Abstract: Methods and systems for particle classification are provided herein. A plurality of images of fluids/samples of pharmaceutical products, drugs, medicines, etc., may be analyzed using one or more machine learning models. The one or more machine learning models may comprise, for example, a convolution neural network. The one or more machine learning models may identify and classify one or more sub-visible particles in each image. The one or more one or more sub-visible particles may comprise, for example, cells, pathogens, protein aggregates, silicon oil droplets, fibers, air bubbles, glass particles, a combination thereof, and/or the like.

Abstract: Various methods and devices are provided for attenuating RF signals propagating within a waveguide. In particular, a plurality of coaxial probes are incorporated into the waveguide for the purpose of attenuating X-band RF signals. In one embodiment, a 7-bit, 3 dB linear digital attenuator is provided having a waveguide in a racetrack configuration. Coaxial probes in communication with the waveguide are adapted to couple energy to and from a signal traveling within the waveguide. The attenuator can also include switches adapted to reflect coupled energy back into the waveguide or pass the coupled energy to a resistive termination.

Abstract: Various methods and devices are provided for attenuating RF signals propagating within a waveguide. In particular, a plurality of coaxial probes are incorporated into the waveguide for the purpose of attenuating X-band RF signals. In one embodiment, a 7-bit, 3 dB linear digital attenuator is provided having a waveguide in a racetrack configuration. Coaxial probes in communication with the waveguide are adapted to couple energy to and from a signal traveling within the waveguide. The attenuator can also include switches adapted to reflect coupled energy back into the waveguide or pass the coupled energy to a resistive termination.