Two-dimensional profiles of fumonisin B1 production by Fusarium moniliforme and Fusarium proliferatum in relation to environmental factors and potential for modelling toxin formation in maize grain

This study has examined in detail the effect of temperature (7-37 degrees C) and water availability (water activity, a(w), 0.89-0.97) on fumonisin B1 (FB1) production by an isolate of Fusarium moniliforme and F. proliferatum on irradiated maize grain after incubation for 28 days. The optimum conditions for F. moniliforme and F. proliferatum were 30 degrees C at 0.97 a(w) and 15 degrees C at 0.97 a(w), respectively. The maximum concentrations were 2861 mg kg(-1) and 17,628 mg kg(-1) dry wt. maize grain, respectively. At marginal a(w)/temperature conditions for growth (e.g. 0.89-0.91 a(w)) no FB1 was detected (<0.1 mg kg(-1)). A high variability was found between replicates for F. moniliforme, but not for F. proliferatum. These data were used to construct two-dimensional diagrams of all the a(w) x temperature conditions favourable for FB1 production for the first time. The data were also subjected to a polynomical regression, which demonstrated that there was a very good fit for the 15-30 degrees C range of temperature and at 0.97 a(w). However, at marginal environmental conditions this was not possible. This suggests that it may be possible to predict within a limited environmental range the potential for significant FB1 production.     

Image modeling based on a 2-D stochastic subspace system identification algorithm

Fitting a causal dynamic model to an image is a fundamental problem in image processing, pattern recognition, and computer vision. In image restoration, for instance, the goal is to recover an estimate of the true image, preferably in the form of a parametric model, given an image that has been degraded by a combination of blur and additive white Gaussian noise. In texture analysis, on the other hand, a model of a particular texture image can serve as a tool for simulating texture patterns. Finally, in image enhancement one computes a model of the true image and the residuals between the image and the modeled image can be interpreted as the result of applying a de-noising filter. There are numerous other applications within the field of image processing that require a causal dynamic model. Such is the case in scene analysis, machined parts inspection, and biometric analysis, to name only a few. There are many types of causal dynamic models that have been proposed in the literature, among which the autoregressive moving average and state-space models (i.e., Kalman filter) are the most commonly used. In this paper we introduce a 2-D stochastic state-space system identification algorithm for fitting a quarter plane causal dynamic Roesser model to an image. The algorithm constructs a causal, recursive, and separable-in-denominator 2-D Kalman filter model. The algorithm is tested with three real images and the quality of the estimated images are assessed.     

Accurate Gate Impedance Determination on Ultraleaky MOSFETs by Fitting to a Three-Lumped-Parameter Model atFrequencies From DC to RF

We present an experimental methodology that demonstrates the suitability of the conventional three-lumped- parameter model for gate impedance of MOSFET devices at frequencies from dc to the gigahertz range, which permits accurate extraction of model parameters. The parasitic effects at a high frequency are minimized by using radio frequency techniques (i.e., short return paths and de-embedding structures), whereas a robust parameter extraction algorithm overcomes possible instrument inaccuracies. When combined, these allow simultaneous extraction of all three parameters (i.e., C_gate, R_DT and R_series) from the model. The technique is applied to conventional SiO₂ -based MOSFET devices and to ultraleaky HfO₂ devices with aggressively scaled gate dielectric thickness.     

FCA-ESPRIT: a closed-form 2-D angle estimation algorithm for filledcircular arrays with arbitrary sampling lattices

This article addresses the simultaneous estimation of the azimuth and elevation angles of multiple co-channel signals incident upon an array of antennas. A new closed-form algorithm that is applicable with filled circular arrays (FCAs) is presented. The algorithm, which is called FCA-ESPRIT, is applicable with any FCA geometry, e.g., FCAs constructed using rectangular, hexagonal, polar, or random sampling lattices. The only constraint imposed on the FCA geometry is that the spacing between adjacent sensors should be half a wavelength or less on average across the entire aperture. The algorithm provides automatically paired azimuth and elevation angle estimates by solving a set of ESPRIT-like equations wherein the unknowns have the form sin(&thetas; _i)e^jφ(i) (where &thetas;_i and φ _i are the elevation and azimuth angles of the ith source, respectively). The algorithm provides arrival angle estimates via a closed-form procedure-it does not require computationally expensive search or optimization procedures     

Nonlinear distortion generated by DSF-based optical-phase conjugators in analog optical systems

