Abstract: A data system is provided for analyzing and maintaining data obtained from one or more data sources on which the data system depends. The system includes a primary database including current values used by the system and a collection of executable algorithms used to generate the data maintained in the primary database. In response to receiving a notification regarding a change in one of the data sources, a dependency database is used to establish an execution order for algorithms of the algorithm collection that are directly or indirectly dependent on the changed data. The algorithms identified in the execution order are then executed in accordance with the execution order and the corresponding result is stored in the primary database. The system may include data harvesters adapted to recognize changes in the data sources and to generate and transmit corresponding change notifications when such changes occur.

Abstract: A system for generating power includes a turbine generator for generating alternating current (AC) power and a power electronics module that provides a first signal to the turbine generator to switch an operating mode of the turbine generator from an off mode to a startup mode. The first signal is variable frequency power. The system includes a controller that provides a second signal that causes the turbine generator to switch from a normal operating mode to a coast down mode. In the startup mode, the turbine generator accelerates to a full rotational rate and in the coast down mode, the turbine generator decelerates from the full rotational rate to a stop over an interval of time. The system includes a power converter that converts rotational inertia by the turbine generator into direct current (DC) power responsive to the turbine generator operating in the coast down mode.

Abstract: An iterative attention-based neural network training and processing method and system iteratively applies a focus of attention of a trained neural network on syntactical elements and generates probabilities associated with representations of the syntactical elements, which in turn inform a subsequent focus of attention of the neural network, resulting in updated probabilities. The updated probabilities are then applied to generate syntactical elements for delivery to a user. The user may respond to the delivered syntactical elements, providing additional training information to the trained neural network.

Abstract: A dental cement with improved radiopacity and delivery methods may feature active barium silicate compounds such as mono-barium silicate, dibarium silicate, and tribarium silicate. The barium silicate compounds are manufactured and then mixed into a paste with an anhydrous carrier and stored in a syringe. Storage in the syringe maintains the paste in an anhydrous state until applied to a treatment site, when water and moisture may be naturally or artificially applied to the paste and begin the curing process. The cement may be use in both dental and orthopedic fields.

Abstract: An insert and insert assembly for facilitating image-based determination of a blood component in medical waste. The medical waste is collected in a waste canister of a medical waste collection system that includes a vacuum source, a fluid measuring subsystem, and a cleaning subsystem. The insert assembly includes means for positioning the insert within the waste canister for an imaging feature of the insert to be spaced apart from an inner surface of the waste canister. The imaging feature may include imaging surfaces in a side-by-side arrangement with each being spaced apart from the inner surface by a respective distance. The insert may include a flow surface configured to limit obstruction of pressurized fluid from the cleaning subsystem being directed at the imaging feature. The insert may define a slot providing fluid communication between a rear side and a front side of the insert.

Abstract: Systems and techniques for aggregation, display, and sharing of data. Graphic items representing data objects identified by a data package may be displayed on timelines. Each timeline may be associated with a respective class of data, and each graphic item displayed on a respective timeline may represent one or more of the data objects in the class associated with the respective timeline. A prediction may be made regarding which data will be displayed in the near future. A pre-fetch request may be generated, and the predicted data may be retrieved from a remote server and stored in a local data cache before the user requests that the predicted data be displayed.

Abstract: Systems and methods for determining the likely responsiveness of a human cancer subject to a checkpoint blockade immunotherapy regimen are provided. Sequencing reads are obtained from samples from the subject representative of the cancer. A human leukocyte antigen type and a plurality of clones is determined from the sequencing reads. For each clone, an initial frequency X? in the one or more samples is determined and a corresponding clone fitness score of the clone is computed, thereby computing clone fitness scores. Each such fitness score is computed by identifying neoantigens in the respective clone, computing a recognition potential for each neoantigen, and determining the corresponding clone fitness score of the respective clone as an aggregate of these recognition potentials. A total fitness, quantifying the likely responsiveness of the subject to the regimen, is computed by summing the clone fitness scores across the plurality of clones.

Abstract: An iterative attention-based neural network training and processing method and system iteratively applies a focus of attention of a trained neural network on syntactical elements and generates probabilities associated with representations of the syntactical elements, which in turn inform a subsequent focus of attention of the neural network, resulting in updated probabilities. The updated probabilities are then applied to generate syntactical elements for delivery to a user. The user may respond to the delivered syntactical elements, providing additional training information to the trained neural network.

Abstract: Provided herein are methods and compositions for disrupting biofilms in vitro and in vivo. Also disclosed are antibodies comprising a specified heavy chain (HC) immunoglobulin variable domain sequence and/or a specified light chain (LC) immunoglobulin variable domain sequence.

Abstract: A method of detecting catheter movement includes positioning a first sensor in a first body cavity, monitoring a first parameter profile of the first body cavity, positioning a second sensor in a second body cavity, monitoring a second parameter profile of the second body cavity, the second parameter profile different than the first parameter profile at a first time, and, when the second parameter profile is the same as the first parameter profile at a second time after the first time, taking a catheter movement action.

Abstract: The present disclosure relates to a sheet comprising a composite material comprising a polymer and hexagonal boron nitride particles, wherein the hexagonal boron nitride particles comprise platelet-shaped hexagonal boron nitride particles, and wherein the platelet-shaped hexagonal boron nitride particles are oriented in a direction perpendicular to the direction of the plane of the sheet, and wherein the composite material comprises at least 70 percent by weight of the hexagonal boron nitride particles, based on the total weight of the composite material, and wherein the sheet has a through-plane thermal conductivity of more than 12 W/m*K. The present disclosure further relates to processes for producing said sheet.

Abstract: An iterative attention-based neural network training and processing method and system iteratively applies a focus of attention of a trained neural network on syntactical elements and generates probabilities associated with representations of the syntactical elements, which in turn inform a subsequent focus of attention of the neural network, resulting in updated probabilities. The updated probabilities are then applied to generate syntactical elements for delivery to a user. The user may respond to the delivered syntactical elements, providing additional training information to the trained neural network.

Abstract: A distributed analytics system to control an operation of a monitored system, and method of operation thereof, including an architect subsystem and an edge processing device. The edge subsystem includes an edge processing device associated with the monitored system. The architect subsystem is configured to deploy an analytic model to the edge processing device based on characteristics of the monitored system. The edge processing device is configured to receive the analytic model and independently perform predictive and prescriptive analytics on dynamic input data associated with the monitored system, provide control signals to the monitored system according to the predictive and prescriptive analytics, and provide information to the architect subsystem, including monitored system responses to the control signals. The architect subsystem is configured to modify the analytic model to improve system performance of the monitored system.

Abstract: The present disclosure relates to an array-based assay for transposase-accessible chromatin and prognostic molecular markers of treatment-resistant/early recurrent cancer.

Abstract: A dental implant with improved sealing capacity utilizes materials compatible with both hard and soft tissues to not only osseointegrate, but also form physiological or static seals with gingival tissue to reduce incidents of perio-implantitis and soft tissue sloughing. Disclosed embodiments contemplate the addition of a biocompatible top insert about an implant which will encourage either physiological integration or at least static sealing of the soft tissue about the implant. The top insert may be fashioned of any biocompatible material, though bone and other similar mineral structures may be utilized. The top insert may be fashioned entirely of the biocompatible material, be impregnated with the material, or the material my be formed into a ceramic surface layer about the insert.

Abstract: A spray gun includes a gun body and a handle removably connected to the gun body. A filter is disposed in the handle for filtering particulate from the spray fluid. A trigger guard is connected to the handle and gun body and includes a contour on a lower portion of the trigger guard for receiving one or more fingers of the user that are not interfacing with and contacting the trigger. The trigger guard can be disconnected from the gun body and rotated relative to the handle. The trigger guard can contact a portion of the handle and exert torque on the handle to connect the handle to and disconnect the handle from the gun body. The portion of the handle at least partially covers a fitting connecting to the handle to provide spray fluid to the spray gun.

Abstract: An iterative attention-based neural network training and processing method and system iteratively applies a focus of attention of a trained neural network on syntactical elements and generates probabilities associated with representations of the syntactical elements, which in turn inform a subsequent focus of attention of the neural network, resulting in updated probabilities. The updated probabilities are then applied to generate syntactical elements for delivery to a user. The user may respond to the delivered syntactical elements, providing additional training information to the trained neural network.

Abstract: The disclosure provides at least one compound, tautomer, deuterated derivative, or pharmaceutically acceptable salt chosen from compounds of Formula I, tautomers thereof, deuterated derivatives of those compounds or tautomers, and pharmaceutically acceptable salts of any of the foregoing, compositions comprising the same, and methods of using the same, including uses in treating APOL1-mediated diseases, including pancreatic cancer, focal segmental glomerulosclerosis (FSGS), and/or non-diabetic kidney disease (NDKD).

Abstract: An iterative attention-based neural network training and processing method and system iteratively applies a focus of attention of a trained neural network on syntactical elements and generates probabilities associated with representations of the syntactical elements, which in turn inform a subsequent focus of attention of the neural network, resulting in updated probabilities. The updated probabilities are then applied to generate syntactical elements for delivery to a user. The user may respond to the delivered syntactical elements, providing additional training information to the trained neural network.