New natural 2-acetoxy fatty acids using chemical ionization and electron impact mass spectrometry

The phospholipids of the spongePolymastia gleneni contain saturated long chain (C_22–30)-acetoxy fatty acids. Their structures were assigned based on chromatographic and spectrometric data as well as comparison with a synthetic sample. The use of capillary gas chromatography combined with chemical ionization and electron impact mass spectrometry was instrumental in the eludication of structures, since only a very small amount of crude lipids was available. Part 10 of “Phospholipids in Marine Organisms.” For Part 9 in this series, see reference 12.     

The Influence of Surfactant on the Surface Characterization of Celestite in Spherical Oil Agglomeration

This study investigates the relationship between the critical surface tension of wetting of celestite and agglomeration recovery as well as the zeta potential in dependence of pH and amount of collector (Na‐Oleate). For this purpose, effects of pH and collector amount on the agglomeration recovery are investigated and zeta potential measurements and Fourier Transform Infrared Spectrophotometer (FTIR) analyses are carried out to determine the adsorption type of Na‐Oleate on celestite surface. The sessile drop technique is used for the measurement of contact angle and determination of the critical surface tension of wetting (Y_C) of celestite. The maximum agglomeration recovery is obtained at pH 7. The critical surface tension of wetting of celestite is very close to the surface tension of kerosene, which is 25.95 mN/m. Furthermore, at the optimum Na‐Oleate amount of 10 kg/ton, the critical surface tension of wetting of celestite is approximately equal to the surface tension of kerosene.     

A combo technology of autotrophic and heterotrophic denitrification processes for groundwater treatment

In this study,a sequential process (heterotrophic up-flow column and completely mixed membrane bioreactors) was proposed combining advantages of the both processes.The system was operated for 249 days with simulated and real groundwater for nitrate removal at concentrations varying from 25 to 145 mg·L-1 NO3-N.The contribution of heterotrophic process to total nitrate removal in the system was controlled by dozing the ethanol considering the nitrate concentration.By this way,sulfur based autotrophic denitrification rate was decreased and the effluent sulfate concentrations were controlled.The alkalinity requirement in the autotrophic process was produced in the heterotrophic reactor,and the system was operated without alkalinity supplementation.Throughout the study,the chemical oxygen demand in the heterotrophic reactor effluent was (23.7 ± 22) mg·L-1 and it was further decreased to(7.5 ± 7.2) mg·L-1 in the system effluent,corresponding to a 70％ reduction.In the last period of the study,the real groundwater containing 145 mg·L-1 NO3-N was completely removed.Membrane was operated without chemical washing in the first 114 days.Between days 115-249 weekly chemical washing was required.     

Investigation of kinetics of agglomerate growth in oil agglomeration process

In this study, the kinetics of agglomerate growth in a batch oil agglomeration process has been studied using bituminous coal. The effect of operating variables such as kerosene concentration, pulp density and speed of agitation on the agglomeration process was investigated. It has been found that the second-order kinetic equation describes the growth of agglomerates adequately. The growth of the agglomerates in the oil agglomeration process shows a self-preserving growth. Using this, a characteristic curve has been developed. For the prediction of the size distribution of the agglomerates, the d₅₀ values of the agglomerates must be known. Therefore, a model has been developed by using the kinetic equation for estimation of d₅₀ values of agglomerates for this coal. It was shown that the size distribution of the agglomerates for any levels of the process variables studied can be predicted using the equation of characteristic curve and d₅₀ values. Knowledge obtained from this study will be helpful for technological advancement of this kind of study.     

Application of the Box-Wilson experimental design method for the spherical oil agglomeration of coal

In this study, the Box-Wilson statistical experimental design method was employed to evaluate the effects of important variables such as bridging liquid (oil) concentration, salt (CaCl₂·2H₂O) concentration and stirring speed on the agglomeration of bituminous coal. Response function coefficients were determined by the regression analysis of experimental data and the predictions were found to be in good agreement with the experimental results. The optimum kerosene concentration, CaCl₂·2H₂O concentration and stirring speed were determined as 30 wt%, 1 M and 1683 rpm, respectively, when considering combustible recovery and ash content.In addition, contact angle and solution surface tension measurements were carried out to evaluate of agglomeration success with the contact angle values and surface tension values. The surface tension of CaCl₂ 2H₂O solutions and the average contact angle increased with increasing CaCl₂·2H₂O concentration.     

