Shear lag is the phenomenon that occurs when a supported slender member undergoes deformation from lateral loading, causing in-plane non-uniform distribution of stresses that results in reducing the member’s minimum strength capacity. This paper investigates the behaviour of shear distribution in steel I-section and box girders when subjected to both static and impact loadings. Three-dimensional finite element analysis models were prepared in Strand7 and validated against experimental results providing a basis for further comparison research into shear lagging effects. A parametric study was conducted comparing the effects of impact loading through certain specified velocities at the midspan of restrained ends. It provided new ins

The banking sector of all kinds is the backbone of the economy in all countries, as it is the main financier of most economic projects in order to achieve economic development and achieve stability, which contributes to providing the necessary resources in return for obtaining a profit margin in exchange for giving up his money and bearing credit risks. Among the aforementioned banking sectors are: Islamic banks that invest their capital in several forms in order to obtain profits that enable them to continue and grow, and the most important of these formulas is the Murabaha formula, which is summarized by the bank selling a commodity after owning it and then selling it to the applicant for this commodity based on a prior request

          This study was done to evaluate a new technique to determine the presence of methamphetamine in the hair using nano bentonite-based adsorbent as the filler of extraction column. The state of the art of this study was based on the presence of silica in the nano bentonite that was assumed can interact with methamphetamine. The hair used was treated using methanol to extract the presence of methamphetamine, then it was continued by sonicating the hair sample. Qualitative analysis using Marquish reagent was performed to confirm the presence of methamphetamine in the isolate.The hair sample that has been taken in a different period confirmed that this current developing method can be used to analyzed methamphetamine. This m

  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

The aim of this study is know the five leadership practices according to the theory of network of leadership by Black and Mouton for the presidents of the Taxation General Board from their prospective, that is through answering the questionnaire questions. To achieving the objectives of this study, the researcher organized a questionnaire form as a main instrument for data collection. It includes (30) items distributed into five leadership practices according to the theory of network of leadership. Each one is subdivided into (6) questions.

The questionnaire was distributed to the presidents of the Taxation General Board of (14). The researcher used the SPSS program to analyses the answers. Through the answers, h

This study investigates the impacts of climate change (CC) on the emergence and proliferation of fungal pathogens, with a particular focus on global food security and the potential of medicinal plants and their by-products as sustainable mitigation strategies. Through a systematic literature review of articles published up to 2024, we analyze how CC exacerbates the spread and severity of fungal diseases in crops, leading to significant agricultural losses and threats to food availability. The findings highlight that, alongside conventional approaches such as genetic resistance and precision farming, bioactive compounds derived from medicinal plants and their by-products offer promising, eco-friendly alternatives for the management of fungal

Wars represent one of the most serious threats to the world order; It is considered a violation of international laws and norms, and humanitarian principles. From this point comes the study of the importance of the topic entitled (The Future of the Russian-Ukrainian war and the extent of its Reflection on the security of Eastern European countries after the year 2022). This study is based on reviewing future possibilities (scenarios) of war. The Russian-Ukrainian war, which was launched by the Russian government led by Russian President Vladimir Putin in February 2022, is still ongoing at the time of writing this research. This chapter includes three possibilities (scenarios). The first possibility deals with the development of the war t

In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.