From the Bay of Biscay to the High Atlas: completing the anisotropic characterization of the upper mantle beneath the westernmost Mediterranean region

The knowledge of the anisotropic properties beneath the Iberian Peninsula and Northern Morocco has been dramatically improved since late 2007 with the analysis of the data provided by the dense TopoIberia broadband seismic network, the increasing number of permanent stations operating in Morocco, Portugal and Spain, and the contribution of smaller scale/higher resolution experiments. Results from the two first TopoIberia deployments have evidenced a spectacular rotation of the fast polarization direction (FPD) along the Gibraltar Arc, interpreted as an evidence of mantle flow deflected around the high velocity slab beneath the Alboran Sea, and a rather uniform N100 degrees E FPD beneath the central Iberian Variscan Massif, consistent with global mantle flow models taking into account contributions of surface plate motion, density variations and net lithosphere rotation. The results from the last Iberarray deployment presented here, covering the northern part of the Iberian Peninsula, also show a rather uniform FPD orientation close to N100 degrees E, thus confirming the previous interpretation globally relating the anisotropic parameters to the LPO of mantle minerals generated by mantle flow at asthenospheric depths. However, the degree of anisotropy varies significantly, from delay time values of around 0.5 s beneath NW Iberia to values reaching 2.0 sin its NE comer. The anisotropic parameters retrieved from single events providing high quality data also show significant differences for stations located in the Variscan units of NW Iberia, suggesting that the region includes multiple anisotropic layers or complex anisotropy systems. These results allow to complete the map of the anisotropic properties of the westernmost Mediterranean region, which can now be considered as one of best constrained regions worldwide, with more than 300 sites investigated over an area extending from the Bay of Biscay to the Sahara platform. (C) 2015 Elsevier B.V. All rights reserved.

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.

Molecular screening of Plasmodium sp. asymptomatic carriers among transfusion centers from Brazilian Amazon region

The transmission of malaria in Brazil is heterogeneous throughout endemic areas and the presence of asymptomatic Plasmodium sp. carriers (APCs) in the Brazilian Amazon has already been demonstrated. Malaria screening in blood banks is based on the selection of donors in respect to possible risks associated with travel or residence, clinical evidence and/or inaccurate diagnostic methods thereby increasing the probability of transfusion-transmitted infection. We evaluated the frequency of APCs in four blood services in distinct areas of the Brazilian Amazon region. DNA was obtained from 400 human blood samples for testing using the phenol-chloroform method followed by a nested-PCR protocol with species-specific primers. The positivity rate varied from 1 to 3% of blood donors from the four areas with an average of 2.3%. All positive individuals had mixed infections for Plasmodium vivax and Plasmodium falciparum. No significant differences in the results were detected among these areas; the majority of cases originated from the transfusion centres of Porto Velho, Rondônia State and Macapá, Amapá State. Although it is still unclear whether APC individuals may act as reservoirs of the parasite, efficient screening of APCs and malaria patients in Brazilian blood services from endemic areas needs to be improved.

A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.

A filter inexact-restoration method for nonlinear programming

A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. (SIAM J. Optim. 14:646–669, 2003) but not yet implement—the internal algorithms are not proposed. The filter, a new concept introduced by Fletcher and Leyffer (Math. Program. Ser. A 91:239–269, 2002), replaces the merit function avoiding the penalty parameter estimation and the difficulties related to the nondifferentiability. In the IR approach two independent phases are performed in each iteration, the feasibility and the optimality phases. The line search filter is combined with the first one phase to generate a “more feasible” point, and then it is used in the optimality phase to reach an “optimal” point. Numerical experiences with a collection of AMPL problems and a performance comparison with IPOPT are provided.

New strategies for active finding of leprosy cases in the Amazonian region

AbstractINTRODUCTION: The use of the Self-Image Form (SIF) expands the identification of active leprosy cases to neighbors of index cases.METHODS: The SIF was used to screen two groups: case (neighbors of index cases of leprosy) and control (individuals residing next to houses without leprosy) group. A specialist investigated suspected leprosy cases for disease confirmation.RESULTS: New cases of leprosy were diagnosed in the case group (n = 7, 8.6%), but not the control group.CONCLUSIONS: The new surveillance strategy is inexpensive, efficient, and feasible within a primary health strategy. Future studies can help improve the use of the SIF.

Implementação de metodologias BIM na Direção de Engenharia de Barragens da EDP: casos de estudo de projeto de estruturas em obras hidroelétricas

Dissertação de mestrado integrado em Engenharia Civil

Methylation at the CpG island shore region upregulates Nr3c1 promoter activity after early-life stress

Early-life stress (ELS) induces long-lasting changes in gene expression conferring an increased risk for the development of stress-related mental disorders. Glucocorticoid receptors (GR) mediate the negative feedback actions of glucocorticoids (GC) in the paraventricular nucleus (PVN) of the hypothalamus and anterior pituitary and therefore play a key role in the regulation of the hypothalamic-pituitary-adrenal (HPA) axis and the endocrine response to stress. We here show that ELS programs the expression of the GR gene (Nr3c1) by site-specific hypermethylation at the CpG island (CGI) shore in hypothalamic neurons that produce corticotropin-releasing hormone (Crh), thus preventing Crh upregulation under conditions of chronic stress. CpGs mapping to the Nr3c1 CGI shore region are dynamically regulated by ELS and underpin methylation-sensitive control of this region's insulation-like function via Ying Yang 1 (YY1) binding. Our results provide new insight into how a genomic element integrates experience-dependent epigenetic programming of the composite proximal Nr3c1 promoter, and assigns an insulating role to the CGI shore.

Effects of fermentation residues on the melt processability and thermomechanical degradation of PHBV produced from cheese whey using mixed microbial cultures

"Available online 28 March 2016"

Evaluation of the determinism of the actuator sensor interface (ASI) on programmable logic controllers (PLC), personal computers (PC) and real-time operating systems (RTOS)

The purpose of this study was to evaluate the determinism of the AS-lnterface network and the 3 main families of control systems, which may use it, namely PLC, PC and RTOS. During the course of this study the PROFIBUS and Ethernet field level networks were also considered in order to ensure that they would not introduce unacceptable latencies into the overall control system. This research demonstrated that an incorrectly configured Ethernet network introduces unacceptable variable duration latencies into the control system, thus care must be exercised if the determinism of a control system is not to be compromised. This study introduces a new concept of using statistics and process capability metrics in the form of CPk values, to specify how suitable a control system is for a given control task. The PLC systems, which were tested, demonstrated extremely deterministic responses, but when a large number of iterations were introduced in the user program, the mean control system latency was much too great for an AS-I network. Thus the PLC was found to be unsuitable for an AS-I network if a large, complex user program Is required. The PC systems, which were tested were non-deterministic and had latencies of variable duration. These latencies became extremely exaggerated when a graphing ActiveX was included in the control application. These PC systems also exhibited a non-normal frequency distribution of control system latencies, and as such are unsuitable for implementation with an AS-I network. The RTOS system, which was tested, overcame the problems identified with the PLC systems and produced an extremely deterministic response, even when a large number of iterations were introduced in the user program. The RTOS system, which was tested, is capable of providing a suitable deterministic control system response, even when an extremely large, complex user program is required.

A possible correlation between the host genetic background in the epidemiology of Hepatitis B virus in the Amazon region of Brazil

The Amazon region of Brazil is an area of great interest because of the large distribution of hepatitis B virus in specific Western areas. Seven urban communities and 24 Indian groups were visited in a total of 4,244 persons. Each individual was interviewed in order to obtain demographic and familial information. Whole blood was collected for serology and genetic determinations. Eleven genetic markers and three HBV markers were tested. Among the most relevant results it was possible to show that (i) there was a large variation of previous exposure to HBV in both urban and non-urban groups ranging from 0 to 59.2%; (ii) there was a different pattern of epidemiological distribution of HBV that was present even among a same linguistic Indian group, with mixed patterns of correlation between HBsAg and anti-HBs and (iii) the prevalence of HBV markers (HBsAg and anti-HBs) were significantly higher (P=0.0001) among the