To promote sustainable steel-concrete composite structures, it is essential to develop special shear connectors that facilitate accelerated construction and deconstruction. A lockbolt demountable shear connector (LBDSC) was recently proposed. While the LBDSC has been evaluated using horizontal and vertical (standard) push-out tests, it is essential to further assess the disassembly mechanism and the positive flexural performance of prefabricated demountable composite beams (PDCBs) under both serviceability and ultimate limit states. Two full-scale test specimens of PDCBs with LBDSC were designed with partial shear connections and assessed using a three or four-point load beam setup under both cyclic and static monotonic loading conditions.

Bromocriptine mesylate is a semisynthetic ergot alkaloid derivative with potent dopaminergic activity, used in the treatment of pituitary tumors, Parkinson's disease (PD), hyperprolactinaemia, neuroleptic malignant syndrome, and type 2 diabetes ,the oral bioavailability is  approximately 6%, therefore aim  its  prepare and evaluate bromocriptine mesylate  as liquid self nano emulsifying drug delivery system to enhance its solubility , dissolution and stability . Solubility study was made in different vehicles to select the best excipients for dissolving bromocriptine mesylate. Pseudo-ternary phase diagrams were constructed at 1:1, 2:1, 3:1 and 4:1 ratios of surfactant and co-surfactant, four formulations were pre

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

The depletion of petroleum reserves and increasing environmental concerns have driven the development of eco-friendly asphalt binders. This research investigates the performance of natural asphalt (NA) modified with waste engine oil (WEO) as a sustainable alternative to conventional petroleum asphalt (PA). The study examines NA modified with 10%, 20%, and 30% WEO by the weight of asphalt to identify an optimal blend ratio that enhances the binder’s flexibility and workability while maintaining high-temperature stability. Comprehensive testing was conducted, including penetration, softening point, viscosity, ductility, multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), energy-dispersive X-ray spectroscopy (EDX), F

Manganese sulfate and Punica granatum plant extract were used to create MnO₂ nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO₂ NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencie