The specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO₂) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO₂. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO₂/

In order to achieve optimal plant growth and production, essential nutrients must be readily available in adequate quantities and in a balanced proportion to give a good yield, especially broccoli which has health benefits that may not be found in many other plants. For this purpose, this experiment was carried out during the seasons 2019/2020 in the botanical garden of the Department of Biology, College of Science for Women, University of Baghdad, to study the effects of nitrogen and sulphur and their interaction on eight parameters reflecting the overall traits of vegetative growth, yield, and chlorophyll content of broccoli Brassica oleracea L. (var. italic JASSMINE F1 Hybrid). A factorial design with three replicates was use

This study was conducted to detect the relationship between organic content in the sediment of Rivers Tigris and Diyala, at two locations south of Baghdad, with some environmental factors and the benthic invertebrates and values of diversity indices. Monthly samples collected from the area for the period November 2007 to October 2008. Results showed differences in the physical and chemical characteristics of the two sites, Where the annual average in Tigris and Diyala were respectively for: water temperature (19, 20) C°, pH (8, 8), dissolved oxygen (4, 8) mg / l , Biochemical oxygen Demand BOD5 (3,44 ) mg/l, TDS (632,1585) mg / l, TSS (42, 44) mg / l, turbidity (28,74) NTU, and total hardness as CaCO3 (485,823) mg / l ,Sulfat

This study aims to study some morphological and reproductional characteristics in eleven species of two genera belonging to the family of Asparagaceae, which are Bellevalia Lapeyrouse, 1808 and Ornithogalum Linnaeus, 1753 and the species are: Bellevalia chrisii Yildirim and Sahin, 2014; Bellevalia flexuosa Boissier, 1854; Bellevalia kurdistanica Feinbrun, 1940; Bellevalia longipes Post, 1895; Bellevalia macrobotrys Boissier, 1853; Bellevalia paradoxa Boissier, 1882; Bellevalia parva Wendelbo, 1973; Bellevalia saviczii Woronow, 1927; Ornithogalum brachystachys C. Koch, 1849; Ornithogalum neurostegium Boissier, 1882 and Ornithogalum pyrenaicum Linnaeus, 1753. These species were identified and compared with each other; the results showed th

Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the

Thermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

     This paper develops the work of Mary Florence et.al. on centralizer of semiprime semirings and presents reverse centralizer of semirings with several propositions and lemmas. Also introduces the notion of dependent element and free actions on semirings with some results of free action of centralizer and reverse centralizer on semiprime semirings and some another mappings.

In order to evaluate the performance of introduced varieties of maize and test them under different levels of plant density, and to determine which of the introduced varieties give a high yield and at what plant density, a field experiment was carried out at Station A in the Department of Field Crops- College of Agricultural Engineering Sciences - University of Baghdad- Jadiriyah, for the fall season 2021, the RCBD design was used with four replications, in a split plot arrangement, the three plant densities (50.000, 70.000, and 90.000 Plant s ha^-1) were the main plates, while the varieties represented the secondary factor, which is six varieties of maize, class 2 = 5783 DKC, Class 3 = 6315 DKC, Class 4= 6590 DKC, whic