The experiment was carried out in the Department of Biology, College of Education for Pure Science –Ibn AL Haitham, University of Baghdad, Iraq, during the growing season 2017 – 2018. The objective was to find out the effect of foliar spraying of tryptophan and IQ COMBI nano fertilizer on cumin plants. The obtained results show that both tryptophan and IQ COMBI nano fertilizer increased plant height, root length, shoot dry weight, the content of nitrogen, phosphorus, potassium, protein percentage, no. compound umbel.plant-1, wt. seeds. plant-1. The optimum treatment combination was calculated as 30 mg.L-1 tryptophan, 1000mg.L-1 IQ COMBI nano fertilizer, which gave the highest values for most of the parameters studied

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

     Cadastral map environment is directed, more than ever before, towards Artificial Intelligence use to produce fast and accurate maps and keep up with the huge population growth. The traditional approach currently in production of maps is expensive and effort-intensive in addition to be considered as highly time-consuming process.  UAV-based cadastral mapping imagery that use automatic techniques are newly being exploited to accelerate the process of production or updating. The state-of-the-art intelligent algorithms are capable to extract land boundaries from images better than conventional techniques. This paper presents an automatic workflow of cadastral map production based on land boundary and automatic f

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener