Abstract: This disclosure discloses inhibitors of CTGF RNA, MITF RNA, and SRD5A2 RNA and their applications, wherein the inhibitors are gene editing systems. The gene editing systems disclosed herein can knock down CTGF RNA, MITF RNA, or SRD5A2 RNA, and can be used to repair scars, whiten skin, reduce or eliminate melasma, prevent or treat melanoma, and/or prevent or treat androgenetic alopecia. This disclosure also discloses a gene editing system that targets AR RNA encoded by the androgen receptor gene, which can be used to treat androgenetic alopecia and other diseases.

Abstract: Disclosed is a Cas12 protein, a guide polynucleotide, an inactivated Cas12 mutant, a fusion protein or conjugate including the Cas12 protein, an isolated nucleic acid, a CRISPR-Cas12 system, a vector system, a delivery system, a cell, a pharmaceutical composition, and a kit, and uses thereof.

Abstract: This application relates to a speech decoding method performed by a computer device. The method includes: obtaining coded speech data corresponding to an original speech signal; decoding the coded speech data to obtain a decoded speech signal; generating target frequency bandwidth feature information corresponding to the decoded speech signal; performing feature extension on target feature information corresponding to a compressed band in the target frequency bandwidth feature information to obtain extended feature information corresponding to a second band, and a frequency interval of the compressed band being less than a frequency interval of the second band; and obtaining, based on the extended feature information corresponding to the second band, a target speech signal corresponding to the original speech signal.

Abstract: This application relates to a speech encoding method performed by a computer device the method, including: performing subband decomposition on a target speech signal to obtain a plurality of subband excitation signals; obtaining an auditory perception representational value that corresponds to each subband excitation signal; determining at least one first subband excitation signal and at least one second subband excitation signal from the at least two subband excitation signals; obtaining a gain of each of the at least one first subband excitation signal relative to a preset reference excitation signal as an encoding parameter that corresponds to the first subband excitation signal; obtaining a corresponding encoding parameter that is obtained by quantizing each of the at least one second subband excitation signal; and performing encoding on each subband excitation signal based on the encoding parameter corresponding to the subband excitation signal.

Abstract: An audio transmission method is described. A packet loss recovery capability corresponding to current encoded data of an audio signal can be determined according to a first audio encoding feature parameter corresponding to the current encoded data and a second audio encoding feature parameter corresponding to previous or subsequent encoded data of the current encoded data using a packet loss recovery capability prediction neural network model. Whether to perform redundant encoding for the current encoded data can be determined according to the packet loss recovery capability. In response to the redundant encoding being determined to be performed, the redundant encoding can be performed according to the current encoded data to generate a corresponding redundancy packet.

Abstract: A packet loss concealment method includes: receiving a speech data packet; determining a speech power spectrum of speech data in the speech data packet in response to determining, according to the speech data packet, that a packet loss occurs; performing lost frame prediction on the speech power spectrum by using a neural network model, to obtain a predicted lost frame power spectrum; and determining restored speech data according to the speech power spectrum and the predicted lost frame power spectrum.

Abstract: Cas12 protein, guide polynucleotide, inactivated Cas12 mutant, fusion protein or conjugate including the Cas 12 protein, isolated nucleic acid, CRISPR-Cas12 system, vector system, delivery system, cell, pharmaceutical composition, and kit, and the use thereof are provided.

Abstract: Provided are a novel Cas effector protein, a gene editing system, and uses thereof. The Cas effector protein is CasRfg.3 and similar proteins. The CasRfg.3 (also referred to as Ca2) protein of the present disclosure has a relatively shorter amino acid sequence compared to the commonly used SpCas9 protein, allowing it to be easily packaged into small-capacity gene therapy vectors. The CasRfg.3 corresponds to a unique PAM sequence. Additionally, the CasRfg.3 exhibits excellent specificity in targeting and editing nucleic acid sequences, shows good adaptation to temperature variations, and has a wide temperature tolerance range, functioning effectively under high-temperature conditions, such as being capable of cleaving or modifying target nucleic acids at temperatures ranging from 25° C. to 55° C. The novel Cas effector protein of the present disclosure has significant application value in fields like gene therapy.

Abstract: Provided is snRNA which targets USH2A pre-mRNA. The recognition domain of the snRNA is the reverse complement of a USH2A pre-mRNA sequence. The snRNA binds to the USH2A pre-mRNA to splice and jump exon 13. The snRNA promotes a higher exon 13 skipping efficiency than AON.

Abstract: An audio decoding method is performed by a computer device. The method includes: obtaining an audio feature parameter corresponding to audio frames in an original audio; performing encoding bit rate prediction processing on the audio feature parameter through an encoding bit rate prediction model, to obtain an audio encoding bit rate of the audio frames, wherein the encoding bit rate prediction model is configured to predict the audio encoding bit rate according to a target encoding quality score; performing audio encoding on the sample audio frames based on the corresponding sample encoding bit rates to generate sample audio data corresponding to the sample audio frames; and generating target audio data from the original audio by performing audio encoding on the audio frames based on the audio encoding bit rate.

Abstract: This application provides an audio processing method performed by a computer device. The method includes: obtaining a real audio signal from a real environment and a virtual audio signal from a virtual environment in an augmented reality scene; selecting one sound mixing mode from a plurality of sound mixing modes configured for the augmented reality scene as a target sound mixing mode; performing sound mixing processing on the real audio signal and the virtual audio signal according to the target sound mixing mode to obtain a sound-mixed signal; and outputting the sound-mixed signal via a speaker of the computer device. In this way, integration of sounds in an augmented reality scene is realized in an auditory dimension, thereby enriching an integration capability in the augmented reality scene, and improving an overall immersed sense of a user in the augmented reality scene.

Abstract: An audio transmission method is described. A packet loss recovery capability corresponding to current encoded data of an audio signal can be determined according to a first audio encoding feature parameter corresponding to the current encoded data and a second audio encoding feature parameter corresponding to previous or subsequent encoded data of the current encoded data using a packet loss recovery capability prediction neural network model. Whether to perform redundant encoding for the current encoded data can be determined according to the packet loss recovery capability. In response to the redundant encoding being determined to be performed, the redundant encoding can be performed according to the current encoded data to generate a corresponding redundancy packet.

Abstract: An audio encoding bit rate prediction model training method is performed by a computer device. The method includes: obtaining a sample audio feature parameter corresponding to each of sample audio frames in a first sample audio; performing encoding bit rate prediction on the sample audio feature parameter through an encoding bit rate prediction model, to obtain a sample encoding bit rate for each of the sample audio frames; performing audio encoding on the sample audio frames based on the corresponding sample encoding bit rates to generate sample audio data corresponding to the sample audio frames; performing audio decoding on the sample audio data, to obtain a second sample audio corresponding to the sample audio data; and training the encoding bit rate prediction model based on the first sample audio and the second sample audio until a sample encoding quality score reaches a target encoding quality score.

Abstract: This application relates to a speech coding method performed by a computer device. The method includes: obtaining initial frequency bandwidth feature information corresponding to a speech signal; performing feature compression on initial feature information corresponding to a second band in the initial frequency bandwidth feature information to obtain target feature information corresponding to a compressed band, a frequency interval of the second band being greater than a frequency interval of the compressed band; obtaining, based on the target feature information corresponding to the compressed band, a compressed speech signal corresponding to the speech signal; and coding the compressed speech signal to obtain coded speech data corresponding to the speech signal, a target sampling rate corresponding to the compressed speech signal being less than a sampling rate corresponding to the speech signal.

Abstract: The present invention relates to a CRISPR-Cas13 system and use thereof, and also relates to a Cas13 protein, a fusion protein, and a guide polynucleotide. The Cas13 protein has at least 90% sequence identity compared to SEQ ID NO: 1. The fusion protein comprises the Cas13 protein fused to a protein domain and/or a polypeptide tag. The guide polynucleotide comprises a same-direction repetition sequence and a guide sequence that has been engineered to hybridize with the target RNA. The same-direction repetition sequence has at least 70% sequence identity to any of SEQ ID NOs: 3 and 80-87. The CRISPR-Cas13 system comprises the Cas13 protein that has at least 90% sequence identity to SEQ ID NO: 1, or a coding nucleic acid therefor, and the guide polynucleotide or a coding nucleic acid therefor.

Abstract: A data transmission method and apparatus, a terminal, a storage medium, and a system. The data transmission method includes: obtaining audio data and transmission status information, determining a compression factor and a redundancy factor based on the transmission status information, performing time domain data compression processing on the audio data according to the compression factor to obtain compressed data, performing channel coding on the compressed data according to the redundancy factor to obtain a data transmission packet, and transmitting the data transmission packet.

Abstract: An electronic device performs sub-band decomposition on a to-be-coded audio to obtain a to-be-coded low frequency signal corresponding to a low frequency band and a to-be-coded high frequency signal corresponding to a high frequency band. The device performs compression coding on the to-be-coded low frequency signal to obtain low frequency coded data of the to-be-coded low frequency signal. The device determines high frequency prediction information according to the to-be-coded low frequency signal. The device performs feature extraction on the to-be-coded high frequency signal to obtain high frequency feature information. The device determines high frequency compensation information of the to-be-coded high frequency signal according to a difference between the high frequency feature information and the high frequency prediction information.

Abstract: Provided are a novel Cas effector protein, a gene editing system, and uses thereof. The Cas effector protein is CasRfg.3 and similar proteins. The CasRfg.3 (also referred to as Ca2) protein of the present disclosure has a relatively shorter amino acid sequence compared to the commonly used SpCas9 protein, allowing it to be easily packaged into small-capacity gene therapy vectors. The CasRfg.3 corresponds to a unique PAM sequence. Additionally, the CasRfg.3 exhibits excellent specificity in targeting and editing nucleic acid sequences, shows good adaptation to temperature variations, and has a wide temperature tolerance range, functioning effectively under high-temperature conditions, such as being capable of cleaving or modifying target nucleic acids at temperatures ranging from 25° C. to 55° C. The novel Cas effector protein of the present disclosure has significant application value in fields like gene therapy.

Abstract: Embodiments of this application provide an audio data processing method performed by a computer device. The method includes the following steps: acquiring recorded audio; determining prototype audio matching a background reference audio component of the recorded audio from an audio database; extracting candidate speech audio from the recorded audio according to the prototype audio; determining a difference between the recorded audio and the candidate speech audio as the background reference audio component comprised in the recorded audio; performing environmental noise reduction on the candidate speech audio to obtain noise-reduced speech audio corresponding to the candidate speech audio; and combining the noise-reduced speech audio with the background reference audio component to obtain noise-reduced recorded audio.

Abstract: This disclosure provides a network call method and apparatus, a computer device, and a storage medium, and belongs to the field of audio data processing. The method includes: performing time-frequency transformation on an acquired audio signal, to obtain a plurality of pieces of frequency domain information of the audio signal; determining a target bit rate corresponding to the audio signal according to the plurality of pieces of frequency domain information; and encoding the audio signal based on the target bit rate, and performing a network call based on the encoded audio signal.