Operation of a high frequency piezoelectric ultrasound array with an application specific integrated circuit

Integration of a piezoelectric high frequency ultrasound (HFUS) array with a microfabricated application specific integrated circuit (ASIC) performing a range of functions has several advantages for ultrasound imaging. The number of signal cables between the array/electronics and the data acquisition / imaging system can be reduced, cutting costs and increasing functionality. Electrical impedance matching is also simplified and the same approach can reduce overall system dimensions for applications such as endoscopic ultrasound. The work reported in this paper demonstrates early ASIC operation with a piezocomposite HFUS array operating at approximately 30 MHz. The array was tested in three different modes. Clear signals were seen in catch-mode, with an external transducer as a source of ultrasound, and in pitch-mode with the external transducer as a receiver. Pitch-catch mode was also tested successfully, using sequential excitation on three array elements, and viable signals were detected. However, these were relatively small and affected by interference from mixed-signal sources in the ASIC. Nevertheless, the functionality and compatibility of the two main components of an integrated HFUS - ASIC device have been demonstrated and the means of further optimization are evident.

Optimum Magnetic Circuit Configurations for Permanent Magnet Aerospace Generators

In the design of high-speed low-power electrical generators for unmanned aircraft and spacecraft, maximization of specific output (power/weight) is of prime importance. Several magnetic circuit configurations (radial-field, axial-field, flux-squeezing, homopolar) have been proposed, and in this paper the relative merits of these configurations are subjected to a quantitative investigation over the speed range 10 000–100000 rev/min and power range 250 W-10 kW. The advantages of incorporating new high energy-density magnetic materials are described. Part I deals with establishing an equivalent circuit for permanent-magnet generators. For each configuration the equivalent circuit parameters are related to the physical dimensions of the generator components and an optimization procedure produces a minimum volume design at discrete output powers and operating speeds. The technique is illustrated by a quantitative comparison of the specific outputs of conventional radial-field generators with samarium cobalt and alnico magnets. In Part II the specific outputs of conventional, flux-squeezing, and claw-rotor magnetic circuit configurations are compared. The flux-squeezing configuration is shown to produce the highest specific output for small sizes whereas the conventional configuration is best at large sizes. For all sizes the claw-rotor configuration is significantly inferior. In Part III the power densities available from axial-field and flux-switching magnetic circuit configurations are maximized, over the power range 0.25-10 kW and speed range 10 000–100000 rpm, and compared to the results of Parts I & II. For the axial-field configuration the power density is always less than that of the conventional and flux-squeezing radial-field configurations. For the flux-switching generator, which is able to withstand relatively high mechanical forces in the rotor, the power density is again inferior to the radial-field types, but the difference is less apparent for small (low power, high speed) generator sizes. From the combined results it can be concluded that the flux-squeezing and conventional radial-field magnetic circuit configurations yield designs with minimum volume over the power and speed ranges considered. © 1985, IEEE. All rights reserved.

Increasing the open-circuit voltage of photoprotein-based photoelectrochemical cells by manipulation of the vacuum potential of the electrolytes.

The innately highly efficient light-powered separation of charge that underpins natural photosynthesis can be exploited for applications in photoelectrochemistry by coupling nanoscale protein photoreaction centers to man-made electrodes. Planar photoelectrochemical cells employing purple bacterial reaction centers have been constructed that produce a direct current under continuous illumination and an alternating current in response to discontinuous illumination. The present work explored the basis of the open-circuit voltage (V(OC)) produced by such cells with reaction center/antenna (RC-LH1) proteins as the photovoltaic component. It was established that an up to ~30-fold increase in V(OC) could be achieved by simple manipulation of the electrolyte connecting the protein to the counter electrode, with an approximately linear relationship being observed between the vacuum potential of the electrolyte and the resulting V(OC). We conclude that the V(OC) of such a cell is dependent on the potential difference between the electrolyte and the photo-oxidized bacteriochlorophylls in the reaction center. The steady-state short-circuit current (J(SC)) obtained under continuous illumination also varied with different electrolytes by a factor of ~6-fold. The findings demonstrate a simple way to boost the voltage output of such protein-based cells into the hundreds of millivolts range typical of dye-sensitized and polymer-blend solar cells, while maintaining or improving the J(SC). Possible strategies for further increasing the V(OC) of such protein-based photoelectrochemical cells through protein engineering are discussed.

Device and circuit-level performance of carbon nanotube field-effect transistor with benchmarking against a nano-MOSFET

The performance of a semiconducting carbon nanotube (CNT) is assessed and tabulated for parameters against those of a metal-oxide-semiconductor field-effect transistor (MOSFET). Both CNT and MOSFET models considered agree well with the trends in the available experimental data. The results obtained show that nanotubes can significantly reduce the drain-induced barrier lowering effect and subthreshold swing in silicon channel replacement while sustaining smaller channel area at higher current density. Performance metrics of both devices such as current drive strength, current on-off ratio (Ion/Ioff), energy-delay product, and power-delay product for logic gates, namely NAND and NOR, are presented. Design rules used for carbon nanotube field-effect transistors (CNTFETs) are compatible with the 45-nm MOSFET technology. The parasitics associated with interconnects are also incorporated in the model. Interconnects can affect the propagation delay in a CNTFET. Smaller length interconnects result in higher cutoff frequency. © 2012 Tan et al.

Design of brushless doubly-fed machines based: On magnetic circuit modeling

This paper proposes a magnetic circuit model (MCM) for the design of a brushless doubly-fed machine (BDFM). The BDFM possesses advantages in terms of high reliability and reduced gearbox stages, and it requires a fractionally-rated power converter. This makes it suitable for utilization in offshore wind turbines. It is difficult for conventional design methods to calculate the flux in the stator because the two sets of stator windings, which have different pole number, form a complex flux pattern which is not easily determined using common analytical approaches. However, it is advantageous to predict the flux density in the teeth and air-gap at the initial design stage for sizing purposes without recourse finite element analysis. Therefore a magnetic circuit model is developed in this paper to calculate the flux density. A BDFM is used as a case study with FEA validation. © 1965-2012 IEEE.

A Balance Equation Determines a Switch in Neuronal Excitability

We use the qualitative insight of a planar neuronal phase portrait to detect an excitability switch in arbitrary conductance-based models from a simple mathematical condition. The condition expresses a balance between ion channels that provide a negative feedback at resting potential (restorative channels) and those that provide a positive feedback at resting potential (regenerative channels). Geometrically, the condition imposes a transcritical bifurcation that rules the switch of excitability through the variation of a single physiological parameter. Our analysis of six different published conductance based models always finds the transcritical bifurcation and the associated switch in excitability, which suggests that the mathematical predictions have a physiological relevance and that a same regulatory mechanism is potentially involved in the excitability and signaling of many neurons. © 2013 Franci et al.

An organizing center in a planar model of neuronal excitability

This paper studies the excitability properties of a generalized FitzHugh-Nagumo model. The model differs from the classical FitzHugh-Nagumo model in that it accounts for the effect of cooperative gating variables such as activation of calcium currents. Excitability is explored by unfolding a pitchfork bifurcation that is shown to organize five different types of excitability. In addition to the three classical types of neuronal excitability, two novel types are described and distinctly associated to the presence of cooperative variables. © 2012 Society for Industrial and Applied Mathematics.

A novel phase portrait for neuronal excitability

Fifty years ago, FitzHugh introduced a phase portrait that became famous for a twofold reason: it captured in a physiological way the qualitative behavior of Hodgkin-Huxley model and it revealed the power of simple dynamical models to unfold complex firing patterns. To date, in spite of the enormous progresses in qualitative and quantitative neural modeling, this phase portrait has remained a core picture of neuronal excitability. Yet, a major difference between the neurophysiology of 1961 and of 2011 is the recognition of the prominent role of calcium channels in firing mechanisms. We show that including this extra current in Hodgkin-Huxley dynamics leads to a revision of FitzHugh-Nagumo phase portrait that affects in a fundamental way the reduced modeling of neural excitability. The revisited model considerably enlarges the modeling power of the original one. In particular, it captures essential electrophysiological signatures that otherwise require non-physiological alteration or considerable complexification of the classical model. As a basic illustration, the new model is shown to highlight a core dynamical mechanism by which calcium channels control the two distinct firing modes of thalamocortical neurons. © 2012 Drion et al.

A novel modeling approach for design studies of brushless doubly fed induction generator based on magnetic equivalent circuit

Brushless doubly fed induction generator (BDFIG) has substantial benefits, which make it an attractive alternative as a wind turbine generator. However, it suffers from lower efficiency and larger dimensions in comparison to DFIG. Hence, optimizing the BDFIG structure is necessary for enhancing its situation commercially. In previous studies, a simple model has been used in BDFIG design procedure that is insufficiently accurate. Furthermore, magnetic saturation and iron loss are not considered because of difficulties in determination of flux density distributions. The aim of this paper is to establish an accurate yet computationally fast model suitable for BDFIG design studies. The proposed approach combines three equivalent circuits including electric, magnetic and thermal models. Utilizing electric equivalent circuit makes it possible to apply static form of magnetic equivalent circuit, because the elapsed time to reach steady-state results in the dynamic form is too long for using in population-based design studies. The operating characteristics, which are necessary for evaluating the objective function and constraints values of the optimization problem, can be calculated using the presented approach considering iron loss, saturation, and geometrical details. The simulation results of a D-180 prototype BDFIG are compared with measured data in order to validate the developed model. © 1986-2012 IEEE.

How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

BACKGROUND: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process. RESULTS: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration. CONCLUSIONS: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.