Generalized synchronization in a system of several non-autonomous oscillators coupled by a medium

An abstract theory on general synchronization of a system of several oscillators coupled by a medium is given. By generalized synchronization we mean the existence of an invariant manifold that allows a reduction in dimension. The case of a concrete system modeling the dynamics of a chemical solution on two containers connected to a third container is studied from the basics to arbitrary perturbations. Conditions under which synchronization occurs are given. Our theoretical results are complemented with a numerical study.

Antibodies against non-structural c100/3 and structural core antigen of hepatitis C virus (HCV) in hemodialysis patients

Two groups of patients undergoing hemodialysis (HD) maintenance were evaluated for their antibody response to non-structural c100/3 protein and structural core protein of hepatitis C virus (HCV). Forty-six patients (Group 1) never presented liver abnormalities during HD treatment, while 52 patients (Group 2) had either current or prior liver enzyme elevations. Prevalence rates of 32.6% and 41.3% were found for anti-c100/3 and anti-HCV core antibodies, respectively, in patients with silent infections (Group 1). The rate of anti-c100/3 in patients of Group 2 was 71.15% and reached 86.5% for anti-HCV core antibodies. The recognition of anti-c100/3 and anti-core antibodies was significantly higher in Group 2 than in Group 1. A line immunoassay composed of structural and non-structural peptides was used as a confirmation assay. HBV infection, measured by the presence of anti-HBc antibodies, was observed in 39.8% of the patients. Six were HBsAg chronic carriers and 13 had naturally acquired anti-HBs antibodies. The duration of HD treatment was correlated with anti-HCV positivity. A high prevalence of 96.7% (Group 2) was found in patients who underwent more than 5 years of treatment. Our results suggest that anti-HCV core ELISA is more accurate for detecting HCV infection than anti-c100/3. Although the risk associated with the duration of HD treatment and blood transfusion was high, additional factors such as a significant non-transfusional spread of HCV seems to play a role as well. The identification of infective patients by more sensitive methods for HCV genome detection should help to control the transmission of HCV in the unit under study.

Non-uniform printed antenna array for wireless communications in sports arenas

Wireless communications had a great development in the last years and nowadays they are present everywhere, public and private, being increasingly used for different applications. Their application in the business of sports events as a means to improve the experience of the fans at the games is becoming essential, such as sharing messages and multimedia material on social networks. In the stadiums, given the high density of people, the wireless networks require very large data capacity. Hence radio coverage employing many small sized sectors is unavoidable. In this paper, an antenna is designed to operate in the Wi-Fi 5GHz frequency band, with a directive radiation pattern suitable to this kind of applications. Furthermore, despite the large bandwidth and low losses, this antenna has been developed using low cost, off-the-shelf materials without sacrificing quality or performance, essential to mass production. © 2015 EurAAP.

The key role of coligands in novel ruthenium(II)-cyclopentadienyl bipyridine derivatives: ranging from non-cytotoxic to highly cytotoxic compounds

A new family of eight ruthenium(II)-cyclopentadienyl bipyridine derivatives, bearing nitrogen, sulfur, phosphorous and carbonyl sigma bonded coligands, has been synthesized. Compounds bearing nitrogen bonded coligands were found to be unstable in aqueous solution, while the others presented appropriate stabilities for the biologic assays and pursued for determination of IC50 values in ovarian (A2780) and breast (MCF7 and MDAMB231) human cancer cell lines. These studies were also carried out for the [5: HSA] and [6: HSA] adducts (HSA=human serum albumin) and a better performance was found for the first case. Spectroscopic, electrochemical studies by cyclic voltammetry and density functional theory calculations allowed us to get some understanding on the electronic flow directions within the molecules and to find a possible clue concerning the structural features of coligands that can activate bipyridyl ligands toward an increased cytotoxic effect. X-ray structure analysis of compound [Ru(η(5)-C5H5)(bipy)(PPh3)][PF6] (7; bipy=bipyridine) showed crystallization on C2/c space group with two enantiomers of the [Ru(η(5)-C5H5)(bipy)(PPh3)](+) cation complex in the racemic crystal packing.

Prevalence of rubella antibodies in a non-immunized urban population, São Paulo, Brazil

The prevalence of rubella antibodies was evaluated through a ramdom Seroepidemiological survey in 1400 blood samples of 2-14 year old children and in 329 samples of umbilical cord serum. Rubella IgG antibodies were detected by ELISA, and the sera were collected in 1987, five years before the mass vaccination campaign with measles-mumps-rubella vaccine carried out in the city of São Paulo in 1992. A significant increase in prevalence of rubella infection was observed after 6 years of age, and 77% of the individuals aged from 15 to 19 years had detectable rubella antibodies. However, the seroprevalence rose to 90.5% (171/189) in cord serum samples from children whose mothers were 20 to 29 years old, and reached 95.6% in newborns of mothers who were 30 to 34 years old, indicating that a large number of women are infected during childbearing years. This study confirms that rubella infection represents an important Public Health problem in São Paulo city. The data on the seroprevalence of rubella antibodies before the mass vaccination campaign reflects the baseline immunological status of this population before any intervention and should be used to design an adequate vaccination strategy and to assess the Seroepidemiological impact of this intervention.

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.

Hyperspectral imagery framework for unmixing and dimensionality estimation

In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.

Gammaretroviral and lentiviral vectors for gene therapy: stability and inactivation mechanisms

Dissertation presented to obtain a Ph.D degree in Engineering and Technology Sciences, Gene Therapy at the Instituto de Tecnologia Quimica e Biológica, Universidade Nova de Lisboa

Characterization of a Trypanosoma cruzi strain isolated from a non-endemic area in Northeast Brazil

A cepa WSL (Wild São Lorenço) de T. cruzi, isolada de um cobaio proveniente de São Lorenço da Mata (Nordeste do Brasil) foi caracterizada através da análise do seu comportamento morfobiológico e perfil isoenzimático. Para o estudo do comportamento morfobiológico, tripomastigotas sanguíneos (1 x 10 5) da cepa WSL foram inoculados por via intraperitonal em camundongos albinos Swiss. Como controle a cepa Y (Tipo I) foi usada. Durante o curso da infecção os seguintes parâmetros foram analisados: parasitemia, mortalidade, morfologia dos parasitas no sangue periférico e tropismo tissular. O perfil isoenzimático foi analisado em relação às enzimas ALAT, GPI e PGM usando como controle de referência as cepas Peruana (Tipo I), 21SF (Tipo II) e Colombiana (Tipo III). A cepa WSL apresentou as seguintes características biológicas: 1) multiplicação lenta e pico parasitêmico entre 21 - 25 dias pós-infecção; 2) mortalidade de 3,3% 40 dias pós-infecção; 3) predominância de formas largas no sangue periférico e 4) miotropismo com predominante envolvimento cardíaco. A análise isoenzimática mostrou um padrão de zimodema 2 (Z2) que corresponde às cepas biológicas Tipo II. Os resultados mostram que a cepa WSL apresenta baixa virulência e patogenicidade.

Autoantibodies before, during and after administration of recombinant interferon-alpha for chronic viral hepatitis

This study was undertaken to investigate the presence of autoantibodies in patients with chronic viral hepatitis B and C, before, during and after interferon-alpha (IFN-alpha) therapy and to study their relation to dose and type of IFN-alpha and response to treatment. Fifty patients with chronic hepatitis were divided in two groups, a control-group of 21 patients (10 type B and 11 type C) who were followed for 6 months without treatment and an IFN-group consisting of 29 patients (8 type B and 21 type C) who received IFN therapy for 6 months. Serum samples were tested for a range of antibodies at the start of the study, during therapy and at the end of the 6 month period. Antibodies tested for included: antinuclear, smooth muscle, antimitochondrial, parietal cell and thyroid microsomal. Four (8%) of the total patient group had autoantibodies at the beginning of the study (two in each group). During the follow-up period no patient in the control group developed antibodies compared with 3 (11%) patients in the treatment group. Autoantibodies developed in patients treated with higher doses of IFN and were found in those patients who tended to show a poor response to IFN-therapy. Further studies are needed to establish the relationship between poor response to IFN-alpha and development of autoantibodies.

Domestic vectors of Chagas' disease in three rural communities of Nicaragua

A triatomine survey was conducted in three rural settlements of Nicaragua (Santa Rosa, Quebrada Honda and Poneloya) where Chagas' disease is endemic, to determine rates of house infestation, evaluate the housing condition and to asess the performance of the María sensor box in detection of domestic vectors. A total of 184 households were selected and vectors were sought by the methods of timed manual capture and by sensor boxes. The sole vectors species found in this study was Triatoma dimidiata. Of the examined bugs 50, 60 and 33%, in the respective communities, were infected with T. cruzi. The rates of house infestation as determined by manual capture and sensor boxes were respectively, 48.3% and 54.2% in Santa Rosa, 29.8% and 51.2% in Quebrada Honda and in Poneloya 3.8 and 5.9% with significant difference between the methods in Quebrada Honda. When compared with the manual capture, the Maria sensor box detected vectors in 71.4% of positive houses in two of the communities but also was able to detect bugs in 39.3% and 41.1% of houses where manual capture had been negative. Housing condition was evaluated according to three structural parameters, in this way, in the first community 79.2% of houses were classified as bad, 20.8% as regular; in the second one 42.5% were bad and 57.5% regular, whereas in the third 62.5% of the houses were regular. Rates of infestation did not differ greatly between the different housing conditions. Our results show that the sensor box is as efficient as manual capture and could be implemented in our country.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

Using Baseline Methods to Identify Non-technical Losses in the Context of Smart Grids

Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers’ performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data.

Effects of non-specific immunopotentiators in experimental Schistosoma mansoni infection: II. Corynebacterium parvum

The effects of Corynebacterium parvum on host protection, tissue reaction and "in vivo" chemotaxis in Schistosoma mansoni infected mice were studied. The C. parvum was given intraperitoneally using a dose of 0.7 mg, twice a week (for 4 weeks), thirty days before (prophylactic treatment) or after infection (curative treatment). The host protection was evaluated through the recovery of adult worms by liver perfusion and was lower in the prophylactic group as compared to the control group (p = 0.018), resulting in 44% protection. The "in vivo" leukocyte response in both prophylactic and curative groups was higher as compared to the infected/non treated group (p = 0.009 and p = 0.003, respectively). Tissue reactions were described in the experimental and control groups, but there were not remarkable differences among them. The possible biological implications and relevance of the findings for the defensive response of the host and control of schistosomiasis are discussed.