Zhisheng Lv

One-step fabrication of membraneless microbial fuel cell cathode by electropolymerization of polypyrrole onto stainless steel mesh.

A unique one-step method for fabrication of a membraneless microbial fuel cell (MFC) cathode was developed by coating a conductive polymer onto stainless steel mesh. The resulting polypyrrole/anthraquinone-2-sulfonate (PPy/AQS) film was synthesized via electropolymerization using AQS as the dopants. The scanning electron microscopy results indicated that the PPy/AQS film was uniformly formed on the metal mesh electrode without cracks on its surface and featuring a globular structure. Being equipped with such a cathode that was able to catalyze oxygen reduction and prevent water leakage, the membraneless MFC allowed power generation over 250 h and exhibited a maximum power density of 575 mW m(-2). Increasing film thickness seemed to result in a reduction in power performance due to the increased ohmic resistance of the cathode material and the enhanced difficulty for oxygen diffusion inside the cathode.

Anode-biofilm electron transfer behavior and wastewater treatment under different operational modes of bioelectrochemical system.

Anode-biofilm electron transfer behavior was investigated during the advanced wastewater treatment process by three bioelectrochemical systems (BESs): microbial fuel cell (MFC), MFC operated under short circuit condition (MSC), and microbial electrolysis cell (MEC). Under different operational modes, current produced by the anode biofilm varied from 0.92, 4.15 to 8.21mA in the sequence of MFC, MSC and MEC, respectively. The cyclic voltammetry test on the anode biofilm suggested that the current generation was achieved via various bioelectroactive species with formal potentials at -0.473, -0.402 and -0.345V (vs. SCE). Gibbs free energy and charge transfer resistance data demonstrated that different amounts of available bioelectroactive species functioned in different BESs. The comparative investigation among MFC, MSC and MEC suggested that MEC was the only feasible operational mode for advanced wastewater treatment, because of its superior current generation capability.

Audio forensic authentication based on MOCC between ENF and reference signals

This paper proposes a new audio authenticity detection algorithm based on the max offset for cross correlation (MOCC) between the extracted ENF (Electric Network Frequency) signal and the reference signal. We first extract the ENF signal from a query audio signal. And then we partition it into overlapping blocks for forgery detection. The MOCC between the extracted ENF and the reference signal is calculated block by block. We also introduce an enhancement scheme to improve the quality of the ENF signal before the calculation of the MOCC. Our proposed method can detect not only audio forgery but also the edited region and audio forgery type. The effectiveness of our method has been verified by experiments on digitally edited audio signals.

Audio forgery detection based on max offsets for cross correlation between ENF and reference signal

The electric network frequency (ENF) is likely to be embedded in audio signals when the electronic recording devices are connected to electric power lines. If an audio signal is edited, the embedded ENF will be altered inevitably. In order to assess audio authenticity, this paper proposes a new method based on the max offset for cross correlation between the extracted ENF and the reference signal. By comparing the max offsets on a block-by-block basis, we can determine whether the audio signal in question was digitally edited as well as the location at which the editing manipulation occurs. The validity and effectiveness of our method have been verified by experiments on both synthetic composite signals and real-world audio signals.

Blind Neural Network Equalizer Based on QAM and Constant Modulus Algorithm

By using QAM signals as input, this paper adopts a blind equalizer based on neural network and constant modulus algorithm. By very few training serial signals to make the network convergent, and then the equalizer changes to the blind algorithm. The simulations show that this equalizer has better performance whether at convergence speed or the remnant errors’ energy, and its convergence capability is steady.