Abstract: A pipe coupling includes a coupling body comprising a first coupling segment and a second coupling segment, each of the first and second coupling segments defining a first end and a second end opposite the first end; a fastener mounted to the coupling body and configured to tighten the pipe coupling from an untightened configuration to a tightened configuration; and an installation indicator arranged between the first end of the first coupling segment and the first end of the second coupling segment, wherein the installation indicator is clamped between the first and second coupling segments in the tightened configuration.

Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.

Abstract: Disclosed are systems for non-invasively determining a measurement of an analyte. The systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device can execute instructions to receive electrocardiogram data from the electrocardiogram sensor and apply a machine learning model, wherein the machine learning model has been trained based on previous electrocardiogram data associated with a subject and source of an analyte measurement associated with the subject. The system may also determine an indication of a level of the analyte based on the electrocardiogram data.

Abstract: Disclosed are systems for non-invasively determining a measurement of an analyte. The systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device can execute instructions to receive electrocardiogram data from the electrocardiogram sensor and apply a machine learning model, wherein the machine learning model has been trained based on previous electrocardiogram data associated with a subject and source of an analyte measurement associated with the subject. The system may also determine an indication of a level of the analyte based on the electrocardiogram data.

Abstract: An injection mold for producing a sprinkler head part and related injection molding methods are described. The sprinkler head part includes a first, second, third and fourth mold portions. The first and second mold portions include first and second shaping elements structured to cooperatively form a body including a substantially cylindrical portion and a substantially planar portion, and two frame arms extending from the substantially planar portion of the body. The third mold portion includes a shaping element structured to form an orifice in the body of the sprinkler head. The fourth mold portion includes a shaping element structured to form a cross member connecting the two frame arms. The injection methods include injecting a composite material in molten form into the mold to form the molded sprinkler head part. The composite material includes thermoplastic polymeric resin and a plurality of reinforcing fibers dispersed in the resin.

Abstract: Disclosed systems and method receive electrocardiogram (EKG) data of a subject. The EKG data comprises a record of at least a full beat of the subject. The EKG data is input into a machine learning model to generate an output. The output can include a segmentation of the full beat or a measurement of a QT interval of the subject.

Abstract: An injection mold for producing a sprinkler head part and related injection molding methods are described. The sprinkler head part includes a first, second, third and fourth mold portions. The first and second mold portions include first and second shaping elements structured to cooperatively form a body including a substantially cylindrical portion and a substantially planar portion, and two frame arms extending from the substantially planar portion of the body. The third mold portion includes a shaping element structured to form an orifice in the body of the sprinkler head. The fourth mold portion includes a shaping element structured to form a cross member connecting the two frame arms. The injection methods include injecting a composite material in molten form into the mold to form the molded sprinkler head part. The composite material includes thermoplastic polymeric resin and a plurality of reinforcing fibers dispersed in the resin.

Abstract: Disclosed systems and method receive electrocardiogram (EKG) data of a subject. The EKG data comprises a record of at least a full beat of the subject. The EKG data is input into a machine learning model to generate an output. The output can include a segmentation of the full beat or a measurement of a QT interval of the subject.

Abstract: A sprinkler installation tool includes a first member, a second member, and at least one bearing. The first member defines an axis and include a first surface transverse to the axis. The first surface includes at least one first opening. The second member includes a second member including a second surface in contact with the first surface. The second surface includes at least one second opening. The at least one bearing is between the at least one first opening and the at least one second opening to engage the at least one first opening and the at least one second opening such that a torque applied to the first member to cause the first member to rotate about the axis relative to the second member causes the second member to rotate with the first member responsive to the torque being less than a target torque of rotation of a sprinkler.

Abstract: Disclosed are techniques for training a machine learning model. A training data set comprising a plurality of electrocardiogram (ECG) measurements and corresponding analyte measurements for each of the plurality of ECG measurements is provided. For each ECG measurement of the training data set, an estimated analyte level at a time of the ECG measurement is determined based on the corresponding set of analyte measurements. The estimated analyte level may be determined using statistical estimation techniques. If it is determined that the estimated analyte level at the time of the ECG measurement meets a certainty threshold, the ECG measurement is labeled based on the estimated analyte level at the time of the ECG measurement. A machine learning is trained to predict a level of an analyte based on ECG data, where the training is done using each of the plurality of ECG measurements that are labeled.

Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.

Abstract: At least one aspect is directed to a device to configure a fire sprinkler. The device can have an elongated member. The elongated member can have an open end, an opposing closed end, and a body extending laterally therebetween. The open end can receive a portion of a fire sprinkler. The closed end can have a main aperture. The main aperture can receive a portion of a ratcheting socket wrench drive. The closed end can have at least one surrounding aperture. The surrounding aperture can be positioned apart from the main aperture to define a solid partition therebetween. The solid partition can have non-uniform thickness between the main aperture and the at least one surrounding aperture.

Abstract: Disclosed systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device receives electrocardiogram data from the electrocardiogram sensor and applies a machine learning model to the received electrocardiogram data. The machine learning model has been trained based on previous electrocardiogram data of a plurality of subjects. The electrocardiogram data of the plurality of subjects have one or more associated analyte measurements. The processing device may determine an indication of a level of the analyte based on the electrocardiogram data.

Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.

Abstract: A sprinkler includes a body including an internal passageway extending from an inlet to an orifice. The body can be made of a composite material, such as a polymeric material. The sprinkler can include a first frame arm extending from the body, a second frame arm extending from the body, and a connector member connecting the first frame arm with the second frame arm.

Abstract: An injection mold for producing a sprinkler head part and related injection molding methods are described. The sprinkler head part includes a first, second, third and fourth mold portions. The first and second mold portions include first and second shaping elements structured to cooperatively form a body including a substantially cylindrical portion and a substantially planar portion, and two frame arms extending from the substantially planar portion of the body. The third mold portion includes a shaping element structured to form an orifice in the body of the sprinkler head. The fourth mold portion includes a shaping element structured to form a cross member connecting the two frame arms. The injection methods include injecting a composite material in molten form into the mold to form the molded sprinkler head part. The composite material includes thermoplastic polymeric resin and a plurality of reinforcing fibers dispersed in the resin.

Abstract: A sprinkler includes a body, a button, and a spring. The body includes an opening and a shoulder arranged around a sprinkler axis. The spring including an aperture that receives the button, a first spring surface, and a second spring surface. At least one of (i) the shoulder includes a first extension that contacts the first spring surface and (ii) the button includes a second extension that contacts the second spring surface.

Abstract: Disclosed are systems for non-invasively determining a measurement of an analyte. The systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device can execute instructions to receive electrocardiogram data from the electrocardiogram sensor and apply a machine learning model, wherein the machine learning model has been trained based on previous electrocardiogram data associated with a subject and source of an analyte measurement associated with the subject. The system may also determine an indication of a level of the analyte based on the electrocardiogram data.

Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.

Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.