Editorial Material
Chemistry, Multidisciplinary
Stefania Albonetti, Changwei Hu, Shunmugavel Saravanamurugan
Summary: In this Editorial, the Guest Editors introduce the significance and challenges of the sustainable transformation of 5-hydroxymethylfurfural, as well as outline the contents of the Special Issue with contributions from scientists around the world.
Editorial Material
Chemistry, Multidisciplinary
Norio Shibata, Dinesh Talwar
Summary: The unique properties and applications of fluorine-containing molecules have had significant impact across different scientific fields, from small to large molecules. This special issue provides a comprehensive overview of the state-of-the-art in fluorine chemistry.
Editorial Material
Chemistry, Multidisciplinary
Andres R. Alcantara, Pablo Dominguez de Maria, Jennifer A. Littlechild, Martin Schurmann, Roger A. Sheldon, Roland Wohlgemuth
Summary: In this article, the authors discuss the importance of biocatalysis in sustainable industrial chemistry and provide insights into future prospects for the field.
Editorial Material
Biochemistry & Molecular Biology
Charles D. Nichols, David E. Nichols
Summary: Psychedelics, a relatively recent field of research, have shown profound therapeutic potential for various psychiatric disorders. This special issue provides a comprehensive review of the basic science of psychedelics, aiming to enhance our understanding of their effects on brain function.
JOURNAL OF NEUROCHEMISTRY
(2022)
Editorial Material
Chemistry, Multidisciplinary
Christoph J. Brabec, Martin Heeney, Youngkyoo Kim, Christine K. Luscombe
Summary: Organic solar cells are gaining attention as a renewable energy source due to their Earth-abundant materials and low energy production. The Guest Editors introduce this field and discuss the contents of the Special Issue.
Editorial Material
Biochemistry & Molecular Biology
Karen J. Smillie, Michael A. Cousin, Sarah L. Gordon
Summary: The synapse is the connection formed between a presynapse, which releases neurotransmitter, and a postsynapse, which transduces the chemical signal. Over the past decade, presynaptic dysfunction has been recognized as a key mediator in various neurodevelopmental and neurodegenerative disorders. This special issue will focus on the disrupted presynaptic molecules and mechanisms in these conditions, as well as potential therapeutic approaches.
JOURNAL OF NEUROCHEMISTRY
(2021)
Article
Behavioral Sciences
Francesco N. Biondi, William J. Horrey, Birsen Donmez
Summary: With the advancement of vehicle automation, the role of human drivers has shifted from system operators to system supervisors. This special issue focuses on the latest research on how drivers utilize vehicle automation and the potential safety risks associated with it. It also examines the accuracy of driver monitoring systems in detecting distractions and drowsiness, as well as explores how future drivers may respond to the widespread adoption of this technology.
Article
Geography, Physical
Gildas Merceron, Thomas Tuetken, Robert Scott
Summary: Vertebrate teeth, composed mainly of bioapatite, are highly mineralized dermal tissues that are resistant to physical and chemical alteration over long periods of time. They provide valuable information about taxonomic classification, phylogenetic relationships, feeding ecology, and climate conditions of fossil species. This special issue includes 21 papers that explore the use of dental proxies in understanding diet and ecological habits, covering experimental studies, real-world observations, and fossil case studies.
PALAEOGEOGRAPHY PALAEOCLIMATOLOGY PALAEOECOLOGY
(2023)
Editorial Material
Computer Science, Theory & Methods
Vijayakumar Varadarajan, Piet Kommers, Vincenzo Piuri
Summary: In the vision of Industry 4.0, the impact of the new industrial revolution lies in cyber-physical systems, with the Internet of Things as a key foundation. This special issue presents 18 papers that provide in-depth research results on the advancement of Smart Cyber-Physical Systems for emerging real-time applications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Mathematics, Applied
Xiang-Ke Chang, Xing-Biao Hu, Jacek Szmigielski
Summary: The theory of orthogonal polynomials has been increasingly important in integrable systems, including Toda type lattices, peakon dynamical systems of Camassa-Holm type, Random Matrix theory, and Painleve Transcendents since the 1990s. This special issue focuses on recent advances in these areas and includes research papers and review articles that highlight the synergy between the theory of integrable systems, approximation theory, and the theory of orthogonal polynomials and generalizations. & COPY; 2023 Published by Elsevier B.V.
PHYSICA D-NONLINEAR PHENOMENA
(2023)
Editorial Material
Chemistry, Applied
Gareth S. Parkinson, Phillip Christopher
Summary: This special issue focuses on determining the structure and mechanisms of single-atom catalysis.
TOPICS IN CATALYSIS
(2022)
Editorial Material
Chemistry, Applied
Sebastian Collins, Paola Quaino
Summary: This special issue presents various theoretical and experimental strategies to understand and explain the physical chemistry principles underlying Catalysis and Surface Science.
TOPICS IN CATALYSIS
(2022)
Editorial Material
Operations Research & Management Science
Nenad Mladenovic, Panos M. Pardalos, Angelo Sifaleras, Rachid Benmansour
Summary: This special issue features selected papers from two recent International Conferences on Variable Neighborhood Search, which took place in Greece in 2018 and Morocco in 2019.
OPTIMIZATION LETTERS
(2022)
Editorial Material
Computer Science, Artificial Intelligence
Yong Zheng, Li Chen, Markus Zanker, Panagiotis Symeonidis
Summary: Recommender systems have successfully alleviated information overload and aided decision making in various domains and applications. This special issue focuses on inviting authors to submit revised and extended versions of their accepted papers on recommender systems, which were presented at the ACM Symposium on Applied Computing in 2020 and 2021. Each submission underwent a rigorous review process to ensure paper quality. The aim is to inspire researchers in the field of recommender systems to go beyond traditional algorithm development and explore new research opportunities.
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS
(2022)
Article
Geography, Physical
Yougui Song, Junsheng Nie, Chunhui Song, Jinbo Zan
Summary: This special issue focuses on the climate and environmental changes in Central Asia during the Cenozoic era and explores their forcing mechanisms. Through 33 publications, covering various themes from present to past, it provides important insights into the tectonic and climate changes in the Asian interior.
PALAEOGEOGRAPHY PALAEOCLIMATOLOGY PALAEOECOLOGY
(2022)
Editorial Material
Plant Sciences
Chunhui Ni, Yurong Liu, Yonggang Liu, Huixia Li, Mingming Shi, Ming Zhang, Bian Han
Article
Automation & Control Systems
Xi Li, Qiankun Song, Yurong Liu, Fuad E. Alsaadi
Summary: This article presents the Hurwicz model of the zero-sum uncertain differential game with jump based on uncertainty theory. It formulates a dynamic system using an uncertain differential equation that satisfies both the canonical Liu process and V-jump uncertain process. An equilibrium equation for solving the saddle-point of the game is proposed. Furthermore, the article analyzes the game with a linear dynamic system and quadratic objective function. Finally, it describes a resource extraction problem using the theoretical results.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Guijun Ma, Zidong Wang, Weibo Liu, Jingzhong Fang, Yong Zhang, Han Ding, Ye Yuan
Summary: This article proposes a two-stage integrated method for predicting the remaining useful life (RUL) of lithium-ion batteries. In the first stage, a convolutional neural network (CNN) is used to estimate the cycle life of each battery, and a similar degradation mode is chosen for capacity identification. In the second stage, a personalized prediction is made using the identified parameters. Experimental results demonstrate the superiority of this method over standard CNN-based and GPR-based prediction methods.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Yurong Liu, Guangpan Lu, Likang Guo, Yanfang Zhang, Ming Chen
Summary: A flexible pressure sensor with co-planar electrodes was fabricated using piezoelectric nanocomposites made from PDMS and ZnO nanotetrapods (ZNTs) fillers. The sensors showed a linear response to external pressure and increased sensitivity with higher growth temperature and ZNTs filler concentration. The sensor demonstrated potential applications in hand gesture and speech recognition.
IEEE SENSORS JOURNAL
(2023)
Article
Automation & Control Systems
Qinyuan Liu, Zidong Wang, Hongli Dong, Changjun Jiang
Summary: In this article, the state estimation problem for networked systems with energy harvesting technologies is investigated. A binary encoding scheme is utilized to transmit the measurement results, which are quantized into a bit string and transmitted via memoryless binary symmetric channels. A minmax robust estimator is designed to minimize the worst-case covariance of the estimation error. The influence of the length of the bit stream on the transmission rate and estimation performance is discussed, and conditions for the boundedness of the proposed estimator are provided.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Chunyu Li, Zidong Wang, Weihao Song, Shixin Zhao, Jianan Wang, Jiayuan Shan
Summary: This article investigates the resilient unscented Kalman filtering fusion issue for a class of nonlinear systems under the dynamic event-triggered mechanism. The dynamic event-triggered scheme is capable of scheduling data transmission frequency more efficiently, reducing communication burden and energy consumption. Furthermore, the sequential covariance intersection fusion strategy is introduced to solve the problem of computing cross covariance between local filters.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Shengkun Jiang, Xianfeng Tang, Silong Huang, Zhifang Lyu, Zhanliang Wang, Tao Tang, Huarong Gong, Yubin Gong, Zhaoyun Duan
Summary: To develop a high power and compact terahertz (THz) sheet beam traveling-wave tube (TWT), an all metal metamaterial (MTM)-inspired slow wave structure (SWS) is proposed. The MTM-inspired SWS exhibits advantages such as high interaction impedance, double beam tunnels, and compactness. Through simulation, it is predicted that the maximum output power of the 0.22 THz TWT with double sheet beams can reach 400 W with a 3-dB bandwidth of 5.4 GHz, while having a total length of only 29.2 mm.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2023)
Article
Engineering, Electrical & Electronic
Junwan Zhu, Zhigang Lu, Jingrui Duan, Zhanliang Wang, Huarong Gong, Yubin Gong
Summary: This paper proposes a modified staggered double grating traveling wave tube (SDG-TWT) slow wave structure (SWS) for wide-band and high-power TWTs operating in the W-band or higher terahertz band, which shows improved performance in terms of saturated power, electron efficiency, and gain.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2023)
Article
Physics, Applied
Cong Wang, Yurong Liu, Baozi Wu, Jian Sui
Summary: The study has used double-stacked gate dielectrics (DSGD) to enhance the electrical performance of zinc oxide thin-film transistors (ZnO-TFT) with single-layer NbLaO gate dielectric (SLGD). Compared to ZnO-TFT with SLGD, the ZnO-TFTs with DSGD have shown significant improvement in electrical performance, particularly for the device with NbLaO/SiO2 DSGD, with increased field-effect mobility, on/off current ratio and reduced subthreshold slope. The enhanced performance is attributed to low surface roughness and trap-state density in the bulk of the channel and at the ZnO/NbLaO interface. These findings suggest the potential application of ZnO-TFTs with DSGD in high-resolution flat panel displays.
