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In this study, the relationship between SCC growth rate and Vickers hardness for Type 316 stainless steel at various temperatures in simulated PWR primary water was investigated. In addition, IGSCC growth measurements were conducted using so-called functionally graded cold-rolled specimens made of Type 316 stainless steel, in simulated PWR primary water. Residual stress measurements were performed using the contour and slitting methods on the functionally graded cold-rolled specimens. The contour method measurements found highly tensile stress (350 MPa) toward the surface of the side with a larger thickness reduction and low-magnitude stress elsewhere. The purpose of these latter specimens was to evaluate the effect of heavily cold-worked layers on the inner surface of components made of Type 316 stainless steel on the possibility that IGSCC could penetrate through the wall thickness. The test data showed that the work-hardened inner surface does not always have a detrimental effect on SCC susceptibility. However, if any surface cracks exist within the work-hardened inner surface layer of any components, the stress at the crack tip becomes very large and SCC easily initiates. Nevertheless, even if IGSCC initiates from a heavily cold-worked layer at the inner surface, IGSCC growth rate in Type 316 stainless steel was found to eventually become negligibly small or arrests in the soft base material.

The basement membrane (BM) is composed of various extracellular molecules and regulates tissue regeneration and maintenance. Here, we demonstrate that collagen XVIII was spatiotemporally expressed in the BM during skin wound healing in a mouse excisional wound-splinting model. Re-epithelialization was detected at days 3 and 6 post-wounding. The ultrastructure of epidermal BM was discontinuous at day 3, whereas on day 6 a continuous BM was observed in the region proximal to the wound edge. Immunohistochemistry demonstrated that collagen XVIII was deposited in the BM zone beneath newly forming epidermis in day 3 and 6 wounds. Laminin-332, known to be the earliest BM component appearing in wounds, was colocalized with collagen XVIII in the epidermal BM zone at days 3 and 6. The deposition of α1(IV) collagen and nidogen-1 in the epidermal BM zone occurred later than that of collagen XVIII. We also observed the short isoform of collagen XVIII in the epidermal BM zone at day 3 post-wounding. Collectively, our results suggested that collagen XVIII plays a role in the formation of the dermal-epidermal junction during re-epithelialization, and that it is the short isoform that is involved in the early phase of re-epithelialization.

This paper presents an approach to supporting the development process for large-scale smart city applications that leverage edge computing resources. A smart city testbed called CitiFlow is developed, which uses Distributed Node-RED as the underlying middleware to facilitate the decomposition and communication among sub components of large scale smart city applications. For the evaluation, a lab-based setup and a real world deployment were executed and are presented.

A growing trend in smart cities is the use of machine learning techniques to gather city data, formulate learning tasks and models, and use these to develop solutions to city problems. However, although these processes are sufficient for theoretical experiments, they often fail when they meet the reality of city data and processes, which by their very nature are highly distributed, heterogeneous, and exhibit high degrees of spatial and temporal variance. In order to address those problems, we have designed and implemented an integrated development environment called CityFlow that supports developing machine learning applications. With CityFlow, we can develop, deploy, and maintain machine learning applications easily by using an intuitive data flow model. To verify our approach, we conducted two case studies: deploying a road damage detection application to help monitor transport infrastructure and an automatic labeling application in support of a participatory sensing application. These applications show both the generic applicability of our approach, and its ease of use; both critical if we wish to deploy sophisticated ML based applications to smart cities. © 2020, Springer Nature Switzerland AG.

This paper presents an approach to supporting the development process for large-scale smart city applications that leverage edge computing resources. A smart city testbed called CitiFlow is developed, which uses Distributed Node-RED as the underlying middleware to facilitate the decomposition and communication among sub components of large scale smart city applications. For the evaluation, a lab-based setup and a real world deployment were executed and are presented.