Abstract: An apparatus and method for detecting undiagnosed sleep disordered breathing uses daytime sleepiness and nighttime Obstructive Sleep Apnea (OSA) severity. This involves detecting people with excessive daytime sleepiness (and high likelihood of falling asleep during the day) caused by OSA through objective and subjective daytime and nighttime monitoring. Screening is provided for those who are most likely to be suffering a daytime impact of their sleep apnea and thus most likely to respond positively to a potential diagnosis, and notifying these people is also provided.

Abstract: An appliance includes an appliance body defining a cavity. A front panel defines a connector slot. A hinge arm is configured to be pivotally coupled with the appliance body and includes an arm body defining an arm receiving well. A flange extends from the arm body and is configured to be received by the connector slot. A door includes a rail defining a rail receiving well and a channel configured to receive the hinge arm so that the rail receiving well is aligned with the arm receiving well. A fastener is configured to be received by the arm and rail receiving wells to fixedly couple the hinge arm within the channel of the rail. A guide is coupled with the front panel and defines an aperture aligned with the connector slot. First and second wings are configured to frame the flange when the flange is received by the connector slot.

Abstract: A file system in a user space partition of virtual memory may be mounted by a computing device that runs a virtual machine which includes a set of storage disks. The file system in user space may then expose one or more virtual files associated with one or more storage disks that correspond to one or more loop devices configured to map files of the virtual machine to the one or more virtual files. The computing device may then receive a request to read a data block stored at the virtual machine and may identify a file and corresponding virtual file that stores the requested data block based on a set of metadata provided by the loop devices. The computing device may then determine the location of the data block stored at the virtual machine, and may read the data block from the determined location.

Abstract: In particular embodiments, a computing system may divide at least a portion of a physical space surrounding a user into a plurality of three-dimensional (3D) regions, wherein each of the 3D regions is associated with an area of a plurality of areas in a plane. The system may generate estimated locations of features of objects in the portion of the physical space. Based on the estimated locations, the system may determine an occupancy state of each of the plurality of 3D regions. Then based on the occupancy states of the plurality of 3D regions, the system may determine that one or more of the plurality of areas have respective airspaces that are likely unoccupied by objects.

Abstract: A data storage transformation system includes a data storage management device that is coupled to a data provisioning device and a storage system. The data storage management device receives first format data that includes a first data format from the data provisioning device, and predicts at least one processing operation that will be performed on the first format data. The data storage management device then determines a second data format for performing the at least one processing operation, and transforms the first format data to second format data that includes the second data format. The data storage management device then transmits the second format data for storage in the storage system.

Abstract: A Directed Acyclic Graph (DAG) performance system includes a DAG management system that is coupled to each of a plurality of compute systems. The DAG management system stores a dynamic DAG, receives a request to perform the dynamic DAG, and identifies a plurality of DAG operations included in the dynamic DAG. The DAG management system then determines a respective compute system type that is configured to perform each of the plurality of DAG operations, and identifies a subset of the plurality of compute systems that each include one of the respective compute system types. The DAG management system then selects a respective compute system from the subset of the plurality of compute systems to perform each of the plurality of DAG operations, and transmits a respective instruction to perform one of the plurality of DAG operations to each respective compute system that was selected to perform that DAG operation.

Abstract: Provided herein are conductive inks and methods of formulation thereof, whose electric and mechanical properties (e.g. viscosity and surface tension) enable its use in a wide array of printing techniques.

Abstract: Disclosed are nucleic acid sequences comprising a cardiomyocyte-specific, cardiac stress-induced promoter operably linked to a mitochondrial targeting sequence (MTS) and/or a gene of interest. Disclosed are vectors comprising one or more of the disclosed nucleic acids. Disclosed are methods of using the disclosed nucleic acid sequences or vectors for treating a subject in need thereof. Disclosed are methods of treating pulmonary hypertension (PH) in a subject comprising administering a therapeutically effective amount of a vector to the subject, wherein the vector comprises a nucleic acid sequence comprising a cardiomyocyte-specific, cardiac stress-induced promoter operably linked to a mitochondrial targeting sequence (MTS) and/or a gene that encodes a PH therapeutic, wherein the PH therapeutic is expressed in cardiomyocytes undergoing cardiac stress.

Abstract: A data storage placement system includes a data storage management device that is coupled to a data provisioning device, a storage system, and a plurality of compute systems. The data storage management device receives data from the data provisioning device, predicts at least one processing operation that will be performed on the data, determines a first storage subsystem type based on the at least one processing operation, and determines a first compute system type based on the at least one processing operation. The data storage management device then identifies a first storage subsystem that is included in the storage system, that includes the first storage subsystem type, and that is proximate a first compute system in the plurality of compute systems that includes the first compute system type. The data storage management device then transmits the data for storage in the first storage subsystem.

