Four metal complexes mixed ligand of 2-aminophenol (2-AP) and tributylphosphine (PBu3) were produced in aqueous ethanol with (1:2:2) (M:2-AP:PBu3). The prepared complexes were identified by using flame atomic absorption, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition antibacterial activity of the two ligands and mixed ligand complexes oboist three species of bacteria were also examined. The ligands and their complexes show good bacterial activities. From the obtained data the octahedral geometry was suggested for all prepared complexes.

(phen) (L(M [formula general a with complexes ligand-mixed new of series A methods analyses different by characterised and synthesised been have ,ligand arysecond as phenanthroline1,10- = phen and ligand primary as dithiocarbamate-1-azolebenzoimid-H-1)sulfinyl)methyl)yl-”-2pyriden)trifluroethoxy2,2,2- “(-4-methyl3-(((2-Sodium = L,ZnIIandCdII,CuII,NiII,CoII= M where,Cl)]phen)(L(Pd [Cland]2)O2H( ligands to metal ,moments magnetic and ,elementalanalysis ,spectrum mass ,surementsmea conductivity ,analysis thermal ,spectroscopy Vis-UV ,IR-FT ,NMR-C,13 H1 such dithiocarbamate the with formed coordination anisobidentate that showed spectra IRFT The.)phen:dithiocarbamate:M) (1:1:1(be to found been has complexes all in ratio nitrogen th

Four metal complexes mixed ligand of 2-aminophenol (2-AP) and tributylphosphine (PBu3) were produced in aqueous ethanol with (1:2:2) (M:2-AP:PBu3). The prepared complexes were identified by using flame atomic absorption, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition antibacterial activity of the two ligands and mixed ligand complexes oboist three species of bacteria were also examined. The ligands and their complexes show good bacterial activities. From the obtained data the octahedral geometry was suggested for all prepared complexes. Keywords: Mixed ligand complexes, spectral studies, 2-aminophenol, tributylphosphine.

In this research, a group of complexes were prepared which were derived from Schiff base ligands, which is called (1E,1'E)-1,1'-(1,2-phenylene)bis(N-(2,4-dichlorophenyl) methanimine) (L) with ortho-phenanthroline (o-phen).The prepared complexes areM(II) [Co(II),Ni(II),Cu(II), Zn(II), Cd(II),and Hg(II)].A range of spectroscopic and technical techniques have been used to characterizethese materials, including:The FTIR, 1H-NMR, LC-Mass Spectrum, UV-Visbale, molar conductance, and magnaticmoment, atomic absorbtion, chlorid contents. Spectral results obtainedare showen that (ortho-phen) and (L) behave as neutral coordinating to the central metal ion by the donatingatoms(N2)of the both compounds. The geometry sha

Some metal ions (Mn+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2 and Hg+2) complexes of quinaldic acid (QuinH) and α-picoline (α-Pic) have been synthesized and characterized on the basis of their , FTIR, (U.V-Vis) spectroscopy, conductivity measurements, magnetic susceptibility and atomic absorption. From the results obtained the following general formula has suggested for the prepared complexes [M(Quin)2( α-Pic)2].XH2O where M+2 = (Mn, Co, Ni, Cu, Zn, Cd and Hg), X = 2, X = zero for (Co+2 and Hg+2) complexes, (Quin-) = quinaldate ion, (α-Pic) = α-picoline. The results showed that the deprotonated ligand (QuinH) by using (KOH) coordinated to metal ions as bidentate ligand through the oxygen atom of the carboxylate group (-COO-) and the nitrogen ato

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

Potential data interpretation is significant for subsurface structure characterization. The current study is an attempt to explore the magnetic low lying between Najaf and Diwaniyah Cities, In central Iraq. It aims to understand the subsurface structures that may result from this anomaly and submit a better subsurface structural image of the region. The study area is situated in the transition zone, known as the Abu Jir Fault Zone. This tectonic boundary is an inherited basement weak zone extending towards the NW-SE direction. Gravity and magnetic data processing and enhancement techniques; Total Horizontal Gradient, Tilt Angle, Fast Sigmoid Edge Detection, Improved Logistic, and Theta Map filters highlight source boundaries and the

Underwater Wireless Sensor Networks (UWSNs) have emerged as a promising technology for a wide range of ocean monitoring applications. The UWSNs suffer from unique challenges of the underwater environment, such as dynamic and sparse network topology, which can easily lead to a partitioned network. This results in hotspot formation and the absence of the routing path from the source to the destination. Therefore, to optimize the network lifetime and limit the possibility of hotspot formation along the data transmission path, the need to plan a traffic-aware protocol is raised. In this research, we propose a traffic-aware routing protocol called PG-RES, which is predicated on the ideas of Pressure Gradient and RESistance concept. The proposed

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

Correlation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.

            In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol –