The present study is a linguistic study of comment clauses in the American Series „Friends‟ .Comment clauses refer to those clauses which comment on the content of the main clause or the attitude of the speaker towards the way of speaking .The problem of this study is to answer the following questions ; what types of comment clauses can be used in the face- to –face conversations , for what functions these comment clauses could be used , and how these comment clauses are used by the participants of these conversations . This study is a qualitative one . The study aims to investigate the types of comment clauses used in the American Series “Friends‟. The study also aims to investigate the pragmatic functions of these comment clause

This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.

Technological and digital development has allowed the emergence of many methods of producing semantics on social media sites within semiotic and propagandistic frameworks. This is what made the image appear in different molds and shapes, especially as it is the first material for visual perception.
This made the Israeli propaganda discourse use it as an important tool to manage the content of suggestive messages with semiological connotations. By doing so, such tool uses social networking sites as an appropriate environment to achieve those goals, which are related to cases of manipulating emotions and minds. It, moreover, changes convictions, attitudes, trends and behaviors according to what the propaganda planner wants.
Many Isra

Cadmium sulfide (CdS) nanocrystalline thin films have been prepared by chemical bath deposition (CBD) technique on commercial glass substrates at 70ºC temperature. Cadmium chloride (CdCl₂) as a source of cadmium (Cd), thiourea (CS(NH₂)₂) as a source of sulfur and ammonia solution (NH₄OH) were added to maintain the pH value of the solution at 10. The characterization of thin films was carried out through the structural and optical properties by X-ray diffraction (XRD) and UV-VIS spectroscopy. A UV-VIS optical spectroscopy study was carried out to determine the band gap of the nanocrystalline CdS thin film and it showed a blue shift with respect to the bulk value (from 3.9 - 2.4eV). In present w

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a