Article
Multidisciplinary Sciences
Amalio Telenti, Ann Arvin, Lawrence Corey, Davide Corti, Michael S. Diamond, Adolfo Garcia-Sastre, Robert F. Garry, Edward C. Holmes, Phillip S. Pang, Herbert W. Virgin
Summary: This article discusses the future patterns of SARS-CoV-2 infection, the development of variants, and the implications for vaccine deployment. It suggests that the virus may become endemic fueled by pockets of susceptible individuals and waning immunity. Effective surveillance and response are crucial to prevent new epidemic or pandemic patterns.
Article
Chemistry, Multidisciplinary
Cristina-Maria Stancioi, Iulia Adina Stefan, Violeta Briciu, Vlad Muresan, Iulia Clitan, Mihail Abrudean, Mihaela-Ligia Unguresan, Radu Miron, Ecaterina Stativa, Michaela Nanu, Adriana Topan, Daniela Oana Toader, Ioana Nanu
Summary: The COVID-19 pandemic has greatly impacted daily activities and the research focuses on developing mathematical models for prediction and simulation of disease spread. Five main input parameters and four output parameters were identified. Three mathematical models were tested and the optimal solution was chosen based on fit values and complexity analysis.
APPLIED SCIENCES-BASEL
(2023)
Article
Mathematics, Interdisciplinary Applications
V. P. Tsvetkov, S. A. Mikheev, I. V. Tsvetkov, V. L. Derbov, A. A. Gusev, S. I. Vinitsky
Summary: A mathematical model of multifractal dynamics is proposed to describe the COVID-19 pandemic, which avoids the shortcomings of other models by solely focusing on the fractal properties of pandemics. The model accurately determines the trend and significant jump in daily cases using calculated parameters. Fractal dimensions of daily incidence segments and variations in the main reproduction number of COVID-19 are calculated based on global statistics.
CHAOS SOLITONS & FRACTALS
(2022)
Review
Immunology
Luca Soraci, Fabrizia Lattanzio, Giulia Soraci, Maria Elsa Gambuzza, Claudio Pulvirenti, Annalisa Cozza, Andrea Corsonello, Filippo Luciani, Giovanni Rezza
Summary: Currently available COVID-19 vaccines have limitations in controlling the pandemic, and alternative R&D strategies and technological platforms are needed to improve long-lasting immunogenicity, reduce adverse events, and support rapid production.
Review
Allergy
Vanitha Sampath, Grace Rabinowitz, Mihir Shah, Surabhi Jain, Zuzana Diamant, Milos Jesenak, Ronald Rabin, Stefan Vieths, Ioana Agache, Mubeccel Akdis, Domingo Barber, Heimo Breiteneder, Sharon Chinthrajah, Tomas Chivato, William Collins, Thomas Eiwegger, Katharine Fast, Wytske Fokkens, Robyn E. O'Hehir, Markus Ollert, Liam O'Mahony, Oscar Palomares, Oliver Pfaar, Carmen Riggioni, Mohamed H. Shamji, Milena Sokolowska, Maria Jose Torres, Claudia Traidl-Hoffmann, Menno van Zelm, De Yun Wang, Luo Zhang, Cezmi A. Akdis, Kari C. Nadeau
Summary: Vaccines are crucial tools in public health, with the COVID-19 vaccines expected to have a positive impact globally. While serious allergic reactions are rare, it is important to consider their mechanisms, clinical implications, and potential causes, as well as to review implications for individual diagnosis, management, and vaccine manufacturing for future research.
Article
Mathematics, Applied
Weiyuan Ma, Nuri Ma, Changping Dai, YangQuan Chen, Xinwei Wang
Summary: As the COVID-19 mutates, the infection rate is increasing rapidly and the vaccine is ineffective against the mutated strain. This paper proposes a SEIR-type fractional model with reinfection and vaccine inefficacy, which successfully captures the dynamics of the mutated COVID-19 pandemic. The model's existence, uniqueness, boundedness, and nonnegativeness are derived, and the local and global stability based on the basic reproduction number R0 are analyzed. Sensitivity analysis evaluates the impact of each parameter on R0 and ranks key epidemiological parameters. Additionally, necessary conditions for implementing fractional optimal control and corresponding optimal solutions for mitigating COVID-19 transmission are obtained.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Public, Environmental & Occupational Health
Khalid Mehmood, Yansong Bao, Sana Mushtaq, Saifullah, Muhammad Ajmal Khan, Nadeem Siddique, Muhammad Bilal, Zhang Heng, Li Huan, Muhammad Tariq, Sibtain Ahmad
Summary: As scientific technology and space science progress, remote sensing has emerged as an innovative solution to ease the challenges of the COVID-19 pandemic. This bibliometric analysis of scientific documents indexed in the Scopus database reveals the research characteristics and growth trends in using remote sensing for monitoring and managing the COVID-19 research. The study found that there has been a significant increase of 30% in the number of articles related to remote sensing and COVID-19, with the United States, China, and the United Kingdom being the top contributors. The most productive journals in this research field were Sustainability, Science of the Total Environment, and International Journal of Environmental Research and Public Health. The predominant themes revolved around COVID-19, remote sensing, spatial analysis, coronavirus, lockdown, and air pollution. The expansion of these topics is associated with cross-sectional research on remote sensing, evidence-based tools, satellite mapping, and geographic information systems. The use of remote sensing technology will greatly enhance the monitoring and management of global pandemic risks in the coming years.
