Paired-angle-rotation scanning optical coherence tomography forward-imaging probe

We report a novel forward-imaging optical coherence tomography (OCT), needle-probe paired-angle-rotation scanning OCT (PARS-OCT) probe. The probe uses two rotating angled gradient-index lenses to scan the output OCT probe beam over a wide angular arc (∼19° half-angle) of the region forward of the probe. Among other advantages, this probe design is readily amenable to miniaturization and is capable of a variety of scan modes, including volumetric scans. To demonstrate the advantages of the probe design, we have constructed a prototype probe with an outer diameter of 1.65 mm and employed it to acquire four OCT images, with a 45° angle between adjacent images, of the gill structure of a Xenopus laevis tadpole. The system sensitivity was measured to be 93 dB by using the prototype probe with an illumination power of 450 μW on the sample. Moreover, the axial and the lateral resolutions of the probe are 9.3 and 10.3-12.5 μm, respectively

Applying lyapunov's method for analyzing rhythms of night breathing of patients suffering from bronchial asthma

This article focuses on the method of analyzing experimental data of people's airflow, who have bronchial asthma, which is a serious global health problem. It presents the results of using the Lyapunov's method - features of people with different types of bronchial asthma

CrossSinger: A Cross-Lingual Multi-Singer High-Fidelity Singing Voice Synthesizer Trained on Monolingual Singers

It is challenging to build a multi-singer high-fidelity singing voice synthesis system with cross-lingual ability by only using monolingual singers in the training stage. In this paper, we propose CrossSinger, which is a cross-lingual singing voice synthesizer based on Xiaoicesing2. Specifically, we utilize International Phonetic Alphabet to unify the representation for all languages of the training data. Moreover, we leverage conditional layer normalization to incorporate the language information into the model for better pronunciation when singers meet unseen languages. Additionally, gradient reversal layer (GRL) is utilized to remove singer biases included in lyrics since all singers are monolingual, which indicates singer's identity is implicitly associated with the text. The experiment is conducted on a combination of three singing voice datasets containing Japanese Kiritan dataset, English NUS-48E dataset, and one internal Chinese dataset. The result shows CrossSinger can synthesize high-fidelity songs for various singers with cross-lingual ability, including code-switch cases.Comment: Accepted by ASRU202