A comparison of SQUID imaging techniques for small defects in nonmagnetic tubes

Although superconducting quantum interference devices (SQUIDs) provide an exquisitively sensitive means for measuring magnetic fields, their usage in the past has been limited chiefly to biomagnetic research. However, over the past few years interest in applying SQUID techniques to the field of nondestructive evaluation (NDE) has blossomed [1]. Many experiments have exploited the sensitivity of SQUIDs for diverse NDE applications, especially those requiring large separation distances between the sensor and the item to be inspected. Our work instead has focused on the potential to detect very small defects with SQUIDs, specifically in thin-walled tubes. In this paper, we discuss three different methods for creating magnetic fields in tubes. The methods comprise (a) directly injecting a current through the tube, (b) using a separate induction coil to create induced currents in the tube, and (c) utilizing a ferromagnetic tracer technique. To illustrate the capabilities of each method, we present two-dimensional maps of the spatial distribution of the magnetic field as measured by a SQUID magnetometer — that is, SQUID images. The images will also be used to compare the sensing methods with respect to such practical considerations as relative sensitivity and signal-to-noise ratio

Magnetic Microscopy Promises a Leap in Sensitivity and Resolution

Twenty years ago, Kirschvink argued that many paleomagnetic studies were limited by the sensitivity of the magnetometer systems then in use [Kirschvink, 1981]. He showed that sedimentary rocks could preserve detrital remanent magnetizations at levels of 10^(-14) to 10^(-15) Am^2, about 100-1000 times below the noise level of today's best superconducting (SQUID) rock magnetometers. If a more sensitive magnetometer could be built, it would dramatically expand the range and variety of rock types amenable to paleomagnetic analysis. Just such an instrument is now on the horizon: the low-temperature superconductivity (LTS) SQUID Microscope

Boundary Integral Equations for Modeling Arbitrary Flaw Geometries in Electric Current Injection NDE

The Electric Current Injection (ECI) method of nondestructive evaluation is applied to materials that are electrically conductive but not magnetically permeable, such as aluminum, magnesium, and titanium. It consists of detecting current-flow anomalies due to voids, nonmetallic inclusions and open cracks in the conducting material, through distortions introduced in the magnetic field generated by the sample [1]

Incorporating Inductances in Tissue-Scale Models of Cardiac Electrophysiology

In standard models of cardiac electrophysiology, including the bidomain and monodomain models, local perturbations can propagate at infinite speed. We address this unrealistic property by developing a hyperbolic bidomain model that is based on a generalization of Ohm's law with a Cattaneo-type model for the fluxes. Further, we obtain a hyperbolic monodomain model in the case that the intracellular and extracellular conductivity tensors have the same anisotropy ratio. In one spatial dimension, the hyperbolic monodomain model is equivalent to a cable model that includes axial inductances, and the relaxation times of the Cattaneo fluxes are strictly related to these inductances. A purely linear analysis shows that the inductances are negligible, but models of cardiac electrophysiology are highly nonlinear, and linear predictions may not capture the fully nonlinear dynamics. In fact, contrary to the linear analysis, we show that for simple nonlinear ionic models, an increase in conduction velocity is obtained for small and moderate values of the relaxation time. A similar behavior is also demonstrated with biophysically detailed ionic models. Using the Fenton-Karma model along with a low-order finite element spatial discretization, we numerically analyze differences between the standard monodomain model and the hyperbolic monodomain model. In a simple benchmark test, we show that the propagation of the action potential is strongly influenced by the alignment of the fibers with respect to the mesh in both the parabolic and hyperbolic models when using relatively coarse spatial discretizations. Accurate predictions of the conduction velocity require computational mesh spacings on the order of a single cardiac cell. We also compare the two formulations in the case of spiral break up and atrial fibrillation in an anatomically detailed model of the left atrium, and [...].Comment: 20 pages, 12 figure

A SQUID NDE Measurement Model Using BEM

As the commercial and military aircraft fleets age, additional resources are required to ensure their airworthiness. As the aircraft become older, the more likely they are to develop structural damage that may lead to unscheduled repairs or, in the worst case, accidents. Fatigue and corrosion are the two main causes of structural damage in aging aircraft and this research examines the use of a Superconducting QUantum Interference Device (SQUID) as a tool for Nondestructive Evaluation (NDE) to detect and characterize these aging aircraft problems. The primary advantage of using SQUIDs in NDE over other techniques is the ability to detect second layer cracks and corrosion commonly found in aircraft structures

External Control of the GAL Network in S. cerevisiae: A View from Control Theory

While there is a vast literature on the control systems that cells utilize to regulate their own state, there is little published work on the formal application of control theory to the external regulation of cellular functions. This paper chooses the GAL network in S. cerevisiae as a well understood benchmark example to demonstrate how control theory can be employed to regulate intracellular mRNA levels via extracellular galactose. Based on a mathematical model reduced from the GAL network, we have demonstrated that a galactose dose necessary to drive and maintain the desired GAL genes' mRNA levels can be calculated in an analytic form. And thus, a proportional feedback control can be designed to precisely regulate the level of mRNA. The benefits of the proposed feedback control are extensively investigated in terms of stability and parameter sensitivity. This paper demonstrates that feedback control can both significantly accelerate the process to precisely regulate mRNA levels and enhance the robustness of the overall cellular control system

FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis

Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci) to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ

A mathematical model for electrical stimulation of a monolayer of cardiac cells

BACKGROUND: The goal of our study is to examine the effect of stimulating a two-dimensional sheet of myocardial cells. We assume that the stimulating electrode is located in a bath perfusing the tissue. METHODS: An equation governing the transmembrane potential, based on the continuity equation and Ohm's law, is solved numerically using a finite difference technique. RESULTS: The sheet is depolarized under the stimulating electrode and is hyperpolarized on each side of the electrode along the fiber axis. CONCLUSIONS: The results are similar to those obtained previously by Sepulveda et al. (Biophys J, 55: 987–999, 1989) for stimulation of a two-dimensional sheet of tissue with no perfusing bath present

Recreating blood-brain barrier physiology and structure on chip: A novel neurovascular microfluidic bioreactor

The blood-brain barrier (BBB) is a critical structure that serves as the gatekeeper between the central nervous system and the rest of the body. It is the responsibility of the BBB to facilitate the entry of required nutrients into the brain and to exclude potentially harmful compounds; however, this complex structure has remained difficult to model faithfully in vitro. Accurate in vitro models are necessary for understanding how the BBB forms and functions, as well as for evaluating drug and toxin penetration across the barrier. Many previous models have failed to support all the cell types involved in the BBB formation and/or lacked the flow-created shear forces needed for mature tight junction formation. To address these issues and to help establish a more faithful in vitro model of the BBB, we have designed and fabricated a microfluidic device that is comprised of both a vascular chamber and a brain chamber separated by a porous membrane. This design allows for cell-to-cell communication between endothelial cells, astrocytes, and pericytes and independent perfusion of both compartments separated by the membrane. This NeuroVascular Unit (NVU) represents approximately one-millionth of the human brain, and hence, has sufficient cell mass to support a breadth of analytical measurements. The NVU has been validated with both fluorescein isothiocyanate (FITC)-dextran diffusion and transendothelial electrical resistance. The NVU has enabled in vitro modeling of the BBB using all human cell types and sampling effluent from both sides of the barrier