Abstract: A system for performing spinal cord stimulation on a subject is disclosed. The system comprises one or more recording arrays, at least one stimulation array, and a processor. The recording arrays, which may be minimally invasively inserted to a target recording site of the brain, include recording electrodes having a diameter of less than about 1 mm and having a spacing of less than about 1 mm therebetween. The stimulation array, which may be minimally invasively inserted to a target stimulation site within the nervous tissue, includes stimulation electrodes. The processor is configured to receive more recorded signals from the recording arrays at the target recording site, determine an electrophysiological state of the brain based on the recorded signals, and deliver electrical stimulation to the target stimulation site through the stimulation array based on the determined electrophysiological state in order to affect the electrophysiological state.

Abstract: A systems and methods for calibrating a neural device using transfer learning techniques. The methods can include aggregating calibration data across a user population to define a global dataset, identifying similar data segments across the global dataset to define a task-independent training dataset, training a feature extraction model based on the task-independent training dataset to define a trained, task-independent feature extraction model, receiving the calibration data from a user calibrating the neural device, and calibrating a user-specific feature extraction model using the trained, task-independent feature extraction model and the calibration data.

Abstract: This invention relates to macrostructures (and pharmaceutical formulations containing them) that include an antiparallel coiled-coil. wherein the antiparallel coiled-coil comprises a first coil of Formula I and a second coil of Formula II: T1-g0-a1-b1-c1-d1-e1-f1-g1-a2-b2-c2-d2-e2-f2-g2-a3-b3-c3-d3-e3-f3-T2 (I) T3-f0-g?0-a?1-b?1-c?1-d?1-e?1-f?1-g?1-a?2-b?2-c?2-d?2-e?2-f?2-g?2-a?3-b?3-c?3-d?3-e?3-T4 (II), as described in the present application. Methods of using these macrostructures are also disclosed.

Abstract: A transmitting apparatus is provided. The transmitting apparatus includes: an encoder configured to generate a low-density parity check (LDPC) codeword by LDPC encoding of input bits based on a parity check matrix including information word bits and parity bits, the LDPC codeword including a plurality of bit groups each including a plurality of bits; an interleaver configured to interleave the LDPC codeword; and a modulator configured to map the interleaved LDPC codeword onto a modulation symbol, wherein the interleaver is further configured to interleave the LDPC codeword such that a bit included in a predetermined bit group from among the plurality of bit groups constituting the LDPC codeword onto a predetermined bit of the modulation symbol.

Abstract: Some implementations relate to using trained robotic action ML models in controlling a robot to perform a robotic task. Some versions of those implementations include (a) a first modality robotic action ML model that is used to generate, based on processing first modality sensor data instances, first predicted action outputs for the robotic task and (b) a second modality robotic action ML model that is used to generate, in parallel and based on processing second modality sensor data instances, second predicted action outputs for the robotic task. In some of those versions, respective weights for each pair of the first and second predicted action outputs are dynamically determined based on analysis of embeddings generated in generating the first and second predicted action outputs. A final predicted action output, for controlling the robot, is determined based on the weights.

Abstract: In various embodiments, the present description relates to the use of factors related to survival. The methods, compositions and systems described herein may be used to determine factors affecting survival, assess survival risk based on factors related to survival and/or make suggestions to increase the likelihood of survival longer than otherwise predicted.

Abstract: A mapping system allows a user to interact with any location on a digital map and present the user with location related information associated with the selected location. The location related information may be in the form or a card, pop-up, image, or other graphic and may be displayed on the map at or near the selected location, around the map, etc. The displayed location related information may include predetermined or pre-stored data about the location or may include location related information collected and generated on the fly in response to the user interaction with the digital map. The displayed location related information may be displayed in the same graphical format on the digital map regardless of whether location related information is predetermined information about the location that already exists or information that is collected and generated on the fly in response to the user interaction.

Abstract: A transmitting apparatus is disclosed. The transmitting apparatus includes an encoder to perform channel encoding with respect to bits and generate a codeword, an interleaver to interleave the codeword, and a modulator to map the interleaved codeword onto a non-uniform constellation according to a modulation scheme, and the constellation may include constellation points defined based on various tables according to the modulation scheme.

