Abstract: A pressure indicator includes a body, a piston, first and second biasing elements, and a rotatable disc. The piston is disposed at least partially in a bore of the body at a first longitudinal axial position relative to the body when pressure of fluid acting on the base is below a threshold pressure. The first biasing element is disposed between a base of the piston and a shoulder of the body, wherein a force of the first biasing element is overcome by pressure of fluid acting on the base at or above the threshold pressure, thereby allowing the piston to move to a second longitudinal axial position. The rotatable disc has a first rotational position when the piston is in the first axial position. The second biasing element is configured to urge the disc to a second rotational position when the piston is in the second axial position.

Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: A pressure indicator includes a body, a piston, first and second biasing elements, and a rotatable disc. The piston is disposed at least partially in a bore of the body at a first longitudinal axial position relative to the body when pressure of fluid acting on the base is below a threshold pressure. The first biasing element is disposed between a base of the piston and a shoulder of the body, wherein a force of the first biasing element is overcome by pressure of fluid acting on the base at or above the threshold pressure, thereby allowing the piston to move to a second longitudinal axial position. The rotatable disc has a first rotational position when the piston is in the first axial position. The second biasing element is configured to urge the disc to a second rotational position when the piston is in the second axial position.

Abstract: In one respect, there is provided a system for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more instruction sequences. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: training, based at least on training data, a machine learning model to detect one or more predetermined interdependencies amongst a plurality of tokens in the training data; and providing the trained machine learning model to enable classification of one or more instruction sequences. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: An aircraft having an upswept tail section fuselage includes a single pair of large vortex generators mounted in the vicinity of the break in the fuselage ahead of or at the beginning of the tail upsweep, each vortex generator being mounted on a side of and adjacent the bottom of the fuselage. The vortex generators, which may be plates or fins, develop strong transverse outflow from the vertical plane of symmetry that relieves or delays the tendency to flow separation by acting on the external flow field while at the same time energizing the boundary layer to increase its resistance to separation. The vortex generator may be thin or slightly thickened, flat or airfoil shaped, and may have triangular, straight, tapered, or reverse tapered planforms and may be rigid or flexible. Either one or both edges may be blunted, although sharp edges are preferred.