As técnicas NASVD e MNF e sua aplicação na redução de ruídos em dados gamaespectrométricos

A desintegração radioativa é um processo aleatório e a estimativa de todas as medidas associadas é governada por leis estatísticas. Os perfis de taxas de contagem são sempre "ruidosos" quando utilizados períodos curtos como um segundo para cada medida. Os filtros utilizados e posteriormente as correções feitas no processamento atual de dados gamaespectrométricos não são suficientes para remover ou diminuir, consideravelmente, o ruído oriundo do espectro. Dois métodos estatísticos que atuam diretamente nos dados coletados, isto é, nos espectros, vêm sendo sugeridos na literatura para remover e minimizar estes ruídos remanescentes o Noise-Adjusted Singular Value Decomposition - NASVD e Maximum Noise Fraction - MNF. Estes métodos produzem uma redução no ruído de forma significativa. Neste trabalho eles foram implementados dentro do ambiente de processamento do software Oasis Montaj e aplicados na área compreendida pelos blocos I e II do levantamento aerogeofísico que recobre a porção oeste da Província Mineral do Tapajós, entre os Estados do Pará e Amazonas. Os dados filtrados e não-filtrados com as técnicas de NASVD e MNF foram processados com os parâmetros e constantes fornecidos pela empresa Lasa Engenharia e Prospecções S.A., sendo estes comparados. Os resultados da comparação entre perfis e mapas apresentaram-se de forma promissora, pois houve um ganho na resolução dos produtos.

Myogenic stem cell function is impaired in mice lacking the forkhead/winged helix protein MNF

Myocyte nuclear factor (MNF) is a winged helix transcription factor that is expressed selectively in myogenic stem cells (satellite cells) of adult animals. Using a gene knockout strategy to generate a functional null allele at the Mnf locus, we observed that mice lacking MNF are viable, but severely runted. Skeletal muscles of Mnf−/− animals are atrophic, and satellite cell function is impaired. Muscle regeneration after injury is delayed and incomplete, and the normal timing of expression of cell cycle regulators and myogenic determination genes is dysregulated. Mnf mutant mice were intercrossed with mdx mice that lack dystrophin and exhibit only a subtle myopathic phenotype. In contrast, mdx mice that also lack MNF die in the first few weeks of life with a severe myopathy. Haploinsufficiency at the Mnf locus (Mnf+/−) also exacerbates the mdx phenotype to more closely resemble Duchenne's muscular dystrophy in humans. We conclude that MNF acts to regulate genes that coordinate the proliferation and differentiation of myogenic stem cells after muscle injury. Animals deficient in MNF may prove useful for evaluation of potential therapeutic interventions to promote muscle regeneration for patients having Duchenne's muscular dystrophy.

Elevated Micronucleus Frequency In Patients With Type 2 Diabetes, Dyslipidemia And Periodontitis.

The over-production of reactive oxygen species (ROS) can cause oxidative damage to a large number of molecules, including DNA, and has been associated with the pathogenesis of several disorders, such as diabetes mellitus (DM), dyslipidemia and periodontitis (PD). We hypothesise that the presence of these diseases could proportionally increase the DNA damage. The aim of this study was to assess the micronucleus frequency (MNF), as a biomarker for DNA damage, in individuals with type 2 DM, dyslipidemia and PD. One hundred and fifty patients were divided into five groups based upon diabetic, dyslipidemic and periodontal status (Group 1 - poor controlled DM with dyslipidemia and PD; Group 2 - well-controlled DM with dyslipidemia and PD; Group 3 - without DM with dyslipidemia and PD; Group 4 - without DM, without dyslipidemia and with PD; and Group 5 - without DM, dyslipidemia and PD). Blood analyses were carried out for fasting plasma glucose, HbA1c and lipid profile. Periodontal examinations were performed, and venous blood was collected and processed for micronucleus (MN) assay. The frequency of micronuclei was evaluated by cell culture cytokinesis-block MN assay. The general characteristics of each group were described by the mean and standard deviation and the data were submitted to the Mann-Whitney, Kruskal-Wallis, Multiple Logistic Regression and Spearman tests. The Groups 1, 2 and 3 were similarly dyslipidemic presenting increased levels of total cholesterol, low density lipoprotein cholesterol and triglycerides. Periodontal tissue destruction and local inflammation were significantly more severe in diabetics, particularly in Group 1. Frequency of bi-nucleated cells with MN and MNF, as well as nucleoplasmic bridges, were significantly higher for poor controlled diabetics with dyslipidemia and PD in comparison with those systemically healthy, even after adjusting for age, and considering Bonferroni's correction. Elevated frequency of micronuclei was found in patients affected by type 2 diabetes, dyslipidemia and PD. This result suggests that these three pathologies occurring simultaneously promote an additional role to produce DNA impairment. In addition, the micronuclei assay was useful as a biomarker for DNA damage in individuals with chronic degenerative diseases.

Repeatability of maximal voluntary force and of surface EMG variables during voluntary isometric contraction of quadriceps muscles in healthy subjects

The repeatability of initial values and rate of change of EMG signal mean spectral frequency (MNF), average rectified values (ARV), muscle fiber conduction velocity (CV) and maximal voluntary contraction (MVC) was investigated in the vastus medialis obliquus (VMO) and vastus lateralis (VL) muscles of both legs of nine healthy male subjects during voluntary, isometric contractions sustained for 50 s at 50% MVC. The values of MVC were recorded for both legs three times on each day and for three subsequent days, while the EMG signals have been recorded twice a day for three subsequent days. The degree of repeatability was investigated using the Fisher test based upon the ANalysis Of VAriance (ANOVA), the Standard Error of the Mean (SEM) and the Intraclass Correlation Coefficient (ICC). Data collected showed a high level of repeatability of MVC measurement (normalized SEM from 1.1% to 6.4% of the mean). MNF and ARV initial values also showed a high level of repeatability (ICC > 70% for all muscles and legs except right VMO). At 50% MVC level no relevant pattern of fatigue was observed for the VMO and VL muscles, suggesting that other portions of the quadriceps might have contributed to the generated effort. These observations seem to suggest that in the investigation of muscles belonging to a multi-muscular group at submaximal level, the more selective electrically elicited contractions should be preferred to voluntary contractions. (C) 2001 Elsevier Science Ltd. All rights reserved.

Repeatability of surface EMG variables in the sternocleidomastoid and anterior scalene muscles

In this study we examined the repeatability and reliability of the surface electromyographic (sEMG) signal mean frequency (MNF), average rectified value (ARV) and conduction velocity (CV) measured for the sternocleidomastoid (SCM) and the anterior scalene (AS) muscles in nine healthy volunteers during 15-s isometric cervical flexion contractions at 50% of the maximal voluntary contraction level over 3 non-consecutive days. Repeatability and reliability estimates were obtained for the initial values and rates of change of each sEMG variable by using both the Intraclass Correlation Coefficient (ICC) and the normalised standard error of the mean (nSEM). Results from SCM indicated good levels of repeatability for the initial value and slope of ARV (ICC > 65%). For the AS, high levels of repeatability were identified for the initial value of MNF (ICC > 70%) and the slope of ARV (ICC > 75%). Values of nSEM in the range 2.8-7.2% were obtained for the initial values of MNF and CV for both SCM and AS, indicating clinically acceptable measurement precision. The low value obtained for the nSEM of the initial value of MNF for the AS, in combination with the high ICC, indicates that of all of the variables examined, this variable could offer the best normative index to distinguish between subjects with and without neck pain, and represents the sEMG variable of choice for future evaluation purposes.

Comportamentos de amamentação e mamada em bubalinos, suas relações com período de lactação, idade e sexo dos bezerros

Objetivou-se neste trabalho investigar a frequência e a duração dos tipos de amamentações durante o período de lactação em fêmeas bubalinas e os tipos de mamadas em relação à idade e ao sexo dos bezerros. Trinta e cinco fêmeas e seus bezerros foram observados durante três dias consecutivos a cada mês, ao longo de nove meses. A amamentação foi caracterizada como: amamentação filial isolada (AFI), amamentação filial coletiva (AFC) e amamentação não-filial (ANF). As mamadas executadas pelos bezerros foram caracterizadas como: mamada filial isolada (MFI), mamada filial coletiva na própria mãe (MFC 1), mamada filial coletiva em outra fêmea (MCF2) e mamada não-filial (MNF). Os dados foram analisados pela análise de variância, e as médias foram comparadas pelo teste Tukey, considerando P < 0,05. A AFI apresentou frequência e duração maiores do que os outros tipos de amamentações (P < 0,05), sendo predominante em quase todo o período de lactação. A frequência da MFI foi alta, principalmente no primeiro mês. A duração foi maior quando comparada aos outros tipos de mamadas até o quinto mês (P < 0,05). Em relação ao sexo dos bezerros não foram encontradas diferenças significativas (P > 0,05) para as médias da frequência e a duração dos tipos de mamadas. Os resultados mostram que as fêmeas bubalinas têm maior aptidão inata para a AFI em relação aos outros tipos de amamentações, predominando durante quase todo o período de lactação. Os bezerros bubalinos são mais dependentes da MFI durante os primeiros cinco meses de idade, e o sexo dos bezerros não influenciou nos tipos de mamadas.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Tratamento de ruídos e caracterização de fisionomias do Cerrado utilizando séries temporais do sensor MODIS

O Cerrado é formado por um mosaico de fisionomias campestres, savânicas e florestais que possuem um típico ciclo fenológico. Nesse contexto, os dados do MODIS fornecem medidas diárias que permitem monitorar a sazonal fenologia da vegetação. O objetivo deste trabalho foi caracterizar formações savânicas, formações florestais e áreas de cerrado convertido pela ação antrópica, utilizando séries temporais de NDVI e EVI do sensor MODIS, após a suavização de ruídos. A metodologia adotada pode ser subdividida nos seguintes passos: (a) confecção do cubo temporal com NDVI e EVI, onde o perfil em z corresponde à assinatura temporal, (b) tratamento do ruído e (c) detecção das assinaturas temporais. A Transformação pela Fração Mínima de Ruído (MNF) foi aplicada para suavizar ruídos contidos nas séries temporais. Os resultados indicaram que os valores de NDVI foram maiores que os valores de EVI e existiu relação com as estações do ano. As formações florestais foram as que apresentaram maiores valores de NDVI e EVI, possuindo ainda as menores variações entre as estações. As áreas convertidas apresentaram os menores valores dos dois índices, tendo grande queda em seus valores no início da estação seca, provavelmente por se tratar do período de colheita. O estudo concluiu que as séries temporais NDVI e EVI são úteis na diferenciação dos tipos de vegetação.

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

The surface electromyography-force relationship during isometric dorsiflexion in males and females

This study evaluated sex-related differences in the tibialis anterior (TA) surface electromyography (EMG) to force relationship. One-hundred participants (50 males and 50 females) performed three isometric contractions at 20, 40, 60, 80, and 100% of maximal voluntary contraction (MVC) in an apparatus designed to isolate the action of the dorsiflexors. The surface EMG signal was amplified (lOOOx), band-pass filtered (10-500Hz), and sampled at 2048 Hz. The load cell signal was low-passed filtered at 100 Hz and sampled at the same rate. Males were stronger than females {P <0.05). However, there was no significant difference in root-mean-square (RMS) values between sexes {P <0.05). Both sexes exhibited a quadratic increase in RMS across force levels (P <0.05). The mean power frequency (MNF) for males was greater than for females {P <0.05). Males and females exhibited a linear increase in both frequency measures up to 80% of MVC (P <0.05). Between 80 and 100% MVC, the frequency values for the females plateaued while males showed a decrease {P <0.05). The magnitude of the difference in MNF between males and females was consistent with sex-specific TA physiology. In general, the pattern of means for RMS and MNF between males and females revealed no sex-related differences in the surface EMG/force relationship. We therefore conclude that there are no sex-related differences in the gradation of muscle force.

