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Novel visible-light-active P-g-CN-based α-Bi2O3/WO3 ternary photocatalysts with a dual Z-scheme heterostructure for the efficient decomposition of refractory ultraviolet filters and environmental hormones: Benzophenones

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Environmental Research 2023年 234卷

作者： Berekute, Abiyu Kerebo Yu, Kuo-Pin Chuang, Yi-Hsueh Brad Lin, Kun-Yi Andrew International Ph.D. Program in Environmental Science and Technology National Yang Ming Chiao Tung University Taipei11221 Taiwan Institute of Environmental and Occupational Health Sciences National Yang Ming Chiao Tung University Taipei11221 Taiwan Institute of Environmental Engineering National Yang Ming Chiao Tung University Hsinchu City30010 Taiwan Department of Environmental Engineering and Innovation and Development Center of Sustainable Agriculture & Research Center of Sustainable Energy and Nano Technology National Chung Hsing University 250 Kuo-Kuang Road Taichung Taiwan Department of Chemistry College of Natural and Computational Sciences Arba Minch University Arbaminch Ethiopia

The ubiquitous and refractory benzophenone (BP)-type ultraviolet filters, which are also endocrine disruptors, were commonly detected in the aquatic matrix and could not be efficiently removed by conventional wastewater treatment processes, thus causing extensive concern. Herein, a novel ternary nanocomposite, P-g-CN/α-Bi2O3/WO3 (P-gBW), was successfully fabricated by mixing cocalcinated components and applied to the decomposition of BP-type ultraviolet filters. The dual-Z-scheme heterostructure of P-gBW enhances visible-light absorption, efficiently facilitates separation and mobility, and prolongs the lifetime of photoinduced charge carriers via double charge transfer mechanisms. The optimum 95 wt% P-gBW exhibited excellent photocatalytic activity, degrading 96% 4-hydroxy benzophenone (4HBP) within 150 min and 93% 2,2′,4,4′-tetrahydroxybenzophenone (BP-2) within 100 min under visible-light illumination, respectively. The pseudo-first-order rate constant of 4HBP (1.15 h−1) was 6.8-, 3.1-, 3.3- and 2.2-fold higher than those of WO3, P-g-CN, α-Bi2O3, and P-g-CN/α-Bi2O3, respectively, while that of BP-2 (1.71 h−1) was 5.2-, 2.2-, 3.2- and 1.5-fold higher, respectively. The improved photocatalytic degradation was attributed to efficient photoinduced charge carrier separation and migration and prevented the recombination of electron holes, as verified by photoluminescence, transient photocurrent response, and electrochemical impedance spectroscopy. Trapping experiments, electron paramagnetic resonance, and band energy position indicated an efficient dual-Z-scheme heterostructure. © 2023 Elsevier Inc.

关键词： Tungsten compounds

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An Innovative Real-Time Cell Viability Analysis: A Cutting-Edge Flexible Bioimpedance Sensor

SSRN

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SSRN 2023年

作者： Chou, Hsin-Yu Ching, Congo Tak-Shing Huang, Hui-Xuan phan, Thien Luan Wang, Hui-Min david Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Ph.D. Program in Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung402 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung40227 Taiwan Department of Electrical Engineering National Chi Nan University Nantou54561 Taiwan Department of Physic and Electronic Engineering Faculty of Physic and Engineering Physic Vietnam National University Ho Chi Minh City University of Science Viet Nam Graduate Institute of Medicine College of Medicine Kaohsiung Medical University Kaohsiung807 Taiwan Department of Medical Laboratory Science and Biotechnology China Medical University Taichung City404 Taiwan

There are many compounds to be used to treat cancer but still only 20% of proposed anticancer agents have been commercialized after clinical trials due to serious side effects and unsatisfactory results. To screen potential drugs precisely and quickly, this study develops a flexible bioimpedance sensor. The sensor is positive to detect the half maximal inhibitory concentration (IC50) of drugs real-time by analyzing phase angle changes during cell mortality. The best results are achieved using a probe separation of A12B34 at logarithmic frequencies of 163 Hz and 77.87 kHz. At these two frequencies, there is a linear relationship with the phase angle at 0% and 50% of the dead cells. dividing the phase angle at the two frequencies shows a 17.98% change in the phase angle, which allows self-correction and insensitivity to the number of cells. A custom phase angle measurement device is developed for detection at 163 Hz and 77.87 kHz, respectively. This study develops a novel sensor that is precise, fast and allows high throughput analysis to detect the inhibition of cancer in real-time. This sensor is an alternative to traditional chemical detection methods because it is faster, cheaper and more accurate. © 2023, The Authors. All rights reserved.

关键词： Chemical detection

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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction

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Scientific Reports 2025年第1期15卷 1-11页

作者： Huang, Kuo-Yang Hsu, Ying-Lin Chung, Che-Liang Chen, Huang-Chi Horng, Ming-Hwarng Lin, Ching-Hsiung Liu, Ching-Sen Xu, Jia-Lang Division of Chest Medicine Department of Internal Medicine Changhua Christian Hospital Changhua Taiwan Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan Ph.D. Program in Medical Biotechnology National Chung Hsing University Taichung Taiwan Institute of Statistics National Chung Hsing University Taichung Taiwan Division of Chest Medicine Department of Internal Medicine Yuanlin Christian Hospital Changhua Taiwan Department of Applied Mathematics National Chung Hsing University Taichung Taiwan Department of Computer Science and Information Engineering Chaoyang University of Technology Taichung Taiwan

The advancement of the Internet of Medical Things (IoMT) has revolutionized data acquisition and processing in critical care settings. Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. The system was deployed on edge devices to enable on-site inference with minimal latency. Among the evaluated models, Random Forest and XGBoost, the latter demonstrated superior predictive performance under both holdout and tenfold cross-validation schemes. Notably, the edge-based architecture reduced server data transmissions by 83.33%, while improving system stability, resilience, and sustainability. This paper details the model evaluation and demonstrates the feasibility and efficiency of edge intelligence in ventilator weaning decision support. © The Author(s) 2025.

关键词： Clinical decision support system Edge-computing Extubation Internet of medical things Machine learning

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Effects of molecular weight fraction on antioxidation capacity of rice protein hydrolysates

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Scientific Reports 2023年第1期13卷 1-11页

作者： Chen, Hui-Ju dai, Fan-Jhen Chen, Cheng-You Fan, Siao-Ling Zheng, Ji-Hong Chau, Chi-Fai Lin, Yung-Sheng Chen, Chin-Shuh Department of Food Science and Biotechnology National Chung Hsing University Taichung 402204 Taiwan Healthmate Co. Ltd Changhua 500016 Taiwan Ph.D. Program in Materials and Chemical Engineering National United University Miaoli 360302 Taiwan Department of Chemical Engineering National United University Miaoli 360302 Taiwan Institute of Food Safety and Health Risk Assessment National Yang Ming Chiao Tung University Taipei 112304 Taiwan

Rice protein was used as a starting material to provide rice protein hydrolysates (Rph) through enzyme-assisted extraction. Rph was further fractionated using ultrafiltration membrane (UF) and classified by molecular weight (MW;MW < 1 kda, MW 1–10 kda, and MW > 10 kda). Peptides with MW < 1 kda possessed superior antioxidant properties (p < 0.05). Therefore, UF demonstrated great efficacy in selectively separating antioxidant peptides. A Pearson correlation analysis revealed that the total phenolic concentration was correlated with oxygen radical absorbance capacity (ORAC;r = 0.999, p < 0.05). Amino acid contents had negative correlations with the scavenging activity (specifically, IC50) of 1,1-diphenyl-2-picrylhydrazyl and 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) radicals (r = − 0.986 to − 1.000). Reducing power was related to aromatic amino acid contents (r = 0.997, p < 0.05). In this study, enzymatic hydrolysis was discovered to be an effective method of extracting and isolating natural antioxidant proteins from broken rice, thus preserving the nutritional quality of rice and making those proteins more accessible in future applications. © 2023, The Author(s).

