Zou F.,Shanghai UniversityShanghai |
Wu B.,Shanghai UniversityShanghai |
Wang X.,Shanghai UniversityShanghai |
Wang X.,Shanghai University |
And 4 more authors.
Sensors and Actuators, B: Chemical | Year: 2017
A signal-amplification and dual-recognition strategy was designed to construct a signal-enhanced surface plasmon resonance (SPR) platform for the highly sensitive detection of dopamine. This strategy was based on the specific recognition of boronic acid to diol and that of calixarene crown ether-modified gold nanoparticles (CAL-AuNPs) to amine groups. A 3-aminophenyl boronic acid monohydrate probe was immobilized onto a gold chip surface as capture probes via covalent bonds with 11-mercaptoundecanoic acid. CAL-AuNPs were designed as signal probes and characterized by transmission electron microscopy and spectroscopic techniques. Upon the binding of dopamine with boronic acid followed by CAL-AuNPs, the AuNPs were captured on the chip surface to enhance the SPR signal, thereby producing an ultra-low background signal. Signal amplification and dual recognition were used to quantify dopamine concentration from 0.1 nM to 1 μM, with a detection limit of 1.17 pM. This strategy is a new concept for the design of highly selective analytical methods to detect small biomolecules. © 2016
Ma Y.,Shanghai University |
Sheng L.,Shanghai University |
Zhao H.,Shanghai UniversityShanghai |
An K.,Shanghai University |
And 3 more authors.
Solid State Sciences | Year: 2015
Abstract In this study, NiO/carbon shell/single-walled carbon nanotube composites are prepared by heat treating the single-walled carbon nanotube samples synthesized by direct current arc discharge method. The morphology and nanostructure of the composites are affected by the heat treatment temperature according to the X-ray diffraction, Raman spectra and high-resolution transmission electron microscopy results. The electrochemical measurements are evaluated in coin-type cells versus metallic lithium. After heat treatment in H2 at 600 °C for 1 h and in air at 300 °C for 10 h, the NiO nanoparticles encapsulated by carbon shells are evenly distributed on the surface of web-like single-walled carbon nanotubes and a perfect NiO/carbon shell/single-walled carbon nanotube nanostructure is formed. This NiO/carbon shell/single-walled carbon nanotube composite shows a high reversible specific capacity of 758 mA h g-1 after 60 cycles at a current density of 100 mA g-1 and an excellent rate capacity of about 594 mA h g-1 even at a high current density of 1600 mA g-1. Therefore, the NiO/carbon shell/single-walled carbon nanotube composites have significant potential for applications in energy storage devices. © 2015 Elsevier Masson SAS.
Ma H.,Shaoxing University |
Ma H.,Shanghai University |
Su S.,Shanghai UniversityShanghai |
Simon D.,Cleveland State University |
Fei M.,Shanghai University
Engineering Applications of Artificial Intelligence | Year: 2015
This paper proposes an ensemble multi-objective biogeography-based optimization (EMBBO) algorithm, which is inspired by ensemble learning, to solve the automated warehouse scheduling problem. First, a real-world automated warehouse scheduling problem is formulated as a constrained multi-objective optimization problem. Then EMBBO is formulated as a combination of several multi-objective biogeography-based optimization (MBBO) algorithms, including vector evaluated biogeography-based optimization (VEBBO), non-dominated sorting biogeography-based optimization (NSBBO), and niched Pareto biogeography-based optimization (NPBBO). Performance is tested on a set of 10 unconstrained multi-objective benchmark functions and 10 constrained multi-objective benchmark functions from the 2009 Congress on Evolutionary Computation (CEC), and compared with single constituent MBBO and CEC competition algorithms. Results show that EMBBO is better than its constituent algorithms, and among the best CEC competition algorithms, for the benchmark functions studied in this paper. Finally, EMBBO is successfully applied to the automated warehouse scheduling problem, and the results show that EMBBO is a competitive algorithm for automated warehouse scheduling. © 2015 Elsevier Ltd.
Wu P.,Shanghai UniversityShanghai |
Xie S.,Shanghai UniversityShanghai |
Luo J.,Shanghai UniversityShanghai |
Qu D.,Shanghai UniversityShanghai |
Li Q.,Shanghai Second Polytechnic University
Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia | Year: 2015
The robot path planning is the important element of .the robot navigation. There were several algorithms for obstacle planning, but the most efficient obstacle avoidance algorithm has not been found. So we should continue to research the problem. Artificial Potential Field (APF) and Ant Colony Optimization (ACO) are often used in local and global path planning. However there are some inherent problems, for examples, the problem of GNRON in APF, slow convergence and prematurity in ACO. In order to solve this issue, the global path planning should be compensated by the local path planning. In this paper, we combine the ACO algorithm with Artificial Potential Field (APF)algorithm in goal path planning, and then the modified ACO algorithm can drive the USV to the target. Otherwise, when the environment is changeable, the algorithm switches to the Angle Potential Field method and the robot can escape from the dilemma smoothly. Then the initial global planning algorithm continues to drive the robot to the target. Finally, the simulation results demonstrate that the modified method is with high quality in optimal path planning.
Lu X.-J.,Shanghai UniversityShanghai |
Lu X.-J.,Polytechnic University of Valencia |
Palmero M.,Polytechnic University of Valencia |
Ruschhaupt A.,University College CorkCork |
And 3 more authors.
Physica Scripta | Year: 2015
We investigate the effect of slow spring-constant drifts of the trap used to shuttle two ions of different mass. We design transport protocols to suppress or mitigate the final excitation energy by applying invariant-based inverse engineering, perturbation theory, and a harmonic dynamical normal-mode approximation. A simple, explicit trigonometric protocol for the trap trajectory is found to be robust with respect to the spring-constant drifts. © 2015 The Royal Swedish Academy of Sciences.
Xing X.,Shanghai UniversityShanghai |
Min J.,Shanghai UniversityShanghai |
Liang X.,Shanghai UniversityShanghai |
Zhang J.,Shanghai UniversityShanghai |
And 5 more authors.
Journal of Crystal Growth | Year: 2015
Abstract The In-doped Cd0.9Zn0.1Te (CZT) crystals were grown by the modified Vertical Bridgeman method and treated by in-situ annealing with six different cooling rates. Photo-Induced Transient Spectroscopy (PICTS) and IR microscopy were employed to investigate the evolution mechanism of point defects and bulk defects (mainly Te inclusions) in the CZT crystals with different cooling rates. Related optical and electrical properties were investigated by Fourier Transform Infrared Spectrometer (FTIR) and I-V measurements. The results indicated that cooling at slow rate (10-20 K/h) could decrease the concentration of point defects, such as A center, Cd vacancy (formula presented), Te antisite (formula presented) and so on, while the Te inclusions are of larger dimension and lower concentration. Otherwise, the faster cooling rate (50-60 K/h), the higher concentration of these point defects, and Te inclusion present small size but much larger concentration. Moreover, cooling too fast or too slow significantly degrades the optical and electrical properties. When cooled at 30-40 K/h, the concentration of internal point defects is the lowest, suggesting that VCd2- compensated with TeCd2+ to reach a new equilibrium corresponding to the theory of quasichemical defect reactions (QCDR). In addition, a certain concentration of TeCd2+ was beneficial to pin the Fermi-level, and the Te inclusions presented lowest total volume fraction, which made the crystals perform great with higher resistivity and infrared transmittance. © 2015 Elsevier B.V.