Abstract: A system for selecting a sensitivity level for adjusting an intensity setting for therapy provided to a patient includes one or more processors and one or more processors coupled to the memory. The one or more processors are configured to receive an indication of an input to adjust an intensity setting related to the therapy provided to the patient and determine a sensitivity level for adjustment of the intensity setting based on an efficacy of the therapy provided to the patient. The one or more processors are further configured to determine an updated intensity level for the intensity setting based on the sensitivity level and the input to adjust the intensity setting and output an instruction to cause a medical device to provide the therapy at the updated intensity level.

Abstract: A method is presented for altering a portion of a substrate. The method includes providing a first device including an outer surface and a second device including a source of vibration energy. The method also includes forming a nip between the source of vibration energy and the outer surface. The method also includes conveying the substrate through the nip and intermittently altering the portion of the substrate in the nip to create a pattern of altered areas forming a shape. The altered areas have a pattern balance that includes one or more of: an average area of the substrate altered in the nip is within a threshold range across the portion of the substrate; and a simple area of integral areas within the altered areas is within a threshold range across the portion of the substrate.

Abstract: A protective clothing equipment is provided that is comfortable, stabilizing, and compatible with varying types of surfaces. One embodiment of the protective clothing equipment includes a shell, padding disposed in front of the knee of the wearer, the padding including a non-uniform stiffness.

Abstract: Various face shield assemblies for hard hats are described. In one embodiment, the face shield assembly includes a hard hat, a mounting bracket, a face shield, a first pivot arm and a second pivot arm. The first pivot arm and second pivot arm are pivotally coupled to the hard hat and rotate with respect to the mounting bracket and the face shield. The face shield is coupled to the first pivot arm and the second pivot arm. The face shield actuates between stowed and operating positions such that the face shield can avoid objects near a front of the hard hat, such as a bill and/or lamp. In other embodiments the face shield assembly includes an adjustable frame coupled to the face shield and the hard hat. The adjustable frame rotates and/or slides with respect to the hard hat.

Abstract: Various embodiments of a voltage detection device and of related safety systems are provided. In various embodiments, the voltage detection device is configured to couple to safety headwear, such as via the one or more housing(s) of the voltage detection device coupling directly to the safety headwear or the voltage detection device coupling to an adaptor mounted to the hard hat.

Abstract: An off-policy reinforcement learning actor-critic neural network system configured to select actions from a continuous action space to be performed by an agent interacting with an environment to perform a task. An observation defines environment state data and reward data. The system has an actor neural network which learns a policy function mapping the state data to action data. A critic neural network learns an action-value (Q) function. A replay buffer stores tuples of the state data, the action data, the reward data and new state data. The replay buffer also includes demonstration transition data comprising a set of the tuples from a demonstration of the task within the environment. The neural network system is configured to train the actor neural network and the critic neural network off-policy using stored tuples from the replay buffer comprising tuples both from operation of the system and from the demonstration transition data.

Abstract: A protective clothing equipment is provided that is comfortable, stabilizing, and compatible with varying types of surfaces. One embodiment of the protective clothing equipment includes a thigh support, a brace coupled to the thigh support, and padding disposed in front of the knee of the wearer.

Abstract: An off-policy reinforcement learning actor-critic neural network system configured to select actions from a continuous action space to be performed by an agent interacting with an environment to perform a task. An observation defines environment state data and reward data. The system has an actor neural network which learns a policy function mapping the state data to action data. A critic neural network learns an action-value (Q) function. A replay buffer stores tuples of the state data, the action data, the reward data and new state data. The replay buffer also includes demonstration transition data comprising a set of the tuples from a demonstration of the task within the environment. The neural network system is configured to train the actor neural network and the critic neural network off-policy using stored tuples from the replay buffer comprising tuples both from operation of the system and from the demonstration transition data.

