Due to the low cost and abundance of multivalent metallic resources (Mg/Al/Zn/Ca), multivalent rechargeable batteries (MRBs) are promising alternatives to Li-ion and Pb-acid batteries for grid-scale ...stationary energy storage applications. However, the high performance of inorganic electrode materials in Li-ion batteries does not extend to MRBs, because the high charge density of multivalent cations dramatically reduces their diffusivity in the crystal lattice of inorganic materials. To achieve high-performance MRBs, organic electrode materials (OEMs) with abundant structural diversity and high structural tunability offer opportunities. This review presents an overview of the state-of-the-art OEMs in MRBs, including non-aqueous rechargeable Mg/Al/Zn and aqueous rechargeable Mg/Al/Zn/Ca batteries. The advantages, challenges, development, mechanism, structure, and performance of OEMs in MRBs are discussed in detail. To provide a comprehensive and thorough understanding of OEMs in MRBs, the correlation between molecular structure and electrochemical behavior is also summarized and discussed. This review offers insights for the rational structure design and performance optimization of advanced OEMs in MRBs.
This review summarizes state-of-the-art organic electrode materials in multivalent rechargeable batteries and discusses the correlation between structure and performance.
The prediction of time series has both the theoretical value and practical significance in reality. However, since the high nonlinear and noises in the time series, it is still an open problem to ...tackle with the uncertainties and fuzziness in the forecasting process. In this article, an evolving recurrent interval type-2 intuitionistic fuzzy neural network (eRIT2IFNN) is proposed for time series prediction and regression problems. The eRIT2IFNN employs interval type-2 intuitionistic fuzzy sets to enhance the modeling of uncertainties by intuitionistic evaluation and noise tolerance of the system. In the eRIT2IFNN, the antecedent part of each fuzzy rule is defined using intuitionistic interval type-2 fuzzy sets, and the consequent realizes the Takagi–Sugeno–Kang type fuzzy inference mechanism. In order to utilize the prior knowledge including intuitionistic information, a local internal feedback is established by feeding the rule firing strength of each rule to itself eRIT2IFNN is fully adaptive to the evolving of sequence data by online learning of structure and parameters. A modified density-based clustering is implemented for the structure learning, where both densities and membership degrees are involved to determine the fuzzy rules. Performance of eRIT2IFNN is evaluated using a set of benchmark problems and compared with existing fuzzy inference systems. Moreover, the eRIT2IFNN is tested for identification of dynamics under both noise-free and noisy environments. Finally, a group of practical financial price-tracking problems including high-frequency data of financial future, commodity future and precious metal are used for the evaluation of the proposed inference system.
•A novel recurrent structure utilizing interval type-2 intuitionistic fuzzy set is proposed.•Self-evolving structure based on density clustering and intuitionistic evaluation.•The uncertain mean of interval type-2 intuitionistic fuzzy set is first constructed.
Pulsation is a universal phenomenon that exists in diverse fields. For nonlinear optics, the soliton pulsating behavior can be meaningful for fundamental physics and industrial purpose owing to its ...fruitful nonlinear dynamics and the possible detrimental effect of instability (or even route to chaos) during pulsating process. Herein, a novel type of soliton pulsation in an ultrafast laser is unveiled. The pulsating behavior features that the soliton experiences periodic peak power variation but with almost invariable pulse energy. This phenomenon is denoted as “invisible soliton pulsation” when referring to the routine diagnostic methods. However, the invisible soliton pulsation can be distinguished by recording the shot‐to‐shot spectra with real‐time spectroscopy technique. It is found that the appearance of the invisible soliton pulsation is sensitive to the pump power level. Moreover, the phenomenon of invisible soliton pulsation is further revealed by numerical simulations. These findings can shed new insights into the complex nonlinear behavior of solitons in dissipative optical systems, and also enrich the performance diagnostic of ultrafast lasers for practical applications.
A novel type of soliton pulsation in an ultrafast laser is unveiled with real‐time spectroscopy technique. It features that the mode‐locked spectrum evolves with time, but the pulse energy remains almost unchanged. Since the pulsation cannot be resolved by the routine diagnostic methods, it can be termed as “invisible” soliton pulsation. Moreover, the phenomenon is further revealed by numerical simulations.
Few-layer black phosphorus (BP), as the most alluring graphene analogue owing to its similar structure as graphene and thickness dependent direct band-gap, has now triggered a new wave of research on ...two-dimensional (2D) materials based photonics and optoelectronics. However, a major obstacle of practical applications for few-layer BPs comes from their instabilities of laser-induced optical damage. Herein, we demonstrate that, few-layer BPs, which was fabricated through the liquid exfoliation approach, can be developed as a new and practical saturable absorber (SA) by depositing few-layer BPs with microfiber. The saturable absorption property of few-layer BPs had been verified through an open-aperture z-scan measurement at the telecommunication band. The microfiber-based BP device had been found to show a saturable average power of ~4.5 mW and a modulation depth of 10.9%, which is further confirmed through a balanced twin detection measurement. By integrating this optical SA device into an erbium-doped fiber laser, it was found that it can deliver the mode-locked pulse with duration down to 940 fs with central wavelength tunable from 1532 nm to 1570 nm. The prevention of BP from oxidation through the "lateral interaction scheme" owing to this microfiber-based few-layer BP SA device might partially mitigate the optical damage problem of BP. Our results not only demonstrate that black phosphorus might be another promising SA material for ultrafast photonics, but also provide a practical solution to solve the optical damage problem of black phosphorus by assembling with waveguide structures such as microfiber.
To investigate the effect and potential mechanisms of lactoferrin on colon cancer cells and tumors, HT29 and HCT8 cells were exposed to varying concentrations of lactoferrin, and the impacts on cell ...proliferation, migration, and invasion were observed. Cell proliferation test showed that high dosage of lactoferrin (5–100 mg/mL) inhibited cell viability in a dose-dependent manner, with the 50% concentration of inhibition at 81.3 ± 16.7 mg/mL and 101 ± 23.8 mg/mL for HT29 and HCT8 cells, respectively. Interestingly, migration and invasion of the cells were inhibited dramatically by 20 mg/mL lactoferrin, consistent with the significant down regulation of VEGFR2, VEGFA, pPI3K, pAkt, and pErk1/2 proteins. HT29 was chosen as the sensitive cell line to construct a tumor-bearing nude mice model. Notably, HT29 tumor weight was greatly reduced in both the lactoferrin group (26.5 ± 6.7 mg) and the lactoferrin/5-Fu group (14.5 ± 5.1 mg), compared with the control one (39.3 ± 6.5 mg), indicating that lactoferrin functioned as a tumor growth inhibitor. Considering lactoferrin also reduced the growth of blood vessels and the degree of malignancy, we concluded that HT29 tumors were effectively suppressed by lactoferrin, which might be achieved by regulation of phosphorylation from various kinases and activation of the VEGFR2-PI3K/Akt-Erk1/2 pathway.
Lithium-ion batteries raise safety, environmental, and cost concerns, which mostly arise from their nonaqueous electrolytes. The use of aqueous alternatives is limited by their narrow electrochemical ...stability window (1.23 volts), which sets an intrinsic limit on the practical voltage and energy output. We report a highly concentrated aqueous electrolyte whose window was expanded to ~3.0 volts with the formation of an electrode-electrolyte interphase. A full lithium-ion battery of 2.3 volts using such an aqueous electrolyte was demonstrated to cycle up to 1000 times, with nearly 100% coulombic efficiency at both low (0.15 coulomb) and high (4.5 coulombs) discharge and charge rates.
Quantitative trading based on intelligent algorithms has been a hot topic in the financial fields. However, the high noises and outliers increase the uncertainty and non-stationary of financial data ...such that intelligent algorithms often cease to be effective in the application scenario. Therefore, how to reduce the influence of uncertainty and extract the main trends of financial data is meaningful for trading. Motivated by it, in this article, a novel trading system based on intuitionistic fuzzy neural networks with gated recurrent unit (GRU) is proposed. Firstly, empirical mode decomposition (EMD) is applied to preprocess the original data and obtain the main trends of financial time series on the basis of smoothing data. Secondly, in order to tackle with uncertainty of financial data, a novel interval type-2 intuitionistic fuzzy system (IT2IFS) is proposed for the reasoning process, where hesitancydegree is involved for the learning processes In view of the strong dependence on the time dimension of series data, the gated recurrent unit is integrated into the reasoning model to strengthen the temporal connection. Thirdly, by using the above IT2IFS-GRU model, the quantitative trading system with a concise trading strategy is constructed. By using commodity futures and foreign exchange data, the superior trading results including net profits and precisions, etc. can be obtained, which verifies the effectiveness and availability of the proposed model.
•A novel interval type-2 intuitionistic fuzzy neural network with GRU is proposed.•The adaptively adjusted parameters of the quantitative trading system.•EMD is applied to capture the main trends of financial data.
A very compact ultrawideband (UWB) multiple-input multiple-output (MIMO) antenna with high isolation is presented in this letter. The proposed antenna, consisting of two UWB slot antennas, has a very ...compact size of 22 ×26 mm 2 , which is smaller than most of UWB antennas only with single antenna element. A T-shaped slot is etched on the ground to improve the impedance matching characteristic in the low-frequency and reduce the mutual coupling for the frequencies ≥ 4 GHz. By etching a line slot to cancel out original coupling, isolation enhancement at the 3-4 GHz band is achieved. The antenna possesses a low mutual coupling of less than - 18 dB over the operating band from 3.1-10.6 GHz. The performance of this antenna both by simulation and by experiment indicates that the proposed antenna is a good candidate for UWB applications.
When applying artificial intelligence technology to quantitative trading, high noise and unpredictability of market environment are the first practical problems to be considered. Therefore, how to ...select the learning features of the market based on rapidly changing financial data is particularly important. In this paper, the real time financial data are first processed by K-line theory, which uses candlesticks as a generalization of price movements over a period of time, so this process can play the role of de-noising. Then, the candlesticks are decomposed into different subparts by mean of a specified spatio-temporal relationship, based on which cluster analysis of the subparts to get the learning features. Further, the learning features that are clustered by the above K-lines are put into the model, and the online adaptive control of the parameters in the unknown environment is realized by the deep reinforcement learning method, so as to realize the high frequency transaction strategy. In order to verify the performance of the model, the data on different financial derivatives transactions such as stocks, financial futures and commodity futures are used. The proposal approach is compared with other methods which are based on price, fuzzified price and K-lines for features learning. In order to verify the accuracy of the proposal approach, prediction-based methods such as recurrent neural network and fuzzy neural network are used for comparison. Experimental results show that the proposed method has higher robustness and prediction accuracy.
In this article, a novel dynamic system, the fractional-order complex Lorenz system, is proposed. Dynamic behaviors of a fractional-order chaotic system in complex space are investigated for the ...first time. Chaotic regions and periodic windows are explored as well as different types of motion shown along the routes to chaos. Numerical experiments by means of phase portraits, bifurcation diagrams and the largest Lyapunov exponent are involved. A new method to search the lowest order of the fractional-order system is discussed. Based on the above result, a synchronization scheme in fractional-order complex Lorenz systems is presented and the corresponding numerical simulations demonstrate the effectiveness and feasibility of the proposed scheme.
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