Theoretical prediction of encapsulation and adsorption of platinum-anticancer drugs into single walled boron nitride and carbon nanotubes

In this research, the adsorption and encapsulation of cisplatin, nedplatin, oxaliplatin and carbaplatin as Pt-anticancer drugs into the (7,7) boron nitride nanotube (BNNT) and carbon nanotube (CNT) are investigated using density functional theory. The different orientation modes of drug molecules onto the outer and inner surfaces of BNNT and CNT are studied. Analysis of the adsorption energy reveals that the complex formation process is favorable. The calculated adsorption energies indicate that the encapsulation of drugs inside the nanotubes is more favorable than the adsorption of drugs outside of the nanotubes. On the other hand, the results show that the BNNT/oxaliplatin(in) system is more stable than the others. The stabilization of nanotube/drug complexes results in electronic and structural properties change in the nanotubes. The natural bond orbital calculations show that the van der Waals forces, hydrogen bonding and electrostatic interactions are the major factors contributed to the overall stabilities of the complexes. The predicted electronic and structural properties of BNNT compared to the CNT towards Pt-anticancer drugs, suggest that BNNT can act as drug delivery vehicles.     

A bi‐level neural‐based fuzzy classification approach for credit scoring problems

The credit scoring is a risk evaluation task considered as a critical decision for financial institutions in order to avoid wrong decision that may result in huge amount of losses. Classification models are one of the most widely used groups of data mining approaches that greatly help decision makers and managers to reduce their credit risk of granting credits to customers instead of intuitive experience or portfolio management. Accuracy is one of the most important criteria in order to choose a credit‐scoring model; and hence, the researches directed at improving upon the effectiveness of credit scoring models have never been stopped. In this article, a hybrid binary classification model, namely FMLP, is proposed for credit scoring, based on the basic concepts of fuzzy logic and artificial neural networks (ANNs). In the proposed model, instead of crisp weights and biases, used in traditional multilayer perceptrons (MLPs), fuzzy numbers are used in order to better model of the uncertainties and complexities in financial data sets. Empirical results of three well‐known benchmark credit data sets indicate that hybrid proposed model outperforms its component and also other those classification models such as support vector machines (SVMs), K‐nearest neighbor (KNN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA). Therefore, it can be concluded that the proposed model can be an appropriate alternative tool for financial binary classification problems, especially in high uncertainty conditions. © 2013 Wiley Periodicals, Inc. Complexity 18: 46–57, 2013     

Adsorption studies of β-naphthol by untreated and treated activated carbon [optimizing of adsorption by central composite design (CCD)]

In the present work the adsorption of aromatic compound, namely ??-naphthol (BN) by two granular activated carbons, one untreated and the other treated with HNO₃ carried out under controlled conditions. The effects of experimental parameters on adsorption process such as pH, contact time and adsorbent dosage have been investigated. Experimental design methodology was applied to optimize the removal of ??-naphthol. The effect of various experimental parameters was investigated using five-level three-factorial central composite design (CCD). The relationship between the parameters and the response for model optimization was found and optimum conditions were obtained by CCD. In the optimum conditions obtained by response surface modeling, 100% BN was adsorbed on the carbons. Treatment with HNO₃ led to a decrease in the point of zero charge and the adsorption capacity (Q _max) of the activated carbon. The adsorption capacity of the carbons was determined using Freundlich and Langmuir homogenous equation. The variation of the model parameters with the solution pH was also studied. The fitted parameters obtained from both models showed the Q _max value decrease with increasing of pH.     

Can bowl-like B30 nanostructure sense toxic cyanogen gas in air?: a theoretical study

In this work, an attempt has been made to study sensing performance of bowl-like B₃₀ nanostructure towards toxic cyanogen gas using density functional theory (DFT) at B97D/6-31+G(d) computational level. The results reveal that B₃₀ nanostructure is a proper sensor for sensing of toxic cyanogen gas. The most favourite adsorption site of B₃₀ is the exterior boron atoms that lead to the adsorption energy of ?78.48 (kJ/mol) with the remarkable change in electronic properties of B₃₀. The competitive sensing of cyanogen gas in the presence of water, oxygen and nitrogen molecules is also considered. Significant changes in the electronic properties of B₃₀ due to adsorption of cyanogen in presence of O₂, H₂O and N₂ gases enable it to be used in the detection of toxic cyanogen gas in air.     

AnO(3, 1) approach to Maxwell's equations

Using the principal series representations of the Lorentz group, a method parallel to that of Gelfand and Yaglom is suggested to obtain Maxwell's equations, which dispenses with the arbitrary introduction of a degenerate transformation with respect to which the photon equations are invariant. The method also gives subsidiary conditions which, in conjunction with the masslessness of the particle, yield the Lorentz condition and the correct values of photon polarization.     

Adsorption of Pb(II) and Ni(II) From Aqueous Solution by a High-Capacity Industrial Sewage Sludge-Based Adsorbent

In the present study, adsorption of Ni(II) and Pb(II) from aqueous solution was investigated using activated carbon synthesized with industrial wastewater sludge. The synthesized adsorbent was analyzed using nitrogen adsorption–desorption and Fourier transfer infrared (FTIR) techniques. Batch adsorption mode was used to evaluate the effect of solution pH, contact time, adsorbent dose, initial metal ion concentration, and temperature on the adsorption capacity of the synthesized adsorbent. The kinetic data were analyzed using different kinetic models. The pseudo-second-order equation gave the best fit to the experimental data for both metal ions. The equilibrium isotherm data were analyzed using the Langmuir, Freundlich, and Dubinin–Radushkevich (D–R) isotherm models. The results showed that the data obtained for the Ni(II) and Pb(II) adsorption are in good agreement with the Langmuir model. The Langmuir mono-layer maximum adsorption capacities for Ni(II) and Pb(II) ions were estimated to be 74.06 and 88.76 mg g^?1 at 25°C, respectively. In addition, the thermodynamic studies proved that the adsorption process of both metals could be considered endothermic.     

A seminumeric approach for solution of the Eikonal partial differential equation and its applications

In this work, a partial differential equation, which has several important applications, is investigated, and some techniques based on semianalytic (or quasi‐numerical) approaches are developed to find its solution. In this article, the homotopy perturbation method (HPM), Adomian decomposition method, and the modified homotopy perturbation method are proposed to solve the Eikonal equation. HPM yields solution in convergent series form with easily computable terms, and in some case, yields exact solutions in one iteration. In other hand, in Adomian decomposition method, the approximate solution is considered as an infinite series usually converges to the accurate solution. Moreover, these methods do not require any discretization, linearization, or small perturbation, and therefore reduce the numerical computation a lot. Several test problems are given and results are compared with the variational iteration method. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2010     

A new application for diethyl azodicarboxylate: efficient and regioselective thiocyanation of aromatics amines

Highly regioselective thiocyanations of indoles, anilines and pyrrole are achieved via an efficient and simple protocol using NH₄SCN and diethyl azodicarboxylate (DEAD) as a mild oxidant.     

The daily radon dose in body organs caused by drinking milk and water

Milk is considered as the richest nutrition, being used by people. When drinking milk or water the radon gas will transfer from air to them rapidly. Since milk is majorly composed of water, probably radon existence in livestock consumable water could be the main cause of its presence in milk. Different portion of milk changed by radon gamma ray and consumption of radon included water or milk has its effects on the human body. For investigation the effect of radon in water or milk on human organs, this study has been done in two phases with MCNPX software. In the first phase, the dose rate of absorbed gamma ray by different portion of milk which is indoctrinated by 1 Bq/m³ of radon during a day is calculated. Moreover, the effects shown by milk and its components in radon gamma spectrum, which is demonstrator of milk absorption spectrum, are also surveyed. In the second phase as well, according to the human body phantom, the absorbed gamma dose caused by daily consumption of indoctrinated water or milk with 1 Bq/m³ radon is calculated. The production rate of free radicals in milk and its different components are derived according to escape data of MCNPX code.     

De-Alloyed PtCu/C Catalysts of Methanol Electrooxidation

Russian Journal of Electrochemistry - The activity of PtCu/C catalysts in methanol electrooxidation is studied in HClO4 solution. The electrochemical behavior of catalysts is compared for samples...