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.

Cytokine Signatures of Innate and Adaptive Immunity in 17DD Yellow Fever Vaccinated Children and Its Association With the Level of Neutralizing Antibody

Background. The live attenuated yellow fever (YF) vaccines have been available for decades and are considered highly effective and one of the safest vaccines worldwide. Methods. The impact of YF-17DD-antigens recall on cytokine profiles of YF-17DD-vaccinated children were characterized using short-term cultures of whole blood samples and single-cell flow cytometry. This study enrolled seroconverters and nonseroconverters after primovaccination (PV-PRNT(+) and PV-PRNT(-)), seroconverters after revaccination (RV-PRNT(+)), and unvaccinated volunteers (UV-PRNT(-)). Results. The analysis demonstrated in the PV-PRNT(+) group a balanced involvement of pro-inflammatory/regulatory adaptive immunity with a prominent participation of innate immunity pro-inflammatory events (IL-12(+) and TNF-alpha(+) NEU and MON). Using the PV-PRNT(+) cytokine signature as a reference profile, PV-PRNT(+) presented a striking lack of innate immunity proinflammatory response along with an increased adaptive regulatory profile (IL-4(+) CD4(+) T cells and IL-10(+) and IL-5(+) CD8(+) T cells). Conversely, the RV-PRNT(+) shifted the overall cytokine signatures toward an innate immunity pro-inflammatory profile and restored the adaptive regulatory response. Conclusions. The data demonstrated that the overall cytokine signature was associated with the levels of PRNT antibodies with a balanced innate/adaptive immunity with proinflammatory/regulatory profile as the hallmark of PV-PRNT(MEDIUM+), whereas a polarized regulatory response was observed in PV-PRNT(-) and a prominent proinflammatory signature was the characteristic of PV-PRNT(HIGH+).

Aspects of adaptive management of coastal wetlands: Case studies of processes, conservation, restoration, impacts and assessment

Coastal wetlands are dynamic and include the freshwater-intertidal interface. In many parts of the world such wetlands are under pressure from increasing human populations and from predicted sea-level rise. Their complexity and the limited knowledge of processes operating in these systems combine to make them a management challenge.Adaptive management is advocated for complex ecosystem management (Hackney 2000; Meretsky et al. 2000; Thom 2000;National Research Council 2003).Adaptive management identifies management aims,makes an inventory/environmental assessment,plans management actions, implements these, assesses outcomes, and provides feedback to iterate the process (Holling 1978;Walters and Holling 1990). This allows for a dynamic management system that is responsive to change. In the area of wetland management recent adaptive approaches are exemplified by Natuhara et al. (2004) for wild bird management, Bunch and Dudycha (2004) for a river system, Thom (2000) for restoration, and Quinn and Hanna (2003) for seasonal wetlands in California. There are many wetland habitats for which we currently have only rudimentary knowledge (Hackney 2000), emphasizing the need for good information as a prerequisite for effective management. The management framework must also provide a way to incorporate the best available science into management decisions and to use management outcomes as opportunities to improve scientific understanding and provide feedback to the decision system. Figure 9.1 shows a model developed by Anorov (2004) based on the process-response model of Maltby et al. (1994) that forms a framework for the science that underlies an adaptive management system in the wetland context.

A Comparison of Bayesian and Sampling Theory Inferences in a Probit Model

HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.

Effects of sampling opportunities on preference for adults with severe disabilities

A variable that appears to affect preference development is the exposure to a variety of options. Providing opportunities for systematically sampling different options is one procedure that can facilitate the development of preference, which is indicated by the consistency of selections. The purpose of this study was to evaluate the effects of providing sampling opportunities on the preference development for two adults with severe disabilities. Opportunities for sampling a variety of drink items were presented, followed by choice opportunities for selections at the site where sampling occurred and at a non-sampling site (a grocery store). Results show that the participants developed a definite response consistency in selections at both sites. Implications for sampling practices are discussed.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.