Background and aim: Pomegranate is a medicinal herb that can promote healing of periodontal tissue through differentiation of mesenchymal cells both in vivo and in vitro. Therefore, this study is to investigate the effect of oral supplementation of Punicagranatum L. peel extract on bone defect in rabbit. Methods: Forty five male rabbits were divided into 3 groups; group 1; baseline group(5 rabbits) left without bone defect. Group 2; study group (20 rabbits) with bone defect model that received daily 1ml of oral supplementation of pomegranate peel extract (PoPx). Group 3; control group (20 rabbits) with bone defect model that received distilled water. Bone defect was done into facial plate of lower right central incisor. Blood biopsies by cardiocentesis at times (base line, 3h, 1, 3 and 7days) for estimation of serum calcium, phosphorous, and vitamin D levels. Results: The results showed a significant increase in serum calcium and phosphorous levels only after 3 hours and 1 day of bone defect, in rabbits receiving water and rabbits receiving pomegranate peel extraction. Serum vitamin D level shows significant increase in all time intervals reaching maximum value after three days in rabbits receiving pomegranate peel extract, while no significant change was observed in rabbits receiving water. Conclusions: Supplementation of pomegranate peel extract can increase vitamin D absorption, thus it may promote the bone healing process.
The current study aimed to standardize the multi-position suicidal tendency scale MAST in the Saudi environment as well as to assess suicidal tendencies in adolescents. Moreover, the study aimed to test the psychometric characteristics of the scale among a sample of (490) high school and undergraduate students, in the adolescence who ranging in age from (16-21) years. The scale demonstrated satisfactory internal consistency in terms of validity and reliability tests. as the results showed of exploratory factor analysis to the four dimensions of suicidal tendencies loading on two factors that accommodate 74.60% of the overall variance of the scale (1) the attitude toward life, and absorbs 43, 20% of the total variance of the scale,
... Show Moresensor sampling rate (SSR) may be an effective and crucial field in networked control systems. Changing sensor sampling period after designing the networked control system is a critical matter for the stability of the system. In this article, a wireless networked control system with multi-rate sensor sampling is proposed to control the temperature of a multi-zone greenhouse. Here, a behavior based Mamdany fuzzy system is used in three approaches, first is to design the fuzzy temperature controller, second is to design a fuzzy gain selector and third is to design a fuzzy error handler. The main approach of the control system design is to control the input gain of the fuzzy temperature controller depending on the cur
... Show More
This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.
The extraction of Cupressus sempervirens L. or cypress essential oil was studied in this paper. This cypress oil was extracted by using the hydro-distillation method, using a clevenger apparatus. Cupressus sempervirens L. leaves were collected from Hit city in Al-Anbar province – Iraq. The influences of three important parameters on the process of oil extraction; water which used as a solvent to the solid ratio (5:1 and 14:1 (ml solvent/g plant), temperature (30 to 100 °C) and processing time, were examined to obtain the best processing conditions to achieve the maximum yield of the essential oil. Also, the mathematical model was described to calculate the mass transfer coefficient. Therefore, the best conditions, that were obtained in
... Show MoreThe consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying
... Show MoreThe ongoing COVID‐19 pandemic caused by SARS‐CoV‐2 is associated with high morbidity and mortality. This zoonotic virus has emerged in Wuhan of China in December 2019 from bats and pangolins probably and continuing the human‐to‐human transmission globally since last two years. As there is no efficient approved treatment, a number of vaccines were developed at an unprecedented speed to counter the pandemic. Moreover, vaccine hesitancy is observed that may be another possible reason for this never ending pandemic. In the meantime, several variants and mutations were identified and causing multiple waves globally. Now the safety and efficacy of these vaccines are debatable and recommended to d
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
... Show More