Search results

The purpose of this paper is to compare the effect of rust inhibitors and surface strengthening materials on the service life of RC structures in tropical marine environments and ultimately to provide basis and recommendations for the durability design of reinforced concrete (RC) structures.

Slag concrete specimens mixed with four kinds of rust inhibitors and coated with four kinds of surface strengthening materials were corroded by seawater exposure for 365 days, and the key parameters of chloride ion diffusion were obtained by testing. Then a new service life prediction model, based on the modified model for chloride ion diffusion and reliability theory, was applied to analyze the effect of rust inhibitors and surface strengthening materials on the service life of RC structures in tropical marine environments.

Rust inhibitors and surface strengthening materials can effectively extend the service life of RC structures through different effects on chloride ion diffusion behavior. The effects of rust inhibitors and surface strengthening materials on the service life extension of RC structures adhered to the following trend: silane material > cement-based permeable crystalline waterproof material > hydrophobic plug compound > spray polyurea elastomer > water-based permeable crystalline waterproof material > calcium nitrite > preservative > amino-alcohol composite.

Using a new method for predicting the service life of RC structures, the attenuation law of the service life of RC structures under the action of rust inhibitors and surface strengthening materials in tropical marine environments is obtained.

The purpose of this paper was to investigate the effects of SO₄2− concentration on the corrosion behaviour of T23 and T12 steels in simulated water chemistry condition solution of 600 MW fossil-fired power boilers.

The influence and mechanism of SO₄2− ions on the pitting corrosion of T23 and T12 steels in simulated oxygenated treatment water chemistry solution was studied using electrochemical potentiodynamic polarization scans and electrochemical impedance spectroscopy.

The results showed that T23 and T12 were susceptible to pitting corrosion in the simulated solution with full SO₄2− concentration for the competitive adsorption of OH− and SO₄2− on the surface of steels. The pitting sensitivity of the steels improved with increasing SO₄2− concentration. The corrosion resistance for SO₄2− of T23 was stronger than that for T12.

This study is an attempt to provide direction for regulating the concentration of SO₄2− in boiler water and for selecting the material for boiler water wall tubes.

Python codes are developed for the versatile structural analysis on a 3 spar multi-cell box beam by means of idealization approach.

Shear flow distribution, stiffener loads, location of shear center and location of geometric center are computed via numpy module. Data visualization is performed by using Matplotlib module.

Python scripts are developed for the structural analysis of multi-cell box beams in lieu of long hand solutions. In-house developed python codes are made available to be used with finite element analysis for verification purposes.

The use of python scripts for the structural analysis provides prompt visualization, especially once dimensional variations are concerned in the frame of aircraft structural design. The developed python scripts would serve as a practical tool that is widely applicable to various multi-cell wing boxes for stiffness purposes. This would be further extended to the structural integrity problems to cover the effect of gaps and/or cut-outs in shear flow distribution in box-beams.

Automatic segmentation of brain tumor from medical images is a challenging task because of tumor's uneven and irregular shapes. In this paper, the authors propose an attention-based nested segmentation network, named DAU-Net. In total, two types of attention mechanisms are introduced to make the U-Net network focus on the key feature regions. The proposed network has a deep supervised encoder–decoder architecture and a redesigned dense skip connection. DAU-Net introduces an attention mechanism between convolutional blocks so that the features extracted at different levels can be merged with a task-related selection.

In the coding layer, the authors designed a channel attention module. It marks the importance of each feature graph in the segmentation task. In the decoding layer, the authors designed a spatial attention module. It marks the importance of different regional features. And by fusing features at different scales in the same coding layer, the network can fully extract the detailed information of the original image and learn more tumor boundary information.

To verify the effectiveness of the DAU-Net, experiments were carried out on the BRATS 2018 brain tumor magnetic resonance imaging (MRI) database. The segmentation results show that the proposed method has a high accuracy, with a Dice similarity coefficient (DSC) of 89% in the complete tumor, which is an improvement of 8.04 and 4.02%, compared with fully convolutional network (FCN) and U-Net, respectively.

The experimental results show that the proposed method has good performance in the segmentation of brain tumors. The proposed method has potential clinical applicability.

This research aims to highlight the connection of entrepreneurial leadership with improved organizational outcomes through employee-driven factors of creativity and behavior. It addresses certain existing research gaps concerning the interaction of leadership practices with organizational performance.

A quantitative cross-sectional design was employed to analyze the interaction among the study variables. Data was collected from 414 employees across various industries in Punjab, Pakistan through an adapted questionnaire which was in structured form. Smart Pls 4 and SPSS were used for analysis of the collected data.

The findings indicate positive and significant effect of entrepreneurial leadership on organizational performance, wherein employee creativity and behavior are the key mediators. The study shows that high levels of employee creativity and positive behavior are directly linked to improved performance metrics in organizations led by entrepreneurial leaders. This consequently underscores the need of creating an environment which encourages creativity and supports positive employee behaviors required for entrepreneurial leadership.

This research enriches the academic discourse by quantitatively confirming the mediating role of employee creativity and behavior between entrepreneurial leadership and organizational performance. Unlike previous studies which focused mainly on direct effects or less quantifiable leadership aspects, this study provides empirical evidence supporting a model where employee attributes significantly impact organizational success under entrepreneurial leadership. This insight is valuable for leaders and practitioners aiming to utilize entrepreneurial leadership in dynamic business settings.