Nitrogen-comprising heterocyclic compounds and their derivatives have empirically been invaluable as therapeutic agents. Fundamentally, 4-chloro-6-nitro-2-amino-1,3-benzothiazole 1 was synthesized via bromination of 2-chloro-4-nitro aniline with ammonium thiocyanate. This new heterocyclic haloorganoamino-1,3-benzothiazole derivative, was a starting material, which condensed and tethered with three different aromatic aldehyde pendant arm in presence of ethanol and glacial acetic acid isolating an interesting sequence of tridentate Schiff bases 2-4. These compounds were used for complexation reactions in 1:1 (metal: ligand) stoichiometry to obtain heteroleptic Al(III), Ni (II) and K(I) benzothiazole chelat

In this work an experimental simulation is made to predict the performance of steady-state natural heat convection along heated finned vertical base plate to ambient air with different inclination angles and configurations of fin array. Two types of fin arrays namely vertical fins array and V-fins array on heated vertical base plate are used with different heights and spaces. The influence of inclination angle of the plate , configuration of fins array and fin geometrical parameters such as fin height and fin spacing on the temperature distribution, base convection heat transfer coefficient and average Nusselt number have been plotted and discussed. The experimental data are correlated to a formula between average Nusselt number versus R

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

The caliphs of Tukalti Able III (Tiglath-pileser) sustained their extension and enclosure strategy whom they were highly talented with outstanding potentialities. They performed their political plan of extinguishingthe ambitions of the upper class and the internal uprisings. The Assyrian Kingdom, in the eighth century BC reached to the highest degree of expansion that no other ancient Iraqi kingdom had reached It dominated the whole near eastbut it did not have absolute command due to the subsequent uprisings that out bursted in the regions attached to the kingdom near the borders.

Abstract

The present paper focuses in a particular on the study of the biochar production conditions by the thermal pyrolysis of biomass from local Iraqi palm fronds, in the absence of oxygen. The biochar product can be used as soil improvers. The effect of temperature on the extent of the thermal pyrolysis process was studied in the range from 523 to 773K with a residence time of 15 minutes and nitrogen gas flow rate of 0.1 l/min. The produced biochar was characterized as will as biomass and degradation products. The results showed that the rate of biochar production decreases with the increasing in temperature, also it was noted that the normalized biochar surface area and pore size increases with the increasin

            In this study, pure SnO₂ Nanoparticles doped with Cu were synthesized by a chemical precipitation method. Using SnCl₂.2H₂O, CuCl₂.2H₂O as raw materials, the materials were annealed at 550°C for 3 hours in order to improve crystallization. The XRD results showed that the samples crystallized in the tetragonal rutile type SnO₂ stage. As the average SnO₂ crystal size is pure 9nm and varies with the change of Cu doping (0.5%, 1%, 1.5%, 2%, 2.5%, 3%),( 8.35, 8.36, 8.67, 9 ,7, 8.86)nm respectively an increase in crystal size to 2.5% decreases at this rate and that the crystal of SnO₂ does not change with the introduction of Cu, and S

Polymer additives binder system provides many properties useful in thermal energy storage (TES) then developed the efficient energy storage materials and green strength bodies system.

This paper studies the thermal energy storage property for polyvinyl alcohol (PVOH) / paraffin wax (WPw) blends. To enhance paraffin wax thermal conductivity, PVOH as a material which high conductivity was employed. A fixed weight of Paraffin wax was dispersed with PVOH heterogeneously at different additive weights ratios of PVOH/Pw (50/50, 67/33, 75/25, and 80/20) wt. ratio respectively. The composite material was prepared using wetted pressing method.

Both base materials (polyvinyl alcohol and paraffin wax) were scanned using differential

          Aleppo bentonite was investigated to remove ciprofloxacin hydrochloride from aqueous solution. Batch adsorption experiments were conducted to study the several factors affecting the removal process, including contact time, pH of solution, bentonite dosage, ion strength, and temperature. The optimum contact time, pH of solution and bentonite dosage were determined to be 60 minutes, 6 and 0.15 g/50 ml, respectively. The bentonite efficiency in removing CIP decreased from 89.9% to 53.21% with increasing Ionic strength from 0 to 500mM, and it increased from 89% to 96.9% when the temperature increased from 298 to 318 K. Kinetic studies showed that the pseudo second-order model was the best in describing  the adsorption sys

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

In this research, the effect of adding two different types of reinforcing particles was investigated, which included: nano-zirconia (nano-ZrO₂) particles and micro-lignin particles that were added with different volume fractions of 0.5%, 1%, 1.5% and 2% on the mechanical properties of polymer composite materials. They were prepared in this research, as a complete prosthesis and partial denture base materials was prepared, by using cold cure poly methyl methacrylate (PMMA) resin matrix. The composite specimens in this research consist of two groups according to the types of reinforced particles, were prepared by using casting methods, type (Hand Lay-Up) method. The first group consists of PMMA resin reinforced by (nano-ZrO