Levofloxacin belongs to the fluoroquinolone family; it is a potent broad-spectrum bactericidal agent. The pharmacophore required for significant antibacterial activity is the C-3 carboxylic acid group and the 4-pyridine ring with the C-4 carbonyl group, into which binding to the DNA bases occur. In this work, we tried to show that by masking the carboxyl group through amide formation using certain amines to form levofloxacin carboxamides, an interesting activity is kept. Levofloxacin carboxamides on the C-3 group were prepared, followed by the formation of their copper complexes. The target compounds were characterized by FT-IR, elemental analysis. The antimicrobial activity of the target compounds was evaluated and showed satisfactory resu

Anastatica Hierochuntica L. Used As an Alternative of Conjugated Estrogen (Premarin) in Rabbit Females

There are risks and benefits with all medicines and estrogen replacement is no exception. In fact, estrogen replacement is one of the most controversial topics in Endocrinology. Anastatica hierochuntica L. is a popular treatment for the management of female reproductive disorders. The present research highlights the effect of aqueous extract of plant against conjugated estrogen(Premarin) in rabbits. Femal oryciolagus cuniculus rabbits were divided into four groups: the 1 st group, rabbits were orally administered (using a feeding solution )with daily dose(5 mL distilled water)for two months, the 2nd group, the rabbits were treated with conjugated estrogen (50 µg/kg b.w, body weight )for one month. The 3rd group, the rabbits were treated w

There are risks and benefits with all medicines and estrogen replacement is no exception. In fact, estrogen replacement is one of the most controversial topics in Endocrinology. Anastatica hierochuntica L. is a popular treatment for the management of female reproductive disorders. The present research highlights the effect of aqueous extract of plant against conjugated estrogen(Premarin) in rabbits. Femal oryciolagus cuniculus rabbits were divided into four groups: the 1 st group, rabbits were orally administered (using a feeding solution )with daily dose(5 mL distilled water)for two months, the 2nd group, the rabbits were treated with conjugated estrogen (50 µg/kg b.w, body weight )for one month. The 3rd group, the rabbits were treated wi

ABSTRACT This study developed two adsorbents for extracting salbutamol sulphate (SAS) from water and urine samples after derivatisation with 2-aminobenzothiazole as a colour reagent. These adsorbents include cetylpyridinium chloride surfactant (CPC) modified silica and alumina-coated magnetite nanoparticles (Fe3O4/SiO2/CPC and Fe3O4/Al2O3/CPC). The derivatisation of SAS with the colour reagent resulted in an orange azo dye with maximum adsorption wavelengths of 443.0 nm. UV–Vis spectroscopy was used to identify the target analyte following the magnetic solid-phase extraction (MSPE) method. Under optimal conditions, the concentration ranges of 0.03–5.00 µg/mL and 0.05–6.00 µg/mL with good linearity (˃ 0.99), the detection limi

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

تصف هذه الدراسة تطوير تقنية سهلة ورخيصة ودقيقة وسريعة لقياس 4-اثيل فينول وتنطوي الطريقة الأولية على تحويل -3 نيترو انيلين إلى ملح ديازونيوم ثم التفاعل مع 4 - إثيل فينول في وسط قلوي.المعقد المتكون هو أصفر اللون وله امتصاص عند اعلى طول موجي عند 426 nm. ويتبع قانون بير في مدى خطي قدره 5-12 μg mL-1 مع معامل ارتباط قدره 0.994 وامتصاص مولاري 6.0024x10^3  L.mol-1.cm-1  وتم استُخدِام تقنية نقطة السحابة لقياس كميات قليلة جدا من الفينول باس

This work describes the development of new spectrophotometric techniques for 3-aminophenol assessment. The first technique involves using benzidine in an alkaline solution to convert 3-aminophenol into a colored complex. The produced complex has a red color with an absorbance of 462 nm. Between the concentration range 5–14 μg mL−1, Beer's law is obeyed with a correlation coefficient (R2) of 0.99781, a limit of detection (LOD) of 0.0423 μg mL−1, and a limit of quantification (LOQ) of 0.1411 μg mL−1. The recovery was between 87.2–95.43%, the relative standard deviation (%RSD) was 2.40–3.31% and the molar absorptivity was 3.545 × 103 L mol−1 cm−1. Secondly, cloud point extraction (CPE) was used to determ

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class