Microwave-assisted synthesis of new pyrimido[4′,5′：4,5]thiazolo[3,2-α] benzimidazol-4（3H）-one derivatives in solvent-free condition

Microwave-assisted synthesis of new 2-arylpyrimido[4′,5′：4,5]thiazolo[3,2-α]benzimidazol-4（3H）-ones from 3-aminothia- zolo[3,2-α]benzimidazol-2-earboxamide and aroyl halides in solvent-free condition is described. In comparison with classical conditions the reactions are faster and the yields are higher under microwave irradiation.     

Chemical composition and antimicrobial activity of the essential oils of Ferula latisecta and Mozaffariania insignis from Iran

The hydrodistilled oils from the aerial parts of Ferula latisecta and Mozaffariania insignis, which is endemic to Iran, were analyzed by GC and GC/MS. (Z)-Ocimenone (32.4%), (E)-ocimenone (20.3%), and cis-pinocarvone (11.4%) were the main components among the 22 constituents characterized in the oil of F. latisecta, representing 87.7% of the total components detected. Twenty-five compounds were identified in the oil of M. insignis, representing 99.0% of the total oil, with octyl acetate (41.1%), β-pinene (30.3%), and α-pinene (23.9%) as the main constituents. The essential oils were examined for their potential antimicrobial activities. Published in Khimiya Prirodnykh Soedinenii, No. 6, pp. 561–563, November–December, 2006.     

Topological efficiency under graph operations

In this paper we present explicit formulas for computing the topological efficiency index of the most important graph operations such as the Cartesian product, composition, corona, join and hierarchical product of two graphs. We apply our results to compute this distance-related invariant for some important classes of molecular graphs and nano-structures by specializing components of these graph operations.     

Using deep learning to learn physics of conduction heat transfer

Journal of Thermal Analysis and Calorimetry - In the present study, an advanced type of artificial intelligence, a deep neural network, is employed to learn the physic of conduction heat transfer...     

An accurate pressure–velocity decoupling technique for semi‐implicit rotational projection methods

In this paper, an accurate semi‐implicit rotational projection method is introduced to solve the Navier–Stokes equations for incompressible flow simulations. The accuracy of the fractional step procedure is investigated for the standard finite‐difference method, and the discrete forms are presented with arbitrary orders or accuracy. In contrast to the previous semi‐implicit projection methods, herein, an alternative way is proposed to decouple pressure from the momentum equation by employing the principle form of the pressure Poisson equation. This equation is based on the divergence of the convective terms and incorporates the actual pressure in the simulations. As a result, the accuracy of the method is not affected by the common choice of the pseudo‐pressure in the previous methods. Also, the velocity correction step is redefined, and boundary conditions are introduced accordingly. Several numerical tests are conducted to assess the robustness of the method for second and fourth orders of accuracy. The results are compared with the solutions obtained from a typical high‐resolution fully explicit method and available benchmark reports. Herein, the numerical tests are consisting of simulations for the Taylor–Green vortex, lid‐driven square cavity, and vortex–wall interaction. It is shown that the present method can preserve the order of accuracy for both velocity and pressure fields in second‐order and high‐order simulations. Furthermore, a very good agreement is observed between the results of the present method and benchmark simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

An improved ensemble learning machine for biological activity prediction of tyrosine kinase inhibitors

Boosting is one of the most important strategies in ensemble learning because of its ability to improve the stability and performance of weak learners. It is nonparametric, multivariate, fast and interpretable but is not robust against outliers. To enhance its prediction accuracy as well as immunize it against outliers, a modified version of a boosting algorithm (AdaBoost R2) was developed and called AdaBoost R3. In the sampling step, extremum samples were added to the boosting set. In the robustness step, a modified Huber loss function was applied to overcome the outlier problem. In the output step, a deterministic threshold was used to guarantee that bad predictions do not participate in the final output. The performance of the modified algorithm was investigated with two anticancer data sets of tyrosine kinase inhibitors, and the mechanism of inhibition was studied using the relative weighted variable importance procedure. Investigating the effect of base learner's strength reveals that boosting is only successful using the classification and regression tree method (a weak to moderate learner) and does not have a significant effect using the radial basis functions partial least square method (a strong base learners). Copyright © 2015 John Wiley & Sons, Ltd.     

Study of size, type and the kerma approximation for thermoluminescent dosimetry

This study aimed to investigate effects of the thermoluminescent dosimeter (TLD) size and type on the absorbed dose value by using of Monte Carlo calculations. The options in creating conditions to establish the kerma approximation were also studied. The Monte Carlo N-Particle (MCNPX 2.4.0) transport code was used to design simulations. Results of this work indicate that if common mineral materials of TLDs are replaced by air and a huge volume is applied for the TLD, the accurate assessment of absorbed doses is possible while the photon energy fluence in the TLD cell is convoluted with mass energy absorption coefficients of the real TLD material. In this method the simulation run-time is strongly decreased.     

Uranium recovery from UCF liquid waste by nanoporous MCM-41: breakthrough capacity and elution behavior studies

Adsorption and recovery of uranium by nanoporous MCM-41 from aqueous solutions (synthetic solution and uranium conversion facility liquid waste) were investigated by use of a fixed-bed column (1.2 cm diameter and 3.0 cm height). Adsorption was carried out at flow rates 0.2 and 0.5 mL min^?1, which correspond to retention times of 10 and 6 min. The maximum breakthrough capacity for uranium ions was achieved by use of nanoporous MCM-41 at the optimum pH of 3.6 and flow rate 0.2 mL min^?1 (61.95 μg g^?1). The Thomas and Yan models were applied to the experimental data, by use of linear regression, to determine the characteristics of the column for process design. The breakthrough curves calculated from the models were in good agreement with the experimental data. The elution behavior of uranium on nanoporous MCM-41 was studied with different eluents; the results showed that 0.1 M HCl is good eluent for uranium recovery. The regenerated column could be used in a multitude of adsorption–desorption cycles.