An optical fibre dynamic instrumented palpation sensor for the characterisation of biological tissue

AbstractThe diagnosis of prostate cancer using invasive techniques (such as biopsy and blood tests for prostate-specific antigen) and non-invasive techniques (such as digital rectal examination and trans-rectal ultrasonography) may be enhanced by using an additional dynamic instrumented palpation approach to prostate tissue classification. A dynamically actuated membrane sensor/actuator has been developed that incorporates an optical fibre Fabry–Pérot interferometer to record the displacement of the membrane when it is pressed on to different tissue samples. The membrane sensor was tested on a silicon elastomer prostate model with enlarged and stiffer material on one side to simulate early stage prostate cancer. The interferometer measurement was found to have high dynamic range and accuracy, with a minimum displacement resolution of ±0.4μm over a 721μm measurement range. The dynamic response of the membrane sensor when applied to different tissue types changed depending on the stiffness of the tissue being measured. This demonstrates the feasibility of an optically tracked dynamic palpation technique for classifying tissue type based on the dynamic response of the sensor/actuator

The Mid-IR Spectral Effects of Darkening Agents and Porosity on the Silicate Surface Features of Airless Bodies

We systematically measured the mid-IR spectra of different mixtures of three silicates (antigorite, lizardite, and pure silica) with varying effective porosities and amounts of darkening agent (iron oxide and carbon). These spectra have broad implications for interpretation of current and future mission data for airless bodies, as well as for testing the capabilities of new instruments. Serpentines, such as antigorite and lizardite, are common to airless surfaces, and their mid-IR spectra in the presence of darkening agents and different surface porosities would be typical for those measured by spacecraft. Silica has only been measured in the plumes of Enceladus and presents exciting possibilities for other Saturn-system surfaces due to long range transport of E-ring material. Results show that the addition of the IR-transparent salt, KBr, to simulate surface porosity affected silicate spectra in ways that were not predictable from linear mixing models. The strengthening of silicate bands with increasing pore space, even when only trace amounts of KBr were added, indicates that spectral features of porous surfaces are more detectable in the mid-IR. Combining iron oxide with the pure silicates seemed to flatten most of the silicate features, but strengthened the reststrahlen band of the silica. Incorporating carbon with the silicates weakened all silicate features, but the silica bands were more resistant to being diminished, indicating silica may be more detectable in the mid-IR than the serpentines. We show how incorporating darkening agents and porosity provides a more complete explanation of the mid-IR spectral features previously reported on worlds such as Iapetus

A monolithic (Si) massively broadband non-reverberant monopole

Accepted versio

Identifying network communities with a high resolution

Community structure is an important property of complex networks. An automatic discovery of such structure is a fundamental task in many disciplines, including sociology, biology, engineering, and computer science. Recently, several community discovery algorithms have been proposed based on the optimization of a quantity called modularity (Q). However, the problem of modularity optimization is NP-hard, and the existing approaches often suffer from prohibitively long running time or poor quality. Furthermore, it has been recently pointed out that algorithms based on optimizing Q will have a resolution limit, i.e., communities below a certain scale may not be detected. In this research, we first propose an efficient heuristic algorithm, Qcut, which combines spectral graph partitioning and local search to optimize Q. Using both synthetic and real networks, we show that Qcut can find higher modularities and is more scalable than the existing algorithms. Furthermore, using Qcut as an essential component, we propose a recursive algorithm, HQcut, to solve the resolution limit problem. We show that HQcut can successfully detect communities at a much finer scale and with a higher accuracy than the existing algorithms. Finally, we apply Qcut and HQcut to study a protein-protein interaction network, and show that the combination of the two algorithms can reveal interesting biological results that may be otherwise undetectable.Comment: 14 pages, 5 figures. 1 supplemental file at http://cic.cs.wustl.edu/qcut/supplemental.pd

Two-stage potassium test turbine. Volume 4 - Materials support of performance and endurance tests

Two stage potassium vapor turbine - materials support of performance and endurance test