Smart Artificial Intelligence techniques using embedded band for diagnosis and combating COVID-19.

Recently, COVID-19 virus spread to create a major impact in human body worldwide. The Corona virus, initiated by the SARS-CoV-2 virus, was known in China, December 2019 and affirmed a worldwide epidemic by the World Health Organization on 11 March 2020. The core aim of this research is to detect the spreading of COVID-19 virus and solve the problems in human lungs infection quickly. An Artificial Intelligence (AI) technique is a possibly controlling device in the battle against the corona virus epidemic. Recently, AI with computational techniques are utilized for COVID-19 virus with the building blocks of Deep Learning method using Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) is used to classify and identify the lung images affected region. These two algorithms used to diagnose COVID-19 infections rapidly. The AI applications against COVID-19 are Medical Imaging for Diagnosis, Lung delineation, Lesion measurement, Non-Invasive Measurements for Disease Tracking, Patient Outcome Prediction, Molecular Scale: from Proteins to Drug Development and Societal Scale: Epidemiology and Infodemiology.

A lightweight and robust authentication scheme for the healthcare system using public cloud server.

Cloud computing is vital in various applications, such as healthcare, transportation, governance, and mobile computing. When using a public cloud server, it is mandatory to be secured from all known threats because a minor attacker's disturbance severely threatens the whole system. A public cloud server is posed with numerous threats; an adversary can easily enter the server to access sensitive information, especially for the healthcare industry, which offers services to patients, researchers, labs, and hospitals in a flexible way with minimal operational costs. It is challenging to make it a reliable system and ensure the privacy and security of a cloud-enabled healthcare system. In this regard, numerous security mechanisms have been proposed in past decades. These protocols either suffer from replay attacks, are completed in three to four round trips or have maximum computation, which means the security doesn't balance with performance. Thus, this work uses a fuzzy extractor method to propose a robust security method for a cloud-enabled healthcare system based on Elliptic Curve Cryptography (ECC). The proposed scheme's security analysis has been examined formally with BAN logic, ROM and ProVerif and informally using pragmatic illustration and different attacks' discussions. The proposed security mechanism is analyzed in terms of communication and computation costs. Upon comparing the proposed protocol with prior work, it has been demonstrated that our scheme is 33.91% better in communication costs and 35.39% superior to its competitors in computation costs.

Advances in nano sensors for monitoring and optimal performance enhancement in photovoltaic cells.

Nanosensors have gained significant attention in recent years for improving energy conversion and storage performance in solar cells. These nanosensors, typically made from nanoparticles or nanowires, can be embedded within the solar cell to monitor parameters like temperature and light intensity. By monitoring these parameters, nanosensors provide real-time feedback and control to optimize the efficiency and performance of the solar cell. They also play a role in detecting potential issues, such as defects, for proactive maintenance and troubleshooting. The integration of nanosensors in solar cells enables the development of smart energy systems, leading to increased power output, improved stability, and a longer lifespan of solar cells. The deployment of nanosensors in solar cells offer promising trajectory for advancing energy conversion, utilization, and storage capabilities. This review summarizes recent advances in nanosensors in solar cells, with a focus on the role they play in enhancing energy conversion, utilization, and storage performance.

Sustainable developments in near-dry electrical discharge machining process using sunflower oil-mist dielectric fluid.

In this study, a near-dry electrical discharge machining (NDEDM) process has been conducted using compressed air mixed with a low quantity of biodegradable refined sunflower oil (called oil-mist) to investigate the machining characteristics. The Box-Behnken method looks at how oil flow rate (OR), air pressure (AR), spark current (SC), and pulse width (PW) affect gas emission concentration (GEC), material removal rate (MRR), and surface roughness (SR). The TOPSIS (The Technique for Order of Preference by Similarity to the Ideal Solution) technique estimates the parameter optimal set for the best machining characteristics. The optimal machining parameters have been used to examine the microstructure of the machined surfaces using a scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS) analysis. The 0.981 mg/min of GEC, 55.145 mg/min of MRR, and 2.43 µm of surface roughness have been attained by the 14 ml/min flow rate, 7 bar of air pressure, 10 A spark current, and 48 µs pulse duration of the sun-flower oil-mist NDEDM process.

Perceptions of Parents towards COVID-19 Vaccination in Children, Aseer Region, Southwestern Saudi Arabia.

Vaccines are an important part of the COVID-19 pandemic response plan. This cross-sectional study aims to assess the attitude and perception levels of parents toward COVID-19 vaccines for children aged 0-18 years in the Aseer region of Saudi Arabia. Data were analyzed using SPSS version 16.0. Out of a total of 1463 parents, 30.6% assumed that COVID-19 vaccination may be more dangerous for children than adults. Nearly 36.5% parents don't have any concern about children's vaccination. About 12.8% of children have not received the vaccination, 55% of parents have some sort of hesitation and 32.2% of parents did not hesitate before vaccinating their children against COVID-19. Only 15.4% of parents expect that the COVID-19 vaccine affects their child's genes. About 23.4% parents strongly agreed and 35.1% agreed about the importance of getting their children vaccinated. About 22.1% of parents strongly agreed and 33.3% agreed regarding their willingness to get their children vaccinated to prevent Coronavirus disease. More than 80% of parents recommended rushing to receive the COVID-19 vaccine. Health professionals and policymakers should implement and support strategies to ensure children are vaccinated for COVID-19. They also need to educate parents and families regarding childhood vaccination.

Association of Non-Carious Cervical Lesions with Oral Hygiene Habits and Dynamic Occlusal Parameters.

Dentists routinely encounter non-carious cervical lesions (NCCLs) in daily clinical practices. The dental literature is contradictory regarding the occlusal etiology of NCCLs. NCCL is defined as the loss of dental structure at the cemento-enamel junction, with no association of bacteria. The aim of this study was to evaluate the association of dynamic occlusal factors and dental hygiene practices with NCCLs. In total, 100 participants were selected by the random stratified sampling method, 50 each for control and NCCL groups. Information regarding oral hygiene practices, including frequency, duration, force, and technique of brushing, was recorded. Dynamic occlusal parameters like initial contact, occlusion time (OT), disocclusion time (DT), and center of force were recorded with T-scan analysis. The obtained data were analyzed with Pearson's correlation and binary logistic regression. We found that 68% of participants in the NCCL group and 31% in the control group utilized the horizontal brushing technique; 46% of NCCL group participants used hard brush against 7% of participants in the control group. The mean OT was 0.727 and 0.516 s for NCCL and control groups, respectively. The OT and left and right lateral DT were strongly related to NCCL, with r-values of 0.661, 0.642, and 0.534, respectively, with p ≤ 0.001. Using a hard toothbrush was found to be associated with NCCL. The NCCL group had extended mean occlusion time and disocclusion time in all eccentric mandibular movements.