Abstract: A head-mounted display apparatus includes a display, a strap and a head-turning assisting device; two ends of the strap are fixedly connected to the display; the head-turning assisting device is positioned in the strap; when the head-mounted display apparatus is worn on the head of the human body, the display is positioned in the position of the eyes of the human body, and the strap is wrapped around the head of the human body; the display includes a master controller and a display module, the master controller is electrically connected to both the head-turning assisting device and the display module. The master controller is configured to acquire a display image from the display module, and to control the head-turning assisting device to assist the head of the human body to turn according to the display image.

Abstract: Disclosed are a super-resolution imaging system (1, 41, 51), a super-resolution imaging method, a biological sample identification system (4, 61) and method, a nucleic acid sequencing imaging system (5) and method, and a nucleic acid identification system (6) and method. The super-resolution imaging system (1, 41, 51) includes an illumination system (A) and an imaging system (B). The illumination system (A) outputs excitation light to irradiate a biological sample to generate excited light, and the imaging system (B) collects and records the excited light to generate an excited light image. The illumination system (A) includes an excitation light source (10, 10a) and a structured light generation and modulation device (11, 11a). The excitation light source (10, 10a) outputs the excitation light, and the structured light generation and modulation device (11, 11a) modulates the excitation light into structured light to irradiate the biological sample to generate the excited light.

Abstract: Disclosed are an isolation method for a high-performance computer system, and a high-performance computer system. The isolation method comprises node-level isolation performed. The node-level isolation comprises: configuring a routing table for each computing node, and configuring, in the routing table, valid routing information for computing node pairs; when any one source computing node needs to communicate with a target computing node, determining, by lookup, whether valid routing information exists between the source computing node and the target computing node according to the configured routing table; if so, allowing the source computing node to communicate with the target computing node; otherwise, forbidding the source computing node from communicating with the target computing node.

Abstract: A method for processing information, includes: performing word segmentation on first corpus data to obtain second corpus data containing at least one word; processing, based on a first pretrained model, the at least one word contained in the second corpus data, to obtain a first eigenvector sequence corresponding to the second corpus data; processing, based on a second pretrained model, characters contained in the first corpus data, to obtain a second eigenvector sequence corresponding to the first corpus data; and obtaining a target eigenvector based on the first eigenvector sequence and the second eigenvector sequence.

Abstract: Provided are a method and apparatuses for training a classification neural network, a text classification method and apparatus and an electronic device. The method includes: acquiring a regression result of sample text data, which is determined based on a pre-constructed first target neural network and represents a classification trend of the sample text data; inputting the sample text data and the regression result to a second target neural network; obtaining a predicted classification result of each piece of sample text data based on the second target neural network; adjusting a parameter of the second target neural network according to a difference between the predicted classification result and a true value of a corresponding category; and obtaining a trained second target neural network after a change of network loss related to the second target neural network meets a convergence condition.

Abstract: A method for processing information, includes: performing word segmentation on first corpus data to obtain second corpus data containing at least one word; processing, based on a first pretrained model, the at least one word contained in the second corpus data, to obtain a first eigenvector sequence corresponding to the second corpus data; processing, based on a second pretrained model, characters contained in the first corpus data, to obtain a second eigenvector sequence corresponding to the first corpus data; and obtaining a target eigenvector based on the first eigenvector sequence and the second eigenvector sequence.