A simple low-cost approach at various exposure times was utilized to generate cold plasma in the aim to fabricate AuNPs. UV-Visible spectra and X-ray diffraction were used to characterize the nanoparticles (XRD). Surface Plasmon resonance was observed in the synthesized AuNPs at 530, 540, and 533 nm. For all samples, the patterns of XRD show very intensive peaks implying the fcc crystalline structure of AuNPs. The average crystallite size of AuNPs is ranging between 20-30 nm. The observation of morphology by FESEM revealed the spherical formation of AuNPs. Doses of 100 and 200 ppm of AuNPs were adapted to investigate their effect on the blood-mixture with and without a 20-second of cold plasma exposure. The WBC components in the blood

CdS Nps (inorganic material) was prepared by the chemical reaction method. ZnPc (organic material) and CdS thin films were prepared separately to compare their characterization with the hybrid BHJ blend ZnPc/CdS thin film (2ml:2ml) by spin coating technique. The structural and morphological properties of the prepared thin films have been measured by XRD and AFM respectively. The XRD pattern for both as-deposited and annealed CdS nanoparticle films shows a hexagonal structure. The crystallite size behavior of as deposited ZnPc films and annealing at 423K for 1h, 2h and 3h was approximately similar to the behavior of heat treated blended films. The grain size was measured by AFM, which decreaseds with annealing temperature for ZnPc films,

The aim of this study was to use low cost adsorbents, which consist of corn cobs as plant wastes adsorbents in treatment of Industrial waste water by fixed bed column technique and study the effect of two variables (pH value and contact time). The sample of plant waste (Corn cobs) was tested to determine its activity which gives the best performance in heavy metals removal and other pollutants (TSS, TDS and COD). Adsorption tests showed the corn cobs adsorbents had significant heavy metal removal efficiency. The best removal efficiency 95.05% of Cr was occurred at pH 5.4 and 4.18hr. Higher removal efficiency 99.90% of Ni was occurred at pH 6.5 and 2.38hr. While, lower removal efficiency 91.35% for Zn obtained at pH 6.5 and 0.15hr. Remova

B Saleem, H Alwan, L Khalid, Journal of Engineering, 2011 - Cited by 2

Background: Head and neck squamous cell carcinoma is the sixth most common cancer world wide. Despite greater emphasis on multi-modality therapy including surgery, radiation and chemotherapy, advanced stage head and neck squamous cell carcinoma continues to have poor 5-year survival rates (0-40%) that have not significantly improved in the last (30) years. To improve outcomes for this deadly disease , It is required a better understanding of the mechanisms underlying head and neck squamous cell carcinoma tumor growth, metastasis, and treatment resistance. This study evaluates the Immunohistochemical expression of E-cadherin and CD44 adhesion molecules in OSCC and to correlate the expression of either marker with each other, with lymph node

The current study was designed for using banana peels to remove zinc, chromium and nickel from industrial waste-water. Three forms of these peels (fresh, dried small pieces and powder) were tested under some environmental factors such as pH, temperature and contact time. Current data show that banana peels are capable of removing zinc, chromium and nickel ions at significant capacity. Furthermore, the powder of banana peels had highest capability in removing all zinc, chromium and nickel ions followed by fresh peels whilst dried peels had the lowest bioremoving capacity again for all metals under test. The highest capacity was for chromium then nickel and finally zinc. All these data were significantly (LSD peel forms = 2.761 mg/l, LSD m

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne