Abstract: Disclosed herein are short interfering nucleic acid (siNA) molecules comprising modified nucleotides and uses thereof. The siNA molecules may be double stranded and comprise modified nucleotides selected from 2?-O-methyl nucleotides and 2?-fluoro nucleotides. Further disclosed herein are siNA molecules comprising (a) a phosphorylation blocker, conjugated moiety, or 5?-stabilized end cap; and (b) a short interfering nucleic acid (siNA).

Abstract: Methods and systems for image registration using an intelligent artificial agent are disclosed. In an intelligent artificial agent based registration method, a current state observation of an artificial agent is determined based on the medical images to be registered and current transformation parameters. Action-values are calculated for a plurality of actions available to the artificial agent based on the current state observation using a machine learning based model, such as a trained deep neural network (DNN). The actions correspond to predetermined adjustments of the transformation parameters. An action having a highest action-value is selected from the plurality of actions and the transformation parameters are adjusted by the predetermined adjustment corresponding to the selected action. The determining, calculating, and selecting steps are repeated for a plurality of iterations, and the medical images are registered using final transformation parameters resulting from the plurality of iterations.

Abstract: Small molecule radiohalogenated PSMA inhibitors and metal complexes thereof and their use in radioimaging and radiotherapy for treating PSMA-related diseases, including prostate cancer, are disclosed. The combination of small molecule radiohalogenated PSMA inhibitors with a competitive PSMA ligand for reducing off target accumulation of the radiohalogenated PSMA inhibitor also is disclosed.

Abstract: Computer-implemented methods for training a neural network, as well as for implementing audio encoders and decoders via trained neural networks, are provided. The neural network may receive an input audio signal, generate an encoded audio signal and decode the encoded audio signal. A loss function generating module may receive the decoded audio signal and a ground truth audio signal, and may generate a loss function value corresponding to the decoded audio signal. Generating the loss function value may involve applying a psychoacoustic model. The neural network may be trained based on the loss function value. The training may involve updating at least one weight of the neural network.

Abstract: Aspects of the disclosure are directed to a storage device including a memory and a controller. The memory may include a plurality of flash memory blocks such as single level cell (SLC) blocks and multi-level cell (MLC) blocks. The controller may maintain a read count of each of the SLC blocks to determine which of the blocks contains data associated with the highest number of read commands. Based on the read commands, the controller may relocate the associated data into pages of MLC blocks that have a lower number of senses required to read the data stored in those blocks.

Abstract: Systems and methods described herein provide techniques for detecting subject behavior by processing video data using one or more trained models configured to detect subject behavior. The described system processes sets of frames from the video data using different trained models. The system further processes different orientations of the sets of frames. The various outputs from the different trained models and from processing the different orientations of the sets of frames may be combined to then make a final determination as to whether the subject is exhibiting a particular behavior during a particular frame.

Abstract: A method includes: determining a wall temperature of a wall enclosing a lumen of a flow line; determining a density, a viscosity, a thermal conductivity, a thermal capacity, and a pressure differential of a medium to be measured flowing in the line; determining a characteristic number value for the medium, which characterizes a heating of the medium flowing in the line as a result of dissipation and is a function of an Eckert number, a Prandtl number, and a pressure loss coefficient of the line as well as line-specific first, second and third exponents; and determining a temperature of the medium using the characteristic number value and the wall temperature. A measuring system for the method includes: a temperature sensor thermally coupled to a lateral surface of the wall and configured to generate a temperature measurement signal; and an operating electronic system electrically connected to the temperature sensor.

Abstract: Embodiments of the present disclosure relate to generating control signals for energy sources. Some embodiments include a method, the method including generating a first control signal at least partially responsive to a request signal and at least partially responsive to a first capability of a first energy source to change a first energy output. The first control signal may be indicative of a first portion of a requested amount of energy to be provided by the first energy source. The method may also include generating a second control signal at least partially responsive to the request signal and at least partially responsive to a second capability of a second energy source to change a second energy output. The second control signal may be indicative of a second portion of the requested amount of energy to be provided by the second energy source. Related devices, systems and methods are also disclosed.

Abstract: Systems, methods, and other embodiments associated with a bot communication system for communicating between channels and bots are described. In one embodiment, a system includes a bot manager configured to provide communication between an individual bot from a plurality of bots and a target channel of a plurality of channels. The bot manager is configured to process a bot response from the individual bot to the target channel by at least: identifying channel configuration metadata from a channel metadata repository that defines a channel dependent format for communicating data with the target channel; converting the bot response to the channel dependent format associated with the target channel including formatting data components from the bot response according to the channel configuration metadata of the target channel; and transmitting, via a network connection, the converted bot response to the target channel in the channel dependent format of the target channel.

Abstract: Systems and methods for continuous monitoring of the behavior of animals, such as small rodents, are provided. Monitoring can include video, audio, and other sensor modalities. In one embodiment, the system can include cameras, arena design, environmental sensors, and ultrasonic sensors. The system uniquely provides a continuous long-term monitoring system suitable for mouse behavioral study. Further provided is a neural network based tracker configured for use with video data acquired by the monitoring system. Three different neural network architectures have been tested to determine their performance on genetically diverse mice under varying environmental conditions. It has been observed that that an encoder-decoder segmentation neural network achieves high accuracy and speed with minimal training data.

