A novel demountable shear connector for precast steel-concrete composite bridges is presented. The connector uses high-strength steel bolts, which are fastened to the top flange of the steel beam with the aid of a special locking nut configuration that prevents bolts from slipping within their holes. Moreover, the connector promotes accelerated construction and overcomes the typical construction tolerance issues of precast structures. Most importantly, the connector allows bridge disassembly. Therefore, it can address different bridge deterioration scenarios with minimum disturbance to traffic flow including the following: (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (

The purpose of the research is to study the impact of knowledge management (personalization and coding strategy) in achieving strategic excellence in the environment of Iraqi private banks, and the descriptive and analytical research approach has been adopted, so the researcher adopted positive philosophy according to the deductive approach for the purpose of deriving the first research hypothesis from the theoretical side and the research reached a group of The most important results are that the personalization strategy has made great progress in its ability to influence strategic superiority as a responsive variable, as the civil bank departments were successful in employing the changes that occurred in the personalization str

Sea level rise (SLR) due to climate change is affecting the coastline, causing shoreline changes, the degradation of mangrove forests, and the destruction of coastal resources. This is the cause of a huge amount of mangrove degradation in many parts of the Ganges–Brahmaputra–Meghna delta. A total of 90% of people have been forced to migrate from the island due to extreme weather conditions. In this study, remote sensing (RS) and geographic information system (GIS) techniques were used for LULC change and shoreline shift analyses of Ghoramara Island. LULC classification was carried out using thirty years of Landsat datasets with intervals of ten years (1990 and 2000) and intervals of five years (2005, 2010, 2015, and 2020). The classific

A new Ni(II) nanostructured chelating system (DHN) was introduced for selective optical heavy-metal ion sensing in an aqueous medium. The cooperative chelating system comprising 8-hydroxyquinoline (8-HQ) and dimethylglyoxime (DMG) has been developed for the first time in association with fibre optic sensing for selective optical heavy-metal ion sensing in an aqueous medium. The Ni(II) nanocompound fluoresces upon 578 nm excitation, showing a highly sensitive optical response with a linear calibration curve in the range 0–100 ng/mL. The regression equation of the calibration curve is y = 0.0035x + 0.9990, which indicates very good linearity, implying R2 = 0.999 with high sensitivity (calibration slope of 0.0035) and low baseline noise (bla

The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated

Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health