Abstract: A method and/or system for automated estimation of 3D orientation of a physical asset using deep learning models and computer vision algorithms, according to one or more embodiments. The system may be configured to receive images of the physical asset and camera orientation data as input, use deep learning neural network models to isolate the physical assets across the images, track each physical asset instance throughout the images and derive a 3D point cloud model of each asset by projecting binary masks of the asset contours from different view-points. The 3D point cloud model is further processed and supplemented with camera orientation data to estimate the 3D orientation of one or more assets present in the images.

Abstract: In some examples, collective application portfolio migration control may include determining, for a plurality of applications that are to be clustered for migration to a cloud environment, a coupling coefficient that represents a type of coupling between pairs of applications from the plurality of applications, a proximity coefficient that represents application proximities, and a connectedness coefficient that represents application connections. A combined application relatedness coefficient may be determined based on the coupling coefficient, the proximity coefficient, and the connectedness coefficient. A portfolio graph may be generated based on the combined application relatedness coefficient to generate migration application clusters to duster the plurality of applications. Migration of the plurality of applications to the cloud environment may be controlled based on the migration application clusters.

Abstract: A surgical robot system includes a surgical robot, a robot arm connected to such surgical robot, and an end-effector connected to the robot arm. A registration fixture is used in conjunction with various registration systems in the surgical robot system. Such registration systems likewise include a detachable base in the form of a detachable dynamic reference base, along with an associated mount, the dynamic reference base and mount having certain features which permit the dynamic reference base to be selectively attached, detached, and reattached at different phases of an operation, whether pre-operative or intra-operative, and such successive attachments are done without the dynamic reference base, and tracking markers associated therewith, losing registration. Related methods allow for the more efficient and effective performance of operations by virtue of the dynamic reference base maintaining its registration during attachments and reattachments.

Abstract: State of the art authentication mechanisms have limitations when used by Basic Emergent User (BEU). Embodiments herein provide method and system for recognition based multi-skill-multi-sensory passwords with dynamic identification of sensor combination based on end user skill, specifically for the BEU. The method disclosed generates user profile using a task-based technique to determine skill and capability of the user associated with each of a plurality of sensory categories used for generating a multi-skill-multi-sensory password. Each of the plurality of sensory categories are graded is descending order based on user's skill and capability and user is offered to select each password entry from a particular sensor category in accordance with the identified grade in each iteration. Thus, the entropy of password generation in the context of user is split among the sensor categories.

Abstract: Machine logic (for example, software) are choosing among pre-existing manufacturing processes to make a newly-designed physical piece part, or a piece part that reflects a modified design with respect to an earlier design. In some embodiments, the manufacturing process includes an additive manufacturing (AM) process. In some embodiments, the manufacturing process involves three dimensional (3D) printing.

Abstract: Embodiments disclosed herein include an electronic package. In an embodiment, the electronic package comprises a substrate and a pad on the substrate. In an embodiment, a layer is over the pad and the substrate, and an opening through the layer is above the pad. In an embodiment, sidewalls of the layer define the opening. In an embodiment, an undercut at an end of the opening adjacent to the pad is provided, where the undercut is positioned between the pad and the layer.

Abstract: Introduced here is a network-accessible platform (or simply “platform”) that is designed to monitor digital activities that are performed across different services to ascertain, in real time, threats to the security of an enterprise. In order to surface insights into the threats posed to an enterprise, the platform can apply machine learning models to data that is representative of digital activities performed on different services with respective accounts. Each model may be trained to understand what constitutes normal behavior for a corresponding employee with respect to a single service or multiple services. Not only can these models be autonomously trained for the employees of the enterprise, but they can also be autonomously applied to detect, characterize, and catalog those digital activities that are indicative of a threat.

Abstract: Introduced here is a network-accessible platform (or simply “platform”) that is designed to monitor digital activities that are performed across different services to ascertain, in real time, threats to the security of an enterprise. In order to surface insights into the threats posed to an enterprise, the platform can apply machine learning models to data that is representative of digital activities performed on different services with respective accounts. Each model may be trained to understand what constitutes normal behavior for a corresponding employee with respect to a single service or multiple services. Not only can these models be autonomously trained for the employees of the enterprise, but they can also be autonomously applied to detect, characterize, and catalog those digital activities that are indicative of a threat.

Abstract: Corneal improvement following a therapeutic procedure, such as Descemet membrane endothelial keratoplasty (“DMEK”), is predicted or otherwise monitored using Scheimpflug imaging and a machine learning model that has been trained to predict or otherwise monitor corneal improvement from Scheimpflug imaging parameters that are independent of corneal thickness. The machine learning model can include a predictive model trained using ensemble learning, or other suitable machine learning models such as neural networks.

Abstract: A system, apparatus, and method for delivering a drug into a target volume of a subject includes an ultrasound scanner for performing a volume scan of a predetermined volume of the subject, a computing device for generating a 3D model of the predetermined volume and computing navigational data to reach the target volume from an entry orifice of the volume of the subject, a housing, for accommodating a barrel, to which a sheath is detachably attached, and a drug delivery device for delivering the drug at one or more locations in the target volume, wherein the drug delivery device is configured for delivering a predetermined volume of drug at one or more locations in the target volume of the subject.

Abstract: Introduced here is a network-accessible platform (or simply “platform”) that is designed to monitor digital activities that are performed across different services to ascertain, in real time, threats to the security of an enterprise. In order to surface insights into the threats posed to an enterprise, the platform can apply machine learning models to data that is representative of digital activities performed on different services with respective accounts. Each model may be trained to understand what constitutes normal behavior for a corresponding employee with respect to a single service or multiple services. Not only can these models be autonomously trained for the employees of the enterprise, but they can also be autonomously applied to detect, characterize, and catalog those digital activities that are indicative of a threat.

Abstract: Introduced here is a network-accessible platform (or simply “platform”) that is designed to monitor digital activities that are performed across different services to ascertain, in real time, threats to the security of an enterprise. In order to surface insights into the threats posed to an enterprise, the platform can apply machine learning models to data that is representative of digital activities performed on different services with respective accounts. Each model may be trained to understand what constitutes normal behavior for a corresponding employee with respect to a single service or multiple services. Not only can these models be autonomously trained for the employees of the enterprise, but they can also be autonomously applied to detect, characterize, and catalog those digital activities that are indicative of a threat.

Abstract: Lyophilised formulations of mRNA adsorbed onto lipid nano-emulsion particles. The present invention relates to lyophilised formulations of mRNA adsorbed onto lipid nano-emulsion particles. It particularly provides a method for lyophilisation of liquid 5 formulations of mRNA adsorbed onto lipid nano-emulsion particles under the conditions that maintain the integrity and pharmaceutical properties of resultant lyophilised formulations for the extended periods at storage temperature of about 5° C.

Abstract: Arrangements for intelligently orchestrating and automating requests are provided. In some aspects, configuration parameters and historical response data indicating a plurality of previous responses to requests may be received. Based on the configuration parameters and the historical response data, intelligence information associated with the requests may be extracted using a machine learning algorithm. An intelligence model may be built using the extracted intelligence information. A subsequent request may be received. One or more actions in response to the subsequent request may be automatically derived using the intelligence model. The subsequent request may be processed by executing the one or more actions. An accuracy of the intelligence model may be determined based on the configuration parameters.

Abstract: Systems, methods, and machine-readable media facilitate adaptive multi-system operations. Electronic communications from resource-controlling systems and/or monitoring devices may be monitored to identify signals corresponding to processes performed by the resource-controlling systems, resource capacities of resources controlled by the resource-controlling systems, and states of the resource-controlling systems. System interactions that correspond to a defined event may be detected. A protocol that includes parameter constraints mapped to the defined event identified. Operating conditions of the resource-controlling systems and/or metrics of processes performed may be determined based on the monitoring. A subset of the resource-controlling systems may be identified as a function of the operating conditions and/or the metrics. A resource-controlling system may be caused to allocate corresponding resources and perform the processes in accordance with the protocol.

Abstract: The present disclosure provides systems and methods for the recovery of protein species from wet mill grain process streams. Systems and methods of the present disclosure may be integrated with a wet mill grain process to separate out protein species that may limit efficiency of the grain process and produce one or more product streams comprising these separated protein species. A feed stream may be fractionated by at least two membranes into retentate and permeate streams. Removing larger proteins through the membrane fractionation may allow previously soluble prolamin products in the permeate stream(s) to precipitate. The recovered protein species may include prolamin, such as zein from a corn grain feed.

Abstract: A processing device receives a request specifying a logical address associated with a host-initiated operation directed at a first portion of a memory device. The processing device accesses a second L2P table comprising a mapping between logical addresses and physical addresses in a second portion of the memory device. A physical location within the second portion of the memory device is identified based on the second L2P table. The physical location corresponds to a portion of a first L2P table that specifies a physical address within the first portion of the memory device that corresponds to the logical address. The physical address is identified based on the portion of the first L2P table and the host-initiated operation is performed at the physical address.

Abstract: A WTRU may track parameters associated with the WTRU or target WTRUs. The parameters may be associated with positioning and/or sidelink communications. The WTRU may receive a configuration for transmission of reference signals to target WTRUs. The WTRU may transmit one or more reference signals on one or more configured sidelink resources. The WTRU may receive respective measurement report(s) from respective target WTRU(s) (e.g., a target WTRU may receive a reference signal transmitted by the WTRU and send an associated measurement report). The WTRU may be configured to send the received target WTRU measurement(s) to the network entity. The WTRU may send each of the received measurements. The WTRU may send the received measurement(s) if condition(s) are satisfied. For example, if a first measurement associated with a first measurement report from a first target WTRU exceeds a first threshold, the WTRU may send the first measurement to the network entity.

Abstract: A pre-patient collimator for a CT imaging system is provided. The pre-patient collimator includes a collimator housing including a plurality of walls, wherein the plurality of walls includes a first wall configured to face an X-ray source when the pre-patient collimator is coupled to the CT imaging system and a second wall and a third wall flanking the first wall. The pre-patient collimator also includes a bowtie filter assembly disposed within the collimator housing and including a bowtie filter. The pre-patient collimator further includes an adjustment mechanism configured to move the bowtie filter assembly in a lateral direction between the second wall and the third wall within the collimator housing.

Abstract: A device for detecting exposure to light includes: a photo-responsive layer including a photochromic material; a skin-mimicking cover layer covering a first side of the photo-responsive layer; and an adhesive layer configured to couple a second side of the photo-responsive layer opposite the first side to a surface.