Abstract: The present disclosure discloses a protection case of an intelligent terminal, wherein the protection case of the intelligent terminal includes a housing, a reinforcing sheet, a RFID coil, a plurality of RFID chips and a plurality of switching elements; an inner surface of the housing is provided with a mounting groove, an outer surface of the housing is provided with a positioning groove; the reinforcing sheet is arranged in the mounting groove; the RFID coil is fixedly attached to the reinforcing sheet; the plurality of the RFID chips are mounted in the mounting groove and are electrically connected to the RFID coil, and the plurality of the RFID chips are arranged in parallel; a plurality of switching elements are mounted in the positioning groove, and the plurality of the switching elements are respectively connected in series to circuits where the corresponding RFID chips are connected with the RFID coil.

Abstract: An intensification mechanism analysis and anthropogenic climate change signal identification method for terrestrial water cycle (TWC) in dry and wet regions, includes: identifying dry regions and wet regions worldwide with observed data; quantifying a precipitation increasing rate; calculating a regional warming rate and a precipitation response warming rate, and investigating a difference between dry regions and wet regions; identifying a fingerprint pattern of a precipitation increase in dry regions and wet regions in response to global warming, and calculating a signal-to-noise ratio (SNR) to quantify a possibility of an anthropogenic climate change signal in dry regions and wet regions; and detecting different external forcing signals in a precipitation change of dry regions and wet regions with an optimal fingerprinting method, and quantifying a contribution of each of the different external forcing signals to the precipitation change.

Abstract: An ocean-onto-land drought (OTLD) identification and propagation mechanism analysis method includes: identifying a new drought event in a global range with data of a historical data and data of a future test; extracting a 3D space-time cube (STC) of the drought event, quantifying spatiotemporal characteristics of the global OTLD, and searching a landfalling hotspot; projecting an OTLD in a future period in combination with different tests, and detecting an anthropogenic signal in an index change of the OTLD in the historical period and in the future period; and analyzing, with moisture transport during the OTLD as a reference, an occurrence mechanism of the OTLD in the historical period and an intensification mechanism of the OTLD in the future period; and clarifying a primary physical factor during the OTLD, and assessing a synthetic risk of a OTLD-affected region with a machine learning method.