Background: Several pathologies of the oral cavity have been associated with stress. Dental students need to gain assorted proficiencies as theoretical knowledge, clinical proficiencies, and interpersonal dexterity which is accompanied with high level of stress. Uric acid is the major antioxidant in saliva. The aim of this study is to assess the dental caries experience among dental students with different levels of dental environment stress in relation to physicochemical characteristics of whole unstimulated saliva.

Materials and Methods: the total sample is composed of 300 dental students (73 males, 227 female) aged 22-23 years old, from collage of dentistry / university of Baghdad, from the 4t

PMMA (Poly methyl methacrylate) is considered one of the most commonly used materials in denture base fabrication due to its ideal properties. Although, a major problem with this resin is the frequent fractures due to heavy chewing forces which lead to early crack and fracture in clinical use. The addition of nanoparticles as filler performed in this study to enhance its selected mechanical properties. The Nano-additive effect investigated in normal circumstances and under a different temperature during water exposure. First, tests applied on the prepared samples at room temperature and then after exposure to water bath at (20, 40, 60) C^° respectively. SEM, PSD, EDX were utilized for samples evaluation in this study. Flexural

The use of sugarcane molasses (SCM) as a sustainable stabilizing agent for geomaterials, particularly granular subbase soils, has recently attracted growing attention as an alternative to traditional stabilization methods employing cement, lime, or bitumen, which are often associated with high costs and environmental concerns. This study presents a mechanistic–experimental evaluation of SCM for stabilizing granular subbase materials at dosages of 2.5%, 5%, 7.5%, and 10% by weight of dry granular material. A comprehensive testing program was conducted, including compaction characteristics, California Bearing Ratio (CBR), resilient modulus (Mr), permanent deformation under repeated loading, optical microscopy, and FTIR spectroscopy.

Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

A novel welded demountable shear connector for sustainable steel-concrete composite structures is proposed. The proposed connector consists of a grout-filled steel tube bolted to a compatible partially threaded stud, which is welded on a steel section. This connector allows for an easy deconstruction at the end of the service life of a building, promoting the reuse of both the concrete slabs and the steel sections. This paper presents the experimental evaluation of the structural behavior of the proposed connector using a horizontal pushout test arrangement. The effects of various parameters, including the tube thickness, the presence of grout infill, and the concrete slab compressive strength, were assessed. A nonlinear finite element mode

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

APDBN Rashid, Review of International Geographical Education Online (RIGEO), 2021