Non-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important role in d

Non-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important rol

     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb

This study was conducted in the College of Agriculture fields /University of Baghdad, during Autumn 2013. This study was aimed to examine the mortality rate on the all black fly stages of Acaudalerodes rachipora Singh) by the biotic fungus Beuveria bassiana. The results of a preliminary survey showed that the samples of Ziziphus spaina christi were infested by blakflies in Agriculture collage during Autumn seasons of 2013 , the presence of species of black flies A. rachipora on the lower surface of the leaf, the study aimed to study and research the effects of fungus B. bassiana on black fly A. rachipora. After six days of treatment results showed the continued superiority 106 spore / ml trends in the western, southern and

Complexes of Au (III), Pd (II), Pt (IV ) and Rh(III) with S–propynyle-2- thiobenzimidazole (BENZA) have been prepared and characterized by IR and UV- Visible spectral methods in addition to magnetic and conductivity measurements and micro–elemental analysis (CHN).The probable structures of the new complexes have been suggested.

This research involves the preparation of new ligands 1,1,2,2- tetrakis (sodium acetate thio)ethylene(L1) and 1,1,2- tris(sodiumacetatethio) ethylene(L2), through the reaction of disodium thioglycolate) with tetra chloro ethylene or tri chloro ethylene in (1:4) or (1:3) moler ratio . Homodinucliar complexes of general formlu [M2(L1)] and [M2(L2)ClH2O] , when M= Co(II), Ni(II), Cu (II) and Zn(II) also mono nuclear complexes of general formula [M(L2)] . The prepared complexes were characterized using spectral method (UV/Visible/ IR) , metal content analysis , magnetic and atomic measurements . The spectral and magnetic measurement indicats that some complexes have tetrahedral or square planar complexes environtment .

Preparation and Identification of some new Pyrazolopyrin derivatives and their Polymerizations study

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines