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Abstract Originating from “rocking‐chair concept”, lithium‐ion batteries (LIBs) have become one of the most important electrochemical energy storage technologies, which have largely impacted our daily life. The utilization of electrolyte additives in small quantities (≤5% by wt or vol) has been long viewed as an economical and efficient approach to regulate the properties of electrolyte and electrode–electrolyte interphases and consequently improve the cycling performance of LIBs. Among all the kinds of electrolyte additives, sulfur‐containing compounds have gained significant attention due to their unique features in building stable electrode–electrolyte interphases and protect battery cells from overcharging. In this work, advances and progresses of sulfur‐containing additives used in LIBs are overviewed, with special attention paid to the working mechanisms of these electrolyte additives. Particularly, four representative sulfur‐containing compounds (i.e., 1,3‐propane sultone, prop‐1‐ene‐1,3‐sultone, 1,3,2‐dioxathiolane‐2,2‐dioxide, and ethylene sulfite) are comparatively discussed concerning their impact on electrode–electrolyte interphases and cell performances. Future work on the development of sulfur‐containing compounds as functional electrolyte additives is also provided. The present review is anticipated to be not only a base document to access the status quo in this research domain but also a guideline to select specialized additives and electrolytes for practical applications.

This paper reports a new fractional-order Chua’s system with arctan function and an algorithm for determining the initial value of fractional-order hidden attractors. Firstly, dynamics of the system is investigated by employing the stability analysis, dissipativeness, phase diagrams, 0-1 test, bifurcation diagram and SampEn complexity measure. It shows rich dynamics in the proposed system. Secondly, using the proposed algorithm, the initial values of the new fractional-order Chua’s system are calculated. And according to two sets of initial conditions, hidden attractors are found and verified by the numerical simulation. Meanwhile, the basin attraction is analyzed to confirm that the hidden attractor is indeed not near the fixed point. Thirdly, the new fractional-order Chua’s system is implemented on the DSP platform, and the arctan function’s processing algorithm is proposed. The DSP experimental results show that the system can produce a pair of coexisting fractional-order hidden attractors, and the experimental results are consistent with the numerical simulation results. It verifies the effectiveness of the presented methods and shows the potential engineering application value of the proposed Chua’s system.

Abstract Discrete chaotic system has complex dynamics and becomes to be a present hot topic, but its analogue circuit implementation is rarely discussed. In this paper, by simplifying the logistic map, a new Logistic‐like map is proposed. Its cobweb plots, bifurcations, Lyapunov exponents, and dynamic map are investigated theoretically and numerically. The results show that the Logistic‐like map has complex dynamical behaviours. And then Psim simulation model is proposed to verify the feasibility of analogue circuit implementation. Finally, an analogue circuit experiment is performed and its results are consistent with the simulation results. The circuit designed is very simple and has less components, which can further broaden the applications of discrete chaotic map in applications.

Further exploration into the influence of a memristor on the behavior of chaotic systems deserves attention. When constructing memristor chaotic systems, it is commonly believed that increasing the number of memristors will lead to better system performance. This paper proposes a class of chaotic maps with different discrete memristors, achieved through internal perturbation based on the Sine map. The I-V curve of the discrete memristor has a symmetrical structure. The dynamic characteristics of the designed system are analyzed using the chaotic attractor phase diagram, Lyapunov exponent (LE) spectrum, and bifurcation diagram. Numerical simulations demonstrate that internal perturbations of discrete memristors enhance the Sine map’s chaotic characteristics, expand the chaos range, and improve the ergodicity and LE value. Moreover, the type of discrete memristors has a significant impact on the dynamic characteristics of the system, while the number of discrete memristors has little influence. Therefore, in this paper, a direction for the design of a discrete memristor chaotic system is provided. Finally, a discrete memristor chaotic map with a simple structure and better performance is selected. Based on this, a pseudo-random sequence generator is designed, and the generated sequence passes the National Institute of Standards and Technology (NIST) test.

Investigation of the classical self-excited and hidden attractors in the modified Chua’s circuit is a hot and interesting topic. In this article, a novel Chua’s circuit system with an absolute item is investigated. According to the mathematical model, dynamic characteristics are analyzed, including symmetry, equilibrium stability analysis, Hopf bifurcation analysis, Lyapunov exponents, bifurcation diagram, and the basin of attraction. The hidden attractors are located theoretically. Then, the coexistence of the hidden limit cycle and self-excited chaotic attractors are observed numerically and experimentally. The numerical simulation results are consistent with the FPGA implementation results. It shows that the hidden attractor can be localized in the digital circuit.

Traumatic brain injury (TBI) is one of the top three specific neurological disorders, requiring reliable, rapid, and sensitive imaging of brain vessels, tissues, and cells for effective diagnosis and treatment. Although the use of medical imaging such as computed tomography (CT) and magnetic resonance imaging (MRI) for the TBI detection is well established, the exploration of novel TBI imaging techniques is of great interest. In this review, recent advances in fluorescence imaging for the diagnosis and evaluation of TBI are summarized and discussed in three sections: imaging of cerebral vessels, imaging of brain tissues and cells, and imaging of TBI-related biomarkers. Design strategies for probes and labels used in TBI fluorescence imaging are also described in detail to inspire broader applications. Moreover, the multimodal TBI imaging platforms combining MRI and fluorescence imaging are also briefly introduced. It is hoped that this review will promote more studies on TBI fluorescence imaging, and enable its use for clinical diagnosis as early as possible, helping TBI patients get better treatment and rehabilitation.

In this paper, we investigate the mathematical models of discrete memristors based on Caputo fractional difference and G–L fractional difference. Specifically, the integer-order discrete memristor is a special model of those two cases. The “∞”-type hysteresis loop curves are observed when input is the bipolar periodic signal. Meanwhile, numerical analysis results show that the area of hysteresis decreases with the increase of frequency of input signal and the decrease of derivative order. Moreover, the memory effect, characteristics and physical realization of the discrete memristors are discussed, and a discrete memristor with short memory effects is designed. Furthermore, discrete memristive systems are designed by introducing the fractional-order discrete memristor and integer-order discrete memristor to the Sine map. Chaos is found in the systems, and complexity of the systems is controlled by the parameter of the memristor. Finally, FPGA digital circuit implementation is carried out for the integer-order and fractional-order discrete memristor and discrete memristive systems, which shows the potential application value of the discrete memristor in the engineering application field.

In recent years, brain–computer interface (BCI) is expected to solve the physiological and psychological needs of patients with motor dysfunction with great individual differences. However, the classification method based on feature extraction requires a lot of prior knowledge when extracting data features and lacks a good measurement standard, which makes the development of BCI. In particular, the development of a multi-classification brain–computer interface is facing a bottleneck. To avoid the blindness and complexity of electroencephalogram (EEG) feature extraction, the deep learning method is applied to the automatic feature extraction of EEG signals. It is necessary to design a classification model with strong robustness and high accuracy for EEG signals. Based on the research and implementation of a BCI system based on a convolutional neural network, this article aims to design a brain–computer interface system that can automatically extract features of EEG signals and classify EEG signals accurately. It can avoid the blindness and time-consuming problems caused by the machine learning method based on feature extraction of EEG data due to the lack of a large amount of prior knowledge.

In this paper, a method for determining the initial value of the hidden attractors in the Chua system is studied. The initial value of the hidden attractors can be calculated quickly and accurately by the proposed method, and the hidden attractors can be found by numerical simulation. Then, the initial values of the hidden attractors are set accurately by digital signal processor (DSP), so as to the circuit realization of the chaotic system with hidden attractors is performed. The results show that the numerical simulation results of Matlab are consistent with the experimental results of DSP.

Based on the proposed generalized memristor, a new jerk system is proposed. The complex dynamics of the system are investigated by means of bifurcation diagrams, Lyapunov exponents, and MSampEn, and rich dynamics are observed. Moreover, the circuits of the generalized memristor and the jerk system are physically implemented in the hardware level. The experimental results show that the memristor circuit can generate “8”-shaped pinched hysteresis loops, and the observed attractors match well with the numerical simulations results. In this paper, we summarize nonlinear systems with memristors in the references. It indicates that there are two symmetry methods to find a memristor model in nonlinear systems. However, some of them cannot be realized using the memristor devices, although a memristor model can be found. For example, the famous Lorenz system contains a memristor function, but it cannot be realized using the memristor device. The principles regarding whether nonlinear systems with a memristor function can be realized using a memristor device are discussed.

Walking is the most common, environment-friendly, and inexpensive type of physical activity. To perform in-depth walkability analysis, one option is to objectively evaluate different aspects of built environment related to walkability. In this study, we proposed a computational framework for walkability measurement using open data. Three major steps of this framework include the web scrapping of publicly available online data, determining varying weights of variables, and generating a synthetic walkability index. The results suggest three major conclusions. First, the proposed framework provides an explicit mechanism for walkability measurement. Second, the synthetic walkability index from this framework is comparable to Walk Score, and it tends to have a slightly higher sensitivity, especially in highly walkable areas in urban core. Third, this framework was effectively applied in a metropolitan area that contains three small cities that together represent a small, old shrinking region, which extends the topical area in the literature. This framework has the potential to quantify walkability in any city, especially cities with a small population where walkability has rarely been studied, or those having no quantification indicator. For such areas, researchers can calculate the synthetic walkability index based on this framework, to assist urban planners, community leaders, health officials, and policymakers in their practices to improve the walking environment of their communities.

Numerical analysis of fractional-order chaotic systems is a hot topic of recent years. The fractional-order Rössler system is solved by a fast discrete iteration which is obtained from the Adomian decomposition method (ADM) and it is implemented on the DSP board. Complex dynamics of the fractional-order chaotic system are analyzed by means of Lyapunov exponent spectra, bifurcation diagrams, and phase diagrams. It shows that the system has rich dynamics with system parameters and the derivative order q. Moreover, tracking synchronization controllers are theoretically designed and numerically investigated. The system can track different signals including chaotic signals from the fractional-order master system and constant signals. It lays a foundation for the application of the fractional-order Rössler system.

The fractional-order hyperchaotic Lorenz system is solved as a discrete map by applying the Adomian decomposition method (ADM). Lyapunov Characteristic Exponents (LCEs) of this system are calculated according to this deduced discrete map. Complexity of this system versus parameters are analyzed by LCEs, bifurcation diagrams, phase portraits, complexity algorithms. Results show that this system has rich dynamical behaviors. Chaos and hyperchaos can be generated by decreasing fractional order q in this system. It also shows that the system is more complex when q takes smaller values. SE and C 0 complexity algorithms provide a parameter choice criteria for practice applications of fractional-order chaotic systems. The fractional-order system is implemented by digital signal processor (DSP), and a pseudo-random bit generator is designed based on the implemented system, which passes the NIST test successfully.