Zero- and Few-shot Sound Event Localization and Detection

Sound event localization and detection (SELD) systems estimate direction-of-arrival (DOA) and temporal activation for sets of target classes. Neural network (NN)-based SELD systems have performed well in various sets of target classes, but they only output the DOA and temporal activation of preset classes that are trained before inference. To customize target classes after training, we tackle zero- and few-shot SELD tasks, in which we set new classes with a text sample or a few audio samples. While zero-shot sound classification tasks are achievable by embedding from contrastive language-audio pretraining (CLAP), zero-shot SELD tasks require assigning an activity and a DOA to each embedding, especially in overlapping cases. To tackle the assignment problem in overlapping cases, we propose an embed-ACCDOA model, which is trained to output track-wise CLAP embedding and corresponding activity-coupled Cartesian direction-of-arrival (ACCDOA). In our experimental evaluations on zero- and few-shot SELD tasks, the embed-ACCDOA model showed a better location-dependent scores than a straightforward combination of the CLAP audio encoder and a DOA estimation model. Moreover, the proposed combination of the embed-ACCDOA model and CLAP audio encoder with zero- or few-shot samples performed comparably to an official baseline system trained with complete train data in an evaluation dataset.Comment: 5 pages, 4 figure

Molecular basis for the dosing time-dependency of anti-allodynic effects of gabapentin in a mouse model of neuropathic pain

<p>Abstract</p> <p>Background</p> <p>Neuropathic pain is characterized by hypersensitivity to innocuous stimuli (tactile allodynia) that is nearly always resistant to NSAIDs or even opioids. Gabapentin, a GABA analogue, was originally developed to treat epilepsy. Accumulating clinical evidence supports the effectiveness of this drug for diverse neuropathic pain. In this study, we showed that the anti-allodynic effect of gabapentin was changed by the circadian oscillation in the expression of its target molecule, the calcium channel α2δ-1 subunit.</p> <p>Results</p> <p>Mice were underwent partial sciatic nerve ligation (PSL) to create a model of neuropathic pain. The paw withdrawal threshold (PWT) in PSL mice significantly decreased and fluctuated with a period length about 24 h. The PWT in PSL mice was dose-dependently increased by intraperitoneal injection of gabapentin, but the anti-allodynic effects varied according to its dosing time. The protein levels of α2δ-1 subunit were up-regulated in the DRG of PSL mice, but the protein levels oscillated in a circadian time-dependent manner. The time-dependent oscillation of α2δ-1 subunit protein correlated with fluctuations in the maximal binding capacity of gabapentin. The anti-allodynic effect of gabapentin was attenuated at the times of the day when α2δ-1 subunit protein was abundant.</p> <p>Conclusions</p> <p>These findings suggest that the dosing time-dependent difference in the anti-allodynic effects of gabapentin is attributable to the circadian oscillation of α2δ-1 subunit expression in the DRG and indicate that the optimizing its dosing schedule helps to achieve rational pharmacotherapy for neuropathic pain.</p

桜島地域の地表大気中の鉛-210およびポロニウム-210

金沢大学低レベル放射能実験施設金沢大学自然計測応用研究センター自然計測研究部

STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events

While direction of arrival (DOA) of sound events is generally estimated from multichannel audio data recorded in a microphone array, sound events usually derive from visually perceptible source objects, e.g., sounds of footsteps come from the feet of a walker. This paper proposes an audio-visual sound event localization and detection (SELD) task, which uses multichannel audio and video information to estimate the temporal activation and DOA of target sound events. Audio-visual SELD systems can detect and localize sound events using signals from a microphone array and audio-visual correspondence. We also introduce an audio-visual dataset, Sony-TAu Realistic Spatial Soundscapes 2023 (STARSS23), which consists of multichannel audio data recorded with a microphone array, video data, and spatiotemporal annotation of sound events. Sound scenes in STARSS23 are recorded with instructions, which guide recording participants to ensure adequate activity and occurrences of sound events. STARSS23 also serves human-annotated temporal activation labels and human-confirmed DOA labels, which are based on tracking results of a motion capture system. Our benchmark results demonstrate the benefits of using visual object positions in audio-visual SELD tasks. The data is available at https://zenodo.org/record/7880637.Comment: 27 pages, 9 figures, accepted for publication in NeurIPS 2023 Track on Datasets and Benchmark

HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes

Vector quantization (VQ) is a technique to deterministically learn features with discrete codebook representations. It is commonly performed with a variational autoencoding model, VQ-VAE, which can be further extended to hierarchical structures for making high-fidelity reconstructions. However, such hierarchical extensions of VQ-VAE often suffer from the codebook/layer collapse issue, where the codebook is not efficiently used to express the data, and hence degrades reconstruction accuracy. To mitigate this problem, we propose a novel unified framework to stochastically learn hierarchical discrete representation on the basis of the variational Bayes framework, called hierarchically quantized variational autoencoder (HQ-VAE). HQ-VAE naturally generalizes the hierarchical variants of VQ-VAE, such as VQ-VAE-2 and residual-quantized VAE (RQ-VAE), and provides them with a Bayesian training scheme. Our comprehensive experiments on image datasets show that HQ-VAE enhances codebook usage and improves reconstruction performance. We also validated HQ-VAE in terms of its applicability to a different modality with an audio dataset.Comment: 34 pages with 17 figures, accepted for TML

Real-Time PCR-Based Analysis of the Human Bile MicroRNAome Identifies miR-9 as a Potential Diagnostic Biomarker for Biliary Tract Cancer

