A novel phosphoric acid loaded quaternary 1,4-diazabicyclo-[2.2.2]-octane polysulfone membrane for intermediate temperature fuel cells

Phosphoric acid loaded quaternary 1,4-diazabicyclo-[2.2.2]-octane (DABCO) polysulfone was synthesised with different degrees of substitution (DS) and the membranes were characterized. The polymer structure was investigated using NMR and FT-IR spectra. The effect of DS on ionic conductivity and fuel cell performance are described. Conductivities of 0.12 and 0.064 S cm⁻¹ were achieved for the high degree of substitution membrane (DS106) and low degree of substitution membrane (DS58), respectively. Fuel cell tests gave a high power output of 400 mW cm⁻² using H₂ and O₂ at 150 °C and atmospheric pressure. Therefore, PA/QDPSU membrane has potential applications for intermediate temperature fuel cells (ITFCs).     

Resolving Disputes over Reservoir-River Operation

The main objective of this work is to allocate water with acceptable quality from a reservoir-river system to different water users and to determine the maximum acceptable pollution load that each user discharges to the river. To achieve this, a bargaining model is developed based on a system dynamics approach, and it is compared with an alternative model based on the Nash bargaining theory. The quality of water released from the reservoir is assessed considering selective withdrawal schemes, obtained from schemes based on operating rules derived from an artificial neural network (ANN) and a K-nearest neighborhood (NN) model. A river water-quality simulation model is also linked with the two bargaining models. These models are then applied to the Karkheh reservoir-river system and using a 50-year monthly time series of qualitative and quantitative data of this system. Finally, the performance criteria for the results of the models are determined and compared. This study shows the significant value of the system dynamics approach in resolving disputes over water allocation among stakeholders/water users of reservoir-river systems considering the water-quality aspects.     

The Determination of Phendimetrazine and Phenmetrazine in Biological Fluids and in Dosage Forms

A highly sensitive gas chromatographic assay was developed for the simultaneous determination of phendimetrazine and its N-demethylated metabolite, phenmetrazine. The analytical procedure proved adaptable for the determination of these drugs in dosage formulations as well as biological fluids. The procedure involves the addition of Isoxsuprine as the internal standard and extraction into diethyl ether. The two drugs along with the internal standard were well resolved on an SP-2250 column using helium as the carrier gas     

Estimation of the CO2-oil minimum miscibility pressure for enhanced oil recovery

The authors' aim was to present new models based on artificial neural network (ANN) and two optimization algorithms including cuckoo optimization algorithm (COA) and teaching learning based optimization (TLBO) to predict the pure and impure CO₂ MMP. Thirty-four and 11 training and testing data sets were used to develop these models with following inputs: reservoir temperature, the mole percent of volatile oil components (C₁ and N₂), mole percent of intermediate oil components (C₂-C₄, CO₂, and H₂S), molecular weight of C₅₊ fraction in oil phase (MW_C5+) and mole percentage of CO₂, N₂, C₁, C₄, and H₂S in the injected gas. Statistical comparisons show that although two models yield acceptable results, the ANN-TLBO model has better performance with the lower mean absolute percentage error (2.6%) and standard deviation (3.37%) and the higher coefficient of determination (0.993). Moreover, among the available correlations, the Cronquist's (1978 Cronquist, C. (1978). Carbon dioxide dynamic miscibility with light reservoir oils. Fourth Annual U.S. DOE Symposium, Tulsa, Oklahoma. [Google Scholar]; corrected by Sebastian et al., 1985 Sebastian, H. M., Wenger, R. S., and Renner, T. A. (1985). Correlation of minimum miscibility pressure for impure CO2 streams. J. Pet. Technol. 37:2076–2082.[Crossref] , [Google Scholar]) correlations have better performance. Finally, the sensitivity analysis on the ANN-TLBO showed that MW_C5+ and reservoir temperature are the most influential parameters in determining the CO₂ MMP, respectively.     

Stock-Watson dynamic OLS (DOLS) and error-correction modelling approaches to estimating long- and short-run elasticities in a demand function: new evidence and methodological implications from an application to the demand for coal in mainland China

In this paper robust elasticity estimates of coal demand for China are derived using annual data 1953–1992. In so doing, we illustrate the use of a powerful yet practically convenient and recently developed modelling procedure devised by Stock and Watson (known as Dynamic OLS (DOLS)), who provide evidence, based on Monte Carlo simulations, of this estimator being superior in small samples compared to a number of alternative estimators, as well as being able not only to accommodate higher orders of integration but also to account for possible simultaneity within regressors of a potential demand system. Furthermore, cointegration and error-correction methods are employed to derive short-run price and income elasticities. Estimated results are quite robust not only in terms of statistical prowess but also in terms of economic intuition and indicate that, over the long run, both price and income elasticities are close to unity. While short-run price and income elasticities are less (in absolute value) than their long-run counterparts, there seems to be some divergence in short-run parameters from a subsample analysis. Overall, results seem to imply that for China, coal consumption should remain relatively constant as future modernization strategies for economic development are pursued. In addition, the study has clear methodological implications for estimating the long- and short-run elasticities in a demand function in general, and in a wide variety of fields in future applied research.     

Oil price volatility and stock price fluctuations in an emerging market: Evidence from South Korea

How important are oil price fluctuations and oil price volatility on equity market performance? What are the policy implications if volatility turns out to be significant? We assess this issue in an economics/finance nexus for Korea using a VEC model including interest rates, economic activity, real stock returns, real oil prices and oil price volatility. Our main aim is to capture the effects of crude oil prices on the Korean economy thoroughly covering the period of the Asian Financial Crisis of 1997, which heavily affected the country, and the oil price hikes in the early 1990s after the Gulf War. South Korea was the country most hit by the financial crisis together with Indonesia and Thailand. Results indicate the dominance of oil price volatility on real stock returns and emphasize how this has increased over time. Oil price volatility can have profound effect on the time horizon of investment and firms need adjust their risk management procedures accordingly. This increase in dependency has been found in other net oil importing emerging equity markets. We test the relationship between oil price movements and economic activity by using modern time series techniques in a cointegrating framework. We expand the standard error correction model by examining the dynamics of out of sample causality through the generalized variance decomposition and impulse response function techniques. The evidence from persistence profiles also gives important guidelines based on how fast the entire system adjusts back to equilibrium. In addition, we find the cointegrating relationship to be stable and find that the linear error correction model to be more favorable than an asymmetric 2 period Markov switching model.