Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

Abstract

The aim of this study was to prepare rebamipide ocular inserts in order to extend its release on the ocular surface for dry eye treatment. Solubility study was applied to the drug with or without l-arginine using different solvents. Solvent casting technique was used to prepare the inserts; l-arginine was used to solubilize the drug, hydroxypropyl methylcellulose grades (E5 and K15M) and poly ethylene glycol 200 were used as excipients. The inserts were evaluated for their physical and mechanical properties, moisture loss% and absorption %, surface pH, and in-vitro drug release. The use l-arginine exhibited an enhancement of rebamipide solubility in both deionized water and phosphate buffer (pH 7.4) by a

This presented study is to make comparison of cross sections to produce 71As, 72As, 73As and 74As via different reactions with particle incident energy up to 60 MeV of alpha 100 MeV of proton as a part of systematic studies on particle-induced activations on enriched Ge, Ga, Rb and Nb targets and neutron capture. Theoretical calculation of production yield, and suggestion of optimum reaction to produce 71As, 72As, 73As and 74As, based on the main published and approved experimental results of excitation functions were calculated.

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

Wastewater recycling for non-potable uses has gained significant attention to mitigate the high pressure on freshwater resources. This requires using a sustainable technique to treat natural municipal wastewater as an alternative to conventional methods, especially in arid and semi-arid rural areas. One of the promising techniques applied to satisfy the objective of wastewater reuse is the constructed wetlands (CWs) which have been used extensively in most countries worldwide through the last decades. The present study introduces a significant review of the definition, classification, and components of CWs, identifying the mechanisms controlling the removal process within such units. Vertical, horizontal, and hybrid CWs

BACKGROUND: Color Vision Deficiency (CVD) is mostly an inherited trait and is not an uncommon problem. Prevalence of CVD differs among different ethnic and geographic properties of the population that affect their genetic constitution. Ishihara plates remain an internationally accepted tool for screening red-green CVD. OBJECTIVE: To determine the prevalence of red-green CVD among adult males from Baghdad province. PATIENTS AND METHODS: One thousand and five (1005) adult males were enrolled in this study, using a systematic sampling technique, and were screened for CVD utilizing 24-plate Ishihara plates and re-tested by EnChroma 39-Color plates. All males were residing in Baghdad and the center of Iraq. RESULTS: Among all tested males, 948 r