Project neptune: Improved operation of water distribution networks

Water service providers (WSPs) in the UK have statutory obligations to supply drinking water to all customers that complies with increasingly stringent water quality regulations and minimum flow and pressure criteria. At the same time, the industry is required by regulators and investors to demonstrate increasing operational efficiency and to meet a wide range of performance criteria that are expected to improve year-on-year. Most WSPs have an ideal for improving the operation of their water supply systems based on increased knowledge and understanding of their assets and a shift to proactive management followed by steadily increasing degrees of system monitoring, automation and optimisation. The fundamental mission is, however, to ensure security of supply, with no interruptions and water quality of the highest standard at the tap. Unfortunately, advanced technologies required to fully understand, manage and automate water supply system operation either do not yet exist, are only partially evolved, or have not yet been reliably proven for live water distribution systems. It is this deficiency that the project NEPTUNE seeks to address by carrying out research into 3 main areas; these are: data and knowledge management; pressure management (including energy management); and the associated complex decision support systems on which to base interventions. The 3-year project started in April of 2007 and has already resulted in a number of research findings under the three main research priority areas (RPA). The paper summarises in greater detail the overall project objectives, the RPA activities and the areas of research innovation that are being undertaken in this major, UK collaborative study. Copyright 2009 ASCE.

A simple combinatorial method aiding research on single-walled carbon nanotube growth on substrates

Establishing fabrication methods of carbon nanotubes (CNTs) is essential to realize many applications expected for CNTs. Catalytic growth of CNTs on substrates by chemical vapor deposition (CVD) is promising for direct fabrication of CNT devices, and catalyst nanoparticles play a crucial role in such growth. We have developed a simple method called "combinatorial masked deposition (CMD)", in which catalyst particles of a given series of sizes and compositions are formed on a single substrate by annealing gradient catalyst layers formed by sputtering through a mask. CMD enables preparation of hundreds of catalysts on a wafer, growth of single-walled CNTs (SWCNTs), and evaluation of SWCNT diameter distributions by automated Raman mapping in a single day. CMD helps determinations of the CVD and catalyst windows realizing millimeter-tall SWCNT forest growth in 10 min, and of growth curves for a series of catalysts in a single measurement when combined with realtime monitoring. A catalyst library prepared using CMD yields various CNTs, ranging from individuals, networks, spikes, and to forests of both SWCNTs and multi-walled CNTs, and thus can be used to efficiently evaluate self-organized CNT field emitters, for example. The CMD method is simple yet effective for research of CNT growth methods. © 2010 The Japan Society of Applied Physics.

In vitro osteoblast response to ferritic stainless steel fiber networks for magneto-active layers on implants

The use of a porous coating on prosthetic components to encourage bone ingrowth is an important way of improving uncemented implant fixation. Enhanced fixation may be achieved by the use of porous magneto-active layers on the surface of prosthetic implants, which would deform elastically on application of a magnetic field, generating internal stresses within the in-growing bone. This approach requires a ferromagnetic material able to support osteoblast attachment, proliferation, differentiation, and mineralization. In this study, the human osteoblast responses to ferromagnetic 444 stainless steel networks were considered alongside those to nonmagnetic 316L (medical grade) stainless steel networks. While both networks had similar porosities, 444 networks were made from coarser fibers, resulting in larger inter-fiber spaces. The networks were analyzed for cell morphology, distribution, proliferation, and differentiation, extracellular matrix production and the formation of mineralized nodules. Cell culture was performed in both the presence of osteogenic supplements, to encourage cell differentiation, and in their absence. It was found that fiber size affected osteoblast morphology, cytoskeleton organization and proliferation at the early stages of culture. The larger inter-fiber spaces in the 444 networks resulted in better spatial distribution of the extracellular matrix. The addition of osteogenic supplements enhanced cell differentiation and reduced cell proliferation thereby preventing the differences in proliferation observed in the absence of osteogenic supplements. The results demonstrated that 444 networks elicited favorable responses from human osteoblasts, and thus show potential for use as magnetically active porous coatings for advanced bone implant applications. © 2012 Wiley Periodicals, Inc.

Short-term cytotoxic and inflammatory responses of human monocytes to stainless steel fibre networks

The aim of the current work was to examine the human monocyte response to 444 ferritic stainless steel fibre networks. 316L austenitic fibre networks, of the same fibre volume fraction, were used as control surfaces. Fluorescence and scanning electron microscopies suggest that the cells exhibited a good degree of attachment and penetration throughout both networks. Lactate Dehydrogenase (LDH) and TNF-α releases were used as indicators of cytotoxicity and inflammatory responses respectively. LDH release indicated similar levels of monocyte viability when in contact with the 444 and 316L fibre networks. Both networks elicited a low level secretion of TNF-α, which was significantly lower than that of the positive control wells containing zymosan. Collectively, the results suggest that 444 ferritic and 316L austenitic networks induced similar cytotoxic and inflammatory responses from human monocytes. © 2012 Materials Research Society.

Avoiding pathologies in very deep networks

Choosing appropriate architectures and regularization strategies of deep networks is crucial to good predictive performance. To shed light on this problem, we analyze the analogous problem of constructing useful priors on compositions of functions. Specifically, we study the deep Gaussian process, a type of infinitely-wide, deep neural network. We show that in standard architectures, the representational capacity of the network tends to capture fewer degrees of freedom as the number of layers increases, retaining only a single degree of freedom in the limit. We propose an alternate network architecture which does not suffer from this pathology. We also examine deep covariance functions, obtained by composing infinitely many feature transforms. Lastly, we characterize the class of models obtained by performing dropout on Gaussian processes.