Low-Power Adaptive Biased Integrated Amplifiers

In this paper the author will present the working principle and the applications of a novel adaptive biasing topology, designed to decrease the stand-by power dissipation without affecting the transient performance of low-power amplifiers. The proposed circuit, whose principle and circuit topology can be implemented both in CMOS and in bipolar standard technologies, gives a biasing current whose value depends on the applied input differential voltage and can be set according to the requested transient performance constraints. The adaptive architecture can be utilized in the design of high-efficient low-power operational amplifiers, for the biasing of both the input stage (where the input source current is dynamically increased) and the output stage (where the output current can be controlled and limited). These amplifiers show a very good behaviour, evaluated in terms of two efficiency factors, if compared with those of other adaptive solutions and class-AB topologies, proposed in the literature. Simulation results and also measurements on a chip prototype, fabricated in a standard CMOS technology, are finally presented.     

Effects of interstitial oxygen on microstructure and mechanical properties of Ti-48Al-2Cr-2Nb with fully lamellar and duplex microstructures

The effect of added oxygen in the range of 1000 to 4000 wt ppm on the microstructures of a Ti-48Al-2Cr-2Nb alloy has been investigated and compared to the microstructures for a high-purity alloy. For specimens cooled from theα phase, interstitial oxygen stabilizes the lamellar microstructure with respect toγ grains, with higher than equilibrium values for theα ₂ volume fraction. For specimens cooled from theα +γ phase field, the lamellar microstructure still tends to be favored by oxygen, but it is found that the phase volume fractions are not significantly different from equilibrium values. This suggests that interstitial O essentially reduces the kinetics of theα toα +γ transformation. Thus, interstitial oxygen will have a strong effect on microstructures obtained by continuous cooling fromα, but significantly less on those, such as the duplex microstructure, obtained by long treatment in theα +γ phase field. In general, increased O content is well correlated with reduced ductility. Finally, the role of interstitial oxygen on this phase transformation is discussed.     

Constructive model-based analysis for safety assessment

The aerospace industry still uses fault trees to perform reliability analysis. This is because fault-tree modeling and analysis (FTA) seems easier to practical engineers when compared with Markov models, even though FTA provides a weaker form of analysis. In this paper, we propose an automatic strategy for generating Markov-based models and corresponding analysis formulations, according to ARP 4761, directly from Simulink diagrams annotated with failure information. The generated Markov-based models are expressed in the formal language PRISM, and the analysis is carried out by the PRISM model checker. The strategy is compositional and based on a comprehensive set of translation rules from Simulink to PRISM. We briefly address soundness and completeness of the rules and, to illustrate the application of the strategy, we apply it to a classical avionics case study: an actuator control system.     

A cubic regularization algorithm for unconstrained optimization using line search and nonmonotone techniques

In recent years, cubic regularization algorithms for unconstrained optimization have been defined as alternatives to trust-region and line search schemes. These regularization techniques are based on the strategy of computing an (approximate) global minimizer of a cubic overestimator of the objective function. In this work we focus on the adaptive regularization algorithm using cubics (ARC) proposed in Cartis et al. [Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results, Mathematical Programming A 127 (2011), pp. 245–295]. Our purpose is to design a modified version of ARC in order to improve the computational efficiency preserving global convergence properties. The basic idea is to suitably combine a Goldstein-type line search and a nonmonotone accepting criterion with the aim of advantageously exploiting the possible good descent properties of the trial step computed as (approximate) minimizer of the cubic model. Global convergence properties of the proposed nonmonotone ARC algorithm are proved. Numerical experiments are performed and the obtained results clearly show satisfactory performance of the new algorithm when compared to the basic ARC algorithm.     

