Abstract: Display substrate, method for manufacturing the same, and display device are disclosed. The display substrate comprises: a base substrate comprising a display region and a peripheral region located at a periphery of the display region, the display region comprises at least two display sub-regions; the display substrate further comprises scanning lines and sub-pixels, wherein the scanning lines comprise first scanning lines comprising at least two scanning line segments independent from each other, and the at least two scanning line segments are located in different display sub-regions; and the sub-pixels are divided into rows of sub-pixels, the rows of sub-pixels comprise a target row of sub-pixels which is divided into at least two sub-pixel groups located in different display sub-regions, and the scanning line segment is coupled to each sub-pixel in a corresponding sub-pixel group belonging to a same display sub-region.

Abstract: The present invention relates to a sodium polyacrylate super absorbent resin for blood absorption with a gradual hierarchical structure. When a blood simulant solution is used as the detection medium, according to ISO 19699-1:2017(E), the absorption capacity of the blood simulant solution is ?18.0 g/g, Preferably ?18.5 g/g; the absorption rate of the blood simulant solution is ?45 s, preferably ?40 s, more preferably ?38 s; when human blood is used as the detection medium, according to ISO 19699-1:2017(E), the absorption capacity of the human blood is ?8.0 g/g, preferably ?8.3 g/g, more preferably ?8.6 g/g; the absorption rate of the human blood is ?45 s, preferably ?40 s, more preferably ?35 s, most preferably ?25 s.

Abstract: Systems, methods, and non-transitory computer-readable media can collect past user information and churn data for a plurality of users. A churn prediction model is trained using the past user information and churn data. A churn propensity score is calculated for a present user based on the churn prediction model, the churn propensity score indicative of the likelihood of the present user to churn.

Abstract: Systems, methods, and non-transitory computer-readable media can collect past user information and churn data for a plurality of users. A churn prediction model is trained using the past user information and churn data. A churn propensity score is calculated for a present user based on the churn prediction model, the churn propensity score indicative of the likelihood of the present user to churn.