MODERN PHYSICS LETTERS B
(2023)
Article
Medicine, General & Internal
Shuang Liu, Limei Yuan, Jinzhu Li, Yurong Liu, Haibo Wang, Xingye Ren
Summary: The aim of this research was to explore the diagnostic value of circDENND4C in EOC and the corresponding mechanism. The expression of circDENND4C and miR-200b/c in tissues, serum, and cell lines of EOC were analyzed. It was found that circDENND4C was lowest while miR-200b/c was highest in EOC tissues and serums. Furthermore, circDENND4C was involved in the malignant progression of EOC by suppressing cell proliferation and stimulating apoptosis through downregulating miR-200b/c. Serum circDENND4C showed a higher specificity and accuracy than serum CA125 or HE4 in EOC diagnosis.
ANNALS OF MEDICINE
(2023)
Article
Mathematics, Applied
Dan Liu, Zidong Wang, Yurong Liu, Changfeng Xue, Fuad E. Alsaadi
Summary: In this paper, a distributed filter is proposed for time-varying systems corrupted by dynamic bias and packet disorders over sensor networks. The system, which includes stochastic bias governed by a dynamical equation, takes into account transmission delays described by random variables with known probability distributions. The paper focuses on the construction of a distributed and recursive filter under the corruption of dynamic bias and packet disorders. Upper bounds on attained error covariances are obtained and minimized by parameterizing filter gains. Additionally, a sufficient condition is presented to ensure mean-square boundedness of filtering errors. An example is provided for verification of the proposed method. (c) 2022 Elsevier Inc. All rights reserved.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Automation & Control Systems
Wei Chen, Zidong Wang, Derui Ding, Xiaojian Yi, Qing-Long Han
Summary: This article discusses the problem of distributed state estimation over wireless sensor networks, introduces a new distributed state estimator, and systematically discusses the probability distribution of energy level. Furthermore, the optimal estimator gain is derived by minimizing the trace of the estimation error covariance, and the convergence of the minimized upper bound of the expected estimation error covariance is analyzed.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Chuang Wang, Zidong Wang, Qing-Long Han, Fei Han, Hongli Dong
Summary: In this article, a novel leader-follower-based particle swarm optimization (LFPSO) algorithm is proposed, which maintains the diversity of the particle population while improving the possibility of escaping from the locally optimal solution. Experimental results demonstrate that the proposed algorithm significantly improves the accuracy and convergence rate of conventional particle swarm optimization algorithms, and its superiority is verified in denoising real-time signals in an oilfield pipeline network.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Kaiqun Zhu, Zidong Wang, Guoliang Wei, Xiaohui Liu
Summary: This article investigates the adaptive neural network-based set-membership state estimation problem for a class of nonlinear systems subject to bit rate constraints and unknown-but-bounded noises. A bit rate allocation mechanism is proposed to relieve the communication burden and improve state estimation accuracy. An NN-based set-membership estimator is designed using the NN learning method, relying upon a prediction-correction structure. The existence of adaptive tuning parameters and set-membership estimators is ensured, and the convergence of NN weights is analyzed.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xin Luo, Yurong Zhong, Zidong Wang, Maozhen Li
Summary: This study proposes an ASNL model for handling large-scale undirected networks, which can efficiently represent incomplete and imbalanced data of SHDI matrices, and has fast model convergence and high computational efficiency. Empirical studies on four SHDI matrices demonstrate that ASNL significantly outperforms other models in prediction accuracy and computational efficiency.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
