Quantifying the benefits of enhanced filter selectivity

Today's mobile communications market is very competitive, with wireless service providers making every effort to improve the performance of their network to retain subscribers. Coupled with the proliferation of radio-frequency signals in the environment due to the growth of all forms of wireless communication, this leads to a very challenging task - namely, to provide ubiquitous high-quality service in spite of ever-increasing interference levels. One of the tools at the disposal of the network operator to provide such service is a cryogenically cooled receiver front end for base stations, wherein each receive path consists of a high-temperature superconducting (HTS) bandpass filter followed by a cryogenically cooled low-noise amplifier. There are two primary benefits achieved by the use of this front end. The first is improved receiver sensitivity through the reduction of electrical noise generated by the front end itself. The second is the significant reduction in the effects of out-of-band interference through the highly selective filtering made possible by the use of HTS materials. While this paper addresses both receiver-sensitivity and filter-selectivity benefits, the focus is on improved out-of-band interference rejection through enhanced filter selectivity.     

Glyconanoparticle–DNA Interactions: An Atomic Force Microscopy Study

Glyconanoparticles which present carbohydrate and amino groups motifs at their surface were produced. These particles were highly stable and soluble in aqueous solutions. The presence of the carbohydrate groups also allowed the inclusion of more strongly binding groups, without affecting solubility. The binding of a model DNA, plasmid by these nanoparticles was studied by atomic force microscopy, transmission electron microscopy, and gel electrophoresis. Significant differences between the nanoparticles based on their affinities for the DNA were found, with implications for their potential use as nonviral gene delivery agents.     

On one boundary-value problem for the Laplace equation

We have derived a Fredholm-type equation of the second kind for a directional derivative problem arising in the stationary theory of heat conduction. One result of Ya. B. Lopatinskii has been refined. __________ Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 80, No. 2, pp. 197–200, March–April, 2007.     

Kernel Spectral Matched Filter for Hyperspectral Imagery

In this paper a kernel-based nonlinear spectral matched filter is introduced for target detection in hyperspectral imagery, which is implemented by using the ideas in kernel-based learning theory. A spectral matched filter is defined in a feature space of high dimensionality, which is implicitly generated by a nonlinear mapping associated with a kernel function. A kernel version of the matched filter is derived by expressing the spectral matched filter in terms of the vector dot products form and replacing each dot product with a kernel function using the so called kernel trick property of the Mercer kernels. The proposed kernel spectral matched filter is equivalent to a nonlinear matched filter in the original input space, which is capable of generating nonlinear decision boundaries. The kernel version of the linear spectral matched filter is implemented and simulation results on hyperspectral imagery show that the kernel spectral matched filter outperforms the conventional linear matched filter.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Models in thermoluminescence

The aim of this paper is to give a review of the main models of thermoluminescence, from the most simple postulated by Randal and Wilkins in 1945. After that, a computer simulation emphasizes some problems relative to the use of the models to describe the behaviour of the thermoluminescent glow curve. Some suggestions are also given for obtaining a correct interpretation from the experimental data.     

The effect of home storage conditions and packaging materials on the quality of frozen green beans

Home storage is the final step of the frozen foods distribution chain, and little is known on how it affects the products quality. The present research describes frozen green beans (Phaseolus vulgaris, L.) quality retention profile during the recommended ‘star marking’ system dates, at the storage temperatures of +5, −6, −12 and −18 °C (along 1, 4, 14 and 60 days, respectively).

The quality profile was assessed by a simulation system. Simulations were set by a response surface methodology to access the effect of different packaging materials (thermal conductivities and thickness), surface heat transfer coefficient, and refrigerator dynamics (effect of refrigeration cycles at the different storage temperatures) on the average retentions of Ascorbic Acid, total vitamin C, colour and flavour.

Green beans quality losses along frozen storage are significantly influenced by temperature, refrigerator dynamics and kinetic properties. Quality is also highly dependent on packaging materials thermal insulation (e.g. at temperatures above the melting point). Temperature cycles inside frozen chambers have a long term effect, and at the higher storage temperatures (e.g. T>−6 °C) are detrimental to frozen green beans quality after shorter periods.