Pyridine-2, 6-dicarbohydrazide comp (2) was synthesized from ethanolic solution of diethyl pyridine-2, 6- dicarboxylate comp (1) with excess of hydrazine hydrate. Newly five polymers (P1-P5) were synthesized from reaction of pyridine-2, 6-dicarbohydrazide comp (2) with five different di carboxylic acid in the presence of poly phosphoric acid (PPA). The antibacterial activity of the synthesized polymers was screened against some gram positive and gram negative bacteria. Antifungal activity of these polymers was evaluated in vitro against some yeast like fungi such as albicans (candida albicans). Polymers P3, P4 and P5 exhibited highest antibacterial and antifungal against all microorganisms under test.

The effect of irradiation and exposure time of laser light on the fluorescence emission of DCM dye in PMMA polymer contained in the composition mold using different metals have been investigated. It was found that the fluorescence intensity decreases as the exposure time increases and then reaches stabilization at long times. The effect of the incident laser power on fluorescence intensity of DCM dye in PMMA polymer at 10-3 M and 20% mixing ratio, using copper disks of composition molds, has been studied too. It was observed that there is an upward knick in the curve at laser intensity of 19.2 W/cm2, which may be associated with the threshold for amplified spontaneous emission (ASE) or laser action. And at intensity higher than about 88.

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

In this work, some of new 2-benzylidenehydrazinecarbothioamide derivatives have been prepared by condensation of thiosemicarbazide and different substituted aromatic benzaldehydes in presence of glacial acetic acid to give compounds (1-6), these compounds have characterized by its physical properties and spectroscopic methods. This work also included theoretical study to prove the ability of these compounds as corrosion inhibitors; The program package of Gaussian 09W with its graphical user interface GaussView 5.0 had used for this purpose; the methods of Density Functional Theory (DFT) with basis set of 6-311G (d,p) / hybrid function of B3LYP and semiempirical method of PM3 have been used, the study included theoretical simulation

This research involves the synthesis of some sulphanyl benzimidazole derivatives (Ia-c), which were prepared from reaction of 2-mercaptobenzimidazole substituted benzyl halide, and structures were identified by spectral methods[FTIR, 1H-NMR and 13C-NMR].These compounds were investigated as corrosion inhibitors for carbon steel in 1M H2SO4 solution using weight loss, potentiostatic polarization methods; obtained results showed that the sulphanyl benzimidazole derivatives retard both cathodic and anodic reactions in acidic media, by virtue of adsorption on the carbon steel surface. This adsorption obeyed Langmuir’s adsorption isotherm. The inhibition efficiency of (Ia-c) ranging between (65-92) %. By using different Ib derivative conc

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai