The present systematic review aimed to combine the evidence on rodent models on molecular regulators of root dentinogenesis across the temporal phases and spatial zones, and evaluate the translation of this map for human dental development and regenerative therapies. A PRISMA 2020‑guided systematic review of experimental studies through the major electronic databases was performed. Data on models, molecules, techniques, spatiotemporal expression and the functional outcomes were extracted. The ARRIVE guidelines and SYRCLE's risk of bias tool were used to assess the risk of bias in animal studies. The evidence form rodent studies supports an organized network that begins with initiation at the cervical loop that requires the downregulation

Aim: This article aims to review the studies on the bond strength between dental ceramics and metal restoration in crowns and bridges using various techniques. Methodology: Electronic databases for scientific research, including PubMed, Cochrane, and Medline, were searched. The following keywords were used: dental ceramic, cobalt-chromium (Co-Cr) alloy, shear bond strengths, Selective Laser Melting (SLM) technique, sandblasting technique, three-point bending test, hardness test, mode of failure, Scanning Electron Microscope (SEM) and roughness test. Initial retrieval of 86 original papers from the worldwide databases was done after careful screening, including reviews of the literature on the different techniques used to enhance the shear b

The port of Gwadar is a major turning point in the Pakistani economy, as it is characterized by a very important strategic location and has characteristics that enable it to play an active role in the region, being a land bridge linking Central Asia, especially the countries of Central and South Asia, by the sea, and also linking the Chinese economy (west of China to the port). And due to its distinguished strategic location, which made it a center of attraction for large commercial ships, despite all the positive advantages, there are obstacles that stand in the way of completing it in the required manner represented by challenges (internal, regional and international) that fear the completion of the port, which will generate profit

Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m