Tuaimah GS, AQ Al-Awadi, Ahmed ME., Effect of Cutibacterium acnes cell free antigen (CFAg) immunization, levofloxacin and cinnamon oil on Cutibacterium acnes infection in rabbits, Onl J Vet Res., 22 (9):811-822, 2018. C. acnes causes acne vulgaris most commonly in 12-24 year olds. Five albino rabbits were immunized at day 1 and 14 with Cutibacterium acnes cell free antigen (CFAg) and then infected intradermally with 0.1 ml C. acnes suspension (2×108 cfu/ml) at day 30. Two groups of five infected rabbits were then treated at Day 30 with 0.5% levofloxacin or 0.2% cinnamon oil twice daily for 12 days. Five control rabbits were infected intradermally with 0.1 ml 2×108 cfu/ml Cutibacterium acnes n (2×108 cfu/ml). At day 42, skin test (mm), se

Background: Oncogenesis in the oral cavity is widely believed to result from cumulative genetic alterations that cause a transformation of the mucosa from normal to dysplastic to invasive carcinoma. The p16 gene produces p16 protein, which in turn inhibits phosphorylation of retinoblastoma (Rb), p16 play a significant role in early carcinogenesis. A number of epidermal growth factor receptor (EGFR) family, HER2/neu, has received much attention because of its therapeutic implications. The aims of the study were to evaluate and compare the immunohistochemical expression of the cell cycle protein P16 INK4a and c-erbB2 (HER2/neu) in NOM, OED, and OSCC. Correlate both marker expression with each other as well as with various clinicopathological

In the present paper, chitosan Schiff base has been synthesized from chitosan’s reaction with the salicyldehyde. The AuNPs was manufacture by extract of onion peels as a reducing agent. The Au NPs that have been prepared were characterized through the UV-vis spectroscopy, XRD analyses and SEM microscopy. The polymer blends of the chitosan Schiff base / PVP has been prepared through using the approach of solution casting. Chitosan Schiff base / PVP Au nano-composites was prepared. Nano composites and polymer blends have been characterized by FTIR which confirm the formation of Schiff base by revealing a new band of absorption at 1651cm^-1 as a result of the (C=N) imine group. SEM, DSC and TGA confirms the thermal stability of

In the present paper, chitosan Schiff base has been synthesized from chitosan’s reaction with the salicyldehyde. The AuNPs was manufacture by extract of onion peels as a reducing agent. The Au NPs that have been prepared were characterized through the UV-vis spectroscopy, XRD analyses and SEM microscopy. The polymer blends of the chitosan Schiff base / PVP has been prepared through using the approach of solution casting. Chitosan Schiff base / PVP Au nano-composites was prepared. Nano composites and polymer blends have been characterized by FTIR which confirm the formation of Schiff base by revealing a new band of absorption at 1651cm-1 as a result of the (C=N) imine group. SEM, DSC and TGA confirms the thermal stability of the pr

Abstract

The analysis of Least Squares: LS is often unsuccessful in the case of outliers ​​in the studied phenomena. OLS will lose their properties and then lose the property of Beast Linear Unbiased Estimator (BLUE), because of the Outliers have a bad effect on the phenomenon. To address this problem, new statistical methods have been developed so that they are not easily affected by outliers. These methods are characterized by robustness or (resistance). The Least Trimmed Squares: LTS method was therefore a good alternative to achieving more feasible results and optimization. However, it is possible to assume weights that take into consideration the location of the outliers ​​in the data and det

حسن السيد عز الدين بحر العلوم العقد الاجتماعي والسلطة الشعبية عند الإمام علي (عليه السلام )

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

As the demands of sixth-generation (6G) networks escalate towards achieving high speeds and improved energy efficiency, there is an increasing need for intelligent and real-time adaptive solutions within the physical processing layer. This study proposes an innovative engineering framework based on an encapsulated architecture utilising FBGA (micro-distributed spherical array) technology, integrated with an internal artificial intelligence module, to achieve adaptive beamforming with high efficiency in dense wireless environments. The primary objective of this research is to develop an intelligent communication architecture that determines the optimal transmission angles and regulates power consumption in real-time by integrating ar

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti