The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

Klebsilla pneumoniae is one of must opportunistic pathogens that causes nosocomial infection, UTI, respiratory tract infections and blood infections. ZrO2 nanoparticles have antimicrobial activity against some pathogenic bacteria and fungi. Ceftazidime is one of third generation cephalosporins groups of antibiotecs, characterized by its broad spectrum on bacteria in general and particularly on Enterobacteriaceae family like Klebsiella spp. Method: Diverse clinical samples of Klebsilla pneumoniae were isolated from several hospitals in Baghdad – Iraq and ZrO2 nanoparticles was investigated against it. Ceftazidime was also investigated against K. pneumoniae. Both of ZrO2 nanoparticles and ceftazidime were mixed together and investigated aga

A significant increase in the incidence of non-O157 verotoxigenic Escherichia coli (VTEC) infections have become a serious health issues, and this situation is worsening due to the dissemination of plasmid mediated multidrug-resistant microorganisms worldwide. This study aims to investigate the presence of plasmid-mediated verotoxin gene in non-O157 E. coli. Standard microbiological techniques identified a total of 137 E. coli isolates. The plasmid was detected by Perfectprep Plasmid Mini preparation kit. These isolates were subjected to disk diffusion assay, and plasmid curing with ethidium bromide treatment. The plasmid containing isolates were subjected to a polymerase chain reaction (PCR) for investigating

In this paper, we used two monomers, 3,3',4,4'-benzophenone tetracarboxylic dianhydride (BTDA) and m,m'-diaminobenzophenone (m, m’-DABP), to produce polyamide acid and then converted it to polyimide (PI). The effects of phosphoric acid (H₃PO₄) molarity (1, 2, and 3 M) on the structural, thermal, mechanical, and electrical characteristics of the polyimides/polyaniline (PI/PANI) nanocomposites were studied. Two sharp reflection peaks were developed by the addition of PANI to PI. When 3 M H₃PO₄ is added, the crystalline sharp peak loses some of its intensity. The complex formation of PI/PANI-H₃PO₄ was confi

The influence of the reaction gas composition during the DC magnetron sputtering process on the structural, chemical and optical properties of Ce-oxide thin films was investigated. X-ray diffraction (XRD) studies confirmed that all thin films exhibited a polycrystalline character with cubic fluorite structure for cerium dioxide. X-ray photoelectron spectroscopy (XPS) analyses revealed that cerium is present in two oxidation states, namely as CeO2 and Ce2O3, at the surface of the films prepared at oxygen/argon flow ratios between 0% and 7%, whereas the films are completely oxidized into CeO2 as the aforementioned ratio increases beyond 14%. Various optical parameters for the thin films (including an optical band gap in the range of 2.25–3.

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s