FRONTIERS IN PUBLIC HEALTH
(2022)
Review
Agriculture, Dairy & Animal Science
Mohamed S. Kamel, Amr A. El-Sayed, Rachel A. Munds, Mohit S. Verma
Summary: During the COVID-19 pandemic, dog owners have found that their dogs help reduce stress and anxiety. Dogs can get COVID-19 from their owners but are usually asymptomatic, and it is unclear if it affects their health. It is also uncertain if dogs can transmit the virus to humans. However, sniffer dogs have shown success in detecting COVID-19-positive individuals.
Review
Clinical Neurology
James E. Siegler, Mohamad Abdalkader, Patrik Michel, Thanh N. Nguyen
Summary: This narrative review summarizes the changing paradigms and latest data regarding the complex relationship between COVID-19 and cerebrovascular disease. Despite the association between COVID-19 and thrombotic complications, global declines in ischemic stroke and other cerebrovascular diseases have been observed, which may be attributed to patient avoidance of healthcare institutions and declines in other transmissible infectious illnesses.
Article
Multidisciplinary Sciences
Khadka Bahadur Pal, Buddha Bahadur Basnet, Ramesh Raj Pant, Kiran Bishwakarma, Kopila Kafle, Namraj Dhami, Motee Lal Sharma, Lal B. Thapa, Binod Bhattarai, Youb Raj Bhatta
Summary: The COVID-19 pandemic has severely impacted the education sector in Nepal, primarily due to a lack of adequate online infrastructure and skilled human resources, as well as limited internet facilities in remote rural areas. The study calls for stakeholders to provide necessary services and strategies to address the consequences of the pandemic.
Article
Environmental Sciences
Khalid Mehmood, Sana Mushtaq, Yansong Bao, Saifullah, Sadia Bibi, Muhammad Yaseen, Muhammad Ajmal Khan, Muhammad Mohsin Abrar, Zaid Ulhassan, Shah Fahad, George P. Petropoulos
Summary: This bibliometric study analyzes the impact of the COVID-19 pandemic on air pollution globally. The study finds that there has been an increase in research output on COVID-19 and air pollution, with China leading in the number of publications. The study also explores keywords related to COVID-19 and air pollution, providing insights into measures to reduce air pollution.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Review
Cardiac & Cardiovascular Systems
Joanna Popiolek-Kalisz, Grzegorz Kalisz
Summary: Remote monitoring for CRT during the COVID-19 pandemic has received increased attention, allowing for earlier detection of issues and improved outcomes for patients.
CURRENT PROBLEMS IN CARDIOLOGY
(2022)
Article
Mathematics, Applied
Victor M. Perez-Garcia
Summary: This special issue presents recent applications of mathematical and nonlinear science methods in studying various issues related to the COVID-19 pandemic. The sixteen original research papers cover a wide range of studies including classical epidemiological models, new models specific to COVID-19, non-pharmaceutical control measures, network models, and other pandemic-related problems.
PHYSICA D-NONLINEAR PHENOMENA
(2021)
Review
Engineering, Chemical
Raluca Elisabeta Lupascu (Moisi), Marina Ionela Ilie, Bruno Stefan Velescu, Denisa Ioana Udeanu, Camelia Sultana, Simona Ruta, Andreea Letita Arsene
Summary: The COVID-19 pandemic has led to an unprecedented international collaborative effort for rapid diagnosis, epidemiologic surveillance, clinical management, prevention, and treatment. This review provides an overview of current and new therapeutic approaches, focusing on specific steps that can be targeted by antiviral drugs, as well as discussing immunomodulatory drugs used for severe COVID-19 treatment and future therapeutic options.
Review
Immunology
Rashmi Rana, Ankit Tripathi, Naveen Kumar, Nirmal Kumar Ganguly
Summary: The outbreak of COVID-19 has been unprecedented, affecting billions of people globally in physical, psychological, and social aspects. SARS-CoV-2, with its high transmissibility and severe post-recovery implications, differs from MERS and SARS. The virus's impacts extend beyond the respiratory system, with no specific treatment currently available.
FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY
(2021)
Article
Engineering, Multidisciplinary
Zahra Sadat Aghayan, Alireza Alfi, J. A. Tenreiro Machado
Summary: In this article, the delay-dependent robust stability of uncertain fractional order neutral-type systems with distributed delays, nonlinear perturbations, and input saturation is addressed. Using the Lyapunov-Krasovskii functional, criteria on asymptotic robust stability of the systems, expressed in terms of linear matrix inequalities, are constructed to compute the state-feedback controller gains. The controller gains are determined through the cone complementarity linearization algorithm to maximize the domain of attraction. Numerical simulations are conducted to validate the theoretical results.
INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION
(2023)
Article
Engineering, Multidisciplinary
Ying Xie, Ping Zhou, Jun Ma
Summary: This paper investigates the problem of information exchange and signal encoding between neural circuits. The results show that adaptive synchronization between different neural circuits can be achieved through coupling, and energy diversity plays an important role in controlling synchronization.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Computer Science, Artificial Intelligence
Yong Wang, Mingxing Gao, Xun Ran, Jun Ma, Leo Yu Zhang
Summary: Matrix factorization (MF) is a popular technique in recommendation systems (RSs). However, the privacy protection of item sets rated by users is often ignored in existing privacy-preserving MF schemes. To address this issue, a strategy based on piecewise mechanism (PM) is proposed to protect both rating values and item sets. An improved MF based on PM (IMFPM) is introduced, which divides item profiles into global and personal information and utilizes random projection technology to reduce privacy noise. Theoretical analysis and experiments show that IMFPM provides strong privacy protection and high prediction quality, making it a promising scheme for distributed recommendation systems.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Mathematics, Interdisciplinary Applications
Zhigang Zhu, Xiaofeng Zhang, Yisen Wang, Jun Ma
Summary: This paper investigates the adaptation and filtering capability of a sound-sensitive neural circuit using a FitzHugh-Nagumo based autaptic neuron. The results show that the excitatory chemical autapse can act as a narrow-band filter, while the inhibitory chemical autapse enables the neuron to converge its amplitude and exhibits bursting adaptation. Additionally, the electrical autaptic neuron's response can be modulated by both time-delay feedback gains.
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
(2023)
Article
Computer Science, Artificial Intelligence
Dong Liu, Yong Wang, Chenhong Luo, Jun Ma
Summary: This study proposes an improved autoencoder to address the challenges of sparsity and uneven distribution of rating data in the recommendation domain. Two recommendation schemes based on the improved autoencoder are presented for rating prediction and top -N ranking tasks. Experimental results demonstrate about 5% and 3% improvements in rating prediction and top -N ranking, respectively. Therefore, the improved model effectively handles the challenges and achieves good recommendation performance.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Mechanical
Ying Xie, Ying Xu, Jun Ma
Summary: Identical nonlinear oscillators can achieve synchronous states through regulation, while non-identical oscillators can reach phase lock when the coupling channels are controllable. Continuous energy supply and pumping are crucial for periodic or chaotic oscillators and energy exchange occurs when coupling channels are activated. In biological neurons, continuous diffusion of intracellular and extracellular ions activates an electromagnetic field, and the inner field energy can be approximated by the equivalent Hamilton energy of the neuron. This paper investigates the impact of energy diversity on the desynchronization of neurons with parameter diversity, and emphasizes the importance of distinct energy diversity in preventing seizures accompanied by synchronous bursting in neurons.
NONLINEAR DYNAMICS
(2023)
Article
Mathematics, Applied
Fuqiang Wu, Yitong Guo, Jun Ma, Wuyin Jin
Summary: In this paper, an equivalent circuit is designed using two memristive Josephson junctions coupled by a resistor and two inductors to mimic the characteristics of biological neurons. The circuit can reproduce bursting activities similar to neurons through numerical simulation. Additionally, the coupled memristive Josephson junctions can achieve in-phase and antiphase synchronization. The synchronous behaviors are analyzed by discerning the interspike interval of phase difference and average Hamilton energy.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Mathematics, Applied
Veli Baysal, Ramazan Solmaz, Jun Ma
Summary: The signal encoding capacity of the nervous system is significantly related to the spiking regime of neurons. Chaotic fluctuations in the neuronal medium are thought to enhance cognitive functions. External chaotic activity at a suitable level enhances the weak signal encoding performance of neurons, especially when the weak signal frequency matches the chaotic fluctuations-induced sub-threshold oscillations frequencies. This manipulation is explained by chaotic resonance.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Mathematics, Applied
Shidong Zhai, Penglei Zhao, Yongtao Xie, Jun Ma
Summary: This paper introduces a complex network of interaction between human behavior and virus transmission, and analyzes the influence of individual group behavior on virus transmission, as well as the reciprocal influence of virus transmission on individual group behavior. The paper also examines the effects of evolving network structures on cluster synchronization and provides discriminant conditions for distinguishing between aggregation behavior and virus extinction. Through simulations conducted under various conditions, the findings are rigorously validated, confirming their validity and reliability.
Article
Mathematics, Applied
Yitong Guo, Fuqiang Wu, Feifei Yang, Jun Ma
Summary: This study investigates the control mechanism of neuron membrane potential and the adaptive characteristics of neurons. By simulating the physical properties of cell membranes and adding an induction channel, coherence resonance and mode selection under adaptive excitation are discovered. An adaptive control law is proposed to explain the controllability of cell membranes under external stimuli.
Review
Engineering, Multidisciplinary
Jun Ma
Summary: Diffusion of ions inside and outside cells leads to a gradient electromagnetic field that regulates membrane potential. External stimuli inject energy to disrupt the energy balance between the magnetic and electric fields in a cell. Activation of biophysical functions and self-adaptation of biological neurons depend on energy flow, and synapse connection is controlled to achieve energy balance. When more neurons are clustered together, field energy is exchanged and shape formation occurs to achieve local energy balance, preventing bursting synchronization and seizure. This review presents various biophysical neuron models and explains their physical aspects, clarifying the controllability of functional synapses, formation of heterogeneity, and defects to understand synchronization stability and cooperation between functional regions. These models and findings provide new insights into nonlinear physics and computational neuroscience.
JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A
(2023)
Article
Mathematics, Applied
Ya Wang, Liang Wang, Huawei Fan, Jun Ma, Hui Cao, Xingang Wang
Summary: Recent in vivo experiments have shown that astrocytes, a type of glial cell previously thought to provide structural and metabolic support to neurons, actively participate in brain functions by regulating neural firing activities. In this study, the authors propose a complex neuron-astrocyte network model and investigate the role of astrocytes in regulating cluster synchronization behaviors of chaotic neurons. They find that a specific set of neurons form a synchronized cluster while the remaining neurons remain desynchronized. Moreover, the cluster switches between synchronous and asynchronous states in an intermittent fashion, known as the breathing cluster phenomenon. The authors conduct theoretical investigations on the synchronizability of the cluster and reveal that the cluster contents are determined by network symmetry, while the breathing of the cluster is attributed to the interplay between the neural network and the astrocyte.
Article
Computer Science, Artificial Intelligence
D. Vignesh, Jun Ma, Santo Banerjee
Summary: In this article, a discrete fractional Hopfield neural network model is proposed to investigate the influence of external stimuli in the presence of electromagnetic induction and radiation. The network model exhibits chaotic dynamics and coexisting behavior. The study also explores the generation of multi-scroll attractors by varying the level of the pulse function introduced to electromagnetic induction. The findings contribute to our understanding of discrete fractional memristors and shed light on the dynamical behavior of neurons and their electrical activity in the brain.
Article
Computer Science, Artificial Intelligence
Fuqiang Wu, Hao Meng, Jun Ma
Summary: Employing electronic components such as memristor and Josephson junction to imitate biological neurons and synapses has been a popular research topic in recent years. This paper revisits a previous work on memristive Josephson junction and proposes a new model called inductive memristive Josephson junction (L-MJJ) by adding an inductor with internal resistor. The L-MJJ model can reproduce the square-wave bursting behavior of classical neuronal models and achieve bursting synchronization similar to nonlinear coupling neurons. This research aims to build a bridge between superconducting physics and theoretical neuroscience, and demonstrates the potential feasibility of using this junction in designing neuron-inspired computations for larger-scale neuromorphic networks.
Article
Mathematics, Applied
Jun Ma
Summary: Continuous dynamical systems with different nonlinear terms can exhibit rich dynamical characteristics. In this study, reliable algorithms for discretization and equivalent maps are proposed to reproduce similar dynamics as the nonlinear oscillators. The application of scale transformation helps convert maps into equivalent nonlinear oscillators and define energy function. Additionally, a generic memristive term is introduced into the map, which can be used to develop memristive oscillators and clarify the energy function and oscillatory characteristics.
APPLIED MATHEMATICS AND COMPUTATION
(2024)