Abstract: The various implementations described herein include a video camera assembly that includes: (1) a housing; (2) an image sensor encased in the housing and configured to capture activity of the smart home environment; (3) a wireless radio configured to transmit video frames captured by the image sensor to an electronic device via a remote server; (4) at least one infrared transmitter configured to selectively illuminate the smart home environment; (5) one or more circuit boards encased in the housing, the one or more circuit boards including at least one processor mounted thereon; and (6) a heating component coupled to the image sensor, the heating component configured to continuously maintain the image sensor at a temperature above a threshold temperature while the image sensor is capturing the activity of the smart home environment.

Abstract: A chair comprising a seat base, a back rest, the back rest having a first arm connected to the seat base by a first pivot and a second arm connected to the seat base by a second pivot so that the back rest can pivot between a first folded position and a second position, the first pivot being biased so that in the absence of any force applied by a user, the back rest maintains the first position wherein a damper is included to ensure to retard the movement of the seat from the second position to the first position in the absence of any force applied.

Abstract: Utilization of past dynamics sample(s), that reflect past contact physics information, in training and/or utilizing a neural network model. The neural network model represents a learned value function (e.g., a Q-value function) and that, when trained, can be used in selecting a sequence of robotic actions to implement in robotic manipulation (e.g., pushing) of an object by a robot. In various implementations, a past dynamics sample for an episode of robotic manipulation can include at least two past images from the episode, as well as one or more past force sensor readings that temporally correspond to the past images from the episode.

Abstract: A method for generating a 3D image of a body shape includes obtaining a set of far-field patterns of electromagnetic waves from a given body shape of a human or animal, establishing a one-to-one correspondence between the body shape and the set of far-field patterns of electromagnetic waves, representing the far-field patterns as a shape generating vector, mapping a vector of characteristic parameters to the shape generating vector, producing a body generation model by taking the vector of characteristic parameters and the shape generating vector as input and output data to form a training dataset for machine learning, specifying a characteristic vector of an unknown geometric body shape and obtaining a shape generating vector of the unknown geometric body shape based on the body generation model, and reconstructing the unknown geometric body shape based on the shape generating vector.

Abstract: In an embodiment, the present invention provides a compound of the formula: or a pharmaceutically acceptable salt thereof, and methods of using this compound for treating type II diabetes mellitus.

Abstract: In an embodiment, the present invention provides a compound of the formula: or a pharmaceutically acceptable salt thereof, and methods of using this compound for treating type II diabetes mellitus.

Abstract: Implementations disclosed herein relate to mitigating the reality gap through feature-level domain adaptation in training of a vision-based robotic action machine learning (ML) model. Implementations mitigate the reality gap through utilization of embedding consistency losses and/or action consistency losses during training of the action ML model.

Abstract: A mechanism for raising and lowering an armrest for a seat includes an armrest, a rotatable hub, and an actuating linkage between the armrest and the hub, the rotatable hub having a cam that operates the actuating linkage to raise the armrest wherein the cam can rotate through a first angle of rotation where the actuating linkage is not operated a second angle of rotation where the actuating linkage is operated. The cam can rotate through a third angle of rotation where the actuating linkage is not operated, this angle being different to the first angle of rotation. The cam is torsionally linked to the rotation of a seat member.

Abstract: A method for managing a current revision on prior revision of an order is described. A modified set of compensations tasks for addressing amendments indicated in the current revision are determined. The modified set of compensation tasks may be determined by carrying over one or more compensation tasks, associated with the prior revision, that have not yet been completed. Alternatively or additionally, the modified set of compensation tasks may be determined by adding new compensation tasks based on the current revision.

Abstract: Methods and system are provided for dynamic process control in substrate processing, for example in semiconductor manufacturing applications. Some example systems and methods are provided for advanced monitoring and machine learning in atomic layer deposition (ALD) processes. Some examples also relate to dynamic process control and monitoring for chamber parameter matching and gas line charge times.

Abstract: Utilization of past dynamics sample(s), that reflect past contact physics information, in training and/or utilizing a neural network model. The neural network model represents a learned value function (e.g., a Q-value function) and that, when trained, can be used in selecting a sequence of robotic actions to implement in robotic manipulation (e.g., pushing) of an object by a robot. In various implementations, a past dynamics sample for an episode of robotic manipulation can include at least two past images from the episode, as well as one or more past force sensor readings that temporally correspond to the past images from the episode.

Abstract: A method for managing a current revision on prior revision of an order is described. A modified set of compensations tasks for addressing amendments indicated in the current revision are determined. The modified set of compensation tasks may be determined by carrying over one or more compensation tasks, associated with the prior revision, that have not yet been completed. Alternatively or additionally, the modified set of compensation tasks may be determined by adding new compensation tasks based on the current revision.