Hydrogen recovery from the photovoltaic electroflocculation-flotation process for harvesting Chlorella pyrenoidosa microalgae

In this paper, an integrated process using photovoltaic power to harvest microalgae by electro-flocculation (EF) and hydrogen recovery is presented. It is mainly favorable in regions with high solar radiation. The electro-flocculation efficiency (EFE) of Chlorella pyrenoidosa microalgae was investigated using various types of electrodes (aluminum, iron, zinc, copper and a non-sacrificial electrode of carbon). The best results regarding the EFE, and biomass contamination were achieved with aluminum and carbon electrodes where the electrical energy demand of the process for harvesting 1 kg of algae biomass was 0.28 and 0.34 kWh, respectively, while the energy yield of harvested hydrogen was 0.052 and 0.005 kWh kg^?1, respectively. The highest harvesting efficiency of 95.83 ± 0.87% was obtained with the aluminum electrode.The experimental hydrogen yields obtained were comparable with those calculated from theory. With a low net energy demand, microalgae EF may be a useful and low-cost technology.     

Preparations and characterizations of new series of TTF ligands containing a nitrogen aromatic heterocycle

The detailed synthesis of a new series of conjugated TTF ligands with nitrogen-based aromatic heterocycle are presented. In all these molecules, trimethyl-TTF or TTF skeleton are bridged to the nitrogen aromatic ligand through a conjugated spacer such as ethenyl or phenylethenyl unit. Their electrochemical characterization as well as the crystal structure of one of these compounds is given.     

Performance comparison between Gaussian interleaver, Rayleigh interleaver, and dithered golden interleaver

This paper is a proposal for a new form of random interleaver for a turbo code based on the probability distribution of channel statistic model of transmission, instead of a uniform probability distribution. In our work, we use the normal (Gaussian) and Rayleigh probability distribution in accordance with the channel type and compare them with classic random interleaver (uniform distribution) and with dithered golden interleaver [invention of the Communications Research Centre (CRC)]. The results show that this new form of random interleaver gives identical results compared to the simulated case of dithered golden interleaver.     

Speech Modeling via Model Reduction

Using model reduction, a new approach for low-order speech modeling is presented. In this approach, the modeling process starts with a relatively high-order (full-order) autoregressive (AR) model obtained by some classical methods. The AR model is then reduced using the state projection method, operating in the state space. The model reduction yields a reduced-order autoregressive moving-average (ARMA) model that interestingly preserves the key properties of the original full-order model such as stability, minimality, and phase minimality. Line spectral frequencies (LSF) and signal-to-noise ratio (SNR) behavior are also investigated. To illustrate the performance and effectiveness of the proposed approach, some computer simulations were conducted on some practical speech segments.