Background: Dental caries and periodontal disease are the most common and widely spread diseases affecting humans at different ages. Aim of this study is the assessment of prevalence and severity of dental caries, gingivitis, oral hygiene and enamel anomalies in relation to gender and residency among 15 years old students in Maysan governorate –Iraq. Materials and methods: The total sample composed of 750 students (400 males and 350 females, 450 urban and 300 rural) selected randomly from different high schools in the Governorate. Diagnoses and recording dental caries was according to the criteria of WHO (1987), Plaque index of Silness and Loe (1964) was used for plaque assessment, Ramfjord index (1959) was applied for the assessment of calculus, gingival index of Loe and Silness (1963) was followed for recording gingival health condition and criteria of WHO (1997) to assess enamel anomalies. Results: Caries prevalence was found to be (92.53%) of the total sample. The DMFS value was higher among females compared to males with statistically high significant difference (P<0.01) also the value was higher among rural compared to urban with statistically high significant difference (P<0.01). Plaque, gingival and calculus indices were higher among rural than urban and higher among males than females, statistically, there were high significant differences regarding plaque and gingival indices (P<0.01) while non-significant difference regarding calculus index (P>0.05), for both genders and residencies. Conclusion: A high prevalence of dental caries and gingivitis were recorded indicating the need of a public health programs in this governorate.
The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t
This research presents a numerical study to simulate the heat transfer by forced convection as a result of fluid flow inside channel’s with one-sided semicircular sections and fully filled with porous media. The study assumes that the fluid were Laminar , Steady , Incompressible and inlet Temperature was less than Isotherm temperature of a Semicircular sections .Finite difference techniques were used to present the governing equations (Momentum, Energy and Continuity). Elliptical Grid is Generated using Poisson’s equations . The Algebraic equations were solved numerically by using (LSOR (.This research studied the effect of changing the channel shapes on fluid flow and heat transfer in two cases ,the first: cha
... Show MorePlantation of humic acid nanoparticles on the inert sand through simple impregnation to obtain the permeable reactive barrier (PRB) for treating of groundwater contaminated with copper and cadmium ions. The humic acid was extracted from sewage sludge which is byproduct of the wastewater treatment plant; so, this considers an application of sustainable development. Batch tests signified that the coated sand by humic acid (CSHA) had removal efficiencies exceeded 98 % at contact time, sorbent dosage, and initial pH of 1 h, 0.25 g/50 mL and 7, respectively for 10 mg/L initial concentration and 200 rpm agitation speed. Results proved that physicosorption was the predominant mechanism for metals-CSHA interaction because the sorption data followed
... Show MoreA robust and sensitive analytical method is presented for the extraction and determination of six pharmaceuticals in freshwater sediments.
This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
... Show MoreMixed ligand of Co and Ni (II) complexes were prepared from [5-(p-nitrophenyl)-4/-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide](TRZ.DTC) as primary ligand and 2,2'-bipyridyl (bipy) as a co-ligand with metal salts. These complexes were analytically and spectroscopically characterized in solid state by elemental analyses, flame atomic absorption, magnetic susceptibility and molar conductance measurements, as well as by UV–Vis and FTIR spectroscopy. Infrared, ultra violet spectra reveal a bidentate coordination of the two ligands with metal ions 1:1:1 mole ratio. Room temperature magnetic moments and solid reflectance spectra data indicate paramagnetic complexes with five-coordinate square pyramidal geometry for nickel (II) comple
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