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.

The physical, mechanical, electrical and thermal properties containing (Viscosity, curing, adhesion force, Tensile strength, Lap shear strength, Resistively, Electrical conductivity and flammability) of adhesive material that prepared from Nitrocellulose reinforced with graphite particles and aluminum streat. A comparison is made between the properties of adhesive material with varying percentage of graphite powder (0%, 25%, 30%, 35%, 40%) to find out the effect of reinforcement on the adhesive material. The ability of property an electrical was studied through the measurement of conductivity a function of temperature varying. The results of comparison have clearly shown that the increasing of conten

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

     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

plaque forming assay was used enumerate the number of plaque forming cells of anti-HBc in eight patintes with chronic hepatitis and eight health

Introduction: Rheumatoid arthritis (RA) is one of the most prevalent systemic inflammatory diseases worldwide. Cardiac complications present the most common mortality cause among RA patients. One of the most important comorbid conditions with RA is diabetic hyperglycemia mainly type 2 diabetes mellitus (T2DM). Aim of the study: The present study was conducted to assess prevalence of T2DM among patients diagnosed with RA from Iraq. Methodology: We included a randomly selected 100 rheumatoid arthritis. All included patients were subjected to anthropometric measurements, diabetic profile assessment and ESR, CRP and rheumatoid factor measurement. Results: Among the included RA patients, 28 patients were diagnosed with new-onset DM. Our

Background: Because of many factors play a role in the developing of late lower arch crowding, therefore the objective of the current study is to do vertical analysis for subjects with late lower dental arch crowding. The conducted study is the first attempt to do vertical analysis for Iraqi subjects with late lower arch crowding to see if there is a vertical discrepancy in such patients. Subjects and methods: Eighty subjects were selected according to certain inclusion criteria from patients attending the Orthodontic Department in the College of Dentistry, Baghdad University, patients ranged between 18-25 years old. The 80 patients were divided into two groups (crowding and normal), 40 patients each (20 males and 20 females). A study cast

The communication networks (mobile phone networks, social media platforms) produce digital traces from their usages. This type of information help to understand and analyze the human mobility in very accurate way. By these analyzes over cities, it can give powerful data on daily citizen activities, urban planners have in that way, relevant indications for decision making on design and development. As well as, the Call detail Records (CDRs) provides valuable spatiotemporal data at the level of citywide or even nationwide. The CDRs could be analyzed to extract the life patterns and individuals mobility in an observed urban area and during ephemeral events. Whereas, their analysis gives conceptual views about human density and mobility pattern