Pipeline network features and leak detection by cross-correlation analysis of reflected waves

This paper describes progress on a new technique to detect pipeline features and leaks using signal processing of a pressure wave measurement. Previous work (by the present authors) has shown that the analysis of pressure wave reflections in fluid pipe networks can be used to identify specific pipeline features such as open ends, closed ends, valves, junctions, and certain types of bends. It was demonstrated that by using an extension of cross-correlation analysis, the identification of features can be achieved using fewer sensors than are traditionally employed. The key to the effectiveness of the technique lies in the artificial generation of pressure waves using a solenoid valve, rather than relying upon natural sources of fluid excitation. This paper uses an enhanced signal processing technique to improve the detection of leaks. It is shown experimentally that features and leaks can be detected around a sharp bend and up to seven reflections from features/ leaks can be detected, by which time the wave has traveled over 95 m. The testing determined the position of a leak to within an accuracy of 5%, even when the location of the reflection from a leak is itself dispersed over a certain distance and, therefore, does not cause an exact reflection of the wave

Stop the Morphological Cycle, I Want to Get Off: Modeling the Development of Fusion

Historical linguists observe that many fusional (unsegmentable) morphological structures developed from agglutinative (segmentable) predecessors. Such changes may result when learners fail to acquire a phonological alternation, and instead, “chunk” the altered versions of morphemes and memorize them as underlying representations. We present a Bayesian model of this process, which learns which morphosyntactic properties are chunked together, what their underlying representations are, and what phonological processes apply to them. In simulations using artificial data, we provide quantitative support to two claims about agglutinative and fusional structures: that optional morphological markers discourage fusion from developing, but that stress-based vowel reduction encourages it

Making it real: exploring the potential of Augmented Reality for teaching primary school science

The use of Augmented Reality (AR) in formal education could prove a key component in future learning environments that are richly populated with a blend of hardware and software applications. However, relatively little is known about the potential of this technology to support teaching and learning with groups of young children in the classroom. Analysis of teacher-child dialogue in a comparative study between use of an AR virtual mirror interface and more traditional science teaching methods for 10-year-old children, revealed that the children using AR were less engaged than those using traditional resources. We suggest four design requirements that need to be considered if AR is to be successfully adopted into classroom practice. These requirements are: flexible content that teachers can adapt to the needs of their children, guided exploration so learning opportunities can be maximised, in a limited time, and attention to the needs of institutional and curricular requirements

Investigating photoexcitation-induced mitochondrial damage by chemotherapeutic corroles using multimode optical imaging

We recently reported that a targeted, brightly fluorescent gallium corrole (HerGa) is highly effective for breast tumor detection and treatment. Unlike structurally similar porphryins, HerGa exhibits tumor-targeted toxicity without the need for photoexcitation. We have now examined whether photoexcitation further modulates HerGa toxicity, using multimode optical imaging of live cells, including two-photon excited fluorescence, differential interference contrast (DIC), spectral, and lifetime imaging. Using two-photon excited fluorescence imaging, we observed that light at specific wavelengths augments the HerGa-mediated mitochondrial membrane potential disruption of breast cancer cells in situ. In addition, DIC, spectral, and fluorescence lifetime imaging enabled us to both validate cell damage by HerGa photoexcitation and investigate HerGa internalization, thus allowing optimization of light dose and timing. Our demonstration of HerGa phototoxicity opens the way for development of new methods of cancer intervention using tumor-targeted corroles

Magnetorheological landing gear: 2. Validation using experimental data

Aircraft landing gears are subjected to a wide range of excitation conditions with conflicting damping requirements. A novel solution to this problem is to implement semi-active damping using magnetorheological (MR) fluids. In part 1 of this contribution, a methodology was developed that enables the geometry of a flow mode MR valve to be optimized within the constraints of an existing passive landing gear. The device was designed to be optimal in terms of its impact performance, which was demonstrated using numerical simulations of the complete landing gear system. To perform the simulations, assumptions were made regarding some of the parameters used in the MR shock strut model. In particular, the MR fluid's yield stress, viscosity, and bulk modulus properties were not known accurately. Therefore, the present contribution aims to validate these parameters experimentally, via the manufacture and testing of an MR shock strut. The gas exponent, which is used to model the shock strut's nonlinear stiffness, is also investigated. In general, it is shown that MR fluid property data at high shear rates are required in order to accurately predict performance prior to device manufacture. Furthermore, the study illustrates how fluid compressibility can have a significant influence on the device time constant, and hence on potential control strategies

An Extended Variational Principle for the SK Spin-Glass Model

The recent proof by F. Guerra that the Parisi ansatz provides a lower bound on the free energy of the SK spin-glass model could have been taken as offering some support to the validity of the purported solution. In this work we present a broader variational principle, in which the lower bound, as well as the actual value, are obtained through an optimization procedure for which ultrametic/hierarchal structures form only a subset of the variational class. The validity of Parisi's ansatz for the SK model is still in question. The new variational principle may be of help in critical review of the issue.Comment: 4 pages, Revtex

Redox-Active Nanomaterials For Nanomedicine Applications

Nanomedicine utilizes the remarkable properties of nanomaterials for the diagnosis, treatment, and prevention of disease. Many of these nanomaterials have been shown to have robust antioxidative properties, potentially functioning as strong scavengers of reactive oxygen species. Conversely, several nanomaterials have also been shown to promote the generation of reactive oxygen species, which may precipitate the onset of oxidative stress, a state that is thought to contribute to the development of a variety of adverse conditions. As such, the impacts of nanomaterials on biological entities are often associated with and influenced by their specific redox properties. In this review, we overview several classes of nanomaterials that have been or projected to be used across a wide range of biomedical applications, with discussion focusing on their unique redox properties. Nanomaterials examined include iron, cerium, and titanium metal oxide nanoparticles, gold, silver, and selenium nanoparticles, and various nanoscale carbon allotropes such as graphene, carbon nanotubes, fullerenes, and their derivatives/variations. Principal topics of discussion include the chemical mechanisms by which the nanomaterials directly interact with biological entities and the biological cascades that are thus indirectly impacted. Selected case studies highlighting the redox properties of nanomaterials and how they affect biological responses are used to exemplify the biologically-relevant redox mechanisms for each of the described nanomaterials

Twisted k-graph algebras associated to Bratteli diagrams

Given a system of coverings of k-graphs, we show that the cohomology of the resulting (k+1)-graph is isomorphic to that of any one of the k-graphs in the system. We then consider Bratteli diagrams of 2-graphs whose twisted C*-algebras are matrix algebras over noncommutative tori. For such systems we calculate the ordered K-theory and the gauge-invariant semifinite traces of the resulting 3-graph C*-algebras. We deduce that every simple C*-algebra of this form is Morita equivalent to the C*-algebra of a rank-2 Bratteli diagram in the sense of Pask-Raeburn-R{\o}rdam-Sims.Comment: 28 pages, pictures prepared using tik

A framework for space-efficient string kernels

String kernels are typically used to compare genome-scale sequences whose length makes alignment impractical, yet their computation is based on data structures that are either space-inefficient, or incur large slowdowns. We show that a number of exact string kernels, like the $k$-mer kernel, the substrings kernels, a number of length-weighted kernels, the minimal absent words kernel, and kernels with Markovian corrections, can all be computed in $O(nd)$ time and in $o(n)$ bits of space in addition to the input, using just a $\mathtt{rangeDistinct}$ data structure on the Burrows-Wheeler transform of the input strings, which takes $O(d)$ time per element in its output. The same bounds hold for a number of measures of compositional complexity based on multiple value of $k$, like the $k$-mer profile and the $k$-th order empirical entropy, and for calibrating the value of $k$ using the data