Background: Periodontal diseases (PD) are common chronic inflammatory diseases caused by pathogenic microorganisms colonizing the gingival area and inducing local and systemic elevations of pro-inflammatory cytokines resulting in tissue destruction by a destructive inflammatory process. Stress was considered as one of the important risk factors that cause many inflammatory diseases including PD. The purpose of this study wasto determines and compares clinical periodontal parameters (PLI, GI and BOP), stress level and salivary IL-1? level among dental students before, during and after mid-year exam, also to find the correlation among stress, IL-1? and clinical periodontal parameters. Materials and methods: The sample was consisted of 24 dent

Background: Adolescence is one of the most dynamic stages of human development. However, Oral health is an integral part of public health, significantly impacts on the quality of life. OHE program is an important issue that should be given to them. The aim of this study was to evaluate oral health outcomes on adolescents' oral health by teachers and mothers Materials and Methods: The study was carried out in seven schools of Diyala - Baquba city. This 14-weeks duration study assessed the effectiveness of school OHE program on oral hygiene status, gingival health, and halitosis assessment of 80, 12 year-old, both genders of school adolescents. From the selected schools, one group was supervised by the teachers and the other was supervised

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

Based on previous research results that recognized the role of paternalistic leadership in promoting a positive work climate, this study explored the impact of a toxic work environment on the mental health and well-being of employees. We used the quantitative methodology to collect and analyze data. A sample of 108 participants from Iraqi internet service provider (ISPs) companies represented the purposive study sample. We targeted employees who experienced the COVID-19 pandemic. All data was collected through an electronic questionnaire (Google and Microsoft Forms). The research model was tested using structural equation modeling (SEM). The results showed a negative effect of the toxic workplace on the mental health of employees. T

Separation of Trigonelline, the major alkaloid in fenugreek seeds, is difficult because the extract of these seeds usually contains Trigonelline, choline, mucilage, and steroidal saponins, in addition to some other substances. This study amis to isolate the quaternary ammonium alkaloid (Trigonelline) and choline from fenugreek seeds (Trigonella-foenum graecum L.) which have similar physiochemical properties by modifying of the classical method. Seeds were defatted and then extracted with methanol. The presence of alkaloids was detected by using Mayer's and Dragendorff's reagents. In this work, trigonilline was isolated with traces of choline by subsequent processes of purification using analytical and preparative TLC techniques.

The present study utilised date palm fibre (DPF) waste residues to adsorb Congo red (CR) dye from aqueous solutions. The features of the adsorbent, such as its surface shape, pore size, and chemical properties, were assessed with X-ray diffraction (XRD), BET, Fourier-transform infrared (FTIR), X-ray fluorescence (XRF), and field emission scanning electron microscope (FESEM). The current study employed the batch system to investigate the ideal pH to adsorb the CR dye and found that acidic pH decolourised the dye best. Extending the dye-DPF waste mixing period at 25°C reportedly removed more dye. Consequently, the influence of the starting dye and DPF waste quantity on dye removal was explored in this study. At 5 g/L dye concentration, 48% d

Abstract

Praise be to Allah and prayers and peace be upon our Prophet, Muhammad, his family and all of his companions,

This research addresses the issue of judge's preaching to the litigants and witnesses; it is a very significant issue since the judge cannot know the insides and facts, but it issues judgments based on the hearings. Since people are originally wrong-doing and ignorant, they, therefore, commit injustice, oppression, false adversarial, and false testimony. However, some people can possibly retreat and return to the right, after being inattentive or recalcitrant, by preaching. This fact led scholars to talk about the judge's preaching to litigant and witnesses and this research is conducted

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise