Abstract: The present invention discloses a method of preparing an alkali activation material by using red mud-based wet grinding and carbon sequestration and an application thereof. The preparation method includes: (1) adding water, red mud, a crystalline control agent, and a grinding aid into a wet grinding carbon sequestration apparatus to perform wet grinding, and simultaneously introducing CO2 until a slurry pH reaches 7 to 7.5; and removing wet grinding balls by a sieve to obtain a slurry A; (2) adding carbide slag, water and a water reducer to a wet planetary ball grinder tank for wet grinding, and removing wet grinding balls by a sieve to obtain a slurry B; (3) taking 50 to 80 parts of the slurry A and 20 to 50 parts of the slurry B and mixing them to obtain an alkali activation material.

Abstract: Systems and methods provide multiple cell activation. A user equipment (UE) receives, from a wireless network, a command to activate multiple cells simultaneously. In response, the UE initiates cell activation procedures for the multiple cells. The cell activation procedures include waiting for an active transmission configuration indicator (TCI) indication. The UE monitors for the active TCI indication on any of the multiple cells. In response to receiving the active TCI indication on a first cell of the multiple cells, the UE determines one or more second cells of the multiple cells that share a same spatial relationship with the first cell according to one or more predetermined rule, and autonomously continues the cell activation procedures for the first cell and the one or more second cells.

Abstract: The present application relates to devices and components including apparatus, systems, and methods to provide adaptive physical downlink control channel (PDCCH) monitoring. In particular, a unified signaling technique for adaptive PDCCH search space monitoring is descried. This signaling can indicate either one or a combination of the switching and skipping. In an example, the signaling includes multiple parts. In a first part, radio resource control (RRC) signaling is sent from the network to the device to configure the device for switching only, skipping only, or switching and skipping. In a second part, first DCI is sent from the network to the device to indicate the particular PDCCH monitoring configuration to use for the PDCCH search space monitoring. Thereafter, network sends second DCI in the relevant PDCCH search space, where this second DCI schedules traffic. The device performs blind decoding to determine the second DCI in order to exchange the traffic.

Abstract: The present invention provides a method of preparing a recycled cementitious material by a phosphogypsum-assisted carbon sequestration pretreatment process. The method includes: (1) placing 100 mass parts of phosphogypsum, 1 to 2 mass parts of grinding aid, 10 to 20 mass parts of sodium-containing alkali component, 150 to 300 mass parts of zirconia balls, and 150 to 300 mass parts of water into a wet grinding tank for wet grinding. After 10 min to 30 min of wet grinding, introducing CO2 at a flow rate of 1.5 to 2.2 mass parts/min to keep a temperature of a wet grinding slurry below 40° C. When the wet grinding slurry reaches pH=10, ending the wet grinding and sieving out a wet grinding slurry; (2) mixing the wet grinding slurry with 700 to 1000 mass parts of slag and 100 to 350 mass parts of water to obtain a recycled cementitious material.

Abstract: A fault detection system for use with a solar hot water system may include a data acquisition module which may, in turn, include a plurality of sensors. Input data may include a sensed condition. The system may also include a neural network to receive the input data which may be a multi-layer hierarchical adaptive resonance theory (ART) neural network. The neural network may perform an analysis on the input data to determine existence of a fault or a condition indicative of a potential fault. The fault and the condition indicative of the potential fault are prioritized according to the analysis performed by the neural network. A warning output relating to the fault and the condition indicative of the potential fault is generated responsive to the analysis, and is displayed on the user interface.