Evolving Multi-Resolution Pooling CNN for Monaural Singing Voice Separation

Monaural Singing Voice Separation (MSVS) is a challenging task and has been studied for decades. Deep neural networks (DNNs) are the current state-of-the-art methods for MSVS. However, the existing DNNs are often designed manually, which is time-consuming and error-prone. In addition, the network architectures are usually pre-defined, and not adapted to the training data. To address these issues, we introduce a Neural Architecture Search (NAS) method to the structure design of DNNs for MSVS. Specifically, we propose a new multi-resolution Convolutional Neural Network (CNN) framework for MSVS namely Multi-Resolution Pooling CNN (MRP-CNN), which uses various-size pooling operators to extract multi-resolution features. Based on the NAS, we then develop an evolving framework namely Evolving MRP-CNN (E-MRP-CNN), by automatically searching the effective MRP-CNN structures using genetic algorithms, optimized in terms of a single-objective considering only separation performance, or multi-objective considering both the separation performance and the model complexity. The multi-objective E-MRP-CNN gives a set of Pareto-optimal solutions, each providing a trade-off between separation performance and model complexity. Quantitative and qualitative evaluations on the MIR-1K and DSD100 datasets are used to demonstrate the advantages of the proposed framework over several recent baselines

Guiding AMR Parsing with Reverse Graph Linearization

Abstract Meaning Representation (AMR) parsing aims to extract an abstract semantic graph from a given sentence. The sequence-to-sequence approaches, which linearize the semantic graph into a sequence of nodes and edges and generate the linearized graph directly, have achieved good performance. However, we observed that these approaches suffer from structure loss accumulation during the decoding process, leading to a much lower F1-score for nodes and edges decoded later compared to those decoded earlier. To address this issue, we propose a novel Reverse Graph Linearization (RGL) enhanced framework. RGL defines both default and reverse linearization orders of an AMR graph, where most structures at the back part of the default order appear at the front part of the reversed order and vice versa. RGL incorporates the reversed linearization to the original AMR parser through a two-pass self-distillation mechanism, which guides the model when generating the default linearizations. Our analysis shows that our proposed method significantly mitigates the problem of structure loss accumulation, outperforming the previously best AMR parsing model by 0.8 and 0.5 Smatch scores on the AMR 2.0 and AMR 3.0 dataset, respectively. The code are available at https://github.com/pkunlp-icler/AMR_reverse_graph_linearization.Comment: Findings of EMNLP202

Electrotunable liquid sulfur microdroplets.

Manipulating liquids with tunable shape and optical functionalities in real time is important for electroactive flow devices and optoelectronic devices, but remains a great challenge. Here, we demonstrate electrotunable liquid sulfur microdroplets in an electrochemical cell. We observe electrowetting and merging of sulfur droplets under different potentiostatic conditions, and successfully control these processes via selective design of sulfiphilic/sulfiphobic substrates. Moreover, we employ the electrowetting phenomena to create a microlens based on the liquid sulfur microdroplets and tune its characteristics in real time through changing the shape of the liquid microdroplets in a fast, repeatable, and controlled manner. These studies demonstrate a powerful in situ optical battery platform for unraveling the complex reaction mechanism of sulfur chemistries and for exploring the rich material properties of the liquid sulfur, which shed light on the applications of liquid sulfur droplets in devices such as microlenses, and potentially other electrotunable and optoelectronic devices

High-stability dead-end anode proton exchange membrane fuel cells by purge optimization

The crossover of nitrogen and oxygen from cathode to anode aggravates the non-uniformity inside dead-end anode proton exchange membrane fuel cell (DEA-PEMFC), inducing some other effects, such as carbon corrosion, to cause irreversible damage to catalyst. Therefore, developing a purge strategy according to the non-uniformity is necessary to improve its stability. In this study, the effects of operating parameters on the uneven electrical-thermal-water performance are investigated based on a three-dimensional transient model of DEA-PEMFC. Afterwards, a purge optimization is carried out based on the uneven distribution of field variables. The results show that the calculated standard deviation (STDEV) of overvoltage is reduced first and then increased quickly for all the cases. Therefore, the purge should be started when the STDEV approaches the minimum value, to avoid the irreversible damage to DEA-PEMFC, achieving high-stability output performance meanwhile. On this basis, the purge interval is optimized to 100 s, which is suitable for almost all the discussed cases. The purge duration is reduced to 0.2 s. In this situation, the minimum voltage is decreased by about 0.95% compared with the maximum value, indicating a good voltage stability. This study is beneficial to provide guidance for the efficient and long-term operation of DEA-PEMFC

Genetic Basis of Virulence Attenuation Revealed by Comparative Genomic Analysis of Mycobacterium tuberculosis Strain H37Ra versus H37Rv

