Objective: The antimicrobial efficacy of three disinfection solutions: 5.25% sodium hypochlorite (NaOCl), 2% chlorhexidine (CHX) and Listerine mouthwash were investigated as routine chair-side gutta-percha (GP) disinfection reagents. Design: four groups of gutta percha points were contaminated with E. faecalis bacteria then disinfected by immersion in different solutions (5.25% sodium hypochlorite, 2% chlorhexidine gluconate, Listerine mouth wash and distilled water as control) after 1 and 7 days culturing periods. The antibacterial efficacy of these disinfection solutions was evaluated by using colonies per units (CPU) Methods: Forty GP cones (F3 Dentsply) were sterilized with ethylene oxide gas before immersed contamination within broth m

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

The current research aims at studying the precise and big movement skills and the ability
of the diabetic child to do them, The research sample consisted of ten diabetic children who
go to the Diabetes Center of Research that is apart of the Yarmook hospital. The sample was
chosen according to the intentional method and it wasn’t possible to have bigger sample
because the parents of the children didn’t agree for fear on the children’s health. It was
apparent through the research that the diabetic child performs the big movement skills better
than his ability to do the precise movement skills because they require accuracy,
concentration and high attention.
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The philosophies don’t forgets the subject silence because it effecting in life human , the kinds artist don’t lost the silence , exactly the theatrical arts because if the actor don’t the select silence he is don’t effect in the audience , this study giving the important for active the select silence in Iraqis theatre , so this search composed of : the preface that composed of : the search problem , and important the search and need it , aimed the search , lines search it composed of the lines time , lines place , and lines subject , and the terms limited . the theatrical line that composed The second topic the first topic the silence in the philosophers, part , active the select silence in the theatre text. The Third topic acti

This research aims to study the optical characteristics of semiconductor quantum dots (QDs) composed of CdTe and CdTe/CdSe core-shell structures. It utilizes the refluxed method to synthesize these nanoscale particles and aims to comprehend the growth process by monitoring their optical properties over varied periods of time and pH 12. Specifically, the optical evolution of these QDs is evaluated using photoluminescence (PL) and ultraviolet (UV) spectroscopy. For CdTe QDs, a consistent absorbance and peak intensity increase were observed across the spectrum over time. Conversely, CdTe/CdSe QDs displayed distinctive absorbance and peak intensity variations. These disparities might stem from irregularities in forming selenium (Se) layers a

In this work we study the influence of the laser pulse energy and ablation time on the aluminum nanoparticles productivity during nanosecond laser ablation of bulk aluminum immersed in liquid.
Aluminum nanoparticles were synthesized by pulsed laser ablation of Al targets in ethanol for 3-8 minutes using the 1064 nm wavelength of a Nd:YAG laser with energies of 300-500 mJ per pulse.The laser energy was varied between 300 and 500 mJ/pulse, whereas the ablation time was set to 5 minutes. UV-Visible absorption spectra was used for the characterization and comparison of products.

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

Embracing digital technological advancements in media and communication has led government entities to adopt communication practices fully aligned with the digital and networked system in government communication. Traditional media practices within the government environment increasingly rely on the ability to utilize digital tools and systems for content creation, communication, evaluation, and the management of the entire communication process within an electronic and intelligent framework for government services. Naturally, this transformation has caught the attention of communication and public relations researchers worldwide, as the digital and networked aspects of government communication now form an intelle

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and