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  1. Article: Fabrication of Robust and Effective Oil/Water Separating Superhydrophobic Textile Coatings.

    Kao, Li-Heng / Lin, Wei-Chen / Huang, Chao-Wei / Tsai, Ping-Szu

    Membranes

    2023  Volume 13, Issue 4

    Abstract: A superhydrophobic (SH) surface is typically constructed by combining a low-surface-energy substance and a high-roughness microstructure. Although these surfaces have attracted considerable attention for their potential applications in oil/water ... ...

    Abstract A superhydrophobic (SH) surface is typically constructed by combining a low-surface-energy substance and a high-roughness microstructure. Although these surfaces have attracted considerable attention for their potential applications in oil/water separation, self-cleaning, and anti-icing devices, fabricating an environmentally friendly superhydrophobic surface that is durable, highly transparent, and mechanically robust is still challenging. Herein, we report a facile painting method to fabricate a new micro/nanostructure containing ethylenediaminetetraacetic acid/poly(dimethylsiloxane)/fluorinated SiO
    Language English
    Publishing date 2023-03-31
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2614641-1
    ISSN 2077-0375
    ISSN 2077-0375
    DOI 10.3390/membranes13040401
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: PLM-ICD

    Huang, Chao-Wei / Tsai, Shang-Chi / Chen, Yun-Nung

    Automatic ICD Coding with Pretrained Language Models

    2022  

    Abstract: Automatically classifying electronic health records (EHRs) into diagnostic codes has been challenging to the NLP community. State-of-the-art methods treated this problem as a multilabel classification problem and proposed various architectures to model ... ...

    Abstract Automatically classifying electronic health records (EHRs) into diagnostic codes has been challenging to the NLP community. State-of-the-art methods treated this problem as a multilabel classification problem and proposed various architectures to model this problem. However, these systems did not leverage the superb performance of pretrained language models, which achieved superb performance on natural language understanding tasks. Prior work has shown that pretrained language models underperformed on this task with the regular finetuning scheme. Therefore, this paper aims at analyzing the causes of the underperformance and developing a framework for automatic ICD coding with pretrained language models. We spotted three main issues through the experiments: 1) large label space, 2) long input sequences, and 3) domain mismatch between pretraining and fine-tuning. We propose PLMICD, a framework that tackles the challenges with various strategies. The experimental results show that our proposed framework can overcome the challenges and achieves state-of-the-art performance in terms of multiple metrics on the benchmark MIMIC data. The source code is available at https://github.com/MiuLab/PLM-ICD

    Comment: Accepted to the ClinicalNLP 2022 workshop
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2022-07-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: Adapting Pretrained Transformer to Lattices for Spoken Language Understanding

    Huang, Chao-Wei / Chen, Yun-Nung

    2020  

    Abstract: Lattices are compact representations that encode multiple hypotheses, such as speech recognition results or different word segmentations. It is shown that encoding lattices as opposed to 1-best results generated by automatic speech recognizer (ASR) ... ...

    Abstract Lattices are compact representations that encode multiple hypotheses, such as speech recognition results or different word segmentations. It is shown that encoding lattices as opposed to 1-best results generated by automatic speech recognizer (ASR) boosts the performance of spoken language understanding (SLU). Recently, pretrained language models with the transformer architecture have achieved the state-of-the-art results on natural language understanding, but their ability of encoding lattices has not been explored. Therefore, this paper aims at adapting pretrained transformers to lattice inputs in order to perform understanding tasks specifically for spoken language. Our experiments on the benchmark ATIS dataset show that fine-tuning pretrained transformers with lattice inputs yields clear improvement over fine-tuning with 1-best results. Further evaluation demonstrates the effectiveness of our methods under different acoustic conditions. Our code is available at https://github.com/MiuLab/Lattice-SLU

    Comment: ASRU 2019
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence
    Subject code 410
    Publishing date 2020-11-02
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Learning Spoken Language Representations with Neural Lattice Language Modeling

    Huang, Chao-Wei / Chen, Yun-Nung

    2020  

    Abstract: Pre-trained language models have achieved huge improvement on many NLP tasks. However, these methods are usually designed for written text, so they do not consider the properties of spoken language. Therefore, this paper aims at generalizing the idea of ... ...

    Abstract Pre-trained language models have achieved huge improvement on many NLP tasks. However, these methods are usually designed for written text, so they do not consider the properties of spoken language. Therefore, this paper aims at generalizing the idea of language model pre-training to lattices generated by recognition systems. We propose a framework that trains neural lattice language models to provide contextualized representations for spoken language understanding tasks. The proposed two-stage pre-training approach reduces the demands of speech data and has better efficiency. Experiments on intent detection and dialogue act recognition datasets demonstrate that our proposed method consistently outperforms strong baselines when evaluated on spoken inputs. The code is available at https://github.com/MiuLab/Lattice-ELMo.

    Comment: Published in ACL 2020 as a short paper
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2020-07-06
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article: Photocatalytic degradation of methylene blue by UV‐assistant TiO2 and natural sericite composites

    Huang, Chao‐Wei / Wu, Min‐Chien

    Journal of chemical technology and biotechnology. 2020 Oct., v. 95, no. 10

    2020  

    Abstract: BACKGROUND: In order to prepare an environmental‐friendly photocatalyst, natural mineral sericite is used as the substrate of photocatalysts. In this study, the TiO₂‐sericite composite materials are synthesized by a facile sol‐gel process, followed via a ...

    Abstract BACKGROUND: In order to prepare an environmental‐friendly photocatalyst, natural mineral sericite is used as the substrate of photocatalysts. In this study, the TiO₂‐sericite composite materials are synthesized by a facile sol‐gel process, followed via a calcination treatment that can improve the crystallinity of the nano‐sized TiO₂. The prepared composites are characterized by XRD, Raman, FTIR, UV‐vis, SEM, and BETanalysis. The effects of the molecular ratio of TiO₂ to sericite and the calcination temperature are also examined. RESULTS: Sericite is not only served as a substrate for nano‐sized TiO₂ to fabricate the micro‐sized composite materials but also affect the formation of different crystalliniteTiO₂. The characteristic results show that the addition of sericite can stabilize the crystal phase of TiO₂; therefore, the sericite can maintain the crystalline anatase of TiO₂ even after the calcination at 700 °C and 900 °C. Accordingly, the adsorption test and the photocatalytic degradation of methylene blue are conducted to verify the photocatalytic performance of the TiO₂‐sericite composite materials. It indicates that the synergetic effect of TiO₂‐sericite composites can facilitate the photocatalytic degradation of TiO₂ accompanied by the initial adsorption of methylene blue by sericite. Based on the presence of various radicals, including ·OH, ·O₂⁻, and ¹O₂, the mechanism of photocatalytic degradation of methylene blue via TiO₂‐sericite composites are successfully proposed. CONCLUSION: The excellent activity reveals that TiO₂‐sericite composites are with potential employed as ecological‐friendly photocatalysts in the degradation of pollutants. © 2020 Society of Chemical Industry
    Keywords adsorption ; biotechnology ; composite materials ; crystal structure ; degradation ; free radicals ; methylene blue ; mica ; photocatalysis ; photocatalysts ; pollutants ; sol-gel processing ; synergism ; temperature ; titanium dioxide
    Language English
    Dates of publication 2020-10
    Size p. 2715-2722.
    Publishing place John Wiley & Sons, Ltd.
    Document type Article
    Note NAL-light ; JOURNAL ARTICLE
    ZDB-ID 1479465-2
    ISSN 1097-4660 ; 0268-2575
    ISSN (online) 1097-4660
    ISSN 0268-2575
    DOI 10.1002/jctb.6392
    Database NAL-Catalogue (AGRICOLA)

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  6. Book ; Online: Learning ASR-Robust Contextualized Embeddings for Spoken Language Understanding

    Huang, Chao-Wei / Chen, Yun-Nung

    2019  

    Abstract: Employing pre-trained language models (LM) to extract contextualized word representations has achieved state-of-the-art performance on various NLP tasks. However, applying this technique to noisy transcripts generated by automatic speech recognizer (ASR) ...

    Abstract Employing pre-trained language models (LM) to extract contextualized word representations has achieved state-of-the-art performance on various NLP tasks. However, applying this technique to noisy transcripts generated by automatic speech recognizer (ASR) is concerned. Therefore, this paper focuses on making contextualized representations more ASR-robust. We propose a novel confusion-aware fine-tuning method to mitigate the impact of ASR errors to pre-trained LMs. Specifically, we fine-tune LMs to produce similar representations for acoustically confusable words that are obtained from word confusion networks (WCNs) produced by ASR. Experiments on the benchmark ATIS dataset show that the proposed method significantly improves the performance of spoken language understanding when performing on ASR transcripts. Our source code is available at https://github.com/MiuLab/SpokenVec

    Comment: ICASSP 2020
    Keywords Computer Science - Computation and Language ; Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Audio and Speech Processing
    Publishing date 2019-09-24
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Book ; Online: Controllable User Dialogue Act Augmentation for Dialogue State Tracking

    Lai, Chun-Mao / Hsu, Ming-Hao / Huang, Chao-Wei / Chen, Yun-Nung

    2022  

    Abstract: Prior work has demonstrated that data augmentation is useful for improving dialogue state tracking. However, there are many types of user utterances, while the prior method only considered the simplest one for augmentation, raising the concern about poor ...

    Abstract Prior work has demonstrated that data augmentation is useful for improving dialogue state tracking. However, there are many types of user utterances, while the prior method only considered the simplest one for augmentation, raising the concern about poor generalization capability. In order to better cover diverse dialogue acts and control the generation quality, this paper proposes controllable user dialogue act augmentation (CUDA-DST) to augment user utterances with diverse behaviors. With the augmented data, different state trackers gain improvement and show better robustness, achieving the state-of-the-art performance on MultiWOZ 2.1

    Comment: 9 pages, 4 figures, accepted to sigdial 2022
    Keywords Computer Science - Computation and Language
    Publishing date 2022-07-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article: Identification of Molecular Profile of Ear Fibroblasts Derived from Spindle-Transferred Holstein Cattle with Ooplasts from Taiwan Yellow Cattle under Heat Stress.

    Lee, Yu-Ju / Lee, Jai-Wei / Huang, Chao-Wei / Yang, Kuo-Tai / Peng, Shao-Yu / Yu, Chi / Lee, Yen-Hua / Lai, I-Ling / Shen, Perng-Chih

    Animals : an open access journal from MDPI

    2024  Volume 14, Issue 9

    Abstract: Global warming has a significant impact on the dairy farming industry, as heat stress causes reproductive endocrine imbalances and leads to substantial economic losses, particularly in tropical-subtropical regions. The Holstein breed, which is widely ... ...

    Abstract Global warming has a significant impact on the dairy farming industry, as heat stress causes reproductive endocrine imbalances and leads to substantial economic losses, particularly in tropical-subtropical regions. The Holstein breed, which is widely used for dairy production, is highly susceptible to heat stress, resulting in a dramatic reduction in milk production during hot seasons. However, previous studies have shown that cells of cows produced from reconstructed embryos containing cytoplasm (o) from Taiwan yellow cattle (Y) have improved thermotolerance despite their nuclei (n) being derived from heat-sensitive Holstein cattle (H). Using spindle transfer (ST) technology, we successfully produced ST-Yo-Hn cattle and proved that the thermotolerance of their ear fibroblasts is similar to that of Y and significantly better than that of H (
    Language English
    Publishing date 2024-05-02
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2606558-7
    ISSN 2076-2615
    ISSN 2076-2615
    DOI 10.3390/ani14091371
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  9. Article ; Online: Rapid genotypic antibiotic susceptibility test using CRISPR-Cas12a for urinary tract infection.

    Chen, Juhong / Jiang, Fuguo / Huang, Chao-Wei / Lin, Liwei

    The Analyst

    2020  Volume 145, Issue 15, Page(s) 5226–5231

    Abstract: The current clinical protocol to conduct a bacterial antibiotic susceptibility test (AST) requires at least 18 hours, and cannot be accomplished during a single visit for patients. Here, a new method based on the technique of CRISPR-Cas12a is utilized to ...

