The compound [L] was produced in the current study through the reaction of 4-aminoacetophenon with 4-methoxyaniline in the cold, concentrated HCl with 10% NaNO2. Curcumin, several transition metal complexes (Ni (II), La (III), and Hg (II)), and compound [L] were combined in EtOH to create new complexes. UV-vis spectroscopy, FTIR, AA, TGA-DSC, conductivity, chloride content, and elemental analysis (CHNS) were used to describe the structure of produced complexes. Biological activities against fungi, S. aureus (G+), Pseudomonas (G-), E. coli (G-), and Proteus (G-) were demonstrated using complexes. Depending on the outcomes of the aforementioned methods, octahedral formulas were given as the geometrical structures for each created comp

In the present study, chitosan Schiff base has been prepared from chitosan reaction with p-chloro benzaldehyde. The AuNPs and AgNPs were manufactured by extract of onion peels as a reducing agent. The AuNPs and AgNPs that have been synthesized were characterized through UV-vis spectroscopy, XRD analyses and SEM microscopy. The polymer blends of the chitosan / PEG has been prepared by using the approach of solution casting. Chitosan Schiff base / PEG Au and Ag nanocomposites were synthesized, nanocomposites and polymer blends have been characterized by FTIR which confirm the formation of Schiff base by revealing a new band of absorption at 1693 cm-1 as a result of the (C=N) imine group. FESEM, DSC and TGA confirm the thermal stability

A novel ligand ((1E)-(2-(4-fluorobenzylidene)amino)methyl) phenyl)diazenyl)-1,3,7-trimethyl-3,7-dihydro-1H-purine-2,6-dione (4-FADPD) was synthesized via the azotization reaction of 2-aminobenzylamine with caffeine, and the resultant compound was condensed with 4-fluorobenzaldehyde to form a newly azo-Schiff base ligand. Its complexes with Cu(II), Ag(I), and Au(III) were synthesized. The results of multi-identifications, including XRD, elemental analysis (C.H.N), UV-vis spectroscopy, FTIR, and 1H-NMR, were used to propose the suggested structures using molar conductivity measurements. These data were utilized to propose appropriate geometric configurations for all complexes. The azo-Schiff base ligand coordinates toward the Cu(II) i

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

Many purposes require communicating audio files between the users using different applications of social media. The security level of these applications is limited; at the same time many audio files are secured and must be accessed by authorized persons only, while, most present works attempt to hide single audio file in certain cover media. In this paper, a new approach of hiding three audio signals with unequal sizes in single color digital image has been proposed using the frequencies transform of this image. In the proposed approach, the Fast Fourier Transform was adopted where each audio signal is embedded in specific region with high frequencies in the frequency spectrum of the cover image to sa

The railways network is one of the huge infrastructure projects. Therefore, dealing with these projects such as analyzing and developing should be done using appropriate tools, i.e. GIS tools. Because, traditional methods will consume resources, time, money and the results maybe not accurate. In this research, the train stations in all of Iraq’s provinces were studied and analyzed using network analysis, which is one of the most powerful techniques within GIS. A free trial copy of ArcGIS®10.2 software was used in this research in order to achieve the aim of this study. The analysis of current train stations has been done depending on the road network, because people used roads to reach those train stations. The data layers for this st

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably