to provide an indication of a level of agreement with the expressed P(x). For each P(x) subject, the client expresses an opinion on a position on the scale, whereby a pixel position corresponds to a rating for the selected subject.

Abstract: A distributed resource may be mapped into a virtual network, where the resource is distributed across a large number of nodes that are uniquely addressable within the distributed resource service's address space. The resource can be represented using a relatively small number of private VIP addresses within the virtual network, while still enabling access to all of the nodes that are uniquely addressable within the address space of the distributed resource service. A resource map may be created that relates the distributed resource service's address space to the virtual network's address space. The resource map may be used by a gateway that facilitates access to a distributed resource by clients. The resource map may also be used to translate packets that are sent from clients within a virtual network into the distributed resource service's address space.

Abstract: A system and method for automated video generation for training machine and deep learning algorithms in aviation environments generates photorealistic digital human characters and an aviation environment according to a desired scenario, including fixtures, free objects, lighting and physics configurations, and camera views. Character actions in the desired scenario are mapped to pose sequences which may be manually generated or transferred from image sequences of human activities, including both main character activities specified by the scenario, characters responding to the main characters, and background character actions. A video automation pipeline animates character actions performed by the digital human characters into video datasets with annotation files incorporating detailed pixel and depth information for each frame. Video datasets may include variant video datasets differentiated from the primary dataset by changes in domain variants (e.g.

Abstract: A distributed resource may be mapped into a virtual network, where the resource is distributed across a large number of nodes that are uniquely addressable within the distributed resource service's address space. The resource can be represented using a relatively small number of private VIP addresses within the virtual network, while still enabling access to all of the nodes that are uniquely addressable within the address space of the distributed resource service. A resource map may be created that relates the distributed resource service's address space to the virtual network's address space. The resource map may be used by a gateway that facilitates access to a distributed resource by clients. The resource map may also be used to translate packets that are sent from clients within a virtual network into the distributed resource service's address space.

Abstract: The present invention relates to biocide-composites providing high retention of biocides in glueline-treated glued-wood products that are hot-pressed or hot-pressed and block-stacked during manufacture.

Abstract: Disclosed herein is a nanovesicles from adult stem cells containing iron nanoparticles and its use. The nanovesicle according to the present disclosure provides effects of maximizing the efficacy of treating mesenchymal stem cells by pretreating cells with iron nanoparticles; reconstituting the cells in a nano-sized form to facilitate intravenous injection; and increasing the efficiency of targeting disease areas through magnet induction. In particular, the present disclosure can replace mesenchymal stem cells as a cell therapeutic agent, and it can be applied to various diseases as a novel biopharmaceutical drug because it can increase the function and efficiency of an exosome-based therapeutic agent.