A preliminary approach to intelligent x-ray imaging for baggage inspection at airports

Identifying explosives in baggage at airports relies on being able to characterize the materials that make up an X-ray image. If a suspicion is generated during the imaging process (step 1), the image data could be enhanced by adapting the scanning parameters (step 2). This paper addresses the first part of this problem and uses textural signatures to recognize and characterize materials and hence enabling system control. Directional Gabor-type filtering was applied to a series of different X-ray images. Images were processed in such a way as to simulate a line scanning geometry. Based on our experiments with images of industrial standards and our own samples it was found that different materials could be characterized in terms of the frequency range and orientation of the filters. It was also found that the signal strength generated by the filters could be used as an indicator of visibility and optimum imaging conditions predicted

On the effect of long-term electrical stimulation on three-dimensional cell cultures: Hen embryo brain spheroids

A comprehensive dataset of multielectrode array recordings was collected from three-dimensional hen embryo brain cell cultures, termed spheroids, under long-term electrical stimulation. The aim is to understand the ongoing changes in the spiking activity under electrical stimulation within the lifetime of 14-72DIV of the neuronal networks contained therein. The spiking dynamics were analyzed and behavioral characteristics derived. Some effects on spiking patterns and exhaustion were followed in culture lifetime. With respect to the culture development, two main types of spiking exhaustion were found: one which materializes in the form of a drop in the sporadic (tonic) spiking frequency at the later maturation stages; and another associated with decreasing spiking train appearance throughout an experimental period. © 2008 Uroukov and Bull

Image Enhancement of X-ray Phase Contrast Images of Micro Objects

In x-ray based baggage scanning, the ability to identify small devices (e.g. detonator components) and explosives in baggage or shipped parcels relies on being able to characterize the materials and details that make up an x-ray image. Recently, an improvement over existing baggage scanning techniques has been proposed in the form of a system employing x-ray phase contrast imaging, as this was shown to detect smaller/fainter features and to be more sensitive to materials textures (small-scale inhomogeneites, etc). This paper deals with additional image processing performed on the phase contrast images produced by the above system, to further improve its potential. It uses textural analysis to enhance imaged micro-structures and devices, and it has been found to be able to provide a contrast increase of up to 300% on a series of images of a phantom mimicking the presence of an explosive device plus detonator components

Towards unconventional computing through simulated evolution: Control of nonlinear media by a learning classifier system

We propose that the behavior of nonlinear media can be controlled automatically through evolutionary learning. By extension, forms of unconventional computing (viz., massively parallel nonlinear computers) can be realized by such an approach. In this initial study a light-sensitive subexcitable Belousov-Zhabotinsky reaction in which archeckerboard image, composed of cells of varying light intensity projected onto the surface of a thin silica gel impregnated with a catalyst and indicator, is controlled using a learning classifier system. Pulses of wave fragments are injected into the checkerboard grid, resulting in rich spatiotemporal behavior, and a learning classifier system is shown to be able to direct the fragments to an arbitrary position through dynamic control of the light intensity within each cell in both simulated and real chemical systems. Similarly, a learning classifier system is shown to be able to control the electrical stimulation of cultured neuronal networks so that they display elementary learning. Results indicate that the learned stimulation protocols identify seemingly fundamental properittes of in vitro neuronal networks. Use of another learning scheme presented in the literature confirms that such fundamental behavioral characteristics of a given network must be considered in training experiments. © 2008 Massachusetts Institute of Technology

Fabrication and Characterization of 3D Micro- and Nanoelectrodes for Neuron Recordings

In this paper we discuss the fabrication and characterization of three dimensional (3D) micro- and nanoelectrodes with the goal of using them for extra- and intracellular studies. Two different types of electrodes will be described: high aspect ratio microelectrodes for studying the communication between cells and ultimately for brain slice recordings and small nanoelectrodes for highly localized measurements and ultimately for intracellular studies. Electrical and electrochemical characterization of these electrodes as well as the results of PC12 cell differentiation on chip will be presented and discussed

Computer music meets unconventional computing: Towards sound synthesis with in vitro neuronal networks

The feasibility of synthesizing sounds with hybrid wetware-silicon devices has been explored with the use of in vitro neuronal networks. The basics of culturing brain cells has been introduced while the procedures that has been established to stimulate the in vitro neuronal networks has been presented. Then, the technique on sonifying the behavior of neuronal networks which has been developed was described while the initial results of developing the techniques to steer the behavior of the networks have been reported. The main goal of this paper is to have some form of controllability and repeatability in the system. This sound-synthesis technique has an important property in that it has the ability to produce different types of sounds with a certain degree of predictable control

Examination of the transition of cultured neuronal cells from submerged to exposed using an environmental scanning electron microscope (ESEM)

Relatively few studies of fully hydrated live or fixed cultured animal cells viewed by environmental scanning electron microscopy (ESEM) have been published. In some cases there may have been some drying out of the cells. In this study the interface between water and cells is imaged as water is carefully evaporated to expose cells. Technical difficulties associated with the process, including inadvertent rewetting of cells are described. Suggestions are made for optimising operating parameters for viewing fully hydrated cultured cells by ESEM. The prospects for viewing live cultured cells are discussed

Towards neuronal computing: simple creation of two logic functions in 3D cell cultures using multi-electrode arrays

In this paper we begin by reviewing a number of previously presented approaches to control the electrical stimulation of in vitro neuronal networks for computation through the use of multi-electrode array technology. Drawing upon this research we describe how universal computation is possible with a form of three-dimensional cell culture so long as the underlying properties of the neuronal networks therein are considered. That is, we describe how it is possible to produce the Boolean logic functions NOT and OR in vitro in a simple way

Consideration of using learning classifier systems to create a simple neuronal computer

UWE Learning Classifier Systems Group Technical Report – UWELCSG07-00