In this paper, the nonlinear distortion induced by dispersion-shifted-fiber-based optical-phase conjugators (OPCs) in intensity-modulated subcarrier multiplexing optical systems is evaluated. In this study, it is shown that the nonlinear distortion mainly arises from the four-wave mixing (FWM) process during the phase conjugation, although there also exists influences from other nonlinear effects. Closed expressions for calculating the second- and third-order harmonic distortions due to FWM, self-phase modulation, cross-phase modulation and group-velocity dispersion effects in the dispersion-shifted-fiber-based OPC are also reported for the first time. The influence of several system design parameters, such as the optical modulation index, the number of channels, the input optical powers, and the effective area of the dispersion-shifted fiber on the compensation of fiber-induced nonlinear distortions employing the optical-phase conjugation technique, is considered.     

PbS/CdS/ZnS Quantum Dots: A Multifunctional Platform for In Vivo Near‐Infrared Low‐Dose Fluorescence Imaging

Over the past decade, near‐infrared (NIR)‐emitting nanoparticles have increasingly been investigated in biomedical research for use as fluorescent imaging probes. Here, high‐quality water‐dispersible core/shell/shell PbS/CdS/ZnS quantum dots (hereafter QDs) as NIR imaging probes fabricated through a rapid, cost‐effective microwave‐assisted cation exchange procedure are reported. These QDs have proven to be water dispersible, stable, and are expected to be nontoxic, resulting from the growth of an outer ZnS shell and the simultaneous surface functionalization with mercaptopropionic acid ligands. Care is taken to design the emission wavelength of the QDs probe lying within the second biological window (1000–1350 nm), which leads to higher penetration depths because of the low extinction coefficient of biological tissues in this spectral range. Furthermore, their intense fluorescence emission enables to follow the real‐time evolution of QD biodistribution among different organs of living mice, after low‐dose intravenous administration. In this paper, QD platform has proven to be capable (ex vivo and in vitro) of high‐resolution thermal sensing in the physiological temperature range. The investigation, together with the lack of noticeable toxicity from these PbS/CdS/ZnS QDs after preliminary studies, paves the way for their use as outstanding multifunctional probes both for in vitro and in vivo applications in biomedicine.     

Autonomous and teleoperation control of a mobile robot

The present work proposes an autonomous tracking control system and a control structure to combine autonomous and teleoperation commands in a bicycle-type mobile robot. This compounded operation renders great flexibility to the control system of the mobile robot. For autonomous operation, a simple tracking controller that includes compensation of the robot dynamics is developed. This tracking control system is proved to be stable in the sense that it asymptotically reaches the tracking objective. Teleoperation with visual access to the robot’s workspace is integrated via a joystick with the autonomous operation of the robot. Simulations and experimental results on a prototype robot show the feasibility and performance of the proposed control system.     

Hybrid higher-order statistics learning in multiuser detection

In this paper, we explore the significance of second- and higher-order statistics learning in communication systems. The final goal in spread-spectrum communication systems is to receive a signal of interest completely free from interference caused by other concurrent signals. To achieve this end, we exploit the structure of the interference by designing second-order statistics detectors, such as the minimum square error, in conjunction with higher-order statistics (HOS) techniques, such as the blind source separation (BSS). This hybrid higher-order statistics (HyHOS) approach enables us to alleviate BSS algorithms of one of their main problems, that is, their sensitiveness to high levels of noise. In addition, we benefit from remarkable properties of BSS in learning such as fast learning (superefficiency) and independence of the initial settings of the problem (equivariance). We successfully applied the results of this approach to the design of multiuser detectors in code-division multiple access channels.     

Low-power voltage-controlled oscillators in 90-nm CMOS using high-quality thin-film postprocessed inductors

Wafer-level packaging (WLP) technology offers novel opportunities for the realization of high-quality on-chip passives needed in RF front-ends. This paper demonstrates a thin-film WLP technology on top of a 90-nm RF CMOS process with one 15-GHz and two low-power 5-GHz voltage-controlled oscillators (VCOs) using a high-quality WLP or above-IC inductor. The 5-GHz VCOs have a power consumption of 0.33 mW and a phase noise of -115 dBc/Hz and -111 dBc/Hz at 1-MHz offset, respectively, and the 15-GHz VCO has a phase noise of -105 dBc/Hz at 1-MHz offset with a power consumption of 2.76 mW.