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In silico identification of a novel Cdc2-like kinase 2 (CLK2) inhibitor in triple negative breast cancer

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Protein science 2024年第6期33卷 e5004-e5004页

作者： Huang, Cheng-Chiao Hsu, Chia-Ming Chao, Min-Wu Hsu, Kai-Cheng Lin, Tony Eight Yen, Shih-Chung Tu, Huang-Ju Pan, Shiow-Lin Ph.D. Program for Cancer Molecular Biology and Drug Discovery College of Medical Science and Technology Taipei Medical University and Academia Sinica Taipei Taiwan Division of General Surgery Department of Surgery Taipei Medical University Hospital Taipei Taiwan Graduate Institute of Cancer Biology and Drug Discovery College of Medical Science and Technology Taipei Medical University Taipei Taiwan School of Medicine College of Medicine National Sun Yat-sen University Kaohsiung Taiwan Institute of Biopharmaceutical Sciences College of Medicine National Sun Yat-sen University Kaohsiung Taiwan The Doctoral Program of Clinical and Experimental Medicine College of Medicine National Sun Yat-sen University Kaohsiung Taiwan Ph.D. Program in Drug Discovery and Development Industry College of Pharmacy Taipei Medical University Taipei Taiwan TMU Research Center of Cancer Translational Medicine Taipei Medical University Taipei Taiwan TMU Research Center of Drug Discovery Taipei Medical University Taipei Taiwan Warshel Institute for Computational Biology The Chinese University of Hong Kong (Shenzhen) Guangdong Shenzhen China

dysregulation of RNA splicing processes is intricately linked to tumorigenesis in various cancers, especially breast cancer. Cdc2-like kinase 2 (CLK2), an oncogenic RNA-splicing kinase pivotal in breast cancer, plays a significant role, particularly in the context of triple-negative breast cancer (TNBC), a subtype marked by substantial medical challenges due to its low survival rates. In this study, we employed a structure-based virtual screening (SBVS) method to identify potential CLK2 inhibitors with novel chemical structures for treating TNBC. Compound 670551 emerged as a novel CLK2 inhibitor with a 50% inhibitory concentration (IC₅₀) value of 619.7 nM. Importantly, Compound 670551 exhibited high selectivity for CLK2 over other protein kinases. Functionally, this compound significantly reduced the survival and proliferation of TNBC cells. Results from a cell-based assay demonstrated that this inhibitor led to a decrease in RNA splicing proteins, such as SRSF4 and SRSF6, resulting in cell apoptosis. In summary, we identified a novel CLK2 inhibitor as a promising potential treatment for TNBC therapy. © 2024 The Authors. Protein science published by Wiley Periodicals LLC on behalf of The Protein Society.

关键词： CLK2 drug discovery kinase inhibitor structure-based virtual screening triple-negative breast cancer

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Export- and import-based economic models for predicting global trade using deep learning

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Expert Systems with Applications 2023年 218卷

作者： Yang, Cheng-Hong Lee, Cheng-Feng Chang, Po-Yin Department of Information Management Tainan University of Technology Tainan City710302 Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung80708 Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung80708 Taiwan Department of Business Administration National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Department of Computer Science and Information Engineering National Quemoy University Kinmen County 892 Taiwan

Forecasting global foreign trade is essential for developing government trade policies and management strategies for multinational corporations. However, achieving an accurate trade forecast is challenging because of the complex structural relationships between exports, imports and other economic variables. Many traditional forecasting models, such as time series, econometric, and machine learning, provide less accurate forecasts for trade data. This paper proposes an ensemble learning approach to improve forecasting performance by hybridizing the structural relationships between trade and deep learning models to predict foreign trade for ten major countries. The proposed method first establishes a cointegration relationship between exports and imports and their structural variables. The cointegrated models are then used to predict the future of trade, which is used as a benchmark model for comparison. A hybrid deep learning algorithm uses the cointegrated variables as input variables to predict trade data, and then are compared with time-series forecasts and economic structural models. The experimental results reveal that the ensemble learning method can achieve excellent forecasting performance for the tested periods of trade data. In most cases, the root means square error and mean absolute percentage error values are smaller than the time series and economic structural models. © 2023 Elsevier Ltd

关键词： Forecasting

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Emulating Neuromorphic and In-Memory Computing Utilizing defect engineering in 2d-Layered WSeOx and WSe2 Thin Films by Plasma-Assisted Selenization Process

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Advanced Functional Materials 2023年第38期33卷

作者： Chaudhary, Mayur Yang, Tzu-Yi Chen, Chieh-Ting Lai, Po-Chien Hsu, Yu-Chieh Peng, Yu-Ren Kumar, Ashish Lee, Chih-Hao Chueh, Yu-Lun Department of Materials Science and Engineering National Tsing-Hua University Hsinchu30013 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan College of Semiconductor Research National Tsing-Hua University Hsinchu30013 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan Department of Physics National Sun Yat-Sen University Kaohsiung80424 Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu30013 Taiwan

The neuromorphic and in-memory computing using memristors are promising for the building of the next generation computing systems. However, the diffusion dynamics of metal ions/atoms inside the switching medium impose variability in conducting filament (CF) formation, thus limiting their use in von-Neumann architecture. The precise modulation on the diffusion of metal ions/atoms and their reduction/oxidation probability holds promise to overcome the speed, size, and energy issues of present-day computers. Here, this study shows that the diffusion of metal ions can be modulated by defects inside the switching medium and confines metal filaments in a precise 1d channel. This filament confinement by the defect engineering leads to an anomalous switching mechanism with two interchangeable modes: unipolar threshold and bipolar modes. The variation between two modes can be modulated by controlling defects in the structures, leading to a uniform switching with low SET/RESET voltage variations of 17.3% and −17.6%, respectively. Moreover, the convolutional neural network is implemented to emulate synaptic plasticity and image recognition to achieve recognition accuracy of 87% due to a highly linear weight update, demonstrating its potential for in-memory computing. © 2023 Wiley-VCH GmbH.

关键词： Image recognition

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Faster Gröbner bases for Lie derivatives of OdE systems via monomial orderings

arXiv

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arXiv 2022年

作者： Bessonov, Mariya Ilmer, Ilia Konstantinova, Tatiana Ovchinnikov, Alexey Pogudin, Gleb Soto, Pedro Department of Mathematics CUNY NYC College of Technology New YorkNY United States Ph.D. Program in Computer Science CUNY Graduate Center New YorkNY United States Department of Mathematics CUNY Queens College New YorkNY United States LIX CNRS École Polytechnique Institute Polytechnique de Paris Paris France

Symbolic computation for systems of differential equations is often computationally expensive. Many practical differential models have a form of polynomial or rational OdE system with specified outputs. A basic symbolic approach to analyze these models is to compute and then symbolically process the polynomial system obtained by sufficiently many Lie derivatives of the output functions with respect to the vector field given by the OdE system. In this paper, we present a method for speeding up Gröbner basis computation for such a class of polynomial systems by using specific monomial ordering, including weights for the variables, coming from the structure of the OdE model. We provide empirical results that show improvement across different symbolic computing frameworks and apply the method to speed up structural identifiability analysis of OdE models. © 2022, CC BY-NC-SA.

关键词： Polynomials

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Frequency-responsive sorption of metal ions onto magnetic polyvinyltetrazole microspheres through a solenoid-wrapped glass tube with magnetophoresis force

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Journal of Water Process engineering 2024年 63卷

作者： Chen, Chih-Wei Wang, Chih-Feng Lu, Chien-Hsing Chen, Jem-Kun Department of Materials Science and Engineering National Taiwan University of Science and Technology 43 Sec. 4 Keelung Road Taipei 106 Taiwan Division of Neurosurgery Department of Surgery Chi Mei Medical Center Tainan 710 Taiwan Institute of Advanced Semiconductor Packaging and Testing National Sun Yat-sen University Kaohsiung 804 Taiwan Department of Obstetrics and Gynecology Taichung Veterans General Hospital Taichung 40705 Taiwan Institute of Biomedical Sciences Ph.D. Program in Translational Medicine Rong-Hsing Research Center for Translational Medicine National Chung-Hsing University Taichung 940227 Taiwan

Concentration gradient predominantly determining both the diffusion rate and the removal rate of pollutants by adsorbents. An external magnetophoresis force (FMEP) is introduced to accelerate the adsorption of metal i... 详细信息