Binarised regression tasks: methods and evaluation metrics

Some supervised tasks are presented with a numerical output but decisions have to be made in a discrete, binarised, way, according to a particular cutoff. This binarised regression task is a very common situation that requires its own analysis, different from regression and classification—and ordinal regression. We first investigate the application cases in terms of the information about the distribution and range of the cutoffs and distinguish six possible scenarios, some of which are more common than others. Next, we study two basic approaches: the retraining approach, which discretises the training set whenever the cutoff is available and learns a new classifier from it, and the reframing approach, which learns a regression model and sets the cutoff when this is available during deployment. In order to assess the binarised regression task, we introduce context plots featuring error against cutoff. Two special cases are of interest, the \( UCE \) and \( OCE \) curves, showing that the area under the former is the mean absolute error and the latter is a new metric that is in between a ranking measure and a residual-based measure. A comprehensive evaluation of the retraining and reframing approaches is performed using a repository of binarised regression problems created on purpose, concluding that no method is clearly better than the other, except when the size of the training data is small.     

Speeding up the spatial adiabatic passage of matter waves in optical microtraps by optimal control

We numerically investigate the performance of atomic transport in optical microtraps via the so called spatial adiabatic passage technique. Our analysis is carried out by means of optimal control methods, which enable us to determine suitable transport control pulses. We investigate the ultimate limits of the optimal control in speeding up the transport process in a triple well configuration for both a single atomic wave packet and a Bose-Einstein condensate within a regime of experimental parameters achievable with current optical technology.     

Coherence-multiplexed acousto-optic correlator for signal processing: theory and applications

A method of multichannel processing to compute correlation products simultaneously is introduced. The signals that process are encoded on a single light beam through the use of an electro-optic modulators that induce optical delays greater than the coherence length of light. The coherence-modulated light beam thus obtained is then spatially and temporally modulated through an acousto-optic Bragg cell. The potential number of channels is estimated to be approximately 5-10. The method can be combined with other existing systems, such as time-, space-, or frequency-multiplexed correlators, to increase the channel number. The method also applies to high-resolution spectral analysis.     

Quantum computing implementations with neutral particles

We review quantum information processing with cold neutral particles, that is, atoms or polar molecules. First, we analyze the best suited degrees of freedom of these particles for storing quantum information, and then we discuss both single- and two-qubit gate implementations. We focus our discussion mainly on collisional quantum gates, which are best suited for atom-chip-like devices, as well as on gate proposals conceived for optical lattices. Additionally, we analyze schemes both for cold atoms confined in optical cavities and hybrid approaches to entanglement generation, and we show how optimal control theory might be a powerful tool to enhance the speed up of the gate operations as well as to achieve high fidelities required for fault tolerant quantum computation.     

iLogDemons: A Demons-Based Registration Algorithm for Tracking Incompressible Elastic Biological Tissues

Tracking soft tissues in medical images using non-linear image registration algorithms requires methods that are fast and provide spatial transformations consistent with the biological characteristics of the tissues. LogDemons algorithm is a fast non-linear registration method that computes diffeomorphic transformations parameterised by stationary velocity fields. Although computationally efficient, its use for tissue tracking has been limited because of its ad-hoc Gaussian regularisation, which hampers the implementation of more biologically motivated regularisations. In this work, we improve the logDemons by integrating elasticity and incompressibility for soft-tissue tracking. To that end, a mathematical justification of demons Gaussian regularisation is proposed. Building on this result, we replace the Gaussian smoothing by an efficient elastic-like regulariser based on isotropic differential quadratic forms of vector fields. The registration energy functional is finally minimised under the divergence-free constraint to get incompressible deformations. As the elastic regulariser and the constraint are linear, the method remains computationally tractable and easy to implement. Tests on synthetic incompressible deformations showed that our approach outperforms the original logDemons in terms of elastic incompressible deformation recovery without reducing the image matching accuracy. As an application, we applied the proposed algorithm to estimate 3D myocardium strain on clinical cine MRI of two adult patients. Results showed that incompressibility constraint improves the cardiac motion recovery when compared to the ground truth provided by 3D tagged MRI.