Beryllium Zinc Oxide (Be_xZn_1-xO) ternary nano thin films were deposited using the pulsed laser deposition (PLD) technique under a vacuum condition of 10^-3 torr at room temperature on glass substrates with different films thicknesses, (300, 600 and 900 nm). UV-Vis spectra study found the optical band gap for Be_0.2Zn_0.8O to be  (3.42, 3.51 and 3.65 eV) for the (300, 600 and 900nm) film thicknesses, respectively which is larger than the value of zinc oxide ZnO (3.36eV) and smaller than that of beryllium oxide BeO (10.6eV). While the X-ray diffraction (XRD) pattern analysis of ZnO, BeO and Be _0.2 Zn _0.8 O powder and nano-thin films indicated a hexa

Moisture damage is described as a reduction in stiffness and strength durability in asphalt mixtures due to moisture. This study investigated the influence of adding nano silica (NS) to the Asphalt on the moisture susceptibility of hot-mix-asphalt (HMA) mixtures under different aging conditions. NS was mixed with asphalt binder at concentrations of 2%, 4%, and 6% by weight of the binder. To detect the microstructure changes of modified Asphalt and estimate the dispersion of NS within the Asphalt, the field emission scanning electron microscope (FE-SEM) was used. To examine the performance of Asphalt mixed with NS at different aging stages (short-term and long-term aging), asphalt mixture tests such as Marshall stability,

High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall s

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

In this paper, Nordhaus-Gaddum type relations on open support independence number of some derived graphs of path related graphs under addition and multiplication are studied.

As a result of industrial development, many types of waste are generated, some of which are discharged into water, causing water pollution and having a negative impact on life. The electro-Fenton process (EF) has verified high efficiency in treating pollutants with low cost, ease of handling and operation, and this technology is one of the more efficient advanced oxidation technologies. The main objective of this present work is to explore the efficiency of a three-dimensional Electro-Fenton system (3DEF) in removing eosin, methylene blue, and methylene violet from simulated wastewater using graphite as anode, nickel foam as the cathode, and alum sludge as the third particle and as the source of catalyst. The study investigated the effect o

Biomass is a popular renewable carbon source because it has a lot of potential as a substitute for scarce fossil fuels and has been used to make essential compounds like 5-hydroxymethylfurfural (HMF). One of the main components of biomass, glucose, has been extensively studied as a precursor for the production of HMF. Several efforts have been made to find efficient and repeatable procedures for the synthesis of HMF, a chemical platform used in the manufacturing of fuels and other high-value compounds. Sulfonated graphite (SG) was produced from spent dry batteries and utilized as a catalyst to convert glucose to 5-hydroxymethylfurfural (HMF). Temperature, reaction time, and catalyst loading were the variables studied. When dimethyl sulfo

Sn(II) complex of the type, [Sn(SMZ)2]Cl2 was synthesized by the interaction of Sulfamethoxazole ligand and Tin Chloride, the complex was confirmed on the basis of results of elemental analyses, FT-IR, UV-Vis, molar conductance (Ëm). The elemental analysis data, suggests the stoichiometry to be 1:2 (metal: ligand) and determination of the formula of a coordination a complex formed between the Sn(II) ion and the SMZ using Job’s method of continuous variations. The study of (Ëm), indicated the electrolytic nature type 1:2. The [Sn(SMZ)2]Cl2 was screened for antibacterial activity against Gram-ve (Escherichia coli and Gram+ve (Staphylococcus aureus) and (Candida albicans) antifungal. The IR spectral data suggested that the coordination sit