Abstract: A display panel includes a display region and a photoelectric sensing region which includes a light transmitting region and a frame region surrounding the light transmitting region; the frame region includes a first region surrounding the light transmitting region, a second region on a side of the first region away from the light transmitting region and surrounding the first region, and a third region between the second region and the display region. The spacers are in an array and in the display region but not in the light transmitting region. A plurality of first support pillars are in the first region, arranged around the light transmitting region, and spaced from each other. A plurality of second support pillars are in the second region, around the second region, and spaced from each other. A plurality of third support pillars are in the third region in an array.

Abstract: Disclosed is a pyridazinone compound represented by Formula (I), or a pharmaceutically acceptable salt, prodrug, hydrate, solvate, polymorph, stereoisomer, or isotopic variant thereof. The compound can be used for preparation of medicinal products for treatment and/or prophylaxis of a disease or condition associated with thyroid hormone abnormalities. The compound has higher selectivity to TH?, better pharmacokinetic parameters, desired stability, and higher agonistic activity toward TH?.

Abstract: Provided is a model interpretation method, an image processing method, an electronic device and a storage medium, relating to the field of artificial intelligence, in particular to the field of deep learning. The model interpretation method includes: obtaining a token vector corresponding to an image feature input to a first model; obtaining a model prediction result output by the first model; and determining, according to a combination of an attention weight and a gradient, an association relation between the token vector input to the first model and the model prediction result output by the first model, where the association relation is used to characterize interpretability of the first model.

Abstract: A method for assessing test adequacy of deep neural networks based on element decomposition is provided. The network testing is divided into black box testing and white box testing, of which key elements are decomposed and defined. Network parameters including a weight matrix and a bias vector are extracted. Importance values of neurons in individual layers of the deep neural network are calculated and clustered, and an importance value hot map of neurons in each layer is generated based on clustering results. Mutation testing, and index calculation and evaluation are performed.

Abstract: A method for rapidly acquiring multi-field response of mining-induced coal rock is provided. Based on 3D printing, the method achieves the control of material deformation and turns from 3D to 4D, thus saving manpower and material resources; further, repeated experiments may still be carried out under approximately the same conditions after each printing, so that the similarity of similarity simulations is greatly improved and a stable and reliable scientific law is conveniently obtained; besides, a BP neural network model may be built based on the data collected from similarity simulations to rapidly acquire an accurate and real coal seam mining response.