In China, neither reproduction and parenthood by lesbian couples nor their marital status are regulated or protected by law. In 2020, the first legal dispute in China involving a lesbian couple over custody of their joint baby was heard in court. This study examines the legal and ethical issues that lesbian couples confront when they decide to give birth to a child of their own. These challenges begin with regulatory restrictions on their lawful access to assisted reproductive technology and extend (...) to gaps in the legal establishment of parenthood. We found that the lack of access to legitimate reproductive assistance for lesbian couples in China has caused them to make efforts to circumvent laws and regulations to have a child. However, the legislative gaps later led to ethical dilemmas when resolving disputes over parenthood. This study discusses different accounts of establishing and determining natural parenthood in China and concludes by pointing out the urgent need for change in legislative and sociocultural attitudes toward both assisted reproductive technology and same‐sex relationships, mapping the way forward for lesbian couples to obtain better protection of procreation and parenthood before their marriage is culturally accepted and finally legalized. (shrink)

DNA–protein interactions are fundamental to many biological processes, including the regulation of gene expression. Determining the binding affinities of transcription factors (TFs) to different DNA sequences allows the quantitative modeling of transcriptional regulatory networks and has been a significant technical challenge in molecular biology for many years. A recent paper by Maerkl and Quake1 demonstrated the use of microfluidic technology for the analysis of DNA–protein interactions. An array of short DNA sequences was spotted onto a glass slide, which was then (...) covered with a microfluidic device allowing each spot to be within a chamber into which the flow of materials was controlled by valves. By trapping the DNA–protein complexes on the surface and measuring their concentrations microscopically, they could determine the binding affinity to a large number of DNA sequences that were varied systematically. They studied four TFs from the basic helix–loop–helix family of proteins, all of which bind to E‐box sites with the consensus CAnnTG (where “n” can be any base), and showed that variations in affinity for different sites allows each TF to regulate different genes. BioEssays 29:717–721, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

In this paper, we propose to incorporate the local attention in WaveNet-CTC to improve the performance of Tibetan speech recognition in multitask learning. With an increase in task number, such as simultaneous Tibetan speech content recognition, dialect identification, and speaker recognition, the accuracy rate of a single WaveNet-CTC decreases on speech recognition. Inspired by the attention mechanism, we introduce the local attention to automatically tune the weights of feature frames in a window and pay different attention on context information for (...) multitask learning. The experimental results show that our method improves the accuracies of speech recognition for all Tibetan dialects in three-task learning, compared with the baseline model. Furthermore, our method significantly improves the accuracy for low-resource dialect by 5.11% against the specific-dialect model. (shrink)

The research on Tibetan speech synthesis technology has been mainly focusing on single dialect, and thus there is a lack of research on Tibetan multidialect speech synthesis technology. This paper presents an end-to-end Tibetan multidialect speech synthesis model to realize a speech synthesis system which can be used to synthesize different Tibetan dialects. Firstly, Wylie transliteration scheme is used to convert the Tibetan text into the corresponding Latin letters, which effectively reduces the size of training corpus and the workload of (...) front-end text processing. Secondly, a shared feature prediction network with a cyclic sequence-to-sequence structure is built, which maps the Latin transliteration vector of Tibetan character to Mel spectrograms and learns the relevant features of multidialect speech data. Thirdly, two dialect-specific WaveNet vocoders are combined with the feature prediction network, which synthesizes the Mel spectrum of Lhasa-Ü-Tsang and Amdo pastoral dialect into time-domain waveform, respectively. The model avoids using a large number of Tibetan dialect expertise for processing some time-consuming tasks, such as phonetic analysis and phonological annotation. Additionally, it can directly synthesize Lhasa-Ü-Tsang and Amdo pastoral speech on the existing text annotation. The experimental results show that the synthesized speech of Lhasa-Ü-Tsang and Amdo pastoral dialect based on our proposed method has better clarity and naturalness than the Tibetan monolingual model. (shrink)