Low-dimensional materials have attracted significant attention in developing and enhancing the performance of quantum well lasers due to their extraordinary unique properties. The optical confinement factor is one of the most effective parameters for evaluating the optimal performance of a semiconductor laser diode when used to measure the optical gain and current threshold. The optical confinement factor and the radiative recombination of single quantum wells (SQW) and multi-quantum wells (MQW) for InGaAsP/InP have been theoretically studied using both radiative and Auger coefficients. Quantum well width, barrier width, and number of quantum wells were all looked at to see how these things changed the optical confinement factor and

The topological indices of the "[(µ3-2, 5-dioxyocyclohexylidene)-bis ((2-hydrido)-nonacarbonyltriruthenium]” were studied within the quantum theory of atoms in the molecule (QTAIM), clusters are
analyzed using the density functional theory (DFT). The estimated topological variables accord with prior
descriptions of comparable transition metal complexes. The Quantum Theory of Atom, in molecules
investigation of the bridging core component, Ru3H2, revealed critical binding points (chemical bonding)
between Ru (1) and Ru (2) and Ru (3). Consequently, delocalization index for this non-bonding interaction
was calculated in the core of Ru3H2, the interaction is of the (5centre–5electron) class.

Urea formaldehyde resin was prepared by using basic media by yield 95%. The Remaining of ureaplasts resin were prepared in acetic acid media by high yield. Alkyde resins were prepared by condensation polymerization by react Succinic, Maleic, Phthalic anhydrides with Ethylene glycol or Glycerol. Select samples of the prepared alkyde resins were mixed with Azo dyes in special ratio. The mixtures were used as coatings for wood, and compaised with pure dyes. The Coating that some alkyde resins showed better adhesion from using dyes alone. Preparation of wood coating by mixing ureaplast resins and alkyde resins with Azo dyes in special ratios. The coating showed better adhesion, brighter colors and better resistance to heat from Preceding coat

Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

The effect of subinhibitory concentration of Antibiotics on the Adherence of S.aureus (Coagulase Positive Staphylococci), and S.epidermidis (Coagulase negative Staphylococci) and Pseudomonas aeruginosa, Enterobacter cloacae, Citobacter freundi (Gram negative bacteria) was done and the results revealed that Rifampicin was the best antibiotic inhibiting Staphylococci adherence and Vancomycin has less effect on the adherence of Staphylococci, whereas Tetracyclin was the best antibiotic inhbiting Gram negative bacteria adherence and Amikacin has the lest less effect on inhibiting bacterial adherence.

Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural