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.

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.

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.

Ecology - Is coral bleaching really adaptive?

From an experiment in which corals are transplanted between two depths on a Panamanian coral reef, Baker1 infers that bleaching may sometimes help reef corals to survive environmental change. Although Baker's results hint at further mechanisms by which reef-building corals may acclimatize to changing light conditions, we do not consider that the evidence supports his inference.

Modeling the optical constants of solids using acceptance-probability-controlled simulated annealing with an adaptive move generation procedure

The acceptance-probability-controlled simulated annealing with an adaptive move generation procedure, an optimization technique derived from the simulated annealing algorithm, is presented. The adaptive move generation procedure was compared against the random move generation procedure on seven multiminima test functions, as well as on the synthetic data, resembling the optical constants of a metal. In all cases the algorithm proved to have faster convergence and superior escaping from local minima. This algorithm was then applied to fit the model dielectric function to data for platinum and aluminum.

In situ apoptosis of adaptive immune cells and the cellular escape of rabies virus in CNS from patients with human rabies transmitted by Desmodus rotundus

The aim of the current study was to investigate the apoptosis of neurons, astrocytes and immune cells from human patients that were infected with rabies virus by vampire bats bite. Apoptotic neurons were identified by their morphology and immune cells were identified using double immunostaining. There were very few apoptotic neurons present in infected tissue samples, but there was an increase of apoptotic infiltrating CD4+ and TCD8+ adaptive immune cells in the rabies infected tissue. No apoptosis was present in NK, macrophage and astrocytes. The dissemination of the human rabies virus within an infected host may be mediated by viral escape of the virus from an infected cell and may involve an anti-apoptotic mechanism, which does not kill the neuron or pro-apoptosis of TCD4+ and TCD8+ lymphocytes and which allows for increased proliferation of the virus within the CNS by attenuation of the adaptive immune response. (C) 2011 Elsevier B.V. All rights reserved.

A description of adaptive and maladaptive behaviour in children and adolescents with Cri-du-chat syndrome

Background Psychological tests can be useful to record adaptive and maladaptive behaviours of children with intellectual disability. The objective of this study was to describe the adaptive and maladaptive behaviour of children and adolescents with Cri-du-chat syndrome. Methods The sample consisted of 10 children and adolescents with Cri-du-chat syndrome (mean chronological age = 11.3 years, mean mental age = 18 months). The developmental quotient was calculated through the Psychoeducational Profile - Revised. An observational protocol was used to record adaptive and maladaptive behaviours. Results The number of maladaptive behaviours observed was different among participants. However, all of them had high rates of adaptive behaviours, such as rule-following. Conclusions These results, though preliminary, justify that we continue to think about the need for psychoeducational interventions aimed at stimulating the repertoire of adaptive behaviours, in people with Cri-du-chat syndrome.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

A Dynamical Modeling to Study the Adaptive Immune System and the Influence of Antibodies in the Immune Memory

Immunological systems have been an abundant inspiration to contemporary computer scientists. Problem solving strategies, stemming from known immune system phenomena, have been successfully applied to chall enging problems of modem computing. Simulation systems and mathematical modeling are also beginning use to answer more complex immunological questions as immune memory process and duration of vaccines, where the regulation mechanisms are not still known sufficiently (Lundegaard, Lund, Kesmir, Brunak, Nielsen, 2007). In this article we studied in machina a approach to simulate the process of antigenic mutation and its implications for the process of memory. Our results have suggested that the durability of the immune memory is affected by the process of antigenic mutation.and by populations of soluble antibodies in the blood. The results also strongly suggest that the decrease of the production of antibodies favors the global maintenance of immune memory.