Biliary tract cancer (BTC) is often difficult to diagnose definitively, even through histological examination. MicroRNAs (miRNAs) regulate a variety of physiological processes. In recent years, it has been suggested that profiles for circulating miRNAs, as well as those for tissue miRNAs, have the potential to be used as diagnostic biomarkers for cancer. The aim of this study was to confirm the existence of miRNAs in human bile and to assess their potential as clinical biomarkers for BTC. We sampled bile from patients who underwent biliary drainage for biliary diseases such as BTC and choledocholithiasis. PCR-based miRNA detection and miRNA cloning were performed to identify bile miRNAs. Using high-throughput real-time PCR-based miRNA microarrays, the expression profiles of 667 miRNAs were compared in patients with malignant disease (n = 9) and age-matched patients with the benign disease choledocholithiasis (n = 9). We subsequently characterized bile miRNAs in terms of stability and localization. Through cloning and using PCR methods, we confirmed that miRNAs exist in bile. Differential analysis of bile miRNAs demonstrated that 10 of the 667 miRNAs were significantly more highly expressed in the malignant group than in the benign group at P<0.0005. Setting the specificity threshold to 100% showed that some miRNAs (miR-9, miR-302c*, miR-199a-3p and miR-222*) had a sensitivity level of 88.9%, and receiver-operating characteristic analysis demonstrated that miR-9 and miR-145* could be useful diagnostic markers for BTC. Moreover, we verified the long-term stability of miRNAs in bile, a characteristic that makes them suitable for diagnostic use in clinical settings. We also confirmed that bile miRNAs are localized to the malignant/benign biliary epithelia. These findings suggest that bile miRNAs could be informative biomarkers for hepatobiliary disease and that some miRNAs, particularly miR-9, may be helpful in the diagnosis and clinical management of BTC

Prolyl Isomerase Pin1 Regulates Mouse Embryonic Fibroblast Differentiation into Adipose Cells

isomerase, Pin1, regulates insulin signal transduction. Pin1 reduces responses to insulin stimulation by binding CRTC2 (CREB-regulated transcriptional co-activator 2) and PPARγ (peroxisome prolifereator- activated receptor γ), but conversely enhances insulin signaling by binding IRS-1 (insulin receptor substrate-1), Akt kinase, and Smad3. Therefore, it is still unclear whether Pin1 inhibits or enhances adipose cell differentiation. mice was restored by increasing expression of Pin1. We found that Pin1 binds to phosphoThr172- and phosphoSer271-Pro sites in CREB suppress the activity in COS-7 cells.Pin1 enhanced the uptake of triglycerides and the differentiation of MEF cells into adipose cells in response to insulin stimulation. Results of this study suggest that Pin1 down-regulation could be a potential approach in obesity-related dysfunctions, such as high blood pressure, diabetes, non-alcoholic steatohepatitis

Estimation of the detected background by the future gamma ray transient mission CAMELOT

This study presents a background estimation for the CubeSats Applied for MEasuring and LOcalising Transients (CAMELOT), which is a proposed fleet of nanosatellites for the all-sky monitoring and timing-based localization of gamma ray transients with precise localization capability at low Earth orbits. CAMELOT will allow us to observe and precisely localize short gamma ray bursts (GRBs) associated with kilonovae, long GRBs associated with core-collapse massive stars, magnetar outbursts, terrestrial gamma ray flashes, and gamma ray counterparts to gravitational wave sources. A fleet of at least nine 3U CubeSats is proposed to be equipped with large and thin CsI(Tl) scintillators read out by multipixel photon counters (MPPC). A careful study of the radiation environment in space is necessary to optimize the detector casing, estimate the duty cycle due to the crossing of the South Atlantic Anomaly and polar regions, and minimize the effect of the radiation damage of MPPCs

The YUIMA project : a computational framework for simulation and inference of stochastic differential equations

The Yuima Project is an open source and collaborative e ort aimed at developing the R package named yuima for simulation and inference of stochastic di erential equations. In the yuima package, stochastic di erential equations can be of very abstract type, multidimensional, driven by Wiener process or fractional Brownian motion with general Hurst parameter, with or without jumps speci ed as L evy noise. The yuima package is intended to o er the basic infrastructure on which complex models and inference procedures can be built on. The computational framework implemented allow for the estimation of high frequency data and also o er the ability to perform Monte Carlo anal- ysis using cluster infrastructure whenever available in a transparent way to the user. Some real examples of model implementation and data estimation will be considere

Infiltration of M1, but not M2, macrophages is impaired after unilateral ureter obstruction in Nrf2-deficient mice

Chronic inflammation can be a major driver of the failure of a variety of organs, including chronic kidney disease (CKD). The NLR family pyrin domain-containing 3 (NLRP3) inflammasome has been shown to play a pivotal role in inflammation in a mouse kidney disease model. Nuclear factor erythroid 2-related factor 2 (Nrf2), the master transcription factor for anti-oxidant responses, has also been implicated in inflammasome activation under physiological conditions. However, the mechanism underlying inflammasome activation in CKD remains elusive. Here, we show that the loss of Nrf2 suppresses fibrosis and inflammation in a unilateral ureter obstruction (UUO) model of CKD in mice. We consistently observed decreased expression of inflammation-related genes NLRP3 and IL-1β in Nrf2-deficient kidneys after UUO. Increased infiltration of M1, but not M2, macrophages appears to mediate the suppression of UUO-induced CKD symptoms. Furthermore, we found that activation of the NLRP3 inflammasome is attenuated in Nrf2-deficient bone marrow–derived macrophages. These results demonstrate that Nrf2-related inflammasome activation can promote CKD symptoms via infiltration of M1 macrophages. Thus, we have identified the Nrf2 pathway as a promising therapeutic target for CKD