Abstract: An out-the-front knife, components thereof, and associated methods. The out-the front knife can be a double-action spring-assisted knife. The knife includes a handle and a blade. The handle includes a rear end and a front opening opposite the rear end. The blade is movable with respect to the handle between stowed and deployed positions. In the stowed position, the blade is biased rearward. The knife includes an actuator movable in a deploying direction to spring the blade forward away from the stowed position toward the deployed position.

Abstract: Systems, methods, computing platforms, and storage media for profile matching are disclosed. Exemplary implementations may: receive a plurality of images from one or more sources; receive, via a first user device, a first request for profile matching from a first user; display, on the first user device, at least a portion of the plurality of images; receive, from the first user device, a first user input comprising one or more first preference indications for at least the portion of the plurality of images; determine an overlap between the first preference indications and one or more second preference indications received from a second user device; and in response to determining the overlap between the first and second preference indications exceeds a threshold, automatically causing the first or the second user device to indicate a match between the first and the second user.

Abstract: Methods and computer apparatus are disclosed for deriving first order logic language rules for use in analyzing new data to identify anomalies in the new data. Historical data is formatted to be in a form suitable for application of a machine-learning algorithm thereto. The machine-learning algorithm is applied to the formatted historical data to generate a set of first order logic language rules that cover the formatted historical data. The set of first order logic language rules are analyzed to obtain a subset of said set of first order logic language rules which can be used as first order logic language rules in analyzing new data.

Abstract: Methods and computer apparatus are disclosed for deriving first order logic language rules for use in analysing new data to identify anomalies in the new data. Historical data is formatted to be in a form suitable for application of a machine-learning algorithm thereto. The machine-learning algorithm is applied to the formatted historical data to generate a set of first order logic language rules that cover the formatted historical data. The set of first order logic language rules are analysed to obtain a subset of said set of first order logic language rules which can be used as first order logic language rules in analysing new data.