Search results

The purpose of this study is to examine how well reinforced concrete structures can be shielded against concrete carbonation using anti-carbonation coatings based on synthetic polymer.

Applying free radical polymerization, an acrylate terpolymer emulsion that a surfactant had stabilized was created. A thermogravimetric analysis, minimum film-forming temperature, Fourier transform infrared spectroscopy and particle size distribution are used to characterize the prepared eco-friendly water base acrylate terpolymer emulsion. Using three different percentages of the acrylate terpolymer emulsion produced, 35%, 45% and 55%, the anti-carbonation coating was formed. Tensile strength, tensile strain, elongation, crack-bridging ability, carbon dioxide permeability, chloride ion diffusion, average pull-off adhesion strength, water vapor transmission, gloss, wet scrub resistance, QUV/weathering and storage stability are the characteristics of the anti-carbonation coating.

The formulated acrylate terpolymer emulsion enhances anti-carbonation coating performance in CO₂ permeability, Cl-diffusion, crack bridging, pull-off adhesion strength and water vapor transmission. The formed coating based on the formulated acrylate terpolymer emulsion performed better than its commercial counterpart.

To protect the steel embedded in concrete from corrosion and increase the life span of concrete, the surface of cement is treated with an anti-carbonation coating based on synthetic acrylate terpolymer emulsion.

In addition to saving lives from building collapse, it maintains the infrastructure for the long run.

The anti-carbonation coating, which is based on the synthetic acrylate terpolymer emulsion, is environmentally benign and stops the entry of carbon dioxide and chlorides, which are the main causes of steel corrosion in concrete.

At the moment, in terms of both research and commercial products, smart shoe technology and applications seem not to attract the same magnitude of attention compared to smart garments and other smart wearables such as wrist watches and wrist bands. The purpose of this study is to fill this knowledge gap by discussing issues regarding smart shoe sensing technologies, smart shoe sensor placements, factors that affect sensor placements and finally the areas of smart shoe applications.

Through a review of relevant literature, this study first and foremost attempts to explain what constitutes a smart shoe and subsequently discusses the current trends in smart shoe applications. Discussed in this study are relevant sensing technologies, sensor placement and areas of smart shoe applications.

This study outlined 13 important areas of smart shoe applications. It also uncovered that majority of smart shoe functionality are physical activity tracking, health rehabilitation and ambulation assistance for the blind. Also highlighted in this review are some of the bottlenecks of smart shoe development.

To the best of the authors’ knowledge, this is the first comprehensive review paper focused on smart shoe applications, and therefore serves as an apt reference for researchers within the field of smart footwear.

The emergence of residential aged care facilities (RACFs) within the Ghanaian health-care system has raised eyebrows because, hitherto, the concept of nursing homes had largely been perceived as an anomaly. The purpose of this study is to understand this emerging phenomenon and the activities of care provided within two facilities in the nation’s capital, Accra.

The study draws on participant observations and in-depth interviews with purposively sampled 15 residents in the two facilities and eight caregivers. The data were analysed using thematic approach.

The study found that the daily forms of care mostly performed for the elderly were intimate and non-intimate physical, medical, emotional and spiritual and end-of-life care. The bulk of activities of care were performed in the morning.

The study reveals that the changing landscape of health-care facilities in Ghana to include RACFs indicates RACFs have come to stay to provide different forms of care to older persons who otherwise were cared for by the family.

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.

Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.

The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.

The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.