Adaptive Carrier Tracking for Mars to Earth Communications During Entry, Descent, and Landing

We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.

Transient and Steady-State Analysis of the Affine Combination of Two Adaptive Filters

In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.

The AdapLib Library for Execution of Adaptive Devices: Architecture and Use

In this paper it is presented the theoretical background, the architecture (using the ""4+1"" model), and the use of the library for execution of adaptive devices, AdapLib. This library was created seeking to be accurate to the adaptive devices theory, and to allow its easy extension considering the specific details of solutions that employ this kind of device. As an example, it is presented a case study in which the library was used to create a proof of concept to monitor and diagnose problems in an online news portal.

Interference of raw milk autochthonous microbiota on the performance of conventional methodologies for Listeria monocytogenes and Salmonella spp. detection

Pathogen detection in foods by reliable methodologies is very important to guarantee microbilogical safety. However, peculiar characteristics of certain foods, such as autochthonous microbiota, can directly influence pathogen development and detection. With the objective of verifying the performance of the official analytical methodologies for the isolation of Listeria monocytogenes and Salmonella in milk, different concentrations of these pathogens were inoculated in raw milk treatments with different levels of mesophilic aerobes, and then submitted to the traditional isolation procedures for the inoculated pathogens. Listeria monocytogenes was inoculated at the range of 0.2-5.2 log CFU/mL in treatments with 1.8-8.2 log CFU/mL. Salmonella Enteritidis was inoculated at 0.9-3.9 log CFU/mL in treatments with 3.0-8.2 log CFU/mL. The results indicated that recovery was not possible or was more difficult in the treatments with high counts of mesophilic aerobes and low levels of the pathogens, indicating interference of raw milk autochthonous microbiota. This interference was more evident for L. monocytogenes, once the pathogen recovery was not possible in treatments with mesophilic aerobes up to 4.0 log CFU/mL and inoculum under 2.0 log CFU/mL. For S. Enteritidis the interference appeared to be more non-specific. (C) 2007 Elsevier GmbH. All rights reserved.

Listeria monocytogenes and Salmonella spp. in raw milk produced in Brazil: Occurrence and interference of indigenous microbiota in their isolation and development

This study aimed to verify the occurrence of Listeria monocytogenes and Salmonella spp. in raw milk produced in Brazil. On account of the poor microbiological quality of this product, possible interference from the indigenous microbiota in these pathogens was also evaluated. Two-hundred and ten raw milk samples were collected in four important milk-producing areas in Brazil, tested for L. monocytogenes and Salmonella spp. presence, and for enumeration of indicator microorganisms: mesophilic aerobes, total coliforms and Escherichia coli. The interference of the indigenous microbiota in the isolation procedures was also tested, as well the frequency of naturally occurring raw milk strains with antagonistic activity against both pathogens. The pathogens were not isolated in any raw milk sample, but poor microbiological quality was confirmed by the high levels of indicator microorganisms. When present at high levels, the indigenous microbiota generated an evident interference in the methodologies of L. monocytogenes and Salmonella spp. isolation, mainly when the pathogens appeared at low levels. Three-hundred and sixty raw milk strains were tested for antagonistic activity against both pathogens, and 91 (25.3%) showed inhibitory activity against L. monocytogenes and 33 (9.2%) against Salmonella spp. The majority of the antagonistic strains were identified as Lactic Acid Bacteria species, mainly Lactococcus lactis subsp. lactis and Enterococcus faecium, known by antimicrobial substance production.

Plasmodium vivax recombinant vaccine candidate AMA-1 plays an important role in adaptive immune response eliciting differentiation of dendritic cells

The Apical Membrane Antigen-1 (AMA-1) is a well-characterized and functionally important merozoite protein and is currently considered a major candidate antigen for a malaria vaccine. Previously, we showed that AMA-1 has an influence on cellular immune responses of malaria-naive subjects, resulting in an alternative activation of monocyte-derived dendritic cells and induction of a pro-inflammatory response by stimulated PBMCs. Although there is evidence, from human and animal malaria model systems that cell-mediated immunity may contribute to both protection and pathogenesis, the knowledge on cellular immune responses in vivax malaria and the factors that may regulate this immunity are poorly understood. In the current work, we describe the maturation of monocyte-derived dendritic cells of P. vivax naturally infected individuals and the effect of P. vivax vaccine candidate Pv-AMA-1 on the immune responses of the same donors. We show that malaria-infected subjects present modulation of DC maturation, demonstrated by a significant decrease in expression of antigen-presenting molecules (CD1a, HLA-ABC and HLA-DR), accessory molecules (CD40, CD80 and CD86) and Fc gamma RI (CD64) receptor (P <= 0.05). Furthermore, Pv-AMA-1 elicits an upregulation of CD1a and HLA-DR molecules on the surface of monocyte-derived dendritic cells (P=0.0356 and P=0.0196, respectively), and it is presented by AMA-1-stimulated DCs. A significant pro-inflammatory response elicited by Pv-AMA-1-pulsed PBMCs is also demonstrated, as determined by significant production of TNF-alpha, IL-12p40 and IFN-gamma (P <= 0.05). Our results suggest that Pv-AMA-1 may partially revert DC down-modulation observed in infected subjects, and exert an important role in the initiation of pro-inflammatory immunity that might contribute substantially to protection. (c) 2009 Elsevier Ltd. All rights reserved.

Interference of dexamethasone in the pulmonary cycle of Strongyloides venezuelensis in rats

The aim of this study was to investigate the interference of a daily treatment of dexamethasone in the pulmonary cycle of Strongyloides venezuelensis infection in rats. Three principal effects were found: 1) increased alveolar hemorrhagic inflammation provoked by the passage of larvae into alveolar spaces; 2) significant decrease of eosinophil and mast cell migration to the axial septum of the lungs; and 3) impaired formation of the reticular fiber network, interfering with granuloma organization. This study showed that the use of drugs with immunomodulatory actions, such as dexamethasone, in addition to interfering with the morbidity from the pulmonary cycle of S. venezuelensis infection, may contribute to showing the mechanisms involved in its pathogenesis.

A wavelet-based adaptive technique for adsorption problems involving steep gradients

A general, fast wavelet-based adaptive collocation method is formulated for heat and mass transfer problems involving a steep moving profile of the dependent variable. The technique of grid adaptation is based on sparse point representation (SPR). The method is applied and tested for the case of a gas–solid non-catalytic reaction in a porous solid at high Thiele modulus. Accurate and convergent steep profiles are obtained for Thiele modulus as large as 100 for the case of slab and found to match the analytical solution.

Interference in hyperbolic space

The interference in a phase space algorithm of Schleich and Wheeler [Nature 326, 574 (1987)] is extended to the hyperbolic space underlying the group SU(1,1). The extension involves introducing the notion of weighted areas. Analytic expressions for the asymptotic forms for overlaps between the eigenstates of the generators of su(1,1) thus obtained are found to be in excellent agreement with the numerical results.[S1050-2947(98)08602-8].

Creating proactive interference in immediate recall: Building a DOG from a DART, a MOP, and a FIG

Phonemic codes are accorded a privileged role in most current models of immediate serial recall, although their effects are apparent in short-term proactive interference (PI) effects as well. The present research looks at how assumptions concerning distributed representation and distributed storage involving both semantic and phonemic codes might be operationalized to produce PI in a short-term cued recall task. The four experiments reported here attempted to generate the phonemic characteristics of a nonrhyming, interfering foil from unrelated filler items in the same list. PI was observed when a rhyme of the foil was studied or when the three phonemes of the foil were distributed across three studied filler items. The results suggest that items in short-term memory are stored in terms of feature bundles and that all items are simultaneously available at retrieval.