Le cours collégial de mise à niveau en français : l’incidence d’un dispositif pédagogique d’interdisciplinarité

Cette thèse présente une exploration de l’impact que des enseignants peuvent exercer sur le développement de l’intérêt d’étudiants envers leur discipline d’enseignement. Le problème visé par l’étude était le faible niveau de maîtrise de l’orthographe des collégiens du cours de mise à niveau en français et le taux d’échec important à ce cours. Spécifiquement, l’objectif de l’étude était d’évaluer un dispositif pédagogique d’interdisciplinarité ayant pour but de stimuler le développement de l’intérêt de collégiens envers leur cours de mise à niveau en français (MNF). Le dispositif a consisté en un pairage entre un cours moins apprécié des collégiens (le cours de MNF) et un cours très populaire (un cours de psychologie de la sexualité). Ces deux cours ont donc été planifiés en construisant entre eux le plus possible de liens facilement perceptibles par les étudiants. Les écrits théoriques permettaient de croire qu’un intérêt envers le cours de MNF pourrait émerger si l’on menait, dans le cours de français, des activités d’apprentissage utilisant les notions étudiées dans le cours de psychologie. De plus, la théorie du développement de l’intérêt d’Hidi et Renninger (2006) laissait anticiper un approfondissement de cet intérêt envers la matière en général (le français) et non seulement envers le cours. Par ailleurs, la littérature du champ de la motivation scolaire permettait de s’attendre à ce que cet intérêt soit lié à une plus grande perception de l’utilité du cours de MNF de la part des étudiants, ainsi qu’à un meilleur engagement et un meilleur rendement. Pour vérifier ces hypothèses, un devis quasi-expérimental avec condition témoin et suivi longitudinal a été adopté. Le groupe expérimental (GE) était composé de 27 collégiens inscrits aux deux cours : le cours de MNF et le cours de psychologie de la sexualité. Le groupe témoin (GT) était composé de 79 collégiens inscrits au cours de MNF sans être exposés à une condition d’interdisciplinarité. L’intérêt, l’utilité, l’engagement cognitif et l’engagement comportemental ont été mesurées à l’aide d’échelles de type Likert. De plus, la prise des présences en classe par les enseignants a été utilisée comme mesure supplémentaire de l’engagement comportemental. Le rendement, représenté par la performance en orthographe, a été évalué par l’administration d’une dictée avant puis après l’intervention. Les résultats d’une analyse de multivariance (MANOVA) ont révélé un intérêt envers le cours de MNF significativement plus grand après l’intervention pour le GE, comparativement au GT, tout comme une plus grande perception de l’utilité du cours et un meilleur engagement comportemental. Concernant le rendement en orthographe, le nombre d’erreurs d’orthographe grammaticale a diminué davantage entre les deux temps de mesure pour le GE comparativement au GT. Cette différence est significative. Ces résultats suggèrent de valoriser l’interdisciplinarité dans l’enseignement au collégial.

Las operaciones para el mantenimiento de la paz en Haití (1991-2005)

La Misión de Estabilización de las Naciones Unidas en Haití -MINUSTAHes la primera intervención en la historia de las operaciones de paz en la cual la participación latinoamericana fue fruto de una concertación política de los gobiernos de la región. El desafío de la operación de paz es por un lado, la reconstrucción de un Estado, y por otro, demostrar la capacidad de los países latinoamericanos para manejar este tipo de conflictos.En el presente trabajo se analizan las operaciones para el mantenimiento de la paz de las Naciones Unidas en Haití,1 se evalúan las capacidades, los recursos y mecanismos políticos que disponen los organismos multilaterales y los gobiernos para manejar y responder a dicho conflicto en forma efectiva.Este trabajo no tiene la finalidad de investigar los eventos que han determinado la intervención de 2004, más bien la finalidad del presente trabajo es analizar las intervenciones de las operaciones para el mantenimiento de la paz de las Naciones Unidas en Haití, la Misión de las Naciones Unidas en Haití (UNMIH), de septiembre de 1993 a junio de 1996; la Misión de Apoyo de las Naciones Unidas en Haití (UNSMIH), de julio de 1996 a julio de 1997; la Misión de Transición de las Naciones Unidas en Haití (UNTMIH), de agosto a noviembre de 1997, y la Misión de Policía Civil de las Naciones Unidas en Haití (MIPONUH), de diciembre de 1997 a marzo de 2000; intervención de la Fuerza Interina Multinacional (FIM) entre marzo y junio de 2004, y particularmente la Misión de Estabilización de las Naciones Unidas en Haití (MINUSTAH) que reemplazó la anterior y que a la fecha continúa en Haití.-----The MINUSTAH mission is the first intervention in the history of peace operations where the Latin American involvement resulted from a political agreement among the region governments. The peace operation challenge is, on the one hand, the reconstruction of a State and, on the other hand, demonstrating the ability of Latin American countries for handling this type of conflicts.This paper analyzes UN peacekeeping operations in Haiti,2 evaluates the abilities, the resources, and the political mechanisms available to multilateral bodies and governments for handling and addressing such conflict on an effective way. The purpose of this paper is not investigating the events that determined the intervention in 2004. Rather, its purpose is to analyze the interventions of the UN peacekeeping operations in Haiti, –UN Mission in Haiti (UNMIH), from September 1993 to June 1996; UN Support Mission in Haiti (UNSMIH), from July 1996 to July 1997; UN Transition Mission in Haiti (UNTMIH), from August to November 1997; and UN Civilian Police Mission in Haiti (MIPONUH), from December 1997 to March 2000;– the intervention of the Multinational Force (MNF) between March and June 2004, and particularly the United Nations Stabilization Mission in Haiti (MINUSTAH) that replaced the latter and remains in Haiti.

Modeling Of District Metered Areas With Relatively High Leakage Rate. The Case Study Of Kalipoli’s DMA

The article reviews the modelling of District Metered Areas (DMAs) with relatively high leakage rate. As a generally recognised approach in modelling of leakage does not exist, modelling of leakage by enginners and other researchers usually takes place by dividing the whole leakage rate evenly to all available nodes of the model. In this article, a new methodology is proposed to determine the nodal leakage by using a hydraulic model. The proposed methodology takes into consideration the IWA water balance methodology, the Minimum Night Flow (MNF) analysis, the number of connections related to each node and the marerial of pipes. In addition, the model is illustrated by a real case study, as it was applied in Kalipoli’s DMA. Results show that the proposed model gives reliable results.

Superparamagnetismo em Jacobsitas sintéticas

In this experimental study sintetic samples of Jacobsites (MnFe2O4) were synthesized by the Pechini method and calcined within ambient atmosphere and afterwards in the vacuum from 400 to 700ºC, the range of calcination temperatures. The X-Ray Diffraction (XRD) and the Scanning Electronic Microscopy (SEM) analysis have shown that the samples treated at 400ºC temperature are composed by a simple type of spinel phase, with a crystallite size of 8:8nm for the sample calcined in ambient atmosphere and 20; 1nm for the sample treated in the vacuum, showing that the cristallite average size can be manipulated by the atmosphere control. The hysteresis loops for the sample calcined at 400ºC in ambient atmosphere reveal features of superparamagnetic behavior with magnetization 29:3emu=g at the maximum field of 1:2T. The sample calcined in 400oC under vacuum show magnetization = 67emu=g at the maximum field of 1:5T. The sample treated at 500oC, under ambient atmosphere, has shown besides the spinel phase, secondary phases of hematite (Fe2O3) and bixbyite (FeMnO3). The hysteresis loops demonstrate a sharp drop of the magnetization compared to the previous sample. The analysis has revealed that for the samples treated in higher temperatures (600ºC and 700ºC) its observed the absence of the spinel phase and the maintenance of the bixbyite and hematite. The hysteresis loops for those samples in accordance to the external magnetic field are straight lines crossing the origin, consistent with the antiferromagnetic behavior of the phases.The Mössbauer espectroscopy show to the sample calcined at 400ºC within ambiente atmosphere two sextet and one doublet. The two sextets are assigned to the hyperfine fields related to the magnetic deployment in the nuclei of Fe3+ ions, at the tetraedric and octaedric sites. The doublet is assigned to superparamagnetic behavior of the particles with smaller diameter than dc . Now the sample calcined at 400ºC under vacuum only show two sextet