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Array optimization has recently received significant attention owing to its several advantages, such as larger array aperture and greater degrees of freedom (DOFs). However, current works focus on far-field sources, while array optimization for near-field sources has not been adequately investigated. Therefore, this work develops a new symmetry sparse array model for near-field sources based on the improved maximum inter-element spacing constraint (IMISC). The proposed symmetry IMISC (S-IMISC) array model has all the advantages of traditional sparse array models. Compared with traditional sparse array models, the S-IMISC array model affords more uniform DOFs and is less affected by mutual coupling. Additionally, in order to improve the real-time performance of near-field sources localization, the characteristic equation-based method (CEM) is used to obtain the azimuth information of near-field sources which can avoid eigenvalue decomposition (EVD), and a spectrum peak search and compression scheme is used to obtain the distance information by searching the partial area instead of the whole Fresnel area, thereby significantly reducing computation complexity. Extensive simulations verify the advantages of the proposed algorithm and the S-IMISC array model.

Vehicle positioning has played an important role in intelligent transportation systems. Previous research has had difficulties in increasing the sensor aperture and reducing the computational complexity of the vehicle positioning algorithm. This paper proposes a new sensor model to extend the sensor aperture, which is similar to the nested sensor model combined with fourth-order cumulants. The proposed algorithm estimates the number of vehicles, which is much higher than the actual number of sensors. An ideal characteristic equation-based method is used to avoid the use of eigenvalue decomposition and spectrum peak search, thereby greatly reducing the computation complexity. In addition, the weighted coefficient matrix is introduced for optimization. Theoretical analysis and simulation results show that the proposed algorithm has lower computational complexity, avoids 2-D parameter matching, and has a high utilization of arrays while still ensuring accurate parameter estimation.

Lead accetate is an important lead source for preparation of organolead trihalide perovskites. In this work, we improved the performance of lead accetate based perovskite solar cells (PSCs) using a mix-solvent of γ-butyrolactone/dimethyl-sulfoxide (GBL/DMSO). Compared with the use of N,N-dimethylformamide (DMF)/DMSO, using GBL/DMSO efficiently retarded the crystallization of perovskite, which improved the crystallinity of the perovskite films. Consequently, the perovskite films processed from GBL/DMSO showed higher light harvesting, longer carrier lifetime and suppressed charge recombination properties in the PSCs. Power conversion efficiency (PCE) of the PSCs was significantly improved from 16.6 to 17.7% with simultaneous improvement in open-circuit voltage, short-circuit current density and fill factor. The best PSC showed a champion PCE of 18.1%, with a stable power output and negligible hysteresis. Moreover, the flexible PSCs (based on polyethylene naphthalate substrates) with perovskite processed from GBL/DMSO exhibited a high PCE of 13.2%. Our results indicate that using GBL/DMSO as a mix-solvent is a simple and effective way for performance improvement of lead-acetate-based PSCs.

Toxins, such as tetraethylammonium (TEA) and tetrodotoxin (TTX), can make potassium or sodium ion channels poisoned, respectively, and hence reduce the number of working ion channels and lead to the diminishment of conductance. In this paper, we have studied by numerical simulations the effects of sodium and potassium ion channel poisoning on the collective spiking activity of an array of coupled stochastic Hodgkin-Huxley (HH) neurons. It is found for a given number of neurons sodium or potassium ion channel block can either enhance or reduce the collective spiking regularity, depending on the membrane patch size. For a given smaller or larger patch size, potassium and sodium ion channel block can reduce or enhance the collective spiking regularity, but they have different patch size ranges for the transformation. This result shows that sodium or potassium ion channel block might have different effects on the collective spiking activity in coupled HH neurons from the effects for a single neuron, which represents the interplay among the diminishment of maximal conductance and the increase of channel noise strength due to the channel blocks, as well as the bi-directional coupling between the neurons.

In this paper, on the basis of mesoscopic stochastic model of NO reduction by CO on single-crystal platinum surfaces, we report a novel effect of the external noise of reaction rate constant coupled to internal noise in stochastic resonance induced by external noise (SREN) or internal noise (SRIN). It is shown that the internal noise can enhance the SREN, and the external noise intensity for the SREN increases with increasing internal noise. However, the external noise can suppress the SRIN, and the suppressions nonmonotonously vary with the increasing external noise intensity. This result is different from the effect of the external noise of NO partial pressure coupled to the internal noise in the SR behavior of the system, which shows that the various external noise sources have different effects in the SRIN. And different roles of positive or negative feedback of the external noise terms may be a probable mechanism for the difference.