Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification

Respiratory sound contains crucial information for the early diagnosis of fatal lung diseases. Since the COVID-19 pandemic, there has been a growing interest in contact-free medical care based on electronic stethoscopes. To this end, cutting-edge deep learning models have been developed to diagnose lung diseases; however, it is still challenging due to the scarcity of medical data. In this study, we demonstrate that the pretrained model on large-scale visual and audio datasets can be generalized to the respiratory sound classification task. In addition, we introduce a straightforward Patch-Mix augmentation, which randomly mixes patches between different samples, with Audio Spectrogram Transformer (AST). We further propose a novel and effective Patch-Mix Contrastive Learning to distinguish the mixed representations in the latent space. Our method achieves state-of-the-art performance on the ICBHI dataset, outperforming the prior leading score by an improvement of 4.08%.Comment: INTERSPEECH 2023, Code URL: https://github.com/raymin0223/patch-mix_contrastive_learnin

High performance moisture-driven power generators using ionic Janus woods

2

Moisture-induced power generator fabricated on a lateral field-excited quartz resonator

Abstract We fabricated a moisture-induced power generator on a lateral field-excited quartz resonator to simultaneously measure changes in mass and voltage generation during water vapor adsorption. Circularly interdigitated gold electrodes were vacuum deposited on the top surface and used to measure changes in mass, and two symmetric semicircular gold electrodes were vacuum deposited on the bottom surface and used to measure changes in voltage generation. After coating a thin film of a mixture comprising sodium alginate, carbon black, and polyvinyl alcohol (SCP) on the top surface, an electric field was applied to create a concentration gradient of sodium ions between the interdigitated electrodes. The changes in the resonant frequency and voltage generation of the SCP-coated quartz resonator were measured simultaneously under various relative humidity conditions. The results revealed, for the first time, three distinct voltage-generation regions during moisture adsorption: (i) a region of negligible voltage generation, (ii) that of an increase in voltage generation, and (iii) that of a decrease in voltage generation

Optogenetic control of endogenous Ca2+ channels in vivo

Calcium (Ca2+) signals that are precisely modulated in space and time mediate a myriad of cellular processes, including contraction, excitation, growth, differentiation and apoptosis1. However, study of Ca2+ responses has been hampered by technological limitations of existing Ca2+-modulating tools. Here we present OptoSTIM1, an optogenetic tool for manipulating intracellular Ca2+ levels through activation of Ca2+-selective endogenous Ca2+ release−activated Ca2+ (CRAC) channels. Using OptoSTIM1, which combines a plant photoreceptor2,3 and the CRAC channel regulator STIM1 (ref. 4), we quantitatively and qualitatively controlled intracellular Ca2+ levels in various biological systems, including zebrafish embryos and human embryonic stem cells. We demonstrate that activating OptoSTIM1 in the CA1 hippocampal region of mice selectively reinforced contextual memory formation. The broad utility of OptoSTIM1 will expand our mechanistic understanding of numerous Ca2+-associated processes and facilitate screening for drug candidates that antagonize Ca2+ signals.131351sciescopu