Access and Affordability of Electricity in Developing Countries

A key objective of developing countries is to provide affordable access to modern energy services in order to support economic and social development. The paper presents a number of arguments for why and in which way energy access and affordability can play a key role in national development programs and in achieving the Millennium Development Goals. Approaches for measuring accessibility and affordability are presented, drawing on case studies of Bangladesh. Brazil, and South Africa, countries with different rates of electrification. Affordability of using electricity is examined in relation to the energy expenditure burden for households and time consumption. Conclusions focus on lessons learned and recommendations for implementing policies, instruments, and regulatory measures to tackle the challenge of affordability. (C) 2011 Elsevier Ltd. All rights reserved.

Indoors lead corrosion: Reassessing the role of formaldehyde

The present work is focused on the role of formaldehyde in indoors Pb corrosion, that is still a controversial issue. Pb coupons were exposed to the atmosphere produced by formaldehyde aqueous solutions (1% and 4% in volume) and corrosion was followed by Raman Microscopy. The compounds formed in both experiments were the same, but were not in agreement with previously reported results in the literature, that identified plumbonacrite, hidrocerussite and Pb oxide. The experiments here reported have clearly shown that formates are produced on Pb surfaces exposed to formaldehyde and that oxidants, such as H(2)O(2), are not necessary. Formaldehyde oxidation also occurs with powdered PbO in a controlled environment. The Raman spectra of the Pb formates are much more complex than the Pb(HCO(2))(2) spectrum and change when exposed to room conditions, by a slow reaction with CO(2), forming Pb carbonates (hidrocerussite and plumbonacrite mostly) and Pb(HCO(2))(2). Such spectral change may be responsible for the differences in terms of chemical composition of the corrosion layer when the data here reported is compared with the literature. Other factors that must be considered are the storage conditions (particularly relative humidity and CO(2) concentration) and time; the effect of metal composition cannot be discarded as it is well known that the presence of other metals can change significantly the Pb resistance to oxidation. (C) 2010 Elsevier B.V. All rights reserved.

Forest-related partnerships in Brazilian Amazonia: There is more to sustainable forest management than reduced impact logging

There is more to sustainable forest management than reduced impact logging. Partnerships between multiple actors are needed in order to create the institutional context for good forest governance and sustainable forest management and stimulate the necessary local community involvement. The idea behind this is that the parties would be able to achieve more jointly than on their own by combining assets, knowledge, skills and political power of actors at different levels of scale. This article aims to demonstrate by example the nature and variety of forest-related partnerships in Brazilian Amazonia. Based on the lessons learned from these cases and the authors` experience, the principal characteristics of successful partnerships are described, with a focus on political and socioeconomic aspects. These characteristics include fairly negotiated partnership objectives, the active involvement of the public sector as well as impartial brokers, equitable and cost-effective institutional arrangements, sufficient and equitably shared benefits for all the parties involved, addressing socioeconomic drawbacks, and taking measures to maintain sustainable exploitation levels. The authors argue that, in addition to product-oriented partnerships which focus on sustainable forest management, there is also a need for politically oriented partnerships based on civil society coalitions. The watchdog function of these politically oriented partnerships, their awareness-raising campaigns regarding detrimental policies and practices, and advocacy for good forest governance are essential for the creation of the appropriate legal and political framework for sustainable forest management. (C) 2008 Elsevier B.V. All rights reserved.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Multifractal regime transition in a modified minority game model

The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual minority game (MG) models do not exhibit multifractality, we study here one of its variants that does. We show that the nonsynchronous MG models in the nonergodic phase is multifractal and in this sense, together with other stylized facts, constitute a better modeling tool. Using the structure function (SF) approach we detected the stationary and the scaling range of the time series generated by the MG model and, from the linear (non-linear) behavior of the SF we identified the fractal (multifractal) regimes. Finally, using the wavelet transform modulus maxima (WTMM) technique we obtained its multifractal spectrum width for different dynamical regimes. (C) 2009 Elsevier Ltd. All rights reserved.

