Education in Human Rights: Reflections on Power, Violence and Authority in the School

This article explores human rights and education based on an intervention experience conducted in three schools located in Sao Paulo City, which had as its main goal a substantial reduction in violence (2004-2005). The guideline was that education should be considered a basic human right, taking into consideration the power and authority relations that exist within this institution. What are the problems that we face, nowadays, to consider education as a human right, in the difficult Brazilian history? Is it possible to think about some kind of democratic authority within the school, when our vision of authority is linked to despotic leaders, or even when there is no space for any authority? How does this discussion associate with the violence in our daily life in school? These are some of the questions included in the debate proposed by this article.

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

What's scene and not seen: Influences of movement and task upon what we see

Studies concerning the processing of natural scenes using eye movement equipment have revealed that observers retain surprisingly little information from one fixation to the next. Other studies, in which fixation remained constant while elements within the scene were changed, have shown that, even without refixation, objects within a scene are surprisingly poorly represented. Although this effect has been studied in some detail in static scenes, there has been relatively little work on scenes as we would normally experience them, namely dynamic and ever changing. This paper describes a comparable form of change blindness in dynamic scenes, in which detection is performed in the presence of simulated observer motion. The study also describes how change blindness is affected by the manner in which the observer interacts with the environment, by comparing detection performance of an observer as the passenger or driver of a car. The experiments show that observer motion reduces the detection of orientation and location changes, and that the task of driving causes a concentration of object analysis on or near the line of motion, relative to passive viewing of the same scene.

It's all very well, in theory: Theoretical perspectives and their applications in contemporary pedagogical research

Current debates about educational theory are concerned with the relationship between knowledge and power and thereby issues such as who possesses a truth and how have they arrived at it, what questions are important to ask, and how should they best be answered. As such, these debates revolve around questions of preferred, appropriate, and useful theoretical perspectives. This paper overviews the key theoretical perspectives that are currently used in physical education pedagogy research and considers how these inform the questions we ask and shapes the conduct of research. It also addresses what is contested with respect to these perspectives. The paper concludes with some cautions about allegiances to and use of theories in line with concerns for the applicability of educational research to pressing social issues.

Calculation of line integrals in boundary integral methods

We propose quadrature rules for the approximation of line integrals possessing logarithmic singularities and show their convergence. In some instances a superconvergence rate is demonstrated.

Wolbachia infections are distributed throughout insect somatic and germ line tissues

Wolbachia are intracellular microorganisms that form maternally-inherited infections within numerous arthropod species. These bacteria have drawn much attention, due in part to the reproductive alterations that they induce in their hosts including cytoplasmic incompatibility (CI), feminization and parthenogenesis. Although Wolbachia's presence within insect reproductive tissues has been well described, relatively few studies have examined the extent to which Wolbachia infects other tissues. We have examined Wolbachia tissue tropism in a number of representative insect hosts by western blot, dot blot hybridization and diagnostic PCR. Results from these studies indicate that Wolbachia are much more widely distributed in host tissues than previously appreciated. Furthermore, the distribution of Wolbachia in somatic tissues varied between different Wolbachia/host associations. Some associations showed Wolbachia disseminated throughout most tissues while others appeared to be much more restricted, being predominantly limited to the reproductive tissues. We discuss the relevance of these infection patterns to the evolution of Wolbachia/host symbioses and to potential applied uses of Wolbachia.

In vitro cultivation of Wolbachia pipientis in an Aedes albopictus cell line

A continuous cell line, Aa23, was established from eggs of a strain of the Asian tiger mosquito, Aedes albopictus, naturally infected with the intracellular symbiont Wolbachia pipientis. The resulting cell line was shown to be persistently infected with the bacterial endosymbiont. Treatment with antibiotics cured the cells of the infection. In the course of establishing this cell line it was noticed that RFLPs in the PCR products of two Wolbachia genes from the parental mosquitoes were fixed in the infected cell line. This indicates that the mosquito host was naturally superinfected with different Wolbachia strains, whereas the infected cell line derived from these mosquitoes only contained one of the original Wolbachia strains. The development of anin vitroculture system for this fastidious microorganism should facilitate molecular analysis of the reproduction distorting phenotypes it induces in natural arthropod hosts.

A power system control scheme based on security visualisation in parameter space

Power system real time security assessment is one of the fundamental modules of the electricity markets. Typically, when a contingency occurs, it is required that security assessment and enhancement module shall be ready for action within about 20 minutes’ time to meet the real time requirement. The recent California black out again highlighted the importance of system security. This paper proposed an approach for power system security assessment and enhancement based on the information provided from the pre-defined system parameter space. The proposed scheme opens up an efficient way for real time security assessment and enhancement in a competitive electricity market for single contingency case

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Specific PCR based detection of Phytophthora medicaginis using the intergenic spacer region of the ribosomal DNA

A technique based on the polymerase chain reaction (PCR) for the specific detection of Phytophthora medicaginis was developed using nucleotide sequence information of the ribosomal DNA (rDNA) regions. The complete IGS 2 region between the 5 S gene of one rDNA repeat and the small subunit of the adjacent repeat was sequenced for P. medicaginis and related species. The entire nucleotide sequence length of the IGS 2 of P. medicaginis was 3566 bp. A pair of oligonucleotide primers (PPED04 and PPED05), which allowed amplification of a specific fragment (364 bp) within the IGS 2 of P. medicaginis using the PCR, was designed. Specific amplification of this fragment from P. medicaginis was highly sensitive, detecting template DNA as low as 4 ng and in a host-pathogen DNA ratio of 1000000:1. Specific PCR amplification using PPED04 and PPED05 was successful in detecting P. medicaginis in lucerne stems infected under glasshouse conditions and field infected lucerne roots. The procedures developed in this work have application to improved identification and detection of a wide range of Phytophthora spp. in plants and soil.

Improved one-step solid-phase extraction method for morphine, morphine-3-glucuronide, and morphine-6-glucuronide from plasma and quantitation using high-performance liquid chromatography with electrochemical detection

This communication describes an improved one-step solid-phase extraction method for the recovery of morphine (M), morphine-3-glucuronide (M3G), and morphine-6-glucuronide (M6G) from human plasma with reduced coextraction of endogenous plasma constituents, compared to that of the authors' previously reported method. The magnitude of the peak caused by endogenous plasma components in the chromatogram that eluted immediately before the retention time of M3G has been reduced (similar to 80%) significantly (p < 0.01) while achieving high extraction efficiencies for the compounds of interest, viz morphine, M6G, and M3G (93.8 +/- 2.5, 91.7 +/- 1.7, and 93.1 +/- 2.2%, respectively). Furthermore, when the improved solid-phase extraction method was used, the extraction cartridge-derived late-eluting peak (retention time 90 to 100 minutes) reported in our previous method, was no longer present in the plasma extracts. Therefore the combined effect of reducing the recovery of the endogenous components of plasma that chromatographed just before the retention time of M3G and the removal of the late-eluting, extraction cartridge-derived peak has resulted in a decrease in the chromatographic run-time to 20 minutes, thereby increasing the sample throughput by up to 100%.

Sensitive detection of sodium in a flame using parametric four-wave mixing and seeded parametric four-wave mixing

Two-photon resonant parametric four-wave mixing and a newly developed variant called seeded parametric four-wave mixing are used to detect trace quantities of sodium in a flame. Both techniques are simple, requiring only a single laser to generate a signal beam at a different wavelength which propagates collinearly with the pump beam, allowing efficient signal recovery. A comparison of the two techniques reveals that seeded parametric four-wave mixing is more than two orders of magnitude more sensitive than parametric four-wave mixing, with an estimated detection sensitivity of 5 x 10(9) atoms/cm(3). Seeded parametric four-wave mixing is achieved by cascading two parametric four-wave mixing media such that one of the parametric fields generated in the first high-density medium is then used to seed the same four-wave mixing process in a second medium in order to increase the four-wave mixing gain. The behavior of this seeded parametric four-wave mixing is described using semiclassical perturbation theory. A simplified small-signal theory is found to model most of the data satisfactorily. However, an anomalous saturationlike behavior is observed in the large signal regime. The full perturbation treatment, which includes the competition between two different four-wave mixing processes coupled via the signal field, accounts for this apparently anomalous behavior.