Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein–Wiener system based on the key-term separation

The identification of the Hammerstein–Wiener (H-W) systems based on the nonuniform input–output dataset remains a challenging problem. This article studies the identification problem of a periodically nonuniformly sampled-data H-W system. In addition, the product terms of the parameters in the H-W system are inevitable. In order to solve the problem, the key-term separation is applied and two algorithms are proposed. One is the key-term-based forgetting factor stochastic gradient (KT-FFSG) algorithm based on the gradient search. The other is the key-term-based hierarchical forgetting factor stochastic gradient (KT-HFFSG) algorithm. Compared with the KT-FFSG algorithm, the KT-HFFSG algorithm gives more accurate estimates. The simulation results indicate that the proposed algorithms are effective.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Controlling thickness to tune performance of high-mobility transparent conducting films deposited from Ga-doped ZnO ceramic target

Structure modification has been found to tune significantly the transparent-conducting performance, especially mobility and conductivity of hydrogenated Ga-doped ZnO (HGZO) films. The strong correlation between film thickness and mobility of the films is revealed. The mobility increases quickly with increasing the thickness from 350 to 900 nm, and then tends to be saturated at further thicknesses. A higher mobility than 50 cm²/Vs can be achieved, which is an extra-high value for polycrystalline ZnO films deposited by using the sputtering technique. The thickness-dependent mobility originates from scatterings on grain boundaries and dislocation-induced defects controlled by thin-film growth. Based on the Volmer-Weber model, an expansion model is built up to describe the thickness-dependent crystal growth of the HGZO films, especially at the thick films. As a result, the 800 nm-thick HGZO film obtains the highest performance with high mobility of 51.5 cm²/Vs, low resistivity of 5.3 × 10^?4 Ωcm, and good transmittance of 83.3 %.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Sequence-Dependent Nanofiber Structures of Phenylalanine and Isoleucine Tripeptides

The molecular design of short peptides to achieve a tailor-made functional architecture has attracted attention during the past decade but remains challenging as a result of insufficient understanding of the relationship between peptide sequence and assembled supramolecular structures. We report a hybrid-resolution model to computationally explore the sequence–structure relationship of self-assembly for tripeptides containing only phenylalanine and isoleucine. We found that all these tripeptides have a tendency to assemble into nanofibers composed of laterally associated filaments. Molecular arrangements within the assemblies are diverse and vary depending on the sequences. This structural diversity originates from (1) distinct conformations of peptide building blocks that lead to different surface geometries of the filaments and (2) unique sidechain arrangements at the filament interfaces for each sequence. Many conformations are available for tripeptides in solution, but only an extended β-strand and another resembling a right-handed turn are observed in assemblies. It was found that the sequence dependence of these conformations and the packing of resulting filaments are determined by multiple competing noncovalent forces, with hydrophobic interactions involving Phe being particularly important. The sequence pattern for each type of assembly conformation and packing has been identified. These results highlight the importance of the interplay between conformation, molecular packing, and sequences for determining detailed nanostructures of peptides and provide a detailed insight to support a more precise design of peptide-based nanomaterials.     

Aripiprazole as a potential pharmacotherapy for stimulant dependence: Human laboratory studies with d-amphetamine.

Amphetamine and cocaine dependence present significant public health concerns, yet no broadly effective pharmacotherapy for stimulant dependence has been developed. Two human laboratory studies are reviewed that tested the ability of aripiprazole, a novel antipsychotic with partial agonist activity at D2 dopamine receptors, to alter the behavioral effects of stimulants using d-amphetamine as a model agent. In each of these experiments, volunteers learned to discriminate 15 mg d-amphetamine (i.e., ≥80% drug-appropriate responding over 4 consecutive sessions). The effects of a range of doses of d-amphetamine (0, 2.5, 5, 10, and 15 mg) were then tested alone and following pretreatment with aripiprazole (20 mg in Experiment 1; 10 mg in Experiment 2). In Experiment 1, aripiprazole (20 mg) attenuated the discriminative stimulus and many of the subject-rated effects of amphetamine. Aripiprazole alone produced performance decrements. To determine whether a lower dose of aripiprazole would also attenuate the behavioral effects of d-amphetamine without impairing performance, Experiment 2 was conducted. Aripiprazole (10 mg) failed to alter the discriminative-stimulus effects but attenuated some of the subject-rated effects of d-amphetamine. This dose of aripiprazole did not impair performance. The results of these experiments indicate that aripiprazole may have clinical utility in treating stimulant dependence. Future human laboratory research should better model the clinical use of aripiprazole by examining the effects of chronic aripiprazole combined with either methamphetamine or cocaine in dependent individuals. A large-scale clinical trial is also needed to evaluate the efficacy of aripiprazole for the treatment of stimulant dependence. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

异构分层无线网络中基于逗留时间的动态流量均衡算法研究

为使异构分层无线网络能服务更多的移动用户,提出了一种基于逗留时间的动态流量均衡算法.该算法首先根据用户移动模型计算其在小区内的逗留时间,然后基于小区呼叫到达率和重叠覆盖小区的流量状态来确定一个周期内呼叫转移的数量,最后依据逗留时间门限值将重负载小区中满足条件的呼叫转移到轻负载的重叠覆盖小区中.为降低切换呼叫掉线率,还对异构网间的呼叫切换策略做了改进.仿真实验结果表明,本算法在新呼叫阻塞率和切换呼叫掉线率等性能指标上比传统方法有显著的提高.     

介孔-大孔结构无定形硅-铝催化剂的核磁共振研究

合成了具有介孔-大孔双模型分级结构的无定形硅-铝催化剂,利用硅和铝核的固体魔角核磁共振谱,考察了合成样品中硅和铝结构上的原子特征.