Celery (Apium graveolens L. ; family : Apiaceae) was often used as a spice in daily food. However, this plant contains many antioxidant compounds useful for attenuating neurodegenerative disorders including Parkinson's disease. Planting celery in the form of microgreens harvested 15 days was expected to increase the content of bioactive compounds. In the current study, we intended to evaluate the neuromodulatory potential of methanol extract of celery microgreens on fruit flies (Drosophila melanogaster Meigen : family Drosophilidae ; ordo : Diptera) which were exposed to paraquat. Neuroprotective capacity was assessed by survival rate, locomotor performance, lipid peroxidation and dopamine content after being treated wi

The aim of this work is to study the factors that affect the welding joint of dissimilar metals. Austenitic stainless steel-type AISI (316L) with a thickness of (2mm) was welded to carbon steel (1mm) using an MIG spot welding.  The filler metal is a welding wire of the type E80S-G (according to AWS) is used with (1.2mm) diameter and CO₂ is used as shielding gas with flow rate (7L/min) for all times was used in this work.

        The results indicate that the increase of the welding current tends to increase the size of spot weld, and also increases the sheer force.  Whereas the sheer force increased inversely with the time of welding. Furthermore, the results indicate that i

Background: The Covid-19 pandemic changed the world; its most important achievement for education was changing the approach from traditional to virtual education. The present study aimed to investigate the role of virtual education networks on mental health of students including personality, beliefs, scientific, and cultural dimensions, in selected countries.Methods: This was an exploratory and applied study. According to the phenomenology strategy, theoretical saturation occurred after 24 semi-structured and targeted qualitative interviews with teachers from Iran, Iraq, Syria and Lebanon, in 2023. Quantitative data was collected through a researcher-made online questionnaire with 423 participants. Teachers with at least a Bachelor’s degr

RM Abbas, AA Abdulhameed, AI Salahaldin, International Conference on Geotechnical Engineering, 2010

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

The current research includes the adsorption of Rhodmine-B Dye on the surface of Citrus Leaves using the technique of UV. Vis spectrophotometer to determine data of quantitative adsorption at various contact time, ionic strength, PH and temperature conditions. As a function of temperatures 25,35,45,55 ⁰C, the dsorption phenomenon was examined, and the results showed that Rhodamine-B adsorption Citrus leaves rose with increasing temperatures on the surface (endothermic process). Using various NaCl solution concentrations, the effect of ionic strength on adsorption has also been studied. Increasing the importance of ionic strength has been shown to improve the amount of adsorption of Rhodamine-B on citrus leaves at constant temp

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f