Recent reports of new pollution issues brought on by the presence of medications in the aquatic environment have sparked a great deal of interest in studies aiming at analyzing and mitigating the associated environmental risks, as well as the extent of this contamination. The main sources of pharmaceutical contaminants in natural lakes and rivers include clinic sewage, pharmaceutical production wastewater, and sewage from residences that have been contaminated by drug users' excretions. In evaluating the health of rivers, pharmaceutical pollutants have been identified as one of the emerging pollutants. The previous studies showed that the contaminants in pharmaceuticals that are widely used are non-steroidal anti-inflammatory drugs, ant

Titanium dioxide nanotubes were synthesized by anodizing Ti sheets in the ethylene glycol solution and were covered in Pt nanoparticles onto the surface of TiO₂NTs using electrodeposition method from using five derivatives of Mannich base Pt complexes which have been used as precursor of platinum. The mean size, shape, elemental composition of the titanium dioxide nanotubes and platinum deposited on the template were evaluated by different techniques such as field emission scanning electron microscope (FE-SEM), transmission electron microscopy (TEM), X-ray diffraction pattern (XRD), and energy dispersive X-ray (EDX) technique. From all these analyses, the TiO₂NTs prepared and Ptnanoparticles deposited on it were ide

The covid-19 global pandemic has influenced the day-to-day lives of people across the world. One consequence of this has been significant distortion to the subjective speed at which people feel like time is passing. To date, temporal distortions during covid-19 have mainly been studied in Europe. The current study therefore sought to explore experiences of the passage of time in Iraq. An online questionnaire was used to explore the passage of time during the day, week and the 11 months since the first period of covid-19 restrictions were imposed in Iraq. The questionnaire also measured affective and demographic factors, and task-load. The results showed that distortions to the passage of time were widespread in Iraq. Participants co

A vocative expression can be defined as an expression of direct address where the participant identity is set forth explicitly within a sentence. This study aims at showing how the vocative particles are used in literally texts, namely in the short story “The Garden Party" written by Kathryn Mansfield and identifying the forms of these vocative particles as used by the characters along with the functions of these vocative particles. For the analysis of vocative forms, the researcher used Quirk and Greenbaum (1973) model. Functionally, the data were analyzed based on Quirk et al. (1985) model. However, the results of this study shows that the characters in “The Garden Party” short story used various forms of vocative particles and

Routing protocols are responsible for providing reliable communication between the source and destination nodes. The performance of these protocols in the ad hoc network family is influenced by several factors such as mobility model, traffic load, transmission range, and the number of mobile nodes which represents a great issue. Several simulation studies have explored routing protocol with performance parameters, but few relate to various protocols concerning routing and Quality of Service (QoS) metrics. This paper presents a simulation-based comparison of proactive, reactive, and multipath routing protocols in mobile ad hoc networks (MANETs). Specifically, the performance of AODV, DSDV, and AOMDV protocols are evaluated and analyz

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an