An opinion dynamics model for the diffusion of innovations

We study the dynamics of the adoption of new products by agents with continuous opinions and discrete actions (CODA). The model is such that the refusal in adopting a new idea or product is increasingly weighted by neighbor agents as evidence against the product. Under these rules, we study the distribution of adoption times and the final proportion of adopters in the population. We compare the cases where initial adopters are clustered to the case where they are randomly scattered around the social network and investigate small world effects on the final proportion of adopters. The model predicts a fat tailed distribution for late adopters which is verified by empirical data. (C) 2009 Elsevier B.V. All rights reserved.

Low dimensional behavior in three-dimensional coupled map lattices

The analysis of one-, two-, and three-dimensional coupled map lattices is here developed under a statistical and dynamical perspective. We show that the three-dimensional CML exhibits low dimensional behavior with long range correlation and the power spectrum follows 1/f noise. This approach leads to an integrated understanding of the most important properties of these universal models of spatiotemporal chaos. We perform a complete time series analysis of the model and investigate the dependence of the signal properties by change of dimension. (c) 2008 Elsevier Ltd. All rights reserved.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Homogenization in a thin domain with an oscillatory boundary

In this paper we analyze the behavior of the Laplace operator with Neumann boundary conditions in a thin domain of the type R(epsilon) = {(x(1), x(2)) is an element of R(2) vertical bar x(1) is an element of (0, 1), 0 < x(2) < epsilon G(x(1), x(1)/epsilon)} where the function G(x, y) is periodic in y of period L. Observe that the upper boundary of the thin domain presents a highly oscillatory behavior and, moreover, the height of the thin domain, the amplitude and period of the oscillations are all of the same order, given by the small parameter epsilon. (C) 2011 Elsevier Masson SAS. All rights reserved.

A Markovian model market-Akerlof`s lemons and the asymmetry of information

In this work we study an agent based model to investigate the role of asymmetric information degrees for market evolution. This model is quite simple and may be treated analytically since the consumers evaluate the quality of a certain good taking into account only the quality of the last good purchased plus her perceptive capacity beta. As a consequence, the system evolves according to a stationary Markov chain. The value of a good offered by the firms increases along with quality according to an exponent alpha, which is a measure of the technology. It incorporates all the technological capacity of the production systems such as education, scientific development and techniques that change the productivity rates. The technological level plays an important role to explain how the asymmetry of information may affect the market evolution in this model. We observe that, for high technological levels, the market can detect adverse selection. The model allows us to compute the maximum asymmetric information degree before the market collapses. Below this critical point the market evolves during a limited period of time and then dies out completely. When beta is closer to 1 (symmetric information), the market becomes more profitable for high quality goods, although high and low quality markets coexist. The maximum asymmetric information level is a consequence of an ergodicity breakdown in the process of quality evaluation. (C) 2011 Elsevier B.V. All rights reserved.

Use of Medical Subject Headings (MeSH) in Portuguese for categorizing web-based healthcare content

Introduction: Internet users are increasingly using the worldwide web to search for information relating to their health. This situation makes it necessary to create specialized tools capable of supporting users in their searches. Objective: To apply and compare strategies that were developed to investigate the use of the Portuguese version of Medical Subject Headings (MeSH) for constructing an automated classifier for Brazilian Portuguese-language web-based content within or outside of the field of healthcare, focusing on the lay public. Methods: 3658 Brazilian web pages were used to train the classifier and 606 Brazilian web pages were used to validate it. The strategies proposed were constructed using content-based vector methods for text classification, such that Naive Bayes was used for the task of classifying vector patterns with characteristics obtained through the proposed strategies. Results: A strategy named InDeCS was developed specifically to adapt MeSH for the problem that was put forward. This approach achieved better accuracy for this pattern classification task (0.94 sensitivity, specificity and area under the ROC curve). Conclusions: Because of the significant results achieved by InDeCS, this tool has been successfully applied to the Brazilian healthcare search portal known as Busca Saude. Furthermore, it could be shown that MeSH presents important results when used for the task of classifying web-based content focusing on the lay public. It was also possible to show from this study that MeSH was able to map out mutable non-deterministic characteristics of the web. (c) 2010 Elsevier Inc. All rights reserved.

Generic hyperbolicity of stationary solutions for a reaction-diffusion system

In this paper, we study the generic hyperbolicity of equilibria of a reaction-diffusion system with respect to nonlinear terms in the set of C(2)-functions equipped with the Whitney Topology. To accomplish this, we combine Baire`s Lemma and the usual Transversality Theorem. (C) 2010 Elsevier Ltd. All rights reserved.

Increasing trends of sleep complaints in the city of Sao Paulo, Brazil

Objective: The aim of this study was to compare the prevalence of sleep habits and complaints and to estimate the secular trends through three population-based surveys carried out in 1987, 1995, and 2007 in the general adult population of the city of Sao Paulo, Brazil. Methods: Surveys were performed using the same three-stage cluster-sampling technique in three consecutive decades to obtain representative samples of the inhabitants of Sao Paulo with respect to gender, age (20-80 years), and socio-economic status. Sample sizes were 1000 volunteers in 1987 and 1995 surveys and 1101 in a 2007 survey. In each survey, the UNIFESP Sleep Questionnaire was administered face-to-face in each household selected. Results: For 1987, 1995, and 2007, respectively, difficulty initiating sleep (weighted frequency %; 95% CI) [(13.9; 11.9-16.2), (19.15; 16.8-21.6), and (25.0; 22.5-27.8)], difficulty maintaining sleep [(15.8; 13.7-18.2), (27.6; 24.9-30.4), and (36.5; 33.5-39.5)], and early morning awakening [(10.6; 8.8-12.7), (14.2; 12.2-16.5), and (26.7; 24-29.6)] increased in the general population over time, mostly in women. Habitual snoring was the most commonly reported complaint across decades and was more prevalent in men. There was no statistically significant difference in snoring complaints between 1987 (21.5; 19.1-24.2) and 1995 (19.0; 16.7-21.6), but a significant increase was noted in 2007 (41.7; 38.6-44.8). Nightmares, bruxism, leg cramps, and somnambulism complaints were significantly higher in 2007 compared to 1987 and 1995. All were more frequent in women. Conclusions: This is the first study comparing sleep complaints in probabilistic population-based samples from the same metropolitan area, using the same methodology across three consecutive decades. Clear trends of increasing sleep complaints were observed, which increased faster between 1995 and 2007 than from 1987 to 1995. These secular trends should be considered a relevant public health issue and support the need for development of health care and educational strategies to supply the population`s increased need for information on sleep disorders and their consequences. (C) 2010 Elsevier B.V. All rights reserved.

Elderly online: Effects of a digital inclusion program in cognitive performance

There is little empirical data about the impact of digital inclusion on cognition among older adults. This paper aimed at investigating the effects of a digital inclusion program in the cognitive performance of older individuals who participated in a computer learning workshop named ""Idosos On-Line`` (Elderly Online). Forty-two aged individuals participated in the research study: 22 completed the computer training workshop and 20 constituted the control group. All subjects answered a sociodemographic questionnaire and completed the Addenbrooke`s cognitive examination, revised (ACE-R), which examines five cognitive domains: orientation and attention, memory, verbal fluency, language, and visuo-spatial skills. It was noted that the experimental group`s cognitive performance significantly improved after the program, particularly in the language and memory domains, when compared to the control group. These findings suggest that the acquisition of new knowledge and the use of a new tool, that makes it possible to access the Internet, may bring gains to cognition. (C) 2010 Elsevier Ireland Ltd. All rights reserved.