Green Procedure for the Synthesis of Phthalazino[2,3‐b]phthalazine‐5,7,12,14‐tetraones

Different novel phthalazino[2,3‐b]phthalazine‐5,7,12,14‐tetraones were synthesized in a simple and environmentally benign method from the reaction of phthalic anhydrides with semicarbazide or thiosemicarbazide using montmorillonite K‐10 clay as solid heterogeneous acidic catalyst and microwaves under solvent‐free conditions in good yields and short reaction times. Products were characterized by the elemental analysis, IR, NMR, and mass spectrometry.     

A fuzzy-stochastic OWA model for robust multi-criteria decision making

All realistic Multi-Criteria Decision Making (MCDM) problems face various kinds of uncertainty. Since the evaluations of alternatives with respect to the criteria are uncertain they will be assumed to have stochastic nature. To obtain the uncertain optimism degree of the decision maker fuzzy linguistic quantifiers will be used. Then a new approach for fuzzy-stochastic modeling of MCDM problems will be introduced by merging the stochastic and fuzzy approaches into the OWA operator. The results of the new approach, entitled FSOWA, give the expected value and the variance of the combined goodness measure for each alternative. Robust decision depends on the combined goodness measures of alternatives and also on the variations of these measures under uncertainty. In order to combine these two characteristics a composite goodness measure will be defined. The theoretical results will be illustrated in a watershed management problem. By using this measure will give more sensitive decisions to the stakeholders whose optimism degrees are different than that of the decision maker. FSOWA can be used for robust decision making on the competitive alternatives under uncertainty.     

Revising the OWA operator for multi criteria decision making problems under uncertainty

Multi criteria decision making (MCDM) problems are usually under uncertainty. One of these uncertain parameters is the decision maker (DM)’s degree of optimism, which has an important effect on the results. Fuzzy linguistic quantifiers are used to obtain the assessments of this parameter from DM and then, because of its uncertainty it is assumed to have stochastic nature. A new approach, entitled FSROWA, is introduced to combine the Fuzzy and Stochastic features into a Revised OWA operator.     

Determination of hydrodynamic behavior of gas–solid fluidized beds using statistical analysis of acoustic emissions

In the processes involving the movement of solid particles, acoustic emissions are caused by particle friction, collision and fluid turbulence. Particle behavior can therefore be monitored and characterized by assessing the acoustic emission signals. Herein, extensive measurements were carried out by microphone at different superficial gas velocities with different particle sizes. Acoustic emission signals were processed using statistical analysis from which the minimum fluidization velocity was determined from the variation of standard deviation, skewness and kurtosis of acoustic emission signals against superficial gas velocity. Initial minimum fluidization velocity, corresponding to onset of fluidization of finer particles in the solids mixture, at which isolated bubbles occur, was also detected by this method. It was shown that the acoustic emission measurement is highly feasible as a practical method for monitoring the hydrodynamics of gas–solid fluidized beds.     

Insights in hydrodynamics of bubbling fluidized beds at elevated pressure by DEM–CFD approach

A numerical simulation was conducted to study the effect of pressure on bubble dynamics in a gas–solid fluidized bed. The gas flow was modeled using the continuum theory and the solid phase, by the discrete element method (DEM). To validate the simulation results, calculated local pressure fluctuations were compared with corresponding experimental data of 1-mm polyethylene particles. It was shown that the model successfully predicts the hydrodynamic features of the fluidized bed as observed in the experiments. Influence of pressure on bubble rise characteristics such as bubble rise path, bubble stability, average bubbles diameter and bubble velocity through the bed was investigated. The simulation results are in conformity with current hydrodynamic theories and concepts for fluidized beds at high pressures. The results show further that elevated pressure reduces bubble growth, velocity and stability and enhances bubble gyration through the bed, leading to change in bed flow structure.     

1H NMR based metabolic profiling in Crohn's disease by random forest methodology

The present study was designed to search for metabolic biomarkers and their correlation with serum zinc in Crohn's disease patients. Crohn's disease (CD) is a form of inflammatory bowel disease that may affect any part of the gastrointestinal tract and can be difficult to diagnose using the clinical tests. Thus, introduction of a novel diagnostic method would be a major step towards CD treatment. Proton nuclear magnetic resonance spectroscopy (¹H NMR) was employed for metabolic profiling to find out which metabolites in the serum have meaningful significance in the diagnosis of CD. CD and healthy subjects were correctly classified using random forest methodology. The classification model for the external test set showed a 94% correct classification of CD and healthy subjects. The present study suggests Valine and Isoleucine as differentiating metabolites for CD diagnosis. These metabolites can be used for screening of risky samples at the early stages of CD diagnoses. Moreover, a robust random forest regression model with good prediction outcomes was developed for correlating serum zinc level and metabolite concentrations. The regression model showed the correlation (R²) and root mean square error values of 0.83 and 6.44, respectively. This model suggests valuable clues for understanding the mechanism of zinc deficiency in CD patients. Copyright © 2014 John Wiley & Sons, Ltd.     

Potentiometric membrane sensor based on 6-(4-nitrophenyl)-2,4-diphenyl-3,5-diaza-bicyclo[3.1.0]hex-2-ene for detection of Sn(II) in real samples

A Sn²⁺ ion-selective electrode which was prepared with a polymeric membrane based on 6-(4-nitrophenyl)-2,4-diphenyl-3,5-diaza-bicyclo[3.1.0]hex-2-ene (NDDBH) as a ionophore. Effects of experimental parameters such as membrane composition, nature and amount of plasticizer, the amount of additive and concentration of internal solution on the potential response of Sn²⁺ sensor were investigated. The electrode exhibited a Nernstian slope of 28.8 ± 1.1 mV/decade of Sn²⁺ over a concentration range of 1.0 × 10⁻⁵ to 1.0 × 10⁻¹ M of Sn²⁺ in an acidic solution (pH 1). The limit of detection was 4.0 × 10⁻⁶ M. The results show that this electrode can be used in ethanol media until 20% (v/v) concentration without interference. It can be used for more than 6 weeks without any considerable divergence in the potentials. The proposed membrane electrode revealed very good selectivity for Sn(II) ions over a wide variety of other cations and could be used in acidic media. The standard electrode potentials were determined at different temperatures and used to calculate the isothermal coefficient of the electrode. The stability constant (log K_s) of the Sn(II)-ionophore complex was determined at 25 °C by potentiometric titration in mixed aqueous solution. It was used as indicator electrode in potentiometric determination of Sn(II) ion in real samples.