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Front Cover: Potassium Carbonate as a Low-Cost and Highly Active Solid Base Catalyst for Low-Temperature Methanolysis of Polycarbonate (ChemSusChem 2/2025)

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ChemSusChem 2025年第2期18卷

作者： Tzu-Ming Lin Philip Anggo Krisbiantoro Miyu Sato Yu-Chia Chang Eduardo C. Atayde Dr. Weisheng Liao Prof. Yuichi Kamiya Dr. Ryoichi Otomo Prof. Kevin C.-W. Wu Department of Chemical Engineering National Taiwan University Taipei 10617 Taiwan Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei 11529 Taiwan International Graduate Program of Molecular Science and Technology National Taiwan University Taipei 10617 Taiwan Graduate School of Environmental Science Hokkaido University Nishi 5 Kita 10 Kita-ku Sapporo 060-0810 Japan Department of Chemistry National Tsing Hua University Hsinchu 30013 Taiwan Faculty of Environmental Earth Science Hokkaido University Nishi 5 Kita 10 Kita-ku Sapporo Japan Department of Chemical Engineering and Materials Science Yuan Ze University Chung-Li Taoyuan Taiwan Department of Chemical Engineering Chung Yuan Christian University Taoyuan City 320 Taiwan

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Developing the “Healthcare CEO App” for patients with type 1 diabetes transitioning from adolescence to young adulthood: A mixed-methods study

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Nursing Open 2023年第3期10卷 1755-1766页

作者： Chiang, Yueh-Tao Chang, Chi-Wen Yu, Hsing-Yi Tsay, Pei-Kwei Lo, Fu-Sung Chen, Chi-Wen Lin, Wen-Yen Hsu, Chien-Lung An, Chi Moons, Philip School of Nursing College of Medicine Chang-Gung University Taoyuan Taiwan Division of Pediatric Endocrinology & Genetics Department of Pediatrics Chang-Gung Memorial Hospital Taoyuan Taiwan Department of Nursing Chang-Gung Memorial Hospital Taoyuan Taiwan Department of Public Health and Center of Biostatistics College of Medicine Chang-Gung University Taoyuan Taiwan College of Medicine Chung-Gung University Taoyuan Taiwan College of Nursing National Yang Ming Chiao Tung University Taipei Taiwan Department of Information Management National Taichung University of Science and Technology Taichung Taiwan Department of Information Management Chang-Gung University Taoyuan Taiwan Graduate Institute of Management Chang Gung University Tao-Yuan Taiwan Master of Science Degree Program in Innovation for Smart Medicine Tao-Yuan Taiwan Department of Psychiatry Chang Gung Memorial Hospital at Linkou Tao-Yuan Taiwan Department of Public Health and Primary Care KU Leuven-University of Leuven Leuven Belgium Institute of Health and Care Sciences University of Gothenburg Gothenburg Sweden Department of Paediatrics and Child Health University of Cape Town Cape Town South Africa

Aim: To develop and test a mobile application that supports the disease self-management of adolescents with type 1 diabetes during their transition to early adulthood. Design: A sequential mixed-methods design was employed. Methods: The application content was designed according to previously identified care needs and expectations, followed by application development on the Android operating system. From the outpatient clinic of the Department of Paediatric Endocrinology and Metabolism at a medical centre in northern Taiwan, 35 individuals aged between 16–25 years participated in application testing. Results: The overall median score of the QUIS was 4–5, most of the 25% quartile was 4–5, and all of the 75% quartile was 5, indicating adequate user interaction satisfaction. © 2022 The Authors. Nursing Open published by John Wiley & Sons Ltd.

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Peptide-Coated Bacteriorhodopsin-Based Photoelectric Biosensor for Detecting Rheumatoid Arthritis

Biosensors

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Biosensors 2023年第10期13卷 929-929页

作者： Chen, Hsiu-Mei Tsai, Yi-Hsuan Hsu, Chien-Yi Wang, Yong-Yi Hsieh, Cheng-En Chen, Jin-Hua Chang, Yu-Sheng Lin, Ching-Yu Department of Chemical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Family Medicine Wan Fang Hospital Taipei Medical University Taipei11696 Taiwan Division of Cardiology and Cardiovascular Research Center Department of Internal Medicine Taipei Medical University Hospital Taipei11031 Taiwan Division of Cardiology Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Taipei Heart Institute Taipei Medical University Taipei11031 Taiwan Graduate Institute of Data Science College of Management Taipei Medical University Taipei11031 Taiwan Office of Data Science Taipei Medical University Taipei11031 Taiwan Division of Allergy Immunology and Rheumatology Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City23561 Taiwan Division of Allergy Immunology and Rheumatology Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan School of Medical Laboratory Science and Biotechnology College of Medical Science and Technology Taipei Medical University Taipei11031 Taiwan Ph.D. Program in Medical Biotechnology College of Medical Science and Technology Taipei Medical University Taipei11031 Taiwan

