Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Do funded papers attract more usage?

Research funding has been seen as one of the most important resource in the reward system of science. And usage of publications denotes an interesting perspective of user behavior in scientific communication. This study aims to address the relationship between funding and Usage Count, which is a new metrics item established on the platform of Web of Science. Full records of 300,010 articles published in 2013 were downloaded in October 2015, and divided into six disciplines, including information science library science, education educational research, economics, computer science, materials science, and chemistry. Seven indicators were proposed to measure the impact, including Funding rate, Citation per paper, Usage rate, Usage per paper, Citation difference, Usage difference, and Conversion rate. It concluded funding has impact on usage and citation, and funded papers attract more usage, but varying in different disciplines. Usage Count can be used in the extension of citation metrics but with limits. This study originally engages with usage metrics and detected that there is positive correlation between usage and funding.     

Headspace fingerprinting approach to identify the major pathway influencing volatile patterns of vinasse-cured duck processed by high pressure,as well as its impact on physicochemical and sensory attributes

As a decisive attribute, flavour could be influenced by HP treatments through multiple physical and chemical pathways within the high pressure (HP)-assisted meat curing process. This investigation aimed to identify the major pathway influencing volatile flavour patterns of two representative vinasse-cured duck (VCD) products with HP treatments (150–300 MPa/15 min), including wet and dry types, by employing headspace fingerprinting as an untargeted approach. Results suggested that HP treatments greatly lowered moisture contents and increased Warner-Bratzler shear force and thiobarbituric acid reactive substances of the cured samples. According to multivariate models, the volatile flavour patterns of the HP-processed VCD could be clearly separated from the unprocessed samples, but the VCD pressurised at different intensities represented similar volatile fingerprinting, which was validated by e-nose analysis. The discriminant analysis (OPLS-DA) model outlined vinasse-derived ethanol, acetic acid, 3-methyl-1-butanol, 2-methyl-1-butanol, phenethyl alcohol and 2-methyl-3-octanone as the major discriminant aromas across the unpressurised and pressurised samples.     

Effects of structural characteristics on microwave dielectric properties of low-loss (Zn1-xNix)ZrNbTaO8 ceramics

Low-loss (Zn_1-xNi_x)ZrNbTaO₈ (0.02?≤?x?≤?0.10) ceramics possessing single wolframite structure are initiatively synthesized by solid-state route. Based on the results of Rietveld refinement, complex chemical bond theory is used to establish the correlation between structural characteristics and microwave performance in this ceramic system. A small amount of Ni²⁺ (x?=?0.06) in A-site with the fixed substitution of Ta⁵⁺ in B-site can effectually raise the Q?×?f value of ZnZrNb₂O₈ ceramic, embodying a dense microstructure and high lattice energy. The dielectric constant and τ_f are mainly affected by bond ionicity and the average octahedral distortion. The (Zn_0.94Ni_0.06)ZrNbTaO₈ ceramic sample sintered at 1150?°C for 3?h exhibits an outstanding combination of microwave dielectric properties: ε_r =?27.88, Q?×?f?=?128,951?GHz, τ_f =?–39.9?ppm/°C. Thus, it is considered to be a candidate material for the communication device applications at high frequency.