Two novel demountable shear connectors for precast steel-concrete composite bridges are presented. The connectors use high-strength steel bolts, which are fastened to the steel beam with the aid of a special locking configuration that prevents slip of bolts within their holes. Moreover, the connectors promote accelerated construction and overcome typical construction tolerances issues of precast structures. Most importantly, the connectors allow bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (3) steel beams can be replaced, while precast decks and shear connectors can be reused. A series of push-out tests and a beam test were conducted to assess the behavior of the connectors and quantify the effect of important parameters. The experimental results showed that shear resistance and slip capacity can reach 2.5 and 2.7 times respectively of those of welded shear studs along with superior stiffness and strength against slab uplift. Additionally, shear stiffness of M16 mm LNSC was equal to that of M19 mm welded studs. Identical tests reveal negligible scatter in the shear load – slip displacement behavior. Design equations are proposed to predict the shear resistance with minimum deviations.
In this paper, some chalcone derivatives (C1, C2) were synthesized based on the reaction of equal amount of substituted acetophenone and substituted banzaldehyde in basic medium. Oxazine and thiazine derivatives were prepared from the reaction of chalcones (C1-C2) with urea and thiourea respectively in a basic medium. Pyrazole derivatives were prepared based on the reaction of chalcones with hydrazine mono hydrate or phenyl hydrazine in the presence of glacial acetic acid as a catalyst. The new synthesized compounds were identified using various physical techniques like1 H-NMR and FT-IR spectra.
Stream of Consciousness technique has a great impact on writing literary texts in the modern age. This technique was broadly used in the late of nineteen century as a result of thedecay of plot, especially in novel writing. Novelists began to use stream of consciousness technique as a new phenomenon, because it goes deeper into the human mind and soul through involving it in writing. Modern novel has changed after Victorian age from the traditional novel that considers themes of religion, culture, social matters, etc. to be a group of irregular events and thoughts interrogate or reveal the inner feeling of readers.
This study simplifies stream of consciousness technique through clarifying the three levels of conscious
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This study aims to deeply analyze the character of serial killers in Thomas Harris’ novels and focuses on his novel Red Dragon. The Study searches in these complex and deep characters through the use of Erich Fromm's concepts about the destructive nature of the human psyche and what are the factors affecting serial killers in all social psychological, and biological aspects. This study Concluded: Thomas Harris portrayed the characters of serial killers in a professional and complex and made the reader go on a contemplative journey in the mind and soul of the serial killer, thus reaching the climax of artistic perfection.
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Fiber‐reinforced elastic laminated composites are extensively used in several domains owing to their high specific stiffness and strength and low specific density. Several studies were performed to ascertain the factors that affect the composite plates’ dynamic properties. This study aims to derive a mathematical model for the dynamic response of the processed composite material in the form of an annular circular shape made of polyester/E‐glass composite. The mathematical model was developed based on modified classical annular circular plate theory under dynamic loading, and all its formulas were solved using MATLAB 2023. The mathematical model was also verified with real experimental work involving the vibration test of the f
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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