Emission of electrons from the ground and first excited states of self-organized InAs/GaAs quantum dot structures

Capacitance- and conductance-voltage studies have been carried out on Schottky barrier structures containing a sheet of self-organized InAs quantum dots. The dots are formed in GaAs n-type matrices after the deposition of four monolayers of InAs. Quasi-static analysis of capacitance-voltage measurements indicates that there are at least two filled electron levels in the quantum dots, located 60 and 140 meV below the GaAs conduction band edge. The conductance of the structure depends on the balance between measurement frequency and the thermionic emission rate of carriers from the quantum dots. An investigation of the temperature-dependent conductance at different frequencies as a function of the reverse bias allows us to study separately the electron emission rates from the ground and first excited levels in the quantum dots. We estimate that the electron escape times from both levels of the quantum dots become comparable at room temperature and equal to about 100 ps.     

Anti-aliasing weighting functions for single-slice helical CT

Spatially variant longitudinal aliasing plagues most volumes reconstructed from single-slice helical computed tomography data, and its presence can degrade resolution and distort image structures. We have recently developed a Fourier-based approach to longitudinal interpolation in helical computed tomography that can, for scans performed at pitch 1 or lower, essentially eliminate this longitudinal aliasing by exploiting a generalization of the Whittaker-Shannon sampling theorem whose conditions are satisfied by the interlaced pairs of direct and complementary longitudinal samples. However, the algorithm is computationally intensive and cannot be pipelined. In this paper, we address this shortcoming by deriving two spatial-domain, projection-data weighting functions that approximate the application of the Fourier-based approach, and preserve its aliasing suppression properties to some degree, while allowing for a pipelined implementation. The first approach, which we call simply 180AA, for anti-aliasing, is a direct spatial-domain approximation of the 180FT approach. The second approach, which we call 180BSP, is based on an approximate generalized interpolation approach making use of B-splines. Studies of aliasing and resolution properties in reconstructions from simulated data indicate that while the 180AA and 180BSP approaches do not perfectly replicate the favorable aliasing suppression and resolution properties of the 180FT approach, they do represent an improvement over the clinically standard 180LI approach on these fronts.     

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.     

A high-level application using belief functions for exchanging and managing uncertain events on the road in vehicular ad hoc networks

This article introduces a high-level system using belief functions for exchanging and managing imperfect information about events on the road in vehicular ad hoc networks. The main purpose of this application is to provide the most reliable information for the driver from multiple messages received informing the driver about events on the roads. This system and some variants are tested using a MATLAB? simulator. An implementation with Android smartphones using a Bluetooth technology to exchange the messages is also introduced.     

On‐Demand Wrinkling Patterns in Thin Metal Films Generated from Self‐Assembling Liquid Crystals

In this work, a new, universal method is described that uses the photopatterning of liquid crystals, which is accurately translated into a controlled, intricately wrinkled metal surface. Remarkably, the patterns have an oscillation in amplitude of the wrinkles. This rapid method allows generation of intricate multidomain patterns and continuous circular structures, including azimuthal, radial, and even higher complexity arrangements as examples. These wrinkled gold surfaces are also strikingly visual, which is interesting for applications ranging from diffractive elements to fine jewelry.     

Fast quasi-flat zones filtering using area threshold and region merging

Quasi-flat zones are morphological operators which segment the image into homogeneous regions according to certain criteria. They are used as an image simplification tool or an image segmentation pre-processing, but they induced a very important oversegmentation. Several filtering methods have been proposed to deal with this issue but they suffer from different drawbacks, e.g., loss of quality or edge deformation. In this article, we propose a new method based on existing approaches which achieves better or similar results than existing approaches, does not suffer from their drawbacks and requires less computation time. It consists of two successive steps. First, small quasi-flat zones are removed according to a minimal area threshold. They are then filled through the growth of remaining zones.     

Micrometer‐Scale Porous Buckling Shell Actuators Based on Liquid Crystal Networks

Micrometer‐scale liquid crystal network (LCN) actuators have potential for application areas like biomedical systems, soft robotics, and microfluidics. To fully harness their power, a diversification in production methods is called for, targeting unconventional shapes and complex actuation modes. Crucial for controlling LCN actuation is the combination of macroscopic shape and molecular‐scale alignment in the ground state, the latter becoming particularly challenging when the desired shape is more complex than a flat sheet. Here, one‐step processing of an LCN precursor material in a glass capillary microfluidic set‐up to mold it into thin shells is used, which are stretched by osmosis to reach a diameter of a few hundred micrometers and thickness on the order of a micrometer, before they are UV crosslinked into an LCN. The shells exhibit radial alignment of the director field and the surface is porous, with pore size that is tunable via the osmosis time. The LCN shells actuate reversibly upon heating and cooling. The decrease in order parameter upon heating induces a reduction in thickness and expansion of surface area of the shells that triggers continuous buckling in multiple locations. Such buckling porous shells are interesting as soft cargo carriers with capacity for autonomous cargo release.     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

A plane-polar near-field to far-field transformation with the fast Hankel transform method

It is known that a direct radial integration, used to compute the far-field from uniformly spaced plane-polar near-field measurements requires the evaluation of a large amount of Bessel functions and hence CPU time. Up to 1985 only unequally spaced fast Hankel algorithms were available. Hansen [3] developed an algorithm that was usable for equally spaced measurements points, but only for order zero. His theory is generalised in this paper and applied to a plane-polar near-field to far-field transformation.     

Moisture sorption study on Nigerian foods: Kuka

Kuka is an important vegetable in the Nigerian food chain. The moisture sorption characteristics of the vegetable studied at 34, 37 and 45°C between a_w 0.10–0.96, revealed a BET type II behaviour. The Kuka exhibited hysteresis and an increase in EMC with increase in a_w and decrease in temperature. Four sorption models (Oswin, Halsey, Kuhn, and GAB) were studied and the Oswin model was the most suitable. The constants in the Oswin model and GAB monolayer moisture contents were obtained and found to be temperature-dependent. Heats of sorption were greater for desorption than adsorption and in either mode, they reduced with an increase in moisture content. An exponential equation was obtained to relate heat of sorption with moisture content.