In this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr2O3) with Titanium dioxide (TiO2) nanofibers (Cr2O3-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO2 exhibits nanofibers (TNFs) shape structure. Doping TiO2 with chromium (Cr) enhances its ability to absorb ultraviolet light while also speeding up the recombination of photogenerated electrons and holes. The prepared TNFs and Cr2O3-TNFs were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDX), and UV-Visible absorbance. The XRD of TNFs showed a tetragonal phase with 6.9 nm of average crystallite size, whereas Cr2O3-TNFs crystallite size was 12.3 nm. FE-SEM images showed that the average particle size of TNFs was in the range of (9-35) nm and UV-Vis absorbance of TNFs showed their energy gap to be 3.9eV while the energy gaps of Cr2O3-TNFs were smaller equal to 2.4 eV. The highest hydrogen production rate for the Cr2O3-TNFs nanocomposite was 4.1ml after 80min of UV exposure. Cr2O3-TNFs have high photocatalytic effectiveness due to their wide ultraviolet light photoresponse range and excellent separation of photogenerated electrons and holes.
Summary First: The importance of the study and the need for it: The society is composed of an integrated unit of groups and institutions that seek to achieve a specific goal within a system of salary, and the family remains the most influential institutions on the individual and the unity of society, with the roles and responsibilities of the individual and society, and through the continuation and strength of other social organizations derive their ability On the other hand, any break-up in the institution of the family is reflected negatively on the cohesion of society and its interdependence, and the causes of this disintegration vary from society to another, but family problems remain the main factor in obtaining it. Second: Study Ob
... Show MoreAttacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover. The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit
... Show MoreDigital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou
... Show MoreScams remain among top cybercrime incidents happening around the world. Individuals with high susceptibility to persuasion are considered as risk-takers and prone to be scam victims. Unfortunately, limited number of research is done to investigate the relationship between appeal techniques and individuals' personality thus hindering a proper and effective campaigns that could help to raise awareness against scam. In this study, the impact of fear and rational appeal were examined as well as to identify suitable approach for individuals with high susceptibility to persuasion. To evaluate the approach, pretest and posttest surveys with 3 separate controlled laboratory experiments were conducted. This study found that rational appeal treatm
... Show MoreBackground: Suppression of quorum sensing (QS) that regulates many virulence factors, including antimicrobial resistance, in bacteria may subject the pathogenic microbes to the harmful consequences of the antibiotics, increasing their susceptibility to such drugs. Aim: The current study aimed to make an aqueous crude extract from the soil Proteus mirabilis isolate with the use of the gas chromatography-mass spectrometry (GC-MS) technique for its analysis, and then, study the impact of the extract on clinical isolates of Pseudomonas aeruginosa. Methods: Preparation of crude extracts from P. mirabilis (both organic and aqueous), which were then analyzed by GC-MS to detect the bioactive ingredients. Furthermore, the extract’s capability to i
... Show MoreThe current study was carried out to study a high injection dose of the ethanolic extract thymus vulgaris leaf (500 ug /Kg) against the immune response combination with partially purified extracted Lipopolysaccharide ( LPS) from Proteus mirablis.Study groups were included four groups; Group I :treated with normal saline. Group II : treated with LPS antigen, Group III: injected subcutaneously ((500 ug /Kg) from ethanolic extract thymus vulgaris, group IV : injected subcutaneously (500 ug /Kg) from ethanolic extract thymus vulgaris leaf and LPS antigen, the immunological assays were measured through the phagocytic activity as (non specific immunity) after day 8 by using the phagocytic activity index.After day I4 the lymphocyte proliferations
... Show MorePredicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be
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