An effective early diagnosis is important for rheumatoid arthritis (RA) management. This study reveals a novel RA detection method using bacteriorhodopsin as a photoelectric transducer, a light-driven proton pump in purple membranes (PMs). It was devised by covalently conjugating a PM monolayer-coated electrode with a citrullinated-inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3)542–556 peptide that recognizes the serum RA-associated autoantibodies. The direct serum coating decreased the photocurrents in the biosensor, with the reduction in the photocurrent caused by coating with an RA-patient serum that is significantly larger than that with a healthy-control serum (38.1% vs. 20.2%). The difference in the reduction in the photocurrent between those two serum groups widened after the serum-coated biosensor was further labeled with gold nanoparticle (AuNP)-conjugated anti-IgA (anti-IgA-AuNP) (53.6% vs. 30.6%). Both atomic force microscopic (AFM) and Raman analyses confirmed the sequential peptide, serum, and anti-IgA-AuNP coatings on the PM-coated substrates. The reductions in the photocurrent measured in both the serum and anti-IgA-AuNPs coating steps correlated well with the results using commercial enzyme-linked immunosorbent assay kits (Spearman rho = 0.805 and 0.787, respectively), with both a sensitivity and specificity close to 100% in both steps. It was shown that an RA diagnosis can be performed in either a single- or two-step mode using the developed biosensor. © 2023 by the authors.

关键词： Peptides

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Real-time tone mapping: A state of the art report

arXiv

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arXiv 2020年

作者： Ou, Yafei Ambalathankandy, Prasoon Ikebe, Masayuki Takamaeda, Shinya Motomura, Masato Asai, Tetsuya Research Center For Integrated Quantum Electronics Hokkaido University Sapporo Japan Department of Computer Science Graduate School of Information Science and Technology University of Tokyo Tokyo Japan Institute of Innovative Research Tokyo Institute of Technology Tokyo Japan Graduate School of Information Science and Technology Hokkaido University Sapporo Japan

The rising demand for high quality display has ensued active research in high dynamic range (HDR) imaging, which has the potential to replace the standard dynamic range imaging. This is due to HDR's features like accurate reproducibility of a scene with its entire spectrum of visible lighting and color depth. But this capability comes with expensive capture, display, storage and distribution resource requirements. Also, display of HDR images/video content on an ordinary display device with limited dynamic range requires some form of adaptation. Many adaptation algorithms, widely known as tone mapping operators, have been studied and proposed in the last few decades. In this state of the art report, we present a comprehensive survey of 50+ tone mapping algorithms that have been implemented on hardware for acceleration and real-time performance. These algorithms have been adapted or redesigned to make them hardware-friendly. This effort leads to various design challenges that are encountered during the hardware development. Any real-time application poses strict timing constraints which requires time exact processing of the algorithm. Also, most of the embedded systems would have limited system resources in terms of battery, computational power and memory resources. These design challenges require novel solutions, and in this report we focus on these issues. In this we survey will discuss those tonemap algorithms which have been implemented on GPU [1-10], FPGA [11-41], and ASIC [42-53] in terms of their hardware specifications and performance. Output image quality is an important metric for tonemap algorithms. From our literature survey we found that, various objective quality metrics have been used to demonstrate the functionality of adapting the algorithm on hardware platform. We have compiled and studied all the metrics used in this survey [54-67]. Finally, in this report we demonstrate the link between hardware cost and image quality thereby illustrating the under

关键词： Surveys

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A parameter optimization method for deep reinforcement learning by evolution strategy using multiple higher-ranked individuals

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2020年第8期140卷 366-366页

作者： Tsuchida, Takahiro Yamaguchi, Satoshi Graduate School of Information and Computer Science Chiba Institute of Technology 2-17-1 Tsudanuma Narashino Chiba275-0016 Japan Dept. of Computer Science Chiba Institute of Technology 2-17-1 Tsudanuma Narashino Chiba275-0016 Japan

As a parameters optimization method for neural networks which is applied to reinforcement learning, Evolution Strategy has been proposed. In this method, neural network parameters are represented by individuals, like ordinary evolutional strategies. While the evolution, a new individual is generated from some distribution that centered a parameter and is weighted according to the order of reward that the neural network corresponding to the individual obtained. However, there are cased that the differences of reward values among the higher order individuals are so few that the updating can not lead to individuals to higher quality. So, in this research, after updating the normal parameters, we select the top individuals who get high rewards and weight them, and propose a method to update the parameters again using those individuals. By focusing on individuals who get a high reward, it is expected to search for a parameter that can obtain a high score earlier than the conventional method. In the experiment, the conventional method and the proposed method are applied to BipedalWalker which is a learning environment of a 2D biped robot in OpenAI Gym, and evaluation is performed and as a result, the proposed method showed better performance than the conventional method. © 2020 The Institute of Electrical Engineers of Japan.

关键词： Reinforcement learning

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Predicting VNF Deployment Decisions under Dynamically Changing Network Conditions 15

Predicting VNF Deployment Decisions under Dynamically Changi...

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15th International Conference on Network and Service Management, CNSM 2019

作者： Lange, Stanislav Kim, Hee-Gon Jeong, Se-Yeon Choi, Heeyoul Yoo, Jae-Hyung Hong, James Won-Ki Pohang University of Science and Technology Computer Science and Engineering Pohang Korea Republic of Handong Global University Pohang Korea Republic of Pohang University of Science and Technology Graduate School of Information Technology Pohang Korea Republic of

ISBN: (纸本)9783903176249

In addition to providing network operators with benefits in terms of flexibility and cost efficiency, softwarization paradigms like SDN and NFV are key enablers for the concept of Service Function Chaining (SFC). The corresponding networks need to support a wide range of services and applications with highly heterogeneous requirements that change dynamically during the network's lifetime. Hence, efficient management and operation of such networks requires a high degree of automation that is paired with fast and proactive decisions in order to cope with these phenomena. In particular, determining the optimal number of VNF instances that is required for accommodating current and upcoming demands is a crucial task that also affects subsequent management decisions. To enable fast and proactive decisions in this context, we propose a machine learning-based approach that uses recent monitoring data to predict whether to adapt the current number of VNF instances of a given type. Furthermore, we present a methodology for generating labeled training data that reflects temporal dynamics and heterogeneous demands of real world networks. We demonstrate the feasibility of the approach using two different network topologies that represent WAN and mobile edge computing use cases, respectively. Additionally, we investigate how well the models generalize among networks and provide guidelines regarding the prediction horizon, i.e., how far ahead predictions can be performed in a reliable manner. © 2019 IFIP.

关键词： Machine learning

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Big data-driven target identification by machine learning: DRD2 as a therapeutic target for psoriasis

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Journal of Dermatological science 2025年

作者： Sakai, Takashi Sawada, Ryusuke Ichinose, Otoha Terabayashi, Takeshi Hatano, Yutaka Yamanishi, Yoshihiro Ishizaki, Toshimasa Department of Dermatology Faculty of Medicine Oita University Oita Japan Department of Pharmacology Okayama University Graduate School of Medicine Dentistry and Pharmaceutical Sciences Okayama Japan Department of Bioscience and Bioinformatics Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Department of Pharmacology Faculty of Medicine Oita University Oita Japan Department of Complex Systems Science Graduate School of Informatics Nagoya University Aichi Japan

Background: The development of medical treatments has traditionally relied on researchers leveraging scientific knowledge to hypothesize disease mechanisms and identify therapeutic agents. However, the depletion of novel therapeutic targets has become a significant challenge, resulting in stagnation within pharmaceutical research. Objective: To address the scarcity of therapeutic targets, we developed a machine learning (ML)-based system capable of predicting therapeutic target molecules for diseases. To validate its utility, we applied this system to psoriasis, aiming to identify novel treatment strategies. Methods: Our approach utilized a large clinical database to calculate reporting odds ratios for all drugs associated with the prevention of diseases of interest. We identified target proteins by analyzing large chemical structure databases to discover proteins commonly associated with preventive drug candidates. Experimental validation was conducted by administering a predicted therapeutic candidate in an imiquimod-induced psoriasis mouse model. Results: The ML-based predictions identified drugs for Parkinson's disease as potential preventive candidates for psoriasis. Further analysis highlighted dopamine receptor D2 (DRD2) as a therapeutic target. Administration of a DRD2 agonist alleviated psoriasis symptoms in mice, evidenced by the downregulation of mRNA expression in the IL-17 pathway and reduced serum tumor necrosis factor-α levels. Conclusion: This study demonstrates the utility of a novel ML-based system for identifying therapeutic targets, as shown by its successful application in uncovering the role of DRD2 in psoriasis. Beyond psoriasis, this system offers significant potential for exploring pathological mechanisms and discovering therapeutic targets across various diseases. © 2025 The Authors

关键词： artificial intelligence big data dopamine receptor D2 machine learning psoriasis

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Dynamic change of gene-to-gene regulatory networks in response to SARS-CoV-2 infection

arXiv

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arXiv 2020年

作者： Tanaka, Yoshihisa Higashihara, Kako Nakazawa, Mai Adachi Yamashita, Fumiyoshi Tamada, Yoshinori Okuno, Yasushi Graduate School of Pharmaceutical Sciences Kyoto University Japan RIKEN Cluster for Science Technology and Innovation Hub Medical Sciences Innovation Hub Program Japan Graduate School of Medicine Kyoto University Japan

The current pandemic of SARS-CoV-2 has caused extensive damage to society. The characterization of SARS-CoV-2 prpfiles has been addressed by researchers globally with the aim of resolving this disruptive crisis. This investigation process is indispensable for an understanding of how SARS-CoV-2 behaves in human host cells. However, little is known about the systematic molecular mechanisms involved in the effect of SARS-CoV-2 infection on human host cells. Here, we have presented gene-to-gene regulatory networks in response to SARS-CoV-2 using a Bayesian network model. We examined the dynamic changes of the SARS-CoV-2-purturbated networks established by our proposed framework for gene network analysis, revealing that interferon signaling gradually switches to the subsequent inflammatory-cytokine signaling cascades. Furthermore, we have succeeded in capturing a COVID-19 patient-specific network in which transduction of these signalings is coincidently induced. This enabled us to explore local regulatory systems influenced by SARS-CoV-2 in host cells more precisely at an individual level. Our panel of network analyses has provided new insight into SARS-CoV-2 research from the perspective of cellular systems. Copyright © 2020, The Authors. All rights reserved.

关键词： SARS

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Multisensory Approaches to Human-Food Interaction 20

Multisensory Approaches to Human-Food Interaction

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22nd ACM International Conference on Multimodal Interaction, ICMI 2020

作者： Velasco, Carlos Nijholt, Anton Spence, Charles Narumi, Takuji Motoki, Kosuke Huisman, Gijs Obrist, Marianna Department of Marketing Bi Norwegian Business School Oslo Norway University of Twente Human Media Interaction Enschede Netherlands Department of Experimental Psychology University of Oxford Oxford United Kingdom Graduate School of Information Science and Technology University of Tokyo Tokyo Japan Department of Food Science and Business Miyagi University Sendai Japan Digital Society School Amsterdam University of Applied Sciences Amsterdam Netherlands Department of Computer Science University College London London United Kingdom

ISBN: (纸本)9781450375818

Here, we present the outcome of the 4th workshop on Multisensory Approaches to Human-Food Interaction (MHFI), developed in collaboration with ICMI 2020 in Utrecht, The Netherlands. Capitalizing on the increasing interest on multisensory aspects of human-food interaction and the unique contribution that our community offers, we developed a space to discuss ideas ranging from mechanisms of multisensory food perception, through multisensory technologies, to new applications of systems in the context of MHFI. All in all, the workshop involved 11 contributions, which will hopefully further help shape the basis of a field of inquiry that grows as we see progress in our understanding of the senses and the development of new technologies in the context of food. © 2020 ACM.

关键词： human-food interaction technology senses multisensory

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Landau Polaritons in the Ultrastrong and Superstrong Coupling Regime in a Multimode Terahertz Photonic-Crystal Cavity

Landau Polaritons in the Ultrastrong and Superstrong Couplin...

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International Conference on Infrared and Millimeter Waves

作者： Fuyang Tay Ali Mojibpour Stephen Sanders Shuang Liang Hongjing Xu Geoff C. Gardner Andrey Baydin Michael J. Manfra Alessandro Alabastri David Hagenmüller Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley–Curl Institute Rice University Houston TX USA Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Department of Physics and Astronomy Rice University Houston TX USA Smalley–Curl Institute Rice University Houston TX USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA ISIS (UMR 7006) Université de Strasbourg and CNRS Strasbourg France Department of Materials Science and NanoEngineering Rice University Houston TX USA

We have demonstrated ultrastrong and superstrong coupling of a Landau-quantized two-dimensional electron gas in GaAs with a multiple-mode three-dimensional terahertz photonic-crystal cavity. The cavity had an asymmetric design such that the real-space profiles of photonic modes depended on the electric field polarization. Terahertz magnetospectroscopy experiments with polarized radiation clearly showed that the degree of hybridization of multiple cavity modes is a function of the spatial overlap of the photonic modes. These findings can be utilized for the dynamical tuning of multimode light–matter interactions, which can lead to the development of novel terahertz devices.

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