Abstract: A device may receive training data that includes datasets associated with natural language processing, and may mask the training data to generate masked training data. The device may train a masked event C-BERT model, with the masked training data, to generate pretrained weights and a trained masked event C-BERT model, and may train an event aware C-BERT model, with the training data and the pretrained weights, to generate a trained event aware C-BERT model. The device may receive natural language text data identifying natural language events, and may process the natural language text data, with the trained masked event C-BERT model, to determine weights. The device may process the natural language text data and the weights, with the trained event aware C-BERT model, to predict causality relationships between the natural language events, and may perform actions, based on the causality relationships.

Abstract: A method, a set-top box, and a non-transitory computer readable medium for content switching and content control based on multi-user profiles. The method includes: capturing, by the set-top box, the facial information of two or more users of the plurality of users viewing content on a media play device, the media play device configured to display content from the set-top box; sending, by the set-top box, the captured facial information of the two or more users of the plurality of user viewing content on the media play device to the server; and receiving, on the set-top box, recommended content for the two or more users viewing the media play device based on a multi-user profile for the two or more users from the plurality of user profiles.

Abstract: Disclosed herein are short interfering nucleic acid (siNA) molecules comprising modified nucleotides and uses thereof. The siNA molecules may be double stranded and comprise modified nucleotides selected from 2?-O-methyl nucleotides and 2?-fluoro nucleotides. Further disclosed herein are siNA molecules comprising (a) a phosphorylation blocker, conjugated moiety, or 5?-stabilized end cap; and (b) a short interfering nucleic acid (siNA).

Abstract: The present disclosure provides for the division of environmental sounds from speech sounds to extract and analyze the behaviors and activities occurring in the environment; thus expanding and improving the functionality of AI assistant devices. These environmental sounds can be securely uploaded to an electronic chart, and may be used to aid in the treatment of existing conditions or the prophylaxis/mitigation of conditions not yet experienced by a patient under observation. Accordingly, the present disclosure provides for improved functionality in assistant devices and devices linked to the AI assistant devices.

Abstract: The disclosure relates to system and method for generating recommendations for capturing images of a real-life object with essential features. The method includes detecting an Augmented Reality (AR) plane for a target object. The method further includes capturing a set of poses corresponding to the target object and a set of coordinate points in the AR plane. The set of poses includes a tracking marker, and the set of coordinate points indicates a location of the target object. The method further includes determining an instant distance between the AR imaging device and the target object, and an instant angle of the AR imaging device with respect to the target object. The method further includes dynamically generating the recommendations for adjusting a position and an orientation of the AR imaging device with respect to the target object.

Abstract: Techniques for predicting caregiver retention using machine learning (ML) are discussed. These techniques include predicting an impact of one or more caregiver tasks on continued employment of the caregiver with a care provider, including determining a plurality of intermediate prediction scores relating to characteristics for the caregiver using one or more first ML models trained to determine intermediate prediction scores. The techniques further include determining a retention prediction for the caregiver using the plurality of intermediate prediction scores, including: generating the retention prediction by providing the plurality of intermediate prediction scores to a second ML model trained to determine the retention prediction based on intermediate prediction scores.

Abstract: Certain aspects of the present disclosure provide techniques for predicting electronic health record data using ML. This includes determining a plurality of attributes of a textual description of a patient medical examination, including: detecting the plurality of attributes based on analyzing the textual description using a first ML model trained to parse patient textual descriptions. This further includes predicting a change to an electronic health record for the patient, including: providing to a second ML model the plurality of attributes of the textual description and patient medical data for the patient, where the second ML model is trained to predict changes to patient electronic health records based on attributes of textual data relating to the patient and patient medical data. The predicted change is provided to an electronic system to change the electronic health record and affect medical treatment for the patient.

Abstract: Example multi-channel display systems are disclosed. An example apparatus includes at least one processor to execute instructions to at least in response to determining that a first display controller is to provide at least a first portion of video data on a first channel, provide a first control signal to the first display controller instructing the first display controller to provide the at least the first portion of the video data on the first channel, and in response to determining that a second display controller is to provide at least a second portion of the video data on a second channel, provide a second control signal to the second display controller instructing the second display controller to provide the at least the second portion of the video data on the second channel, the second channel different from the first channel.

Abstract: Techniques for improved machine learning are provided. Resident data describing a first condition of a first resident of a residential care facility is received. An optimized treatment plan is selected for the first resident by extracting a first plurality of resident attributes, from the resident data, generating a first approach to remediate the first condition, and generating a first predicted recovery score by inputting the first approach and the first plurality of resident attributes into a trained machine learning model. The optimized treatment plan is implemented for the first resident.

Abstract: Techniques for improved computer modeling are provided. Resident data describing a resident of a healthcare facility is received, and a set of resident attributes corresponding to a defined set of features is extracted from the resident data. An acuity score is generated for the resident by processing the set of resident attributes using an acuity model, the acuity model specifying a respective weight for each respective feature in the defined set of features. One or more interventions are initiated for the resident based on the acuity score.