Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Green synthesis of silver nanoparticles (AgNPs) using different plant parts has shown a great potential in medicinal and industrial applications. In this study, AgNPs were in vitro green synthesized using A. graecorum, and its antifungal and antitumoractivities were investigated. Scanning electron microscopy (SEM) image result indicated spherical shape of AgNPs with a size range of 22-36 nm indicated by using Image J program. The functional groups indicated by Fourier-transform infrared spectroscopy (FTIR) represented the groups involved in the reduction of silver ion into nanoparticles. Alhagi graecorum AgNPs inhibited MCF-7 breast cancer cell line growth in increased concentration depend manner, significant differences shown at

Stable new derivative of L-ascorbic acid, 5,6-O-iso propylidene 2,3-O,O acetic acid-Lascorbic acid (L) was synthesized in good yield by the reaction of 5,6-O-isopropylidene-Lascorbic acid with chloroacetic acid in presence of potassium hydroxide. The new product (L) was characterized by 1H, 13C–NMR, mass spectrum and fourier transform infrared (FTIR). The reaction of the ligand (L) with metal bivalent ion., M+2 = (Co, Ni, Cu, Cd, Hg, Mg, Ca, Pb) synthesized and characterized by FTIR, UV-Visible, Molar conductance, Atomic absorption and the molar ratio (Ni+2, Cd+2) complexes. Spectroscopic evidence showed that the binding of the M(II) ions with (L) are through the (C–I=O) Lacton and O-2-CH2COO– as a bidentate manar re

Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with mis

In this work, we synthesized thirteen compounds of 1-(2-furoyl)thiourea derivatives 1-13 by conversion of 2-furoyl chloride to 2-furoyl isothiocyanate by reacting it with potassium thiocyanate in dry acetone in a quite short reflux time then, in the same pot, different of (primary and secondary amines) were added individually to achieve thiourea derivatives. The products were characterized spectroscopically using (FT-IR, 1H NMR and 13C NMR) techniques. Some of them were evaluated as antioxidant agents using DPPH radical scavenging method, and all were examined theoretically as enzyme inhibitors against Bacillus pasteurii urease (pdb id: 4ubp) and  by studying  molecular docking using Autodock (4.2.6) software.

A total of 551 water samples (drinking and raw water) were collected In this study, Aeromonas.hydrophila, were detected by biochemical tests and PCR (16s rRNA gene). The results of identification showed that A.hydrophila had recovery rate 63 isolates (49.21%). The results revealed that all A.hydrophila isolates were PCR positive or the 16S rRNA gene and the results of sequencing showed that two isolates of A.hydrophila(local isolates) had percentage similarities 100% with A. hydrophila ATCC 7966 in GenBank database .All strains had a minimal Inhibitory Concentration(MIC) distribution pattern for lead cetate rranged (900-1200 μg/ml), and mercury chloride ranged (40-80 μg /ml).

The N-[(2,3-dioxoindolin-1-yl)-N-methylbenzamide] was prepared by the reaction of acetanilide with isatin then in presence of added paraformaldehyde, the prepared ligand was identified by microelemental analysis, FT.IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following selected metal ions (CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio, yielded a series of complexes of the general formula [M(L)2Cl2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) analysis, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). From the obtained data the octahed