Background: Coronavirus disease 2019 (COVID-19) is an emerging zoonotic disease caused by the new respiratory virus SARS-CoV2. It has a tropism in the lung tissues where excess target receptors exist. Periostin plays a role in subepithelial fibrosis associated with bronchial asthma. Since the Coronavirus's target is the human respiratory system, Periostin has been recently described as a valuable new biomarker in the diagnosis and evaluation of disease in patients with COVID-19 lung involvement. Objectives: To assess the level of Periostin in the serum of COVID-19 patients and to correlate its role in disease severity and prognosis. Subjects and Methods: Periostin serum levels were measured for 63 patients attending three main COVID-19 Control Centers in Baghdad, compared to 25 healthy subjects, using an enzyme-linked immunosorbent assay (ELISA) from January 2021 to April 2022. Results: Serum levels of Periostin among studied groups with (mild - moderate, severe - critical, post-COVID, and controls) were (17.3, 664, 597, and 48) ng/dl respectively. The serum concentration of Periostin was highly significant in (severe- critical and post-COVID) than in other groups. Conclusions: The elevated level of serum Periostin in COVID-19 patients correlated with disease severity and post-COVID lung complications. The high Periostin level is consistent with high inflammatory markers, which might be used as an indicator of COVID-19 severity and predict a bad prognosis.
Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
... Show MoreThroughout this paper, a generic iteration algorithm for a finite family of total asymptotically quasi-nonexpansive maps in uniformly convex Banach space is suggested. As well as weak / strong convergence theorems of this algorithm to a common fixed point are established. Finally, illustrative numerical example by using Matlab is presented.
By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model. In addition, the efficiency of the PV panel is established by the genetic algorithm
... Show MoreInefficient wastewater disposal and wastewater discharge problems in water bodies have led to increasing pollution in water bodies. Pollutants in the river contribute to increasing the biological oxygen demand (BOD), total suspended solids (SS), total dissolved solids (TDS), chemical oxygen demand (COD), and toxic metals render this water unsuitable for consumption and even pose a significant risk to human health. Over the last few years, water conservation has been the subject of growing awareness and concern throughout the world, so this research focused on review studies of researches that studied the importance of water quality of wastewater treated disposal in water bodies and modern technology to management w
... Show MoreFourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.
... Show MoreThis study is aimed to Green-synthesize and characterize Al NPs from Clove (Syzygium aromaticum
L.) buds plant extract and to investigate their effect on isolated and characterized Salmonella enterica growth.
S. aromaticum buds aqueous extract was prepared from local market clove, then mixed with Aluminum nitrate
Al(NO3)3. 9 H2O, 99.9% in ¼ ratio for green-synthesizing of Al NPs. Color change was a primary confirmation
of Al NPs biosynthesis. The biosynthesized nanoparticles were identified and characterized by AFM, SEM,
EDX and UV–Visible spectrophotometer. AFM data recorded 122nm particles size and the surface roughness
RMs) of the pure S. aromaticum buds aqueous extract recorded 17.5nm particles s