Tuberculosis, caused by Mycobacterium tuberculosis, remains a leading infectious disease despite the availability of chemotherapy and BCG vaccine. The commonly used avirulent M. tuberculosis strain H37Ra was derived from virulent strain H37 in 1935 but the basis of virulence attenuation has remained obscure despite numerous studies. We determined the complete genomic sequence of H37Ra ATCC25177 and compared that with its virulent counterpart H37Rv and a clinical isolate CDC1551. The H37Ra genome is highly similar to that of H37Rv with respect to gene content and order but is 8,445 bp larger as a result of 53 insertions and 21 deletions in H37Ra relative to H37Rv. Variations in repetitive sequences such as IS6110 and PE/PPE/PE-PGRS family genes are responsible for most of the gross genetic changes. A total of 198 single nucleotide variations (SNVs) that are different between H37Ra and H37Rv were identified, yet 119 of them are identical between H37Ra and CDC1551 and 3 are due to H37Rv strain variation, leaving only 76 H37Ra-specific SNVs that affect only 32 genes. The biological impact of missense mutations in protein coding sequences was analyzed in silico while nucleotide variations in potential promoter regions of several important genes were verified by quantitative RT-PCR. Mutations affecting transcription factors and/or global metabolic regulations related to in vitro survival under aging stress, and mutations affecting cell envelope, primary metabolism, in vivo growth as well as variations in the PE/PPE/PE-PGRS family genes, may underlie the basis of virulence attenuation. These findings have implications not only for improved understanding of pathogenesis of M. tuberculosis but also for development of new vaccines and new therapeutic agents

Practical and Asymmetric Synthesis of Apremilast Using Ellman’s Sulfinamide as a Chiral Auxiliary

Herein, we described a new protocol for the asymmetric synthesis of apremilast using tert-butanesulfinamide as a chiral auxiliary. This synthetic route consisted of four steps starting from the commercially available 3-hydroxy-4-methoxybenzaldehyde, and apremilast was accordingly obtained in an overall 56% yield and with 95.5% ee

Identification of Prostate Cancer-Associated Genomic Alterations by Analyzing Variant Frequencies, Functional Effects, and Protein Interactions

With the ever-increasing varieties of sequencing techniques, the volume and scope of genomic data are explosively expanded, offering unparalleled opportunities for researchers to study gene-disease associations, identify biomarkers, and thus develop more effective diagnostic and therapeutic strategies. In this project, I have developed a computational workflow and a new scoring scheme, which combine statistical frequency-based analyses with two well-established functional effect prediction tools FATHMM and PROVEAN, to evaluate nonsynonymous GSVs and identify potential cancer-related protein-coding genes for downstream enrichment and protein-protein interaction (PPI) studies.This method has been applied to process a collection of 503 whole exome sequencing datasets for patients with prostate cancer (PrCa). The datasets were downloaded from The Cancer Genome Atlas as variant call format (VCF) files containing GSV information for paired tumor and normal samples. Exploratory statistics revealed unusually high level of transitions G→A and C→T among cancer samples. Furthermore, 5 GSVs were found significantly associated with the disease. Among 61 high-scoring genes identified by our scoring scheme, 27 were found by PPI analysis to have degrees of connection ≥ 4 with well-known PrCa-related genes. While 18 of them are reportedly associated with PrCa, 9 genes (TRRAP, EPHB1, HERC2, MCM3, SPTA1, SALL1, HERC1, TTN, and MYH6) have not been previously documented in relation to PrCa. Their potential roles in PrCa could be investigated by further bioinformatics and wet-lab studies

Identification Of Prostate Cancer-Associated Genomic Alterations By Analyzing Variant Frequencies, Functional Effects, And Protein Interactions

With the ever-increasing varieties of sequencing techniques, the volume and scope of genomic data are explosively expanded, offering unparalleled opportunities for researchers to study gene-disease associations, identify biomarkers, and thus develop more effective diagnostic and therapeutic strategies. In this project, I have developed a computational workflow and a new scoring scheme, which combine statistical frequency-based analyses with two well-established functional effect prediction tools FATHMM and PROVEAN, to evaluate nonsynonymous GSVs and identify potential cancer-related protein-coding genes for downstream enrichment and protein-protein interaction (PPI) studies. This method has been applied to process a collection of 503 whole exome sequencing datasets for patients with prostate cancer (PrCa). The datasets were downloaded from The Cancer Genome Atlas as variant call format (VCF) files containing GSV information for paired tumor and normal samples. Exploratory statistics revealed unusually high level of transitions G→A and C→T among cancer samples. Furthermore, 5 GSVs were found significantly associated with the disease. Among 61 high-scoring genes identified by our scoring scheme, 27 were found by PPI analysis to have degrees of connection ≥ 4 with well-known PrCa-related genes. While 18 of them are reportedly associated with PrCa, 9 genes (TRRAP, EPHB1, HERC2, MCM3, SPTA1, SALL1, HERC1, TTN, and MYH6) have not been previously documented in relation to PrCa. Their potential roles in PrCa could be investigated by further bioinformatics and wet-lab studies

Regio and diastereoselective synthesis of allylic amine through hydrocupration of terminal alkynes

Thesis (Master's)--University of Washington, 2023Allylic amines play a crucial role in organic synthesis, owing to their versatility and unique chemical reactivity resulting from the allylic double bond. The significance of them is further evident in their incorporation as structural backbones in natural products and drug molecules. Allylic amines can be synthesized using various strategies including C-N bond formation via allylic substitution, C-H bond amination, and C-C bond formation by adding alkenyl metal to imine or reductive cross-coupling reactions. Herein, we develop an innovative approach to allylic amine synthesis based on copper-catalyzed stereoselective reductive cross-coupling between alkynes and α-Cl phthalimide. We demonstrate that the reaction is compatible with various functional groups under mild conditions. Interestingly, different from our proposed mechanism, the preliminary mechanistic study shows that the process does not involve the generation of a radical at the α-nitrogen position