FloWaveNet : A Generative Flow for Raw Audio

Most modern text-to-speech architectures use a WaveNet vocoder for synthesizing high-fidelity waveform audio, but there have been limitations, such as high inference time, in its practical application due to its ancestral sampling scheme. The recently suggested Parallel WaveNet and ClariNet have achieved real-time audio synthesis capability by incorporating inverse autoregressive flow for parallel sampling. However, these approaches require a two-stage training pipeline with a well-trained teacher network and can only produce natural sound by using probability distillation along with auxiliary loss terms. We propose FloWaveNet, a flow-based generative model for raw audio synthesis. FloWaveNet requires only a single-stage training procedure and a single maximum likelihood loss, without any additional auxiliary terms, and it is inherently parallel due to the characteristics of generative flow. The model can efficiently sample raw audio in real-time, with clarity comparable to previous two-stage parallel models. The code and samples for all models, including our FloWaveNet, are publicly available.Comment: 9 pages, ICML'201

UnitSpeech: Speaker-adaptive Speech Synthesis with Untranscribed Data

We propose UnitSpeech, a speaker-adaptive speech synthesis method that fine-tunes a diffusion-based text-to-speech (TTS) model using minimal untranscribed data. To achieve this, we use the self-supervised unit representation as a pseudo transcript and integrate the unit encoder into the pre-trained TTS model. We train the unit encoder to provide speech content to the diffusion-based decoder and then fine-tune the decoder for speaker adaptation to the reference speaker using a single $$ pair. UnitSpeech performs speech synthesis tasks such as TTS and voice conversion (VC) in a personalized manner without requiring model re-training for each task. UnitSpeech achieves comparable and superior results on personalized TTS and any-to-any VC tasks compared to previous baselines. Our model also shows widespread adaptive performance on real-world data and other tasks that use a unit sequence as input.Comment: INTERSPEECH 2023, Ora

Omega-K Algorithm Using Plane Wave Approximation for Forward-Looking Imaging Radar

We propose an Omega-K algorithm that uses plane wave approximation for image formation in forward-looking imaging radar (FIRA) with the multi-input/double-output configuration. We assume that each of the transmitting antennas is located at the center of the receiving antenna array by applying a virtual antenna array. Then, we solve numerical equations in an approximation of the plane wave with the direction normal to the antenna array. Finally, we can obtain an image by proceeding with the following steps in order: the matched filtering, Stolt interpolation, two-dimensional inverse fast Fourier transform, phase compensation, image registration, and image merging. The performance of the proposed algorithm is verified through a simulation and a real experiment with neighboring targets. The results show that the proposed Omega-K algorithm with plane wave approximation can be successfully applied to FIRA systems with bistatic synthetic aperture radar configuration

Usefulness and safety of the “God’s Hand” pneumatic compression device for hemostasis in femoral catheterization

PURPOSE :We aimed to assess the usefulness and safety of the God’s Hand pneumatic compression device for hemostasis in patients undergoing percutaneous endovascular procedures via femoral artery.METHODS:Two hundred thirty-seven patients in whom hemostasis of femoral catheterization was achieved using a God’s Hand pneumatic compression device were enrolled. The patients were divided into group A, those in whom the device was applied for four hours, and group B, those in whom the device was applied for two hours, with an additional two hours of bed rest in both groups. Groups A and B were regrouped to groups A’ and B’ using the propensity score matching method (n=65, for both). Chi-squared test and logistic regression models were used to analyze the relationship between the complication rate and patient characteristics and procedure-related factors.RESULTS:Clinical success was achieved in 216 of 237 patients (91.1%): 63 in group A (84%) and 153 in group B (94.4%); in propensity score matched groups, clinical success was seen in 47 patients in group A’ (81.5%) and 62 patients in group B’ (95.4%). Group B’ showed a higher clinical success rate than group A’ (P = 0.028). There were no major complications. In logistic regression models, a negative association was noted between the complication rate and the duration of God’s Hand application; however, this association was not statistically significant.CONCLUSION:The God’s Hand pneumatic compression device is effective and safe for the hemostasis of femoral catheterization, and four hours of bed rest is sufficient for hemostasis in selected patients

Putative spin liquid in the triangle-based iridate Ba3_3IrTi2_2O9_9

We report on thermodynamic, magnetization, and muon spin relaxation measurements of the strong spin-orbit coupled iridate Ba$_3$IrTi$_2$O$_9$, which constitutes a new frustration motif made up a mixture of edge- and corner-sharing triangles. In spite of strong antiferromagnetic exchange interaction of the order of 100~K, we find no hint for long-range magnetic order down to 23 mK. The magnetic specific heat data unveil the $T$-linear and -squared dependences at low temperatures below 1~K. At the respective temperatures, the zero-field muon spin relaxation features a persistent spin dynamics, indicative of unconventional low-energy excitations. A comparison to the $4d$ isostructural compound Ba$_3$RuTi$_2$O$_9$ suggests that a concerted interplay of compass-like magnetic interactions and frustrated geometry promotes a dynamically fluctuating state in a triangle-based iridate.Comment: Physical Review B accepte

Stimulation of the Migration and Expansion of Adult Mouse Neural Stem Cells by the FPR2-Specific Peptide WKYMVm

Neural stem cells (NSCs) are multipotent cells capable of self-renewal and differentiation into different nervous system cells. Mouse NSCs (mNSCs) are useful tools for studying neurogenesis and the therapeutic applications of neurodegenerative diseases in mammals. Formyl peptide receptor 2 (FPR2), expressed in the central nervous system and brain, is involved in the migration and differentiation of murine embryonic-derived NSCs. In this study, we explored the effect of FPR2 activation in adult mNSCs using the synthetic peptide Trp-Lys-Tyr-Met-Val-D-Met-NH2 (WKYMVm), an agonist of FPR2. After isolation of NSCs from the subventricular zone of the adult mouse brain, they were cultured in two culture systems—neurospheres or adherent monolayers—to demonstrate the expression of NSC markers and phenotypes. Under different conditions, mNSCs differentiated into neurons and glial cells such as astrocytes, microglia, and oligodendrocytes. Treatment with WKYMVm stimulated the chemotactic migration of mNSCs. Moreover, WKYMVm-treated mNSCs were found to promote proliferation; this result was confirmed by the expansion of mNSCs in Matrigel and the increase in the number of Ki67-positive cells. Incubation of mNSCs with WKYMVm in a supplement-free medium enhanced the survival rate of the mNSCs. Together, these results suggest that WKYMVm-induced activation of FPR2 stimulates cellular responses in adult NSCs. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.1

3D Cascaded U-Net with a Squeeze-and-Exicitation Block for Semantic Segmentation on Kidney and Renal Cell Carcinoma in Abdonimal Volumetric CT

Segmentation is a fundamental process in medical image analysis. Recently, convolutional neural networks (CNNs) has allowed for automatic segmentation; however, segmentaiton of complex organs and diseases including the kidney or renal cell carcinoma (RCC) remains a different task due to limited data and labor-intensive labeling work. The purpose of this study is to segment kideny and RCC in CT using cascaded 3D U-Net with a squeeze-and-excitation (SE) block using a cascaded method. 210 kidneys and their RCC in abdominal CT images were used as training and validation sets. The Dice similarity coefficients (DSCs) of kidney and RCC in test set were 0.963 and 0.734 respectively. The cascaded semantic segmentation can potentially reduce segmentation efforts and increase the efficiency in clinical workflow