Concentration gradient predominantly determining both the diffusion rate and the removal rate of pollutants by adsorbents. An external magnetophoresis force (F_MEP) is introduced to accelerate the adsorption of metal ions on adsorbents under an alternating magnetic field (AMF). A solenoid-wrapped glass tube (SWGT) containing adsorbents is designed to generate F_MEP in a flowing system. Magnetic Fe₃O₄ nanoparticles (MFs) are coated on polyacrylonitrile microspheres (PANs) as precursors (PAN@MFs) by Pickering emulsion polymerization. The core@shell polyvinyltetrazole@MFs (PVT@MFs) are obtained as the adsorbents after subsequent cyano-tetrazole conversion of PAN@MFs for the adsorption of Pb(II), Cu(II), and Cr(III) ions. The theoretical adsorption rate constants of these metal ions onto the PVT@MFs in the presence of F_MEP are enhanced by approximately three times under an AMF at 1 kHz and 87.6 G. At a high frequency of 10 kHz, hyperthermia occurs on the PVT@MFs, facilitating the desorption of metal ions from the adsorbents. Compared with reuse using an acidic solution, the magnetic PVT@MFs can be reused up to 10 times by switching the frequency of the AMF between 1 and 10 kHz. Our proposed platform provides a novel methodology with a magnetic adsorbent for metal ions to rapidly improve either the adsorption or desorption processes. © 2024

关键词： Adsorption rate Hyperthermia Magnetic susceptibility Polyvinyltetrazole

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Applications of engineered biochar in remediation of heavy metal(loid)s pollution from wastewater: Current perspectives toward sustainable development goals

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science of the Total Environment 2024年 926卷 171859页

作者： Tran, Thien-Khanh Huynh, Loan Nguyen, Hoang-Lam Nguyen, Minh-Ky Lin, Chitsan Hoang, Tuan-dung Hung, Nguyen Tri Q. Nguyen, X. Hoan Chang, S. Woong Nguyen, d. duc Advanced Applied Sciences Research Group Dong Nai Technology University Bien Hoa City76100 Viet Nam Faculty of Technology Dong Nai Technology University Bien Hoa City76100 Viet Nam Department of Civil Engineering McGill University Montreal Canada Faculty of Environment and Natural Resources Nong Lam University Hamlet 6 Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam Ph.D. Program in Maritime Science and Technology National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan School of Chemistry and Life Science Hanoi University of Science and Technology No. 1 Dai Co Viet Hai Ba Trung Hanoi100000 Viet Nam Vietnam National University Hanoi - School of Interdisciplinary Sciences and Arts 144 Xuan Thuy Street Cau Giay District Hanoi100000 Viet Nam Ho Chi Minh City University of Industry and Trade Ho Chi Minh City Viet Nam Department of Civil & Energy System Engineering Kyonggi University Suwon16227 Korea Republic of Institute of Applied Technology and Sustainable Development Nguyen Tat Thanh University Ho Chi Minh City700000 Viet Nam

Environmental pollution of heavy metal(loid)s (HMs) caused adverse impacts, has become one of the emerging concerns and challenges worldwide. Metal(loid)s can pose significant threats to living organisms even when present in trace levels within environmental matrices. Extended exposure to these substances can lead to adverse health consequences in humans. Removing HM-contaminated water and moving toward sustainable development goals (SdGs) is critical. In this mission, biochar has recently gained attention in the environmental sector as a green and alternative material for wastewater removal. This work provides a comprehensive analysis of the remediation of typical HMs by biochars, associated with an understanding of remediation mechanisms, and gives practical solutions for ecologically sustainable. Applying engineered biochar in various fields, especially with nanoscale biochar-aided wastewater treatment approaches, can eliminate hazardous metal(loid) contaminants, highlighting an environmentally friendly and low-cost method. Surface modification of engineered biochar with nanomaterials is a potential strategy that positively influences its sorption capacity to remove contaminants. The research findings highlighted the biochars' ability to adsorb HM ions based on increased specific surface area (SSA), heightened porosity, and forming inner-sphere complexes with oxygen-rich groups. Utilizing biochar modification emerged as a viable approach for addressing lead (Pb), cadmium (Cd), arsenic (As), mercury (Hg), and chromium (Cr) pollution in aqueous environments. Most biochars investigated demonstrated a removal efficiency >90 % (Cd, As, Hg) and can reach an impressive 99 % (Pb and Cr). Furthermore, biochar and advanced engineered applications are also considered alternative solutions based on the circular economy. © 2024 Elsevier B.V.

关键词： Nanostructured materials

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