HD-DEMUCS: General Speech Restoration with Heterogeneous Decoders

This paper introduces an end-to-end neural speech restoration model, HD-DEMUCS, demonstrating efficacy across multiple distortion environments. Unlike conventional approaches that employ cascading frameworks to remove undesirable noise first and then restore missing signal components, our model performs these tasks in parallel using two heterogeneous decoder networks. Based on the U-Net style encoder-decoder framework, we attach an additional decoder so that each decoder network performs noise suppression or restoration separately. We carefully design each decoder architecture to operate appropriately depending on its objectives. Additionally, we improve performance by leveraging a learnable weighting factor, aggregating the two decoder output waveforms. Experimental results with objective metrics across various environments clearly demonstrate the effectiveness of our approach over a single decoder or multi-stage systems for general speech restoration task.Comment: Accepted by INTERSPEECH 202

Gut Microbial Metabolites Induce Changes in Circadian Oscillation of Clock Gene Expression in the Mouse Embryonic Fibroblasts

Circadian rhythm is an endogenous oscillation of about 24-h period in many physiological processes and behaviors. This daily oscillation is maintained by the molecular clock machinery with transcriptional-translational feedback loops mediated by clock genes including Period2 (Per2) and Bmal1. Recently, it was revealed that gut microbiome exerts a significant impact on the circadian physiology and behavior of its host; however, the mechanism through which it regulates the molecular clock has remained elusive. 3-(4-hydroxyphenyl)propionic acid (4-OH-PPA) and 3-phenylpropionic acid (PPA) are major metabolites exclusively produced by Clostridium sporogenes and may function as unique chemical messengers communicating with its host. In the present study, we examined if two C. sporogenes-derived metabolites can modulate the oscillation of mammalian molecular clock. Interestingly, 4-OH-PPA and PPA increased the amplitude of both PER2 and Bmal1 oscillation in a dosedependent manner following their administration immediately after the nadir or the peak of their rhythm. The phase of PER2 oscillation responded differently depending on the mode of administration of the metabolites. In addition, using an organotypic slice culture ex vivo, treatment with 4-OH-PPA increased the amplitude and lengthened the period of PER2 oscillation in the suprachiasmatic nucleus and other tissues. In summary, two C. sporogenes-derived metabolites are involved in the regulation of circadian oscillation of Per2 and Bmal1 clock genes in the host's peripheral and central clock machineries.1

Fast synthesis of platinum nanopetals and nanospheres for highly-sensitive non-enzymatic detection of glucose and selective sensing of ions

Novel methods to obtain Pt nanostructured electrodes have raised particular interest due to their high performance in electrochemistry. Several nanostructuration methods proposed in the literature use costly and bulky equipment or are time-consuming due to the numerous steps they involve. Here, Pt nanostructures were produced for the first time by one-step template-free electrodeposition on Pt bare electrodes. The change in size and shape of the nanostructures is proven to be dependent on the deposition parameters and on the ratio between sulphuric acid and chloride-complexes (i.e., hexachloroplatinate or tetrachloroplatinate). To further improve the electrochemical properties of electrodes, depositions of Pt nanostructures on previously synthesised Pt nanostructures are also performed. The electroactive surface areas exhibit a two order of magnitude improvement when Pt nanostructures with the smallest size are used. All the biosensors based on Pt nanostructures and immobilised glucose oxidase display higher sensitivity as compared to bare Pt electrodes. Pt nanostructures retained an excellent electrocatalytic activity towards the direct oxidation of glucose. Finally, the nanodeposits were proven to be an excellent solid contact for ion measurements, significantly improving the time-stability of the potential. The use of these new nanostructured coatings in electrochemical sensors opens new perspectives for multipanel monitoring of human metabolism

Assessment of Pain Onset and Maximum Bearable Pain Thresholds in Physical Contact Situations

With the development of robot technology, robot utilization is expanding in industrial fields and everyday life. To employ robots in various fields wherein humans and robots share the same space, human safety must be guaranteed in the event of a human–robot collision. Therefore, criteria and limitations of safety need to be defined and well clarified. In this study, we induced mechanical pain in humans through quasi-static contact by an algometric device (at 29 parts of the human body). A manual apparatus was developed to induce and monitor a force and pressure. Forty healthy men participated voluntarily in the study. Physical quantities were classified based on pain onset and maximum bearable pain. The overall results derived from the trials pertained to the subjective concept of pain, which led to considerable inter-individual variation in the onset and threshold of pain. Based on the results, a quasi-static contact pain evaluation method was established, and biomechanical safety limitations on forces and pressures were formulated. The pain threshold attributed to quasi-static contact can serve as a safety standard for the robots employed

Ultradian Rhythms in the Hypothalamic Arcuate Nucleus Kisspeptin Neurons and Developmental Processes

Numerous physiological processes in nature have multiple oscillations within 24 h, that is, ultradian rhythms. Compared to the circadian rhythm, which has a period of approximately one day, these short oscillations range from seconds to hours, and the mechanisms underlying ultradian rhythms remain largely unknown. This review aims to explore and emphasize the implications of ultradian rhythms and their underlying regulations. Reproduction and developmental processes show ultradian rhythms, and these physiological systems can be regulated by short biological rhythms. Specifically, we recently uncovered synchronized calcium oscillations in the organotypic culture of hypothalamic arcuate nucleus (ARN) kisspeptin neurons that regulate reproduction. Synchronized calcium oscillations were dependent on voltage-gated ion channel-mediated action potentials and were repressed by chemogenetic inhibition, suggesting that the network within the ARN and between the kisspeptin population mediates the oscillation. This minireview describes that ultradian rhythms are a general theme that underlies biological features, with special reference to calcium oscillations in the hypothalamic ARN from a developmental perspective. We expect that more attention to these oscillations might provide insight into physiological or developmental mechanisms, since many oscillatory features in nature still remain to be explored.1

Calibration of Visco-Hyperelastic Model for Tensile Behavior of Porcine Skin

Uniaxial tensile tests were performed on porcine skin to investigate the tensile stress-strain constitutive characteristic at qua-sistatic deformations using uniaxial tensile tests. Experimental results were then used to determine the parameters of the various constitutive model types for rubber, including the Mooney-Rivlin, Yeoh, Ogden, and others. The Prony series viscoelastic model was also calibrated based on the stress relaxation test. To investigate the calibrated constitutive equations (visco-hyperelastic), the falling impact test was conducted. From the viewpoint of the maximum impact load, the error was approximately 15.87%. Overall, the Ogden model predicted the experimental measurements most reasonably. The calibrated constitutive model is expected to be of practical use in describing the mechanical properties of porcine skin

Generalization of U-Net Semantic Segmentation for Forest Change Detection in South Korea Using Airborne Imagery

Forest change detection is essential to prevent the secondary damage occurring by landslides causing profound results to the environment, ecosystem, and human society. The remote sensing technique is a solid candidate for identifying the spatial distribution of the forest. Even though the acquiring and processing of remote sensing images are costly and time- and labor-consuming, the development of open source data platforms relieved these burdens by providing free imagery. The open source images also accelerate the generation of algorithms with large datasets. Thus, this study evaluated the generalizability of forest change detection by using open source airborne images and the U-Net model. U-Net model is convolutional deep learning architecture to effectively extract the image features for semantic segmentation tasks. The airborne and tree annotation images of the capital area in South Korea were processed for building U-Net input, while the pre-trained U-Net structure was adopted and fine-tuned for model training. The U-Net model provided robust results of the segmentation that classified forest and non-forest regions, having pixel accuracies, F1 score, and intersection of union (IoU) of 0.99, 0.97, and 0.95, respectively. The optimal epoch and excluded ambiguous label contributed to maintaining virtuous segmentation of the forest region. In addition, this model could correct the false label images because of showing exact classification results when the training labels were incorrect. After that, by using the open map service, the well-trained U-Net model classified forest change regions of Chungcheong from 2009 to 2016, Gangwon from 2010 to 2019, Jeolla from 2008 to 2013, Gyeongsang from 2017 to 2019, and Jeju Island from 2008 to 2013. That is, the U-Net was capable of forest change detection in various regions of South Korea at different times, despite the training on the model with only the images of the capital area. Overall, this study demonstrated the generalizability of a deep learning model for accurate forest change detection

Development of Polymersomes Co-Delivering Doxorubicin and Melittin to Overcome Multidrug Resistance

Multidrug resistance (MDR) is one of the major barriers in chemotherapy. It is often related to the overexpression of efflux receptors such as P-glycoprotein (P-gp). Overexpressed efflux receptors inhibit chemotherapeutic efficacy by pumping out intracellularly delivered anticancer drugs. In P-gp-mediated MDR-related pathways, PI3K/Akt and NF-kB pathways are commonly activated signaling pathways, but these pathways are downregulated by melittin, a main component of bee venom. In this study, a polymersome based on a poly (lactic acid) (PLA)-hyaluronic acid (HA) (20k-10k) di-block copolymer and encapsulating melittin and doxorubicin was developed to overcome anticancer resistance and enhance chemotherapeutic efficacy. Through the simultaneous delivery of doxorubicin and melittin, PI3K/Akt and NF-κB pathways could be effectively inhibited, thereby downregulating P-gp and successfully enhancing chemotherapeutic efficacy. In conclusion, a polymersome carrying an anticancer drug and melittin could overcome MDR by regulating P-gp overexpression pathways

Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting

In this paper, we propose a novel end-to-end user-defined keyword spotting method that utilizes linguistically corresponding patterns between speech and text sequences. Unlike previous approaches requiring speech keyword enrollment, our method compares input queries with an enrolled text keyword sequence. To place the audio and text representations within a common latent space, we adopt an attention-based cross-modal matching approach that is trained in an end-to-end manner with monotonic matching loss and keyword classification loss. We also utilize a de-noising loss for the acoustic embedding network to improve robustness in noisy environments. Additionally, we introduce the LibriPhrase dataset, a new short-phrase dataset based on LibriSpeech for efficiently training keyword spotting models. Our proposed method achieves competitive results on various evaluation sets compared to other single-modal and cross-modal baselines.Comment: Accepted to Interspeech 202

Development of Polymersomes Co-Delivering Doxorubicin and Melittin to Overcome Multidrug Resistance

Multidrug resistance (MDR) is one of the major barriers in chemotherapy. It is often related to the overexpression of efflux receptors such as P-glycoprotein (P-gp). Overexpressed efflux receptors inhibit chemotherapeutic efficacy by pumping out intracellularly delivered anticancer drugs. In P-gp-mediated MDR-related pathways, PI3K/Akt and NF-kB pathways are commonly activated signaling pathways, but these pathways are downregulated by melittin, a main component of bee venom. In this study, a polymersome based on a poly (lactic acid) (PLA)-hyaluronic acid (HA) (20k-10k) di-block copolymer and encapsulating melittin and doxorubicin was developed to overcome anticancer resistance and enhance chemotherapeutic efficacy. Through the simultaneous delivery of doxorubicin and melittin, PI3K/Akt and NF-κB pathways could be effectively inhibited, thereby downregulating P-gp and successfully enhancing chemotherapeutic efficacy. In conclusion, a polymersome carrying an anticancer drug and melittin could overcome MDR by regulating P-gp overexpression pathways