Biosynthesis of nanoparticles has received considerable attention due to the growing need to develop environmentally benign nanoparticle synthesis processes that do not use toxic chemicals. Therefore, biosynthetic methods employing both biological agents such as bacteria and fungus or plant extracts have emerged as a simple and a viable alternative to chemical synthetic and physical method .It is well known that many microbes produce an organic material either intracellular or extracellular which is playing important role in the remediation of toxic metals through reduction of metal ions and acting as interesting Nano factories. As a result, in the present study Ag NPs were synthesized by two methods biosynthetic technique using supernatant of Corynebacterium glutamicum that isolated from soil and green synthesis method by using plant extracts of fresh green plants.Ag NPs which synthesized by two methods were investigated visually by monitoring the color shift of reaction mixture from pale yellow to brown color, UV-Visible spectrophotometer was used to measure maximum absorbance of synthesized Ag NPs. The nanoparticles synthesized from Corynebacterium glutamicum exhibited maximum antimicrobial activity against selected pathogenic and environmental strains more than Ag NPs synthesized by green synthesis method from Spinacia oleracea, Malva parviflora and Eruca sativa. plant extracts
Acinetobacter baumannii ability to form biofilm makes it to be opportunistic pathogen causing of nosocomial infections and to be good survivor in adverse environmental conditions including medical devices and hospital environments. Six isolates of A. baumannii were isolated from drinking water and tested to investigate biofilm formation capacity on three different type of abiotic surface, also several factors were examined such as hydrophobicity, PH and temperature. All A. baumannii isolates displayed a positive biofilm on congored aga test CRA (pigmented colonies with black color) and Christensen's test (adhesive layer of stained material to the inside surface of the tube).The obtained data of microbial adhesion to hydrocarbons assay (MATH
... Show MoreThe aesthetic and technical expertise help in producing the artistic work and achieving results in aesthetic formulations that reflect the aesthetic and expressive dimensions and the reflective dimensions of the pottery, surpassing its traditions, asserting its active presence in life, cherishing it even when it breaks or get damaged by employing techniques that are originated from the Japanese environment.
The research problem is to study how ( Kintsugi) technique and similar techniques are used to create new rebirths of pottery piec
... Show MoreIdentifying phenolic compounds in some genera belonging in the Amaranthaceae family by HPLC technique
In this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.
Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
... Show MoreIsolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to find the best bacteria to remove kerosene from soil. The active bacteria are isolated for kerosene degradation process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradation which is 88.5%. The optimum conditions of kerosene degradation by Klebsiella pneumonia sp. are pH5, 48hr incubation period, 35°C temperature and 10000ppm the best kerosene concentration. The results 10000ppm showed that the maximum kerosene degradation can reach 99.58% after 48 h of incubation. Higher Kerosene degradation which was 99.83% was obtained at pH5. Kerosene degradation was found to be maximum at 3
... Show MoreThis research aims to develop new spectrophotometric analytical method to determine drug compound Salbutamol by reaction it with ferric chloride in presence potassium ferricyanide in acid median to formation of Prussian blue complex to determine it by uv-vis spectrophotmetric at wavelengths rang(700-750)nm . Study the optimal experimental condition for determination drug and found the follows: 1- Volume of(10M) H2SO4 to determine of drug is 1.5 ml . 2- Volume and concentration of K3Fe(CN)6 is 1.5 ml ,0.2% . 3- Volume and concentration of FeCl3 is 2.5ml , 0.2%. 4- Temperature has been found 80 . 5- Reaction time is 15 minute . 6- Order of addition is (drug + K3Fe(CN)6+ FeCl3 + acid) . Concentration rang (0.025-5 ppm) , limit detecti
... Show MoreIsolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to nd the best bacteria to remove kerosene from soil. The acve bacteria are isolated for kerosene degradaon process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradaon which is 88.5%. The opmum condions of kerosene degradaon by Klebsiella pneumonia sp. are pH5, 48hr incubaon period, 35°C temperature and 10000ppm the best kerosene concentraon. The results 10000ppm showed that the maximum kerosene degradaon can reach 99.58% aer 48 h of incubaon. Higher Kerosene degradaon which was 99.83% was obtained at pH5. Kerosene degradaon was found
... Show MoreIn this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
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