Abstract: A power system may include a high-speed flywheel connected to an engine of a machine; a battery; a motor-generator unit (MGU) connected to the engine and the battery; and a turbocharger connected to the engine. One or more of the high-speed flywheel, the battery and the MGU, or the turbocharger may be configured to provide supplemental power to power provided by the engine to operate the machine, or provide replacement power when no power is provided by the engine to operate the machine.

Abstract: Introduced here are approaches to determining causal relationships in mixed datasets containing data related to continuous variables and discrete variables. To accomplish this, a marketing insight and intelligence platform may employ a multi-phase approach in which dependency is established before the data related to continuous variables is discretized. Such an approach ensures that information regarding dependence is not lost through discretization.

Abstract: According to certain embodiments, a message bus system comprises a first client and a second client. The first client is configured to publish messages associated with a message topic to a message bus, and the second client is configured to receive the messages associated with the message topic from the message bus. The message bus system is configured to unsubscribe the second client from the message topic based at least in part on determining that a demand of the second client for the messages associated with the message topic has fallen below a threshold.

Abstract: A depth image of an object can be input to a deep neural network to determine a first four degree-of-freedom pose of the object. The first four degree-of-freedom pose and a three-dimensional model of the object can be input to a silhouette rendering program to determine a first two-dimensional silhouette of the object. A second two-dimensional silhouette of the object can be determined based on thresholding the depth image. A loss function can be determined based on comparing the first two-dimensional silhouette of the object to the second two-dimensional silhouette of the object. Deep neural network parameters can be optimized based on the loss function and the deep neural network can be output.

Abstract: Illustrative embodiments represent a dynamic on-demand approach to configuring destination storage for bare metal restore (BMR) operations without operator intervention, including destination storage that is smaller than source storage devices. The illustrative operations rely on system state information collected concurrently with or shortly after source data is backed up, thereby capturing current actual storage metrics for the source data. The illustrative embodiments further rely on enhanced data agent components to collect and restore system state information as well as to restore backup data, thereby streamlining the configurations needed for the BMR operation to proceed. Additional business logic matches source mount points with suitable smaller destination storage resources and ensures that the BMR operation successfully completes with diverse and/or smaller storage destinations.

Abstract: A non-transitory computer-readable medium having program instructions for a method implemented in a Software as a Service (SaaS) management platform (SMP) is provided, including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: System and method to generate a unique security proof for secure accessing of data are disclosed. The method includes acquiring at least one image of a user's environment, analysing the at least one image for obtaining a first set of features, generating a unique security proof comprising a pair of keys, transmitting the unique security proof a key storage unit for storing the pair of keys, receiving at least one real-time image of the user's environment in real time, extracting a second set of features of the corresponding at least one real-time image, comparing the second set of features with the first set of features, determining one or more similarities between the second set of features and the first set of features, generating a confidence score, generating a notification for enabling the use of the pair of keys based on the confidence score generated for securely accessing of the data.

Abstract: An example apparatus includes a first frame buffer configured to store video data; a second frame buffer configured to store video data; and one or more processors configured to: reconstruct samples of a first block of a current picture of video data; store, in parallel, a compressed version of the samples of the first block of video data in the first frame buffer and an uncompressed version of the samples of the first block of video data in the second frame buffer; and responsive to determining to reconstruct a second block of the current picture of video data using intra block copy: obtain, from the second frame buffer, samples of a predictor block located in the current picture of video data, the predictor block at least partially overlapping the first block of video data; and predict, based on the obtained samples of the predictor block, samples of the second block.

Abstract: Systems and methods for automated code analysis and tagging are disclosed. In one embodiment, a method for automated code analysis and tagging may include: (1) receiving, by a code annotation computer program executed by a computer processor, a training code snippet from a training codebase; (2) parsing, by the code annotation computer program, the training code snippet into a data structure; (3) quantifying, by the code annotation computer program, the data structure, (4) parsing, by the code annotation computer program, a docstring associated with the training code snippet into a plurality of keywords; (5) quantifying, by the code annotation computer program, the plurality of keywords; and (6) training, by the code annotation computer program, a code annotation model based on a similarity between the quantified data structure and a smoothing parameter for a Dirichlet prior smoothing estimate.

Abstract: A medical treatment device is disclosed herein. In one example, the medical treatment device includes a core assembly which has a first conduct and a second conductor. An insulative material can surround the second conductor and define an electrode portion of the second conductor that is uncovered by the insulative material. The medical treatment device can include an interventional element that electrical couples to the first conductor. The electrode portion of the second conductor can be disposed radially adjacent to or distal of the interventional element.

Abstract: A system including a plurality of processor cores, a plurality of graphics processing units, a plurality of peripheral circuits, and a plurality of memory controllers is configured to support scaling of the system using a unified memory architecture.