Decolourisation of Acid orange 7 in a microbial fuel cell with a laccase-based biocathode: Influence of mitigating pH changes in the cathode chamber

Biocathodes may be a suitable replacement of platinum in microbial fuel cells (MFCs) if the cost of MFCs is to be reduced. However, the use of enzymes as bio-cathodes is fraught with loss of activity as time progresses. A possible cause of this loss in activity might be pH increase in the cathode as pH gradients in MFCs are well known. This pH increase is however, accompanied by simultaneous increase in salinity; therefore salinity may be a confounding variable. This study investigated various ways of mitigating pH changes in the cathode of MFCs and their effect on laccase activity and decolourisation of a model azo dye Acid orange 7 in the anode chamber. Experiments were run with catholyte pH automatically controlled via feedback control or by using acetate buffers (pH 4.5) of various strength (100 mM and 200 mM), with CMI7000 as the cation exchange membrane. A comparison was also made between use of CMI7000 and Nafion 117 as the transport properties of cations for both membranes (hence their potential effects on pH changes in the cathode) are different.

Monetary policy, exchange rates and stock prices in the Middle East region

A structural vector autoregressive model is employed to investigate the impact of monetary policy and real exchange rate shocks on the stock market performance of Kuwait, Oman, Saudi Arabia, Egypt and Jordan. In order to identify the structural shocks both short run and long run restrictions are applied. Unlike previous literature the contemporaneous interdependence between the financial variables are left unrestricted to give a more accurate depiction of the relationships. The heterogeneity of the results reflect the different monetary policy frameworks and stock market characteristics of these countries. Mainly, monetary policy and the real exchange rate shocks have a significant short run impact on the stock prices of the countries that apply a relatively more independent monetary policy and flexible exchange rates.

Volatility and VaR Forecasting in the Madrid Stock Exchange

This paper provides an empirical study to assess the forecasting performance of a wide range of models for predicting volatility and VaR in the Madrid Stock Exchange. The models performance was measured by using different loss functions and criteria. The results show that FIAPARCH processes capture and forecast more accurately the dynamics of IBEX-35 returns volatility. It is also observed that assuming a heavy-tailed distribution does not improve models ability for predicting volatility. However, when the aim is forecasting VaR, we find evidence of that the Student’s t FIAPARCH outperforms the models it nests the lower the target quantile.