Abstract: Supporting value prediction by a first wireless device being served by a wireless communication network. The network sends, to the first wireless device, configuration information for configuring the first wireless device to, train a machine learning, ML, model to predict certain output values. The training uses input training data that at least partly are determined by operative conditions of the first wireless device and uses desired output values with the input training data. The training ends when the ML model being trained fulfills certain one or more ready criteria. The first wireless device trains the ML model based on the configuration information and sends reporting information to the network indicating that it has trained the ML model and fulfilled the ready criteria. The network determines, based on the reporting information, regarding application of the trained ML model by the first wireless device.

Abstract: A pocket filter assembly with reduced risk for exposing a user to contaminations leaving the pocket filter assembly during and after removal of the pocket filter assembly from an installation is disclosed. A first pocket filter comprises a grip member configured to be gripped by the user to enable folding of the pocket filters in a controlled manner before removal of the pocket filter assembly from an installation.

Abstract: A pocket filter assembly (1) with reduced risk for exposing a user to contaminations leaving the pocket filter assembly during and after removal of the pocket filter assembly from an installation is disclosed. A first pocket filter (6a) comprises a grip member (10) configured to be gripped by the user to enable folding of the pocket filters in a controlled manner before removal of the pocket filter assembly from an installation.