    Abstract The current clinical protocol to conduct a bacterial antibiotic susceptibility test (AST) requires at least 18 hours, and cannot be accomplished during a single visit for patients. Here, a new method based on the technique of CRISPR-Cas12a is utilized to accomplish a bacterial genotypic AST within one hour with good accuracy. Two amplification approaches are employed and compared: (1) enriching the bacterial concentration by culturing in growth media; and (2) amplifying target DNA from raw samples by recombinase polymerase amplification (RPA). The results show that CRISPR combined with RPA can rapidly and accurately provide a bacterial genotypic AST of urine samples with urinary tract infections for precise antibiotic treatment. As such, this technology could open a new class of rapid bacterial genotypic AST for various infectious diseases.
    MeSH term(s) Anti-Bacterial Agents/pharmacology ; Bacteria/genetics ; CRISPR-Cas Systems/genetics ; Clustered Regularly Interspaced Short Palindromic Repeats ; Humans ; Urinary Tract Infections/diagnosis ; Urinary Tract Infections/drug therapy
    Chemical Substances Anti-Bacterial Agents
    Language English
    Publishing date 2020-06-29
    Publishing country England
    Document type Journal Article
    ZDB-ID 210747-8
    ISSN 1364-5528 ; 0003-2654
    ISSN (online) 1364-5528
    ISSN 0003-2654
    DOI 10.1039/d0an00947d
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  10. Article ; Online: Single Nucleotide Polymorphisms of Immunity-Related Genes and Their Effects on Immunophenotypes in Different Pig Breeds.

    Chen, Ann Ying-An / Huang, Chao-Wei / Liu, Shyh-Hwa / Liu, An-Chi / Chaung, Hso-Chi

    Genes

    2021  Volume 12, Issue 9

    Abstract: Enhancing resistance and tolerance to pathogens remains an important selection objective in the production of livestock animals. Single nucleotide polymorphisms (SNPs) vary gene expression at the transcriptional level, influencing an individual's immune ... ...

    Abstract Enhancing resistance and tolerance to pathogens remains an important selection objective in the production of livestock animals. Single nucleotide polymorphisms (SNPs) vary gene expression at the transcriptional level, influencing an individual's immune regulation and susceptibility to diseases. In this study, we investigated the distribution of SNP sites in immune-related genes and their correlations with cell surface markers of immune cells within purebred (Taiwan black, Duroc, Landrace and Yorkshire) and crossbred (Landrace-Yorkshire) pigs. Thirty-nine SNPs of immune-related genes, including 11 cytokines, 5 chemokines and 23 Toll-like receptors (TLRs) (interferon-α and γ (IFN-α, γ), tumor necrosis factor-α (TNF-α), granulocyte-macrophage colony-stimulating factor (GM-CSF), Monocyte chemoattractant protein-1 (MCP-1) and TLR3, TLR4, TLR7, TLR8, and TLR9) were selected, and the percentages of positive cells with five cell surface markers of CD4, CD8, CD80/86, MHCI, and MHCII were analyzed. There were 28 SNPs that were significantly different among breeds, particularly between Landrace and Taiwan black. For instance, the frequency of SNP1 IFN-α -235A/G in Taiwan black and Landrace was 11.11% and 96.15%, respectively. In addition, 18 SNPs significantly correlated with the expression of cell surface markers, including CD4, CD8, CD80/86, and MHCII. The percentage of CD4+ (39.27%) in SNP33 TLR-8 543C/C was significantly higher than those in A/C (24.34%), at
    MeSH term(s) Animals ; Biomarkers ; Disease Resistance/genetics ; Genetic Predisposition to Disease ; Immunophenotyping ; Polymorphism, Single Nucleotide ; Selective Breeding ; Sus scrofa/blood ; Sus scrofa/genetics ; Sus scrofa/immunology
    Chemical Substances Biomarkers
    Language English
    Publishing date 2021-08-31
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2527218-4
    ISSN 2073-4425 ; 2073-4425
    ISSN (online) 2073-4425
    ISSN 2073-4425
    DOI 10.3390/genes12091377
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