Abstract: The present invention provides a gas filter comprising an active element and a housing structure for said active element, said housing structure comprising a gas inlet and a gas outlet, said active element comprising or consisting of: a matrix material; a CO2 sorbent; and water, wherein at least some of the CO2 sorbent is embedded within the matrix material.

Abstract: Techniques are disclosed for equipment support management comprising proactive identification and remediation for one or more impacted components of the equipment using a machine learning-based approach. By way of one example, a method identifies, for given equipment comprising a plurality of components, one or more components of the plurality of components that may be impacted by another component of the plurality of components for which an issue has been reported, wherein one or more machine learning-based algorithms are used to perform at least a portion of the identification. The method then generates, for the given equipment, a plan to proactively remedy the one or more identified components in conjunction with remedying the issue-reported component. In some further examples, a relevance tree is used to identify the one or more impacted components.

Abstract: The present invention provides an air filter comprising a polymer foam and an adsorbent material wherein said polymer foam comprises metal particles.

Abstract: The present invention provides an air filter comprising a polymer foam and an adsorbent material wherein said polymer foam comprises metal particles.