Abstract: A wearable device. In some embodiments, the wearable device includes: a sensing module; and a strap attached to the sensing module, the wearable device being configured to be worn by a user, with a lower surface of the sensing module in contact with the user, the strap extending over an upper surface of the sensing module.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for improving operational efficiency within a data center by modeling data center performance and predicting power usage efficiency. An example method receives a state input characterizing a current state of a data center. For each data center setting slate, the state input and the data center setting slate are processed through an ensemble of machine learning models. Each machine learning model is configured to receive and process the state input and the data center setting slate to generate an efficiency score that characterizes a predicted resource efficiency of the data center if the data center settings defined by the data center setting slate are adopted t. The method selects, based on the efficiency scores for the data center setting slates, new values for the data center settings.

Abstract: The present invention provides novel hybrid polymers having unique physical properties. The hybrid polymers comprise a cellulose ether moiety, a linking group moiety, a spacer group moiety, and a lactam moiety. The present invention also provides compositions comprising the hybrid polymers and methods for preparing and using the hybrid polymers.

Abstract: An electrolytic ozone generator for use with a faucet and methods for assembling and using the same.

Abstract: Various analyte sensor systems for controlling activation of analyte sensor electronics circuitry are provided. Related methods for controlling analyte sensor electronics circuitry are also provided. Various analyte sensor systems for monitoring an analyte in a host are also provided. Various circuits for controlling activation of an analyte sensor system are also provided. Analyte sensor systems utilizing a state machine having a plurality of states for collecting a plurality of digital counts and waking a controller responsive to a wake up signal are also provided. Related methods for such analyte sensor systems are also provided. Systems for controlling activation of analyte sensor electronics circuitry utilizing a magnetic sensor are further provided. One or more display device configured to display one or more analyte concentration values are also provided.

Abstract: Various embodiments of an accessory bracket for attaching accessories to protective equipment are shown. The accessory bracket includes a mounting bracket body, a center tab, and one or more cam levers that allow for secure attachment to protective equipment. The accessory bracket is designed to improve attachment and retention of accessories to protective equipment.

Abstract: Various analyte sensor systems for controlling activation of analyte sensor electronics circuitry are provided. Related methods for controlling analyte sensor electronics circuitry are also provided. Various analyte sensor systems for monitoring an analyte in a host are also provided. Various circuits for controlling activation of an analyte sensor system are also provided. Analyte sensor systems utilizing a state machine having a plurality of states for collecting a plurality of digital counts and waking a controller responsive to a wake up signal are also provided. Related methods for such analyte sensor systems are also provided. Systems for controlling activation of analyte sensor electronics circuitry utilizing a magnetic sensor are further provided. One or more display device configured to display one or more analyte concentration values are also provided.

Abstract: An electrolytic ozone generator for use with a faucet and methods for assembling and using the same.

Abstract: Formation of a sterile connection includes inserting a first aseptic coupling device into a second aseptic coupling device while a locking ring of the first aseptic device is in an indexed initial position, rotating the locking ring to a secured position in which a compressive force is created and in which a first membrane from the first aseptic coupling device and a second membrane from the second aseptic coupling device can removed thereby resulting in a first a first sealing member of the first aseptic coupling device sealing with a second sealing member of the second aseptic coupling device to form a sterile fluid passageway.

Abstract: A method of training an action selection neural network to perform a demonstrated task using a supervised learning technique. The action selection neural network is configured to receive demonstration data comprising actions to perform the task and rewards received for performing the actions. The action selection neural network has auxiliary prediction task neural networks on one or more of its intermediate outputs. The action selection policy neural network is trained using multiple combined losses, concurrently with the auxiliary prediction task neural networks.

Abstract: Media content is encoded based on network quality of service parameters. For instance, quality of service parameters for a network between a media server and a media client are determined by a system. The system selects an encoder based on a list of decoders available at the media client and the quality of service parameters, and encodes at least a portion of the media via the encoder. The system can further determine settings for the encoder based on a media type, and encode the media via the encoder according to the settings. The system can detect when the media client moves to a new network, detect new quality of service parameters, and select a new encoder based on the list of decoders available at the media client, the media type, and the new quality of service parameters.