Time-weighted Frequency Domain Audio Representation with GMM Estimator for Anomalous Sound Detection

Although deep learning is the mainstream method in unsupervised anomalous sound detection, Gaussian Mixture Model (GMM) with statistical audio frequency representation as input can achieve comparable results with much lower model complexity and fewer parameters. Existing statistical frequency representations, e.g, the log-Mel spectrogram's average or maximum over time, do not always work well for different machines. This paper presents Time-Weighted Frequency Domain Representation (TWFR) with the GMM method (TWFR-GMM) for anomalous sound detection. The TWFR is a generalized statistical frequency domain representation that can adapt to different machine types, using the global weighted ranking pooling over time-domain. This allows GMM estimator to recognize anomalies, even under domain-shift conditions, as visualized with a Mahalanobis distance-based metric. Experiments on DCASE 2022 Challenge Task2 dataset show that our method has better detection performance than recent deep learning methods. TWFR-GMM is the core of our submission that achieved the 3rd place in DCASE 2022 Challenge Task2.Comment: To appear at ICASSP 202

Polymer Pen Lithography Using Dual-Elastomer Tip Arrays

Dual-elastomer tip arrays are developed as a simple and cost-effective approach to significantly improve the uniformity and precision of polymer pen lithography (PPL). Both experiment and mechanical simulation demonstrate that the hard-apex, soft-base tip structure of the dual-elastomer tip array leads to precise control of feature size and reduced variation among different tips over large areas through fine control of the tip deformation. The dual-elastomer tip array is believed to be readily applied to fabricate nano- and microstructures for fundamental study and applications such as bioassays, sensors, optical and electronic devices. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Vacuum level dependent photoluminescence in chemical vapor deposition-grown monolayer MoS 2

Abstract The stronger photoluminescence (PL) in chemical vapor deposition (CVD) grown monolayer MoS2 has been attributed to its high crystal quality compared with that in mechanically exfoliated (ME) crystal, which is contrary to the cognition that the ME crystal usually have better crystal quality than that of CVD grown one and it is expected with a better optical quality. In this report, the reason of abnormally strong PL spectra in CVD grown monolayer crystal is systematically investigated by studying the in-situ opto-electrical exploration at various environments for both of CVD and ME samples. High resolution transmission electron microscopy is used to investigate their crystal qualities. The stronger PL in CVD grown crystal is due to the high p-doping effect of adsorbates induced rebalance of exciton/trion emission. The first principle calculations are carried out to explore the interaction between adsorbates in ambient and defects sites in MoS2, which is consistent to the experimental phenomenon and further confirm our proposed mechanisms

Thermal treatment enhances the resisting exercise fatigue effect of Phyllanthus emblica L.: novel evidence from tannin conversion in vitro, metabolomics, and gut microbiota community analysis

Abstract Polyphenols are the main component of Phyllanthus emblica (PE). However, polyphenols are so easy to transform that it is unknown that how drying methods driven by heating affect the anti-fatigue effect of PE. This manuscript investigated the effects of five drying methods on the chemical composition transformation and anti-fatigue of PE, and discussed the action mechanism. The results suggested that the anti-fatigue effect of PE with hot-air-dried at 100 °C was the best, which was as 1.63 times as that with freeze-drying. Ellagic acid (EA) may be a key component of PE in anti-fatigue, and its mechanism of action may be related to regulating intestinal microbiota, protecting mitochondria, and regulating energy metabolism. This study first revealed the thermal transformation of polyphenols in PE, found the most effective strategy for enhancing the anti-fatigue function, and explores its action mechanism