New isatinic hydrazone Schiff-base ligands, namely furan-2-carboxylic acid (2-oxo-1,2-dihydro-indol- 3-ylidene)-hydrazide (L1), thiophene-2-carboxylic acid (2- oxo-1,2-dihydro-indol-3-ylidene)-hydrazide (L2) and 2-(pyridine-2-yl-hydrazono)-1,2-dihydro-indol-3-one) (L3) are reported. The ligands were prepared by the condensation of furan-2-carboxylic acid hydrazide (L1), thiophene- 2-carboxylic acid hydrazide (L2), and 2-hydrazino pyridine (L3) with isatine. Monomeric complexes were prepared from the reaction of the corresponding metal chloride with the ligands. The ligands and their nine new complexes of the general formulae [M(Ln)2]Cl2 [where M = Co(II), Zn(II) and Cd(II); n = L1, L2 and L3] were characterised by spectroscopic methods (FTI

This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

The nucleon momentum distributions (NMD) for the ground state and elastic electron scattering form factors have been calculated in the framework of the coherent fluctuation model and expressed in terms of the weight function (fluctuation function). The weight function has been related to the nucleon density distributions of nuclei and determined from theory and experiment. The nucleon density distributions (NDD) is derived from a simple method based on the use of the single particle wave functions of the harmonic oscillator potential and the occupation numbers of the states. The feature of long-tail behavior at high momentum region of the NMD has been obtained using both the theoretical and experimental weight functions. The observed ele

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

In this work chemical vapor deposition method (CVD) for the production of carbon nanotubes (CNTs) have been improved by the addition of S. Steel mesh container (SSMC) inside which the catalyst (Fe/Al2O3) was placed. Scanning electron microscopy (SEM) investigation method used to study nanotubes produced, showed that high yield of two types of (CNTs) obtained, single wall carbon nanotube (SWCNTs) with diameter and length of less than 50nm and several micrometers respectively and nanocoil tubes with a diameter and length of less than 100nm and several micrometers respectively. The chemical analysis of (CNTs) reveals that the main component is carbon (94%) and a little amount of Al (0.32%), Fe (2.22%) the reminder is oxygen. It was also fou

The adsorption of hexavalent chromium by preparing activated carbon from date seeds with zinc chloride as chemical activator and granular date seeds was studied in a batch system. The characteristics of date seeds and prepared activated carbon (ZAC) were determined and found to have a surface area 500.01 m²/g and 1050.01  m²/g , respectively and  iodine number of 485.78 mg/g and 1012.91  mg/g, respectively. The effects of PH value (2-12), initial sorbate concentration(50-450mg/L), adsorbent weight (0.004-0.036g) and contact time (30-150 min) on the adsorption process were studied . For Cr(VI) adsorption on ZAC, at 120 min time contact, pH solution 2 and 0.02  adsorbent  weight  will ach

تهدف هذه الدراسة للتعرف على السياسات اإلاسرائيلية المتبعة على الارض والمتمثلة في االاستيطان
الاستعماري والطرق التفافية، ومصادرة الاراضي وجدار الضم والتوسع العنصري، بالاضافة إلى التصنيف
الاداري للمناطق في الضفة الغربية حسب ما جاء في اتفاقية أوسلو، والتي من شأنها التأثير على تلك
المناطق، وال سيما قطاع اإلسكان الذي يعد من أهم القطاعات التي تتر كب وبالتحديد في منطقة الدراسة،
وسوف تحاول هذه الدراسة تس

Bioethanol production from sugar fermentation is one of the most sustainable alternatives to substitute fossil fuel. production of bioethanol from low grade dates which are rich of sugars. An available sugar from a second grade dates (reduction sugar) was 90g/l in this study. Sugar can be served as essential carbon sources for yeast growth in aerobic condition and can also be converted to bioethanol in anaerobic condition. The effect of various parameters on bioethanol production, fermentation time, pH-values, inoculum size and initial sugar concentration were varied in order to determine the optimal of bioethanol production. The highest bioethanol yield was 33g/l which was obtained with sugar concentration 90 g/l, inocu

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col