In this study, the flexural performance of a new composite beam–slab system filled with concrete material was investigated, where this system was mainly prepared from lightweight cold-formed steel sections of a beam and a deck slab for carrying heavy floor loads as another concept of a conventional composite system with a lower cost impact. For this purpose, seven samples of a profile steel sheet–dry board deck slab (PSSDB/PDS) carried by a steel cold-formed C-purlins beam (CB) were prepared and named “composite CBPDS specimen”, which were tested under a static bending load. Specifically, the effects of the profile steel sheet (PSS) direction (parallel or perpendicular to the span of the specimen) using different C-purlins c

Background: Over the last few years, nanocrystal technology has expanded to improve the bioavailability of poorly water-soluble drugs, which is challenging. Nanocrystals (NCs) exhibit many properties, such as enhancing drug solubility, dissolution, oral absorption, and high drug loading. Ondansetron hydrochloride (ONH) is an antiemetic drug that antagonizes a serotonin 5-HT3 receptor in the peripheral and central nervous system and is widely prescribed for the management of chemotherapy and radiotherapy-induced vomiting and nausea, as well as for postoperative nausea. ONH exhibits approximately 60% bioavailability due to its poor solubility and first-pass metabolism in the liver. Its solubility is pH-dependent, its precipitates abov

This study proposed control system that has been presented to control the electron lens resistance in order to obtain a stabilized electron lens power. This study will layout the fundamental challenges, hypothetical plan arrangements and development condition for the Integrable Optics Test Accelerator (IOTA) in progress at Fermilab. Thus, an effective automatic gain  control (AGC) unit has been introduced which prevents fluctuations in the internal resistance of the electronic lens caused by environmental influences to affect the system's current and power values ​​and keep them in stable amounts. Utilizing this unit has obtained level balanced out system un impacted with electronic lens surrounding natural varieties.

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

The long – term behaviour of polyethylene products used out doors is affected by weathering. In the present work,
weathering test was carried out to find the effect of the environment conditions on the mechanical properties of
HDPE/LLDPE blends with different weight percents (0, 15, 30, and 45 %) relative to the LLDPE by increasing the
exposure times to (100, 150, 200, 250, 300) hr.
A series of tests (destructive), tensile, impact and hardness were carried out on the prepared samples, the results
obtained declare the changes on the material behaviour from ductile to brittle and the polymer shows a decline in the
mechanical properties with increasing the exposure times.
In the present work empirical equations were r

   The petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli

The cathodic deposition of zinc from simulated chloride wastewater was used to characterize the mass transport properties of a flow-by fixed bed electrochemical reactor composed of vertical stack  of stainless steel nets, operated in batch-recycle mode. The electrochemical reactor employed potential value in such a way that the zinc reduction occurred under mass transport control. This potential was determined by hydrodynamic voltammetry using a borate/chloride solution as supporting electrolyte on stainless steel rotating disc electrode. The results indicate that mass transfer coefficient (K_m) increases with increasing of flow rate (Q) where .The electrochemical reactor proved to be efficient in removing zinc and was abl