Florida is one of the most important American states. It was discovered by the Spanish explorer (De León), and subsequently, French and English colonies were established. By June 25, 1868, Florida had become one of the American states. Its economic importance became prominent after the increase in commercial activities, and its economy grew significantly in the first quarter of the twentieth century. In addition, its important geographical location enabled it to play a significant role in global politics.

   Municipal solid waste is one of the most important environmental problems in the world and is an important source of environmental pollution and contributes significantly to the pollution of the basic environmental elements of soil, water and air. The management of municipal waste in general is a process of monitoring, collection, treatment or recycling if possible or disposal of waste. This term is used for waste produced by some human activities. States provide this process to mitigate the negative effects of waste on the environment, health and appearance of the city. It is possible to find solutions to the problem of solid waste and make it an important source of income and contribute to securing employment oppor

This study was designed to investigate the effect of aqueous extract of ginger Zingiber officinale Roscoe on the histology of corpus luteum and the concentration of the hormones progesterone and estrogen during the first trimester of pregnancy (0 - 7) days from fertilization. 30 pregnant mice were divided into five experimental groups: control group (administrated with distilled water), and four groups treated at doses (284, 568, 1136,1420 mg / kg), orally administrated , daily with (0.1 ml). Microscopic examination results have shown histopathological changes in corpus luteum included: Pyknosis in some nuclei of granulosa cells, Karyorrhexis, Karyolysis in some granulosa cells, and necrosis in corpus luteum, with additional significant dec

Background: Poly (methyl methacrylate) has several disadvantages (poor mechanical properties) like impact and transverse strength. In order to overcome these disadvantages, several methods were used to strengthen the acrylic resin by using different fibers or fillers. This study was conducted to evaluate the effect of Plasma treatment of the fiber on mechanical properties Poly (methyl methacrylate) denture base material. Materials and methods: Specimens were prepared from poly methyl metha acrylic (PMMA) divided according to present of fiber into 4 groups (first group without fiber as control group, second group with Plasma treated polyester fibers, third group with Plasma treated polyamide fibers and fourth group Plasma treated combination

ABSTRACT Porous silicon has been produced in this work by photochemical etching process (PC). The irradiation has been achieved using ordinary light source (150250 W) power and (875 nm) wavelength. The influence of various irradiation times and HF concentration on porosity of PSi material was investigated by depending on gravimetric measurements. The I-V and C-V characteristics for CdS/PSi structure have been investigated in this work too.

The physical, mechanical, electrical and thermal properties containing (Viscosity, curing, adhesion force, Tensile strength, Lap shear strength, Resistively, Electrical conductivity and flammability) of adhesive material that prepared from Nitrocellulose reinforced with graphite particles and aluminum streat. A comparison is made between the properties of adhesive material with varying percentage of graphite powder (0%, 25%, 30%, 35%, 40%) to find out the effect of reinforcement on the adhesive material. The ability of property an electrical was studied through the measurement of conductivity a function of temperature varying. The results of comparison have clearly shown that the increasing of conten

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Thermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.

Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the