Adsorption of Cr(III), Ni(II), Zn(II), Co(II) ions onto phenolated wood resin

In this study, phenolated wood resin was used an adsorbent for the removal of Cr(III), Ni(II), Zn(II), Co(II) ions by adsorption from aqueous solution. The adsorption of metal ions from solution was carried at different contact times, concentrations and pHs at room temperature (25°C). For individual metal ion, the amount of metal ions adsorbed per unit weight of phenolated wood resin at equilibrium time increased with increasing concentration and pH. Also, when the amounts of metal ions adsorbed are compared to each other, it was seen that this increase was order of Cr(III) > Ni(II) > Zn(II) > Co(II). This increase was order of Cr(III) > Ni(II) > Co(II) > Zn(II) for commercial phenol–formaldehyde resin. Kinetic studies showed that the adsorption process obeyed the intraparticle diffusion model. It was also determined that adsorption isotherm followed Langmuir and Freundlich models. Adsorption isotherm obtained for commercial phenol–formaldehyde resin was consistent with Freundlich model well. Adsorption capacities from Langmuir isotherm for commercial phenol–formaldehyde resin were higher than those of phenolated wood resin, in the case of individual metal ions. Original adsorption isotherm demonstrated the monolayer coverage of the surface of phenolated wood resin. Adsorption kinetic followed the intraparticle diffusion model. The positive values of ΔG° determined using the equilibrium constants showed that the adsorption was not of spontaneous nature. It was seen that values of distribution coefficient (K_D) decreasing with metal ion concentration in solution at equilibrium (C_e) indicated that the occupation of active surface sites of adsorbent increased with metal ions. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2838–2846, 2006     

Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange

Prediction of stock price index movement is regarded as a challenging task of financial time series prediction. An accurate prediction of stock price movement may yield profits for investors. Due to the complexity of stock market data, development of efficient models for predicting is very difficult. This study attempted to develop two efficient models and compared their performances in predicting the direction of movement in the daily Istanbul Stock Exchange (ISE) National 100 Index. The models are based on two classification techniques, artificial neural networks (ANN) and support vector machines (SVM). Ten technical indicators were selected as inputs of the proposed models. Two comprehensive parameter setting experiments for both models were performed to improve their prediction performances. Experimental results showed that average performance of ANN model (75.74%) was found significantly better than that of SVM model (71.52%).     

Supplier selection with an integrated methodology in unknown environment

This paper proposes an integrated methodology and its solution for supplier selection problem. A two-stage stochastic programming model and fuzzy TOPSIS methods are consolidated in this methodology. After pre-research phase, in the second part of the methodology, fuzzy TOPSIS is used for ranking potential suppliers considering qualitative data under fuzzy environment. In the third part of the methodology a group of ranked potential suppliers are included in a two-stage stochastic programming model for evaluation. In the two-stage stochastic programming model demand is assumed as uncertain and different scenarios are generated for this parameter. With this methodology, supplier evaluation procedure can be done in unknown environment. Our methodology is interested with a problem in multi-product, multi-period and multi-sourcing environment.     

Feature tracking and matching in video using programmable graphics hardware

This paper describes novel implementations of the KLT feature tracking and SIFT feature extraction algorithms that run on the graphics processing unit (GPU) and is suitable for video analysis in real-time vision systems. While significant acceleration over standard CPU implementations is obtained by exploiting parallelism provided by modern programmable graphics hardware, the CPU is freed up to run other computations in parallel. Our GPU-based KLT implementation tracks about a thousand features in real-time at 30 Hz on 1,024 × 768 resolution video which is a 20 times improvement over the CPU. The GPU-based SIFT implementation extracts about 800 features from 640 × 480 video at 10 Hz which is approximately 10 times faster than an optimized CPU implementation.