Effect of layer thickness variations on propagation delay andpenetration depth of a quarter-wave distributed Bragg reflector

The authors derive an analytical formula for the change of propagation delay and phase penetration depth of a quarter-wave distributed Bragg reflector (DBR) owing to thickness and/or composition variations. The analytical expression provides a very good estimate of change in penetration depth with arbitrary thickness perturbation in one or more layers of the DBR. For a Fabry-Perot cavity clad on both sides by two quarter-wave DBRs, the shift in the Fabry-Perot mode due to thickness variations in one or both of the DBRs can be simply obtained by calculation using the change in penetration depths of the corresponding DBR or both DBRs     

Beta-mercaptolactate cysteine disulphiduria in a mentally retarded Scottish male

Antenatal diagnosis of hereditary disease is highly dependent on sufficient theoretical knowledge and on a number of practical methods of studying the foetus such as obtaining, cultivating and assaying amniotic fluid cells. Knowledge of the primary defect in any monogenic disorder cannon be used in prenatal diagnosis unless the metabolic error is expressed in vitro. Modern cytogenetics can diagnose in utero a large majority of karyotyping abnormalities although the karyotype-phenotype correlation is not an absolute one. This task must be assigned to special laboratories where technical pitfalls are reliably avoided. In both metabolic and chromosomal hereditary disease, the pathologist can confirm and extend the phenotypic findings and improve knowledge on foetal features and physiopathology. Pathology is the more important, the less means of in utero diagnosis are available as in the non-chromosomal syndromes of localized or multiple malformations. Here it helps eliminating a present major drawback of prenatal diagnosis: the lack of a strict diagnosis in the previous patient in a family at risk.     

Automatic Generation of Redundant Models for Permutation Constraint Satisfaction Problems

If we have two representations of a problem as constraint satisfaction problem (CSP) models, it has been shown that combining the models using channeling constraints can increase constraint propagation in tree search CSP solvers. Handcrafting two CSP models for a problem, however, is often time-consuming. In this paper, we propose model induction, a process which generates a second CSP model from an existing model using channeling constraints, and study its theoretical properties. The generated induced model is in a different viewpoint, i.e., set of variables. It is mutually redundant to and can be combined with the input model, so that the combined model contains more redundant information, which is useful to increase constraint propagation. We also propose two methods of combining CSP models, namely model intersection and model channeling. The two methods allow combining two mutually redundant models in the same and different viewpoints respectively. We exploit the applications of model induction, intersection, and channeling and identify three new classes of combined models, which contain different amounts of redundant information. We construct combined models of permutation CSPs and show in extensive benchmark results that the combined models are more robust and efficient to solve than the single models.     

A 3.1–10.6 GHz Ultra-Wideband Low Noise Amplifier With 13-dB Gain, 3.4-dB Noise Figure, and Consumes Only 12.9 mW of DC Power

A 3.1-10.6 GHz ultra-wideband two-stage pseudomorphit high electron mobility transistor low noise amplifier is presented. The first stage of the amplifier employs a resistive shunt feedback topology and two T-network sections to provide wideband input matching to a 50-Omega antenna. The current-sharing dc bias topology is used to ensure the low power consumption under fixed 3-V battery operation. The amplifier exhibits state of the art performance consuming only 12.9mW of dc power with a power gain of 12.5dB, plusmn0.5dB gain flatness, and 3.4-4.0dB noise figure. Input match is better than -12.0dB, output match is better than -15dB, and group delay is 184pSplusmn28pS     

Electrostatic Deposition of Pesticide Sprays onto Ionizing Targets: Charge- and Mass-Transfer Analysis

Electrostatic deposition of charged pesticide sprays onto biological targets may be undesirably limited under certain operational conditions by gaseous-discharge currents induced to flow between the incoming charged spray cloud and grounded points on the target (e.g. leaf tips). Spray deposition and charge transfer onto idealized target models as functions of target characteristics and intensity of spray-droplet charging are quantified experimentally to achieve a more fundamental understanding of this phenomenon. As compared to similar uncharged sprays, deposition onto smooth spherical, and planar targets was increased up to seven-fold and three-fold, respectively, at optimum spray-charge levels. Space-charge induced target ionization from a 20-mm point protrustion self-limited this electrostatic deposition to only a 3.5-fold increase for the spherical target but caused little reduction for the planar target. As compared with a hydraulic-atomizing nozzle, the charging nozzle increased deposition approximately eight-fold and 24-fold, respectively, onto the spherical and the planar targets. The ratios of charge-to-mass collected on all targets were unexpectedly found to exceed values calculated for the airborne charged-droplet cloud, indicating a possible contact-discharge during elastic collision of conductive droplets at the target.     

A biologically constrained architecture for developmental learning of eye–head gaze control on a humanoid robot

In this paper we describe a biologically constrained architecture for developmental learning of eye–head gaze control on an iCub robot. In contrast to other computational implementations, the developmental approach aims to acquire sensorimotor competence through growth processes modelled on data and theory from infant psychology. Constraints help shape learning in infancy by limiting the complexity of interactions between the body and environment, and we use this idea to produce efficient, effective learning in autonomous robots. Our architecture is based on current thinking surrounding the gaze mechanism, and experimentally derived models of stereotypical eye–head gaze contributions. It is built using our proven constraint-based field-mapping approach. We identify stages in the development of infant gaze control, and propose a framework of artificial constraints to shape learning on the robot in a similar manner. We demonstrate the impact these constraints have on learning, and the resulting ability of the robot to make controlled gaze shifts.     

Position estimation using ultra-wideband time difference of arrival measurements

Positioning enables many applications such as emergency services, target identification and tracking, health monitoring and geographic routing and so on. Time difference of arrival (TDOA) ranges measured using ultra-wideband signals are used in the position estimation process. A TDOA error-minimising localisation method has been proposed to estimate the locations of blind nodes and its performance is investigated in both LOS and NLOS propagations. Theoretical lower bound on the variance of the blind node positions has also been derived for the LOS situation.