This paper deals with one of the most important issues in a foreign language teaching and learning, i.e. speaking test assessment. After giving a survey of literature written on the meaning and definition of a speaking test assessment, two sections have been devoted to tackle the most important issues in this topic. Section one, which is the theoretical part of this paper, sheds light on the basic definitions of the term ‘speaking assessment’ which are, according to the researcher’s point of view, sufficient to cover the area of the study. This section based on applied linguistic theories and researches in order to enhance our understanding of the what is meant by «a speaking test assessment«In addition,it explains the most importan

This work suggests a system of ordinary differential equations (ODEs) containing a three-species food chain model incorporating wind and fear effects. The properties of the solution, like positivity and bound-ness, were investigated. All equilibrium points (biologically feasible) have been obtained, and the local stability of these equilibriums has been carried out. The global stability outcomes on the equilibrium points under specific restrictions have been established. Also, the persistence restrictions have been investigated. By utilizing Sotomayor’s theorem, the local bifurcation of the suggested model has been inspected. Furthermore, numerical analysis was carried out to ensure the theoretical results obtained by utilizing MA

This work aimed to investigate the effect of Diode laser 805 nm on plasmid DNA and RNA
contents of some Gram negative bacteria represented by Escherichia coli and Proteus mirabilis isolates
.Plasmid extraction was done using two methods (Salting out and CTAB method).Different powers and
pulse repetition rates for 805 nm Diode Laser were used to study this effect. Results revealed that the
plasmid profile of the two species were highly affected using (2, 3) W at different frequencies including
5and 10 kHz as compared with 1 kHz while plasmids were gradually disappeared at 1W, 10 kHz. In the
same time the shining of RNA was also decreased gradually then disappeared with increasing powers
especially at 2W and 10 kHz cau

This study focuses on synthesizing Niobium pentoxide (Nb2O5) thin films on silicon wafers and quartz substrates using DC reactive magnetron sputtering for NO2 gas sensors. The films undergo annealing in ambient air at 800 °C for 1 hr. Various characterization techniques, including X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity measurements, are employed to evaluate the structural, morphological, electrical, and sensing properties of the Nb2O5 thin films. XRD analysis confirms the polycrystalline nature and hexagonal crystal structure of Nb2O5. The optical band gap values of the Nb2O5 thin films demonstrate a decrease from 4.74 to 3.73 eV

This study focuses on synthesizing Niobium pentoxide (Nb₂O₅) thin films on silicon wafers and quartz substrates using DC reactive magnetron sputtering for NO₂ gas sensors. The films undergo annealing in ambient air at 800 °C for 1 hr. Various characterization techniques, including X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity measurements, are employed to evaluate the structural, morphological, electrical, and sensing properties of the Nb₂O₅ thin films. XRD analysis confirms the polycrystalline nature and hexagonal crystal structure of Nb₂O₅. The optical band gap val

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c