Introduction: We aimed to assess the impact of adhesive and wires types on the tensile bond strength of fixed lingual retainers. Methods: A total of 160 intact bovine teeth were collected, cleaned, stored in 25% sodium hypochlorite, and randomly assigned to two groups based on the adhesive type: a two-step adhesive and a one-step adhesive. Each group was further divided into four subgroups based on the type of lingual retainer wire, which included (A) 8-strand braided stainless steel wire, (B) three-strand titanium retainer wire, (C) stainless steel chain, and (D) fiber-reinforced retainer. A tensile bond strength test was conducted using a universal testing machine at a controlled speed of 10 mm/min. Result: The 8-strand braided stainless steel wire and stainless steel chain bonded by one-step self-priming adhesive showed significantly higher tensile bond strength (P < 0.001). The adhesive wire significantly affected the tensile bond strength (P < 0.001). Conclusion: Within the limitations of this in vitro study, it can be concluded that stainless steel wire and chain bonded by one-step self-priming adhesive showed higher tensile bond strength.
The present work involved designing and synthesizing of a series of new. compounds which their molecules are composed from two biologically active components namely sulfamethoxazole or β-lactam containing drugs and cyclic imides. The target new compounds were synthesized by two steps in the first one a series of six bis (N-drug phthalamic acid_4-yl) ketone (1-6) were prepared from the reaction of sulfamethoxazole or β-lactam containing drugs with benzophenone 3, 3′, 4, 4′ -tetracarboxylic dianhydride.
In the second step, compounds (1-6) were introduced in dehydration reaction via fusion process producing the target compounds bis (N-drug phthalimidyl-4-yl) ketone (7-12). The antibacterial and antifungal high
... Show MoreThe smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec
... Show MoreThis paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them in terms of accuracy.
Diabetes mellitus caused by insulin resistance is prompted by obesity. Neuropeptide Nesfatin-1 was identified in several organs, including the central nervous system and pancreatic islet cells. Nesfatin-1 peptide appears to be involved in hypothalamic circuits that energy homeostasis and control food intake. Adiponectin is a plasma collagen-like protein produced by adipocytes that have been linked to the development of insulin resistance (IR), diabetes mellitus type 2 (DMT2), and cardiovascular disease (CVD). Resistin was first identified as an adipose tissue–specific hormone that was linked to obesity and diabetes. The aim of this study was to estimate the relationship between human serum nesfatin-1, adiponect
... Show MoreIn this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which
... Show MoreThe current research aimed to identify the level of moral identity and social affiliation among students exposed to shock pressures, as well as to reveal the relationship between these variables. To achieve these objectives, the researcher adopted the diagnostic tool for the measure of post-traumatic stress disorder (PDS-5) scale (Foa, 2013) translated to Arabic language by (Imran, 2017). The researcher also adopted the moral identity scale built by (Al-Bayati, 2015) and the measure of social affiliation built by (Al-Jashami, 2013), which were applied to a random sample of (200) male and female students chose from al Anbar University. They were exposed to shock pressures. The results of the research showed that the sample has an average
... Show MoreIn this work an experimental study is performed to evaluate the thermal performance
of locally made closed loop solar hot water system using a shell and helical coiled tube
heat exchanger as a storage tank. Several measurements are taken include inlet and outlet
temperatures of both collectors and supply water and temperature distribution within the
storage tank. This is beside the water flow rate in both collectors and load cycle. The
main parameters of the system are obtained.
Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
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