Abstract: Systems, computer program products, and methods are described herein for implementing dynamic multi-factor soft lock on user identifiers. The present invention is configured to receive, from a first user input device, a network registration request from a user to obtain authorization to execute resource transfers within a distributed network using a first user identifier; query, using an information retrieval engine, metadata associated with the user within the distributed network for traceable instances of digital activities of the user; determine one or more user identifiers based on at least the metadata associated with the user; execute, using an authentication subsystem, a soft lock on the one or more user identifiers; approve authorization for the user to execute the resource transfers within the distributed network using the first user identifier; and transmit control signals configured to cause the first user device to display the authorization.

Abstract: A system includes memory hardware storing processor-executable instructions, a persona, and a data structure associated with the persona. Processor hardware executes the processor-executable instructions. The instructions include generating a graphical user interface and, in response to a first condition, inputting a first set of explanatory variables to a first trained machine learning model to generate a first metric and transforming the graphical user interface according to the persona and the first metric. The instructions include, in response to a second condition, inputting a second set of explanatory variables to a second trained machine learning model to generate a second metric and transforming the graphical user interface according to the persona and the second metric. The first trained machine learning model is different from the second trained machine learning model.

Abstract: Disclosed is a buoyancy tube for a life raft having: a first panel including: a first panel top edge and a first panel bottom edge, the first panel top edge defines a first repeating pattern, and the first panel bottom edge defines a second repeating pattern that is a rotated version of the first panel top edge; a second panel that has a same shape as the first panel, the first and second panels connected by a first elongated seam and a second elongated seam that are non-overlapping with one another, the first and second panels, when connected, define outer an inner boundaries of the life raft, the outer boundary defines an outer polygon having outer sides and the inner boundary defines an inner polygon having inner sides such that each of the plurality of outer sides is parallel with one of the plurality of inner sides.

Abstract: A method of activating a head-worn device is disclosed. The method includes activating the head-worn device and performing a partial bootup. When an instruction to perform a function is received, it is determined whether or not the instruction is permitted for partial bootup execution. The instruction is executed based on the instruction being permitted for partial bootup execution, and a bootup of the head-work device is completed based on the instruction not being permitted for partial bootup execution. The method may further comprise determining if the instruction requires user authentication in order to be executed, and based on the instruction being partial bootup compatible and not requiring user authentication, executing the instruction.

Abstract: The present disclosure relates to a method for controlling at least one actuator of a vehicle, the actuator being configured to apply a torque on at least one wheel of the vehicle, wherein the applied torque is determined by a control function associated with a control bandwidth, the method comprising configuring the control function to control the applied torque to reduce a difference between a first parameter value related to a current rotational speed of the wheel and a second parameter value related to target rotational speed of the wheel; obtaining data indicative of a current operating condition of the vehicle; setting the control bandwidth of the control function in dependence of the current operating condition of the vehicle; and controlling the actuator using the control function.

Abstract: A system for conducting multi-session user interactions accesses a first interaction session between the user and a first entity, where the first interaction session is via a first communication channel. The system determines first context information associated with the first interaction session, where the first context information associated with the first interaction session comprises a summary associated with the first interaction session. The system generates a token identifier (ID) uniquely identifying the user and the first context information. The system associates the token ID to the user interaction information. The system accesses a second interaction session between the user and a second entity, wherein the second interaction session is via a second communication channel. The system authenticates the user based at least in part upon the token ID. The system communicates the first context information associated with the first interaction session to the second entity.

Abstract: An example computing system includes one or more processing units implemented in circuitry and configured to: process an intent for configuration of a plurality of managed network devices, the intent representing authorization of access to capabilities of applications accessible to users of the managed network devices according to roles assigned to the users; receive advertised capabilities from a new application accessible to the users; receive a request for authorization to one of the capabilities of the new application from one of the users; determine one of the roles assigned to the one of the users; determine whether the intent grants authorization to the one of the capabilities according to the one of the roles; and grant the one of the users access to the one of the capabilities when the intent grants authorization to the one of the capabilities according to the one of the roles.

Abstract: A method of training a fingerprint image enhancing engine for use in a fingerprint capturing device, and a corresponding apparatus and computer readable medium, include producing a synthetic image dataset comprising plural pairs of synthetic images. Each pair of synthetic images include a clean synthetic image and a raw synthetic image corresponding to the clean synthetic image. Each raw synthetic image is produced according to a model of the fingerprint capturing device. The method also includes training a neural network using the synthetic image dataset.

Abstract: An exemplary modular hold-open device is configured for use with a door closer comprising a body, a pinion rotatably mounted to the body, and an armature connected with the pinion. The modular hold-open device is configured to be mounted to the door closer, to selectively prevent rotation of the pinion by exerting on the pinion a resistive torque in a door-opening direction, and to cease exerting the resistive torque in response to a door-closing torque on the pinion exceeding a threshold torque to thereby permit rotation of the pinion in the door-closing direction.

Abstract: A neural network in multi-task deep learning paradigm for machine vision includes an encoder that further includes a first, a second, and a third tier. The first tier comprises a first-tier unit having one or more first-unit blocks. The second tier receives a first-tier output from the first tier at one or more second-tier units in the second tier, a second-tier unit comprises one or more second-tier blocks, the third tier receives a second-tier output from the second tier at one or more third-tier units in the third tier, and a third-tier block comprises one or more third-tier blocks. The neural network further comprises a decoder operatively the encoder to receive an encoder output from the encoder as well as one or more loss function layers that are configured to backpropagate one or more losses for training at least the encoder of the neural network in a deep learning paradigm.

Abstract: A sequencing kit includes a plurality of particles and a flow cell. The plurality of particles includes a primer set attached to a surface of each of the plurality of particles; and a flow cell surface attachment mechanism attached to the surface of each of the plurality of particles. The flow cell surface attachment mechanism is selected from the group consisting of a capture primer, an alkene, an alkyne, biotin, and a charged polymer. The flow cell includes a plurality of chemical pads that are spatially separated from one another on a substantially flat substrate surface, each of the chemical pads including chemistry to attach to the surface attachment mechanism.

Abstract: The present disclosure provides a new and improved process for preparation of intermediate compounds and synthesis of mesotrione therefrom. The present disclosure provides an economical, efficient and eco-friendly process for preparation of mesotrione.

Abstract: Electrodes having a usability indicator to indicate a usability of the electrodes are described. The electrodes include a first electrode and a second electrode, as well as an output device(s) that are configured to output a usability indication indicative of a usability of the set of electrodes. If the usability indication indicates that the electrodes should be replaced, the user can discard the set of electrodes and replace them with a new set of electrodes, thereby mitigating the risk of compromising patient care for a patient.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an object recognition neural network using multiple data sources. One of the methods includes receiving training data that includes a plurality of training images from a first source and images from a second source. A set of training images are obtained from the training data. For each training image in the set of training images, contrast equalization is applied to the training image to generate a modified image. The modified image is processed using the neural network to generate an object recognition output for the modified image. A loss is determined based on errors between, for each training image in the set, the object recognition output for the modified image generated from the training image and ground-truth annotation for the training image. Parameters of the neural network are updated based on the determined loss.

Abstract: Disclosed is a buoyancy tube for a life raft having: a first panel including: a first panel top edge and a first panel bottom edge, the first panel top edge defines a first repeating pattern, and the first panel bottom edge defines a second repeating pattern that is a rotated version of the first panel top edge; a second panel that has a same shape as the first panel, the first and second panels connected by a first elongated seam and a second elongated seam that are non-overlapping with one another, the first and second panels, when connected, define outer an inner boundaries of the life raft, the outer boundary defines an outer polygon having outer sides and the inner boundary defines an inner polygon having inner sides such that each of the plurality of outer sides is parallel with one of the plurality of inner sides.

Abstract: An exemplary clutch mechanism includes a casing, first and second hubs rotatably mounted to the casing, an electrically-actuated drive assembly mounted within the casing, and a clutching lug movably mounted within the casing. The lug has an engaged position in which the lug couples the hubs for joint rotation and a disengaged position in which the hubs are rotationally decoupled. The drive assembly is operable to drive the lug between the engaged and disengaged positions to couple and decouple the hubs. The clutch mechanism is modular and self-contained within the casing such that the mechanism can be installed to each of a plurality of different lockset products without opening the casing.

Abstract: An example controller device that manages a plurality of network devices includes one or more processors implemented in circuitry and configured to: determine that configuration of one or more network devices of the plurality of network devices is to be updated; determine dependencies between types of resources provided by the network devices; construct a directed acyclic graph (DAG) representing the dependencies, the DAG having nodes representing the corresponding types of resources of the network devices of the plurality of network devices; sort the nodes of the DAG according to a grouped topological sort into a plurality of hierarchical levels according to the dependencies; and submit queries for two or more resources of the network devices at a common level of the plurality of hierarchical levels in parallel to determine resources of the determined types of resources of the two or more resources to configure the two or more network devices.

Abstract: An exemplary indicator mechanism is configured for use with a door closer including a body and an adjustment screw. The indicator mechanism generally includes an indicator, at least one indicium, and a cycloidal drive. The cycloidal drive is configured to selectively align the indicator and the at least one indicium in response to rotation of the adjustment screw to thereby indicate an operating characteristic of the door closer.

Abstract: A computerized method for transforming an interactive graphical user interface according to machine learning includes selecting a persona, loading a data structure associated with the selected persona, and generating the interactive graphical user interface. The method includes, in response to a user selecting a first selectable element, inputting a first set of explanatory variables to a first trained machine learning model to generate a first metric, and transforming the user interface according to the selected persona and the first metric. The method includes, in response to the user selecting a second selectable element, inputting a second set of explanatory variables to a second trained machine learning model to generate a second metric, and transforming the user interface according to the selected persona and the second metric. In various implementations, first metric is a first probability of the persona being approved for a first prior authorization prescription.

Abstract: An apparatus includes a memory and a processor. The memory stores an identification of information and a document associated with an external system. The processor receives information associated with a user, and uses the information to generate a file of a first type. The processor also receives a selection of an option to initiate automatic generation of a file of a second type by the external system. In response, the processor identifies, from the information and based on the identification of the information used by the external system, a subset of information associated with the user. The processor transmits the subset to the external system. The processor additionally presents the document to the user, determines that the user edited the document, and transmits the edited document to the external system. In response to receiving the subset and the edited document, the external system generates the file of the second type.