Background: Cluster of differentiation 14 (CD14) is a serum/cell surface glycoprotein; and it is a pattern recognition receptor. CD14 expressed on the surface of various cells, or it found soluble in saliva and other body fluids. It has been proposed that soluble CD14 (sCD14) may play a protective role by controlling Gram negative bacterial infections through its capacity to bind lipopolysaccharide. This study was conducted to assess the level of soluble CD14 in saliva of patients with different periodontal diseases and healthy subjects and determine its correlation with clinical periodontal parameters. Materials & Methods: A total of 80 subjects, age ranged (25-50) years old, divided into three main groups, group ? consisted of 45 chronic periodontitis patients, group ?? consisted of 20 gingivitis patients, lastly group ??? comprised 15 apparently- healthy volunteers. Unstimulated whole saliva samples were collected to determine levels of soluble CD14 in saliva by enzyme-linked immune–sorbent assay (ELISA). Clinical periodontal parameters were recorded at four sites per tooth including plaque index, gingival index, bleeding on probing, probing pocket depth and clinical attachment level. Results: A highly significant difference (P<0.01) was found for salivary sCD14 levels among the three groups, also it was greater in chronic periodontitis group than those detected for gingivitis and healthy controls with a highly significant difference (P<0.01). Furthermore, Spearman’s correlation analysis showed statistically highly significant strong correlations (P < 0.05) between salivary sCD14 levels and each of (probing pocket depth, clinical attachment level). And non-significant correlation between salivary sCD14 level with plaque, gingival & bleeding on probing indices. Conclusion: The findings of the present study reemphasize the importance of whole saliva as sampling method in terms of immunological purposes in periodontal disease and suggest that the elevated sCD14 concentration may be one of the host-response components associated with the clinical manifestations of periodontal disease.
Fire incidences are classed as catastrophic events, which mean that persons may experience mental distress and trauma. The development of a robotic vehicle specifically designed for fire extinguishing purposes has significant implications, as it not only addresses the issue of fire but also aims to safeguard human lives and minimize the extent of damage caused by indoor fire occurrences. The primary goal of the AFRC is to undergo a metamorphosis, allowing it to operate autonomously as a specialized support vehicle designed exclusively for the task of identifying and extinguishing fires. Researchers have undertaken the tasks of constructing an autonomous vehicle with robotic capabilities, devising a universal algorithm to be employed
... Show MoreIn this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th
... Show MoreFace Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d
... Show MoreOptical fiber technology is without a doubt one of the most significant phases of the communications revolution and is crucial to our daily lives. Using the free version (2022) of RP Fiber Calculator, the modal properties for optical fibers with core radii (1.5−7.5) μm, core index (1.44−1.48) and cladding index (1.43−1.47) have been determined at a wavelength of 1000 nm. When the fiber core’s radius is larger than its operating wavelength, multimode fibers can be created. The result is a single-mode fiber in all other cases. All of the calculated properties, it has been shown, increase with increasing core radius. The modes’ intensity profiles were displayed.
The interaction of interplanetary coronal mass ejections (ICME) with each other and with co-rotating interaction regions (CIR) changes their configuration, dynamics, magnetic field and plasma characteristics and can make space weather forecasting difficult. During the period of March 20–25, 2011, the Solar Terrestrial Relation Observatory (
In the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can b
... Show MoreThe research discussed the possibility of adsorption of Brilliant Blue Dye (BBD) from wastewater using 13X zeolite adsorbent, which is considered a byproduct of the production process of potassium carbonate from Iraqi potash raw materials. The 13X zeolite adsorbent was prepared and characterized by X-ray diffraction that showed a clear match with the standard 13X zeolite. The crystallinity rate was 82.15% and the crystal zeolite size was 5.29 nm. The surface area and pore volume of the obtained 13X zeolite were estimated. The prepared 13X zeolite showed the ability to remove BBD contaminant from wastewater at concentrations 5 to 50 ppm and the removal reached 96.60% at the lower pollutant concentration. Adsorption measurements versus tim
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