Polymer metal complexes of poly ethylene glycol acetal and Ag (I), Cu (II), Ni (II), Mn (II), Co (III) and Hg (II) were prepared from the reaction of PEG with aldehyde derived from Erythro-ascorbic acid (pentulosono-ɣ-lactone-2, 3- enedianisoate). All these compounds were characterized by Thin Layer Chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR,13CNMR, and mass spectra. It has been established that, the polymer and its metal complexes showed good activities against four pathogenic bacteria (Escherichia coli ,Klebsiellapneumonae, Staphylococcusaureus, Staphylococcus Albus) and two fungal (Aspergillus Niger,Yeast). The polymer metal complexes showed higher activity than the free polymer. The

Complexes of Cr+3, Ni+2 and Cu+2 with the ligand 2-(p- nitrobenzoyl) thiobenzimidazol) (L) were prepared and characterized by FT-IR ,UV-Visible, TG analysis ,Atomic absorption spectroscopy , Molar conductivity and magnetic moments measurements .The general formula has been suggested for all the prepared complexes [Cr(L)2Cl2]Cl.4H2O, [Ni(L)2(H2O)2]Cl2.2H2O and [Cu(L)2(H2O)2]Cl2.2C2H5OH to be an octahedral geometry. A theoretical treatment of these compounds in gas phase was done using HyperChem.8.7 program. Semi –empirical PM3 method was performed to evaluate the ∆H° ƒ, ∆ Eb and ∆ET for all compounds, also vibration frequencies, electronic spectra and electrostatic potential HOMO and LUMO energies for the ligand was estimated to de

Polymer metal complexes of poly ethylene glycol acetal and Ag (I), Cu (II), Ni (II), Mn (II), Co (III) and Hg (II) were prepared from the reaction of PEG with aldehyde derived fromErythro-ascorbic acid (pentulosono-ɣ-lactone-2, 3- enedianisoate). All these compounds were characterized by Thin Layer Chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR,13CNMR, and mass spectra. It has been established that, the polymer and its metal complexes showedgood activities against four pathogenic bacteria (Escherichia coli , Klebsiellapneumonae,Staphylococcusaureus, Staphylococcus Albus) and two fungal (Aspergillus Niger,Yeast). The polymer metal complexes showed higher activity than the free polymer.Theorder

Complexes reaction of Fe+2, Cd+2, Hg+2 and Ag+ with the 2-thiotolylurea were prepared in ethanolic medium with the (1:1) M:L ratio yielded a series of neutral complexes. The prepared complexes were characterized using flame atomic absorption, micoelemental analysis (C.H.N), chloride content (Mohr Method) , FT.IR and UV-Vis spectroscopic, as well as magnetic susceptibility and conductivity measurement. From the above data, the proposed molecular structure for Fe+2, Cd+2 and Hg+2 complexes are tetrahedral geometry while Ag+ complex is trigonal structure.

Aeromonas salmonicida is a fish pathogen and recognized to cause a variety of diseases in humans. There are a few information about A.salmonicida in Iraq and there is no any previous molecular study on it. During the period of December 2017 to May 2018; Sixteen isolates of the A. salmonicida were isolated and identified from 300 common carp (Cyprinus carpio) fishes stomach in aquarium of Erbil city/ Iraq by using manual, automated Vitek 2 compact system, and confirmed by PCR using gene TonB-dependent siderophore (364bp). Antimicrobial susceptibility was determined by disk diffusion method and the results found that all isolates 100% susceptible to imipenem, 100% resistant to nalidixic acid and variable resistan

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

This paper presents a brief study undertaken for improving the performance of information and communication management of construction projects through investing in information and communication technologies (ICT). The work aims at first to investigate and diagnose the problems, challenges, weaknesses, and inefficiencies related to information and communication management in projects in the construction industry of Iraq. Studying the diagnosed matters and the different solutions of ICT to improve project management performance is following the investigation process. The research presents a technological system suggested to process a lot of the diagnosed problems, challenges, weakness, and inefficiencies of the construction projects and t

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The aim of the research is to investigate the effect of cold plasma on the bacteria grown on texture of sesame paste in its normal particle and nano particle size. Starting by using the image segmentation process depending on the threshold method, it is used to get rid of the reflection of the glass slides on which the sesame samples are placed.  The classification process implemented to separate the sesame paste texture from normal and abnormal texture. The abnormal texture appears when the bacteria has been grown on the sesame paste after being left for two days in the air, unsupervised k-mean classification process used to classify the infected region, the normal region and the treated region. The bacteria treated with cold plasma, t