Since the appearance of COVID-19 disease as an epidemic and pandemic disease, many studies are performed to uncover the genetic nature of the newly discovered coronavirus with unique clinical features. The last three human coronavirus outbreaks, SARS-CoV, MERS-CoV and SARS-CoV-2 are caused by Beta-Coronaviruses. Horizontal genetic materials transfer was proven from one coronavirus to the other coronavirus of non-human origin like infectious bronchitis virus (IBV) of avian. Horizontal genetic materials transfer was also from non-corona viruses like astroviruses and equine rhinovirus (ERV-2) or from coronavirus-unrelated viruses, like influenza virus type C. However, SARS-CoV-2 is identical to SARS-CoV and MERS-CoV. Interestingly, Wuhan ci

In this research, new series of Furo-2-quinolone [FQ] compounds have been synthesized. These novel [FQ] compounds were prepared from coumarin derivatives (Furocoumarins: psoralen and isopsoralen).Identifications of these FQ compounds were performed by using infrared spectrum (I.R), Ultraviolet spectrum (U.V) and Nuclear Magnetic Resonance spectrum (H¹-NMR) besides some physical data. The cytotoxic screening involves ;using HEP-2 cell line which gave differential responses against tested compounds : 4,6 Dimethyl furo[2, 3-g] coumarin (C₁), 1-(2`, 4`, Dimethoxy benzylideneimino)-2,6-dimethyl Furo [2, 3-g] quinoline-2-one (C₃) and the angular psoralen of the same derivative

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i

chloride or poluacrulic acid with different primary amines to mesuring==================================638one hundred three patinents with rheumatic symptoms were include in this study and their sera tested for

The paper presents an original method to make the geometric synthesis of the rotary cam and translated tappet with roll. Classical method uses to the geometric synthesis and the reduced tappet velocity, and in this mode the geometric classic method become a geometric and kinematic synthesis method. The new geometric synthesis method uses just the geometric parameters (without velocities), but one utilizes and a condition to realize at the tapped the velocities predicted by the tapped movement laws imposed by the cam profile. Then, it makes the dynamic analyze for the imposed cam profile, and one modify the cam profile geometric parameters to determine a good dynamic response (functionality). In this mode it realizes the dynamic synthesis

ABSTRACT Background: This study aimed to study the effect of some acidic drinks (Vinegars and fresh Orange juice) and energy drinks (Red bull) on surface roughness of three types of bulkfill composite materials: Filtek posterior bulkfill (3M), Sonicfill (Kerr) and Filtek p60 (3M). Materials and Methods: Total number of 120 samples are prepared by using a mold of (12mm diameter and 3mm height), which were divided into three groups forty samples for each group: Group A: Filtek bulkfill posterior composite (3M), Group B: Sonicfill composite (Kerr), Group C: Filtek P60 (3 M) which then divided into four sub- groups (n=10) (1) samples were kept in distilled water as a control group (2) samples were immersed in Redbull (3) samples were immersed