Abstract: A system for estimating maximum heart rate and maximal oxygen uptake from submaximal exercise intensities can include an exercise intensity monitor, a cardiopulmonary monitor, and one or more computers. The computers can be configured, by virtue of appropriate programming, to receive submaximal exercise intensity data from the exercise intensity monitor and submaximal cardiopulmonary data from the cardiopulmonary monitor while a user, who coupled to the exercise intensity monitor and the cardiopulmonary monitor, is performing an exercise at a submaximal exercise intensity. The one or more computers then determine a heuristic estimate of a maximal cardiopulmonary state of the user based on the submaximal exercise intensity data and the submaximal cardiopulmonary data.

Abstract: A system for assessing lower extremity movement quality includes one or more user sensors, at least one processor, and a movement evaluator implemented using the at least one processor. The movement evaluator is configured, by virtue of appropriate programming, for receiving movement data from the one or more user sensors during a user's performance of a movement task; extracting one or more movement features from the movement data, each movement feature characterizing a respective aspect of a movement pattern of the user's performance that is associated with lower extremity injury risk; and classifying the movement pattern into a classified risk category for lower extremity injury for the user based on the one or more movement features.

Abstract: A system for estimating maximum heart rate and maximal oxygen uptake from submaximal exercise intensities can include an exercise intensity monitor, a cardiopulmonary monitor, and one or more computers. The computers can be configured, by virtue of appropriate programming, to receive submaximal exercise intensity data from the exercise intensity monitor and submaximal cardiopulmonary data from the cardiopulmonary monitor while a user, who coupled to the exercise intensity monitor and the cardiopulmonary monitor, is performing an exercise at a submaximal exercise intensity. The one or more computers then determine a heuristic estimate of a maximal cardiopulmonary state of the user based on the submaximal exercise intensity data and the submaximal cardiopulmonary data.

Abstract: A heater cable, which may particularly be a self-regulating heater cable, has a heating element including two bus wires spaced a distance apart by a positive temperature coefficient (PTC) material, giving the heating element a major axis and a minor axis. Bending the heater cable transverse to the major axis gives a tighter bend radius than bending the heater cable transverse to the minor axis. To facilitate bending in multiple directions, the heating element is twisted around the longitudinal axis of the heater cable. The twisting may be done uniformly to give the bus wires a helical configuration, which reduces electromagnetic interference and facilitates heater cable diameters as small as 0.25 inches. Additional layers, such as polymer jackets and a braided metal ground plane layer, may be added over the heating element. Each of these layers may be twisted or untwisted in various implementations.

Abstract: Integrated fuzzing techniques are described. A fuzzing system may employ a container configured as a separate component that can host different target pages to implement fuzzing for an application. A hosted target file is loaded as a subcomponent of the container and parsed to recognize functionality of the application invoked by the file. In at least some embodiments, this involves building a document object model (DOM) for a browser page and determining DOM interfaces of a browser to call based on the page DOM. The container then operates to systematically invoke the recognized functionality to cause and detect failures. Additionally, the container may operate to perform iterative fuzzing with multiple test files in an automation mode. Log files may be created to describe the testing and enable both self-contained replaying of failures and coverage analysis for multiple test runs.

Abstract: Integrated fuzzing techniques are described. A fuzzing system may employ a container configured as a separate component that can host different target pages to implement fuzzing for an application. A hosted target file is loaded as a subcomponent of the container and parsed to recognize functionality of the application invoked by the file. In at least some embodiments, this involves building a document object model (DOM) for a browser page and determining DOM interfaces of a browser to call based on the page DOM. The container then operates to systematically invoke the recognized functionality to cause and detect failures. Additionally, the container may operate to perform iterative fuzzing with multiple test files in an automation mode. Log files may be created to describe the testing and enable both self-contained replaying of failures and coverage analysis for multiple test runs.

Abstract: Integrated fuzzing techniques are described. A fuzzing system may employ a container configured as a separate component that can host different target pages to implement fuzzing for an application. A hosted target file is loaded as a subcomponent of the container and parsed to recognize functionality of the application invoked by the file. In at least some embodiments, this involves building a document object model (DOM) for a browser page and determining DOM interfaces of a browser to call based on the page DOM. The container then operates to systematically invoke the recognized functionality to cause and detect failures. Additionally, the container may operate to perform iterative fuzzing with multiple test files in an automation mode. Log files may be created to describe the testing and enable both self-contained replaying of failures and coverage analysis for multiple test runs.

Abstract: Integrated fuzzing techniques are described. A fuzzing system may employ a container configured as a separate component that can host different target pages to implement fuzzing for an application. A hosted target file is loaded as a subcomponent of the container and parsed to recognize functionality of the application invoked by the file. In at least some embodiments, this involves building a document object model (DOM) for a browser page and determining DOM interfaces of a browser to call based on the page DOM. The container then operates to systematically invoke the recognized functionality to cause and detect failures. Additionally, the container may operate to perform iterative fuzzing with multiple test files in an automation mode. Log files may be created to describe the testing and enable both self-contained replaying of failures and coverage analysis for multiple test runs.