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This paper provides a comprehensive review of the current state of 3D printing technology in the construction industry, highlighting the potential applications, benefits, and future directions of this emerging field. The review indicates that 3D printing technology has the potential to revolutionize the construction industry by offering more efficient, precise, and sustainable methods of construction. The technology offers numerous advantages, including the ability to create complex geometries and custom components, improved precision and accuracy, reduction in waste materials, improved worker safety, and potential for use in remote or inaccessible locations. Furthermore, the advent of additive manufacturing, colloquially known as 3D printing, presents prospects for the advancement of novel material compositions, printing methodologies, and cybernetic systems that have the potential to optimize the efficiency and effectiveness of the construction domain. Future research should focus on developing larger printers with more efficient support structures, improving the accuracy and speed of printing, and exploring the potential of using new and innovative materials in the construction process. Additionally, the environmental impact of 3D printing technology should be further examined, particularly in terms of its potential for reducing waste and energy consumption in the construction industry. Overall, the potential utilizations and advantageous outcomes stemming from the implementation of 3D printing technology within the construction sector are momentous. Persistent exploration and innovation within this realm hold the capacity to engender noteworthy strides in construction technology and foster heightened sustainability within building methodologies.

Computational simulation models have been widely used to study the dynamics of COVID-19. Among those, bottom-up approaches such as agent-based models (ABMs) can account for population heterogeneity. While many studies have addressed COVID-19 spread at various scales, insufficient studies have investigated the spread of COVID-19 within closed indoor settings. This study aims to develop an ABM to simulate the spread of COVID-19 in a closed indoor setting using three transmission sub-models. Moreover, a comprehensive sensitivity analysis encompassing 4374 scenarios is performed. The model is calibrated using data from Calabria, Italy. The results indicated a decent consistency between the observed and predicted number of infected people (MAPE = 27.94%, RMSE = 0.87 and χ 2 (1 , N = 34) = (44.11 , p = 0.11) ). Notably, the transmission distance was identified as the most influential parameter in this model. In nearly all scenarios, this parameter had a significant impact on the outbreak dynamics (total cases and epidemic peak). Also, the calibration process showed that the movement of agents and the number of initial asymptomatic agents are vital model parameters to simulate COVID-19 spread accurately. The developed model may provide useful insights to investigate different scenarios and dynamics of other similar infectious diseases in closed indoor settings. [ABSTRACT FROM AUTHOR]

In this study, we demonstrate the development of a fast-response soft composite actuator fabricated by mechanical mixing of silicone elastomer (matrix) and ethanol (as phase-change fluid). Joule heating generated by electrical actuation causes a liquid-vapor transition of ethanol embedded in silicone microcapsules; provides the required pressure for mimicking the natural movements. We discuss the critical design variables to improve the temperature response, chemical composition, mechanical properties, force generated, and microstructure of soft actuator. Our soft actuator produces a high load-to-weight ratio (1000 times greater than its own) using a low-voltage source (˂20V). The stability of the soft actuator under multiple working cycles would bring the application to different robotic areas. The actuator using the mechanism presented here is easy to manufacture, automate, and recyclable. It can be used in a range of robotic applications. [ABSTRACT FROM AUTHOR]

Hereditary sensory autonomic neuropathy type VIII (HSAN-VIII) is a rare genetic disease that occurs due to mutations in the PRDM12 gene. Here, we describe a novel homozygous mutation c.826_840dupTGCAACCGCCGCTTC (p.Cys276_Phe280dup) on exon 5 in the PRDM12 gene identified by WES and confirmed using Sanger sequencing method. [ABSTRACT FROM AUTHOR]