In vitro pharmacological screening of three newly synthesised pyrimidine derivatives

The antibacterial and antifungal activities of three new pyrimidine derivatives, namely, 2,6-bis(4,6-dimethylpyrimidin-2-ylthio)benzene-1,4-diol (1),3,5-bis(4,6-dimethylpyrimidin-2-ylthio)-2-methylbenzene-1,4-diol (2) and 3,5-bis(4,6-dimethylpyrimidin-2-ylthio)-2-methoxybenzene-1,4-diol (3), synthesised by electrochemical method are presented here. The compounds were screened for their activities against Gram-positive and Gram-negative bacteria, Bacillus subtilis, Staphylococcusaureus, Escherichia coli and a pathogenic fungus Aspergillus niger. The results show that these compounds have significant activity against these bacteria and fungus. The minimum inhibitory concentration of compound 1 was determined as 62.5 μg/mL against B. subtilis, 125 μg/mL against E. coli and 250 μg/mL against S. aureus establishing its promising activities higher than susceptible ranges.     

Heat pipes: progress in thermal performance enhancement for microelectronics

Journal of Thermal Analysis and Calorimetry - The aim of this study is to oversee the impact of various techniques on thermal performance of heat pipes and to comprehensively cover the progress...     

Rhodamine B degradation and reactive oxygen species generation by a ZnSe-graphene/TiO2 sonocatalyst

Nanostructured ZnSe-graphene/TiO2 was synthesized by a hydrothermal-assisted approach. ZnSe-graphene/TiO2 exhibited favorable adsorption of rhodamine B, a wide wavelength absorption range, and efficien...     

Chemically reactive accelerating radiative flow of Eyring Powell nanofluid with microorganisms and buoyancy forces

Recently, the nanofluids report multidisciplinary applications in the various era of engineering like engine cooling, solar energy production, cooling of engineering devices, diesel generator performance etc. Owing to such novel applications, the aim of current communication is to report the significances of bio-convection for unsteady Eyring Powell nanofluid due to bidirectional oscillatory stretching surface. The enrollment of buoyancy forces and magnetic impact are worked out to inspect the stability and thermal on set of nanofluids. Heat transformation features are explored by utilizing thermal radiation. Further, the characteristics of chemical reaction and activation energy have been considered for physical significance. Unlike traditional approach, the governing equations are not altered into ordinary set of equation but only diminish the independent variables. This task makes the non-dimensional equations in highly complicated from which the convergent technique via HAM is successfully implemented. The physical outcomes of dominant variables on profiles of microorganisms, concentration, temperature, velocity and skin frictions are conferred graphically while local motile density, Sherwood and Nusselt numbers are deliberated through different tables. It is noted that the amplitude of bidirectional shear stresses and velocities periodically get increase for higher material parameter. This analysis emphasized that concentration distribution augments for rising values of activation energy variable, whereas conflicting situation occurs for temperature difference parameter. Moreover, motile microorganism's distributions are diminished by improved values of bio-convected Peclet and bio-convected Lewis numbers.     

Optimization of entropy production in flow of hybrid nanomaterials through Darcy–Forchheimer porous space

Journal of Thermal Analysis and Calorimetry - Heat transportation advancement in liquid is a crucial work which can be easily obtained via utilization of hybrid nanoparticles. Therefore, main...     

Micro-level reserving for general insurance claims using a long short-term memory network

Detailed information about individual claims are completely ignored when insurance claims data are aggregated and structured in development triangles for loss reserving. In the hope of extracting predictive power from the individual claims characteristics, researchers have recently proposed to use micro-level loss reserving approaches. We introduce a discrete-time individual reserving framework incorporating granular information in a deep learning approach named Long Short-Term Memory (LSTM) neural network. At each time period, the network has two tasks: first, classifying whether there is a payment or a recovery, and second, predicting the corresponding non-zero amount, if any. Based on a generalized Pareto model for excess payments over a threshold, we adjust the LSTM reserve prediction to account for extreme payments. We illustrate the estimation procedure on a simulated and a real general insurance dataset. We compare our approach with the chain-ladder aggregate method using the predictive outstanding loss estimates and their actual values.     

Common fixed point results for new Ciric-type rational multivalued <Emphasis Type="Italic">F</Emphasis>-contraction with an application

In this article, common fixed point theorems for a pair of multivalued mappings satisfying a new Ciric-type rational F-contraction condition in complete dislocated metric spaces are established. An example is constructed to illustrate our results. An application to the system of integral equations is presented to support the usability of proved results. Our results combine, extend and infer several comparable results in the existing literature.