Abstract: The disclosure describes methods of synthesis of pyridazinone compounds as thyroid hormone analogs and their prodrugs. Preferred methods according to the disclosure allow for large-scale preparation of pyridazinone compounds having high purity. In some embodiments, preferred methods according to the disclosure also allow for the preparation of pyridazinone compounds in better yield than previously used methods for preparing such compounds. Also disclosed are morphic forms of a pyridazinone compound. Further disclosed is a method for treating resistance to thyroid hormone in a subject having at least one TR? mutation.

Abstract: A method for constructing a large-span station by two-wing open type semi-covered excavation and semi-reverse construction, is divided into three stages of excavation. First, excavate a first-stage inner small foundation pit, then excavate a second-stage annular foundation pit within the first-stage retaining piles and outside the range of the first-stage inner small foundation pit, and finally excavate a third-stage semi-covered excavation foundation pit below the first-stage inner small foundation pit and the second-stage annular foundation pit. By setting graded retaining piles, middle upright post piles, middle top plates, local waist beams and local concrete supports in the soil-rock combination strata, so that the force transfer between the foundation pit enclosure and the station main body structures and the underlying rock layer is clear and reliable, and a stable frame structure is achieved.

Abstract: The present disclosure is generally related to 3D imaging capable OLED displays. A light field display comprises an array of 3D light field pixels, each of which comprises an array of corrugated OLED pixels, a metasurface layer disposed adjacent to the array of 3D light field pixels, and a plurality of median layers disposed between the metasurface layer and the corrugated OLED pixels. Each of the corrugated OLED pixels comprises primary or non-primary color subpixels, and produces a different view of an image through the median layers to the metasurface to form a 3D image. The corrugated OLED pixels combined with a cavity effect reduce a divergence of emitted light to enable effective beam direction manipulation by the metasurface. The metasurface having a higher refractive index and a smaller filling factor enables the deflection and direction of the emitted light from the corrugated OLED pixels to be well controlled.

Abstract: A deep-sea crawling robot and a crawling method thereof are provided. The deep-sea crawling robot includes a crawling robot body and a countertop, wherein a top of the crawling robot body is fixedly connected to the countertop, left and right sides of a bottom of the crawling robot body are respectively provided with crawler belts, and left and right sides of the countertop are respectively provided with weight-increasing auxiliary crawling mechanisms; and an outer plate is fixedly connected to a front side or back side of the countertop, a multifunctional propelling mechanism is arranged on the outer plate, and a rapid dewatering mechanism is arranged in a chamber of the countertop. The deep-sea crawling robot can not only accelerate the propulsion and crawling speed when it is on the seabed but also further enhance its stability during the crawling process on the seabed.

Abstract: A method for constructing a large-span station by two-wing open type semi-covered excavation and semi-reverse construction, is divided into three stages of excavation. First, excavate a first-stage inner small foundation pit, then excavate a second-stage annular foundation pit within the first-stage retaining piles and outside the range of the first-stage inner small foundation pit, and finally excavate a third-stage semi-covered excavation foundation pit below the first-stage inner small foundation pit and the second-stage annular foundation pit. By setting graded retaining piles, middle upright post piles, middle top plates, local waist beams and local concrete supports in the soil-rock combination strata, so that the force transfer between the foundation pit enclosure and the station main body structures and the underlying rock layer is clear and reliable, and a stable frame structure is achieved.

Abstract: A battery includes a conductive housing, an insulation layer, a pole, and a cell unit. The insulation layer is disposed in the housing, the pole penetrates through the insulation layer and is insulated from the housing. The electrode plates include a first and a second electrode plates. The first electrode plate includes a first current collector with a first active layer being disposed on one side of it facing the separator, an uncoated region on the other side is to form a first electrode output, which is electrically connected to the pole or the housing. The second electrode plate includes a second current collector, where a second active layer is disposed on at least one side of the second current collector, the second current collector forms a second electrode output end, which is electrically connected to the other one of the housing or the pole.

Abstract: A hardware environment-based data operation method, apparatus and device, and a storage medium. The method includes: determining data to be operated and target hardware, wherein the target hardware is a hardware resource that needs to perform convolution computation on the data to be operated currently; determining the maximum number of channels in which the target hardware executes parallel computation, and determining a data layout corresponding to the maximum number of channels to be an optimal data layout; and converting the data layout of the data to be operated into the optimal data layout, and performing the convolution computation on the data to be operated by using the target hardware after the conversion is completed.

Abstract: A method, an apparatus, and a device for target detection in consecutive images, and a computer-readable storage medium. A second frame is divided into multiple sub-images, before a target in the second frame in a video sequence is detected through a target-detecting network model. A first frame is searched, according to a preset rule for motion estimation, for a corresponding image block matched with each sub-image. Pixels of a sub-image, of which the matched image block is found in the first frame, are replaced with preset background pixels. Hence, a target repeating in both frames is replaced. Finally, the second frame subject to the replacement is inputted in to the target-detecting network model, to obtain a bounding box of a target object of the second frame and a category of such target object. An algorithm for target detection in consecutive images is optimized.

Abstract: An image recognition method and apparatus based on a systolic array, and a medium are disclosed. The method includes: converting obtained image feature information into a one-dimensional feature vector; converting an obtained weight matrix into a one-dimensional weight vector, and allocating a corresponding weight group to each node in a trained three-dimensional systolic array model; performing multiply-accumulate of the feature vector and a weight value on the one-dimensional feature vector in parallel by using the three-dimensional systolic array model, to obtain a feature value corresponding to each node, the feature values with different values reflecting article categories contained in an image; and determining an article category contained in the image according to the feature value corresponding to each node and a pre-established corresponding relationship between the feature value and the article category.

Abstract: Provided are a method, apparatus and device for extracting image features, and a storage medium. The method includes: obtaining parameters to be quantized of a network layer in a neural network model (S101); determining whether values of the parameters to be quantized are all positive numbers (S102); when the values of the parameters to be quantized are all positive numbers, executing, based on an asymmetric linear quantization logic, a quantization operation on the parameters to be quantized (S103); when the values of the parameters to be quantized are not all positive numbers, executing, based on a symmetric linear quantization logic, a quantization operation on the parameters to be quantized (S104); and extracting features of an input image by using the neural network model for which the quantization operation has been executed (S105).

Abstract: The present invention provides a method and apparatus for data caching. The method comprises: output matrixes are acquired one by one, a plurality of acquired output matrixes are written alternately into two queue sets of a first cache unit according to a sequence in which the output matrixes are acquired, and the output matrixes stored line by line in a first cache unit are written into a second cache unit one by one, according to the sequence in which the output matrixes are written into the second cache unit, valid data of each output matrix of the second cache unit is determined one by one according to preset parameters, and the valid data of each output matrix is written into a third cache unit, and the valid data of the output matrixes stored in the third cache unit are configured to be sequentially written into a memory according to a sequence in which the valid data are written into the third cache unit.

Abstract: An image recognition method and device, and a computer-readable storage medium. The method includes: inputting a sample image data set into an original neural network model in advance; and for each convolution layer of the original neural network model, using a feature map of the sample image data set in the current layer as a reconstruction target, firstly obtaining an update weight of a convolution kernel by using a kernel set construction method, then calculating an input channel combination having a minimum reconstruction error, cutting a redundant input channel to obtain a compression result of the current convolution layer, and finally, splicing compression results of the convolution layers to generate an image recognition model.

Abstract: An image recognition method and apparatus based on a systolic array, and a medium are disclosed. The method includes: converting obtained image feature information into a one-dimensional feature vector; converting an obtained weight matrix into a one-dimensional weight vector, and allocating a corresponding weight group to each node in a trained three-dimensional systolic array model; performing multiply-accumulate of the feature vector and a weight value on the one-dimensional feature vector in parallel by using the three-dimensional systolic array model, to obtain a feature value corresponding to each node, the feature values with different values reflecting article categories contained in an image; and determining an article category contained in the image according to the feature value corresponding to each node and a pre-established corresponding relationship between the feature value and the article category.

Abstract: A system for accelerating an RNN network including: a first cache, which is used for outputting Wx1 to WxN or Wh1 to WhN in parallel in N paths in a cyclic switching manner, and the degree of parallelism is k; a second cache, which is used for outputting xt or ht-1 in the cyclic switching manner; a vector multiplication circuit, which is used for, by using N groups of multiplication arrays, respectively calculating Wx1xt to WxNxt, or respectively calculating Wh1ht-1 to WhNht-1; an addition circuit, which is used for calculating Wx1xt+Wh1ht-1+b1 to WxNxt+WhNht-1+bN; an activation circuit, which is used for performing an activation operation according to an output of the addition circuit; a state updating circuit, which is used for acquiring ct-1, calculating ct and ht, updating ct-1, and sending ht to the second cache; a bias data cache; a vector cache; and a cell state cache.

Abstract: A neural network compression method, apparatus and device, and a storage medium are provided. The method includes: performing forward inference on target data by using a target parameter sharing network to obtain an output feature map of the last convolutional module; extracting a channel related feature from the output feature map; inputting the extracted channel related feature and a target constraint condition into a target meta-generative network; and predicting an optimal network architecture under the target constraint condition by using the target meta-generative network to obtain a compressed neural network model. By using the technical solution, the computation load of a performance evaluation process of a neural architecture search may be reduced, and the speed of the searching for a high-performance neural network architecture may be increased.

Abstract: A data processing method, system and device, and a readable storage medium. The method includes: marking each layer of a network model as a key layer or a non-key layer according to acquired structural information of the network model; respectively determining a quantization bit width range of the key layer and a quantization bit width range of the non-key layer according to hardware resource information that needs to be deployed; determining, in the quantization bit width range, optimal quantization bit widths of each layer of the network model; and training the network model based on the optimal quantization bit widths of each layer of the network model, so as to obtain an optimal network model, and performing data processing using the optimal network model.

Abstract: A hardware environment-based data quantization method includes: parsing a model file under a current deep learning framework to obtain intermediate computational graph data and weight data that are independent of a hardware environment; performing calculation on image data in an input data set through a process indicated by an intermediate computational graph to obtain feature map data; separately performing uniform quantization on the weight data and the feature map data of each layer according to a preset linear quantization method, and calculating a weight quantization factor and a feature map quantization factor (S103); combining the weight quantization factor and the feature map quantization factor to obtain a quantization parameter that makes hardware use shift instead of division; and finally, writing the quantization parameter and the quantized weight data to a bin file according to a hardware requirement so as to generate quantized file data (S105).

Abstract: A video data processing method, including: obtaining three-dimensional feature data and three-dimensional weight data corresponding to video data; separately preprocessing the three-dimensional feature data and the three-dimensional weight data to obtain a feature value matrix and a weight value matrix; and inputting the feature value matrix and the weight value matrix into a plurality of three-dimensional systolic arrays for parallel computing to obtain a video data processing result. The present method can fully expand the degree of parallelism of computation and a four-dimensional systolic computation architecture is constructed by using multiple three-dimensional systolic arrays, so as to perform parallel computing on a three-dimensional feature value matrix and a three-dimensional weight value matrix, thereby shortening the computation time of three-dimensional convolution, and improving the video data processing efficiency.

Abstract: Disclosed is an image processing method. In the invention, weighted calculation is carried out on a first quantification threshold value obtained with a saturated mapping method and a second quantification threshold value obtained with an unsaturated mapping method, that is, two quantification threshold values are fused, and an obtained optimal quantification threshold value can be suitable for most activation output layers, and therefore, effective information of the activation output layers can be more effectively reserved, the optimal quantification threshold value is used for subsequent image processing work, and the precision of reasoning and calculation of a quantized deep neural network on a low-bit-width hardware platform is improved. An image processing apparatus and device are disclosed, which have the same beneficial effects as the image processing method.

Abstract: A data storage method, apparatus, and device, and a readable storage medium. The method includes: after a random access memory is powered on, obtaining target data to be stored in a fixed storage address of the random access memory; determining a target transmission mode from a bit value change transmission mode and a bit value fixed transmission mode, wherein the target transmission mode is different from a historical transmission mode determined after the random access memory is powered on last time; and transmitting the target data from and to the random access memory according to the target transmission mode. The method can prevent data from being stolen after power-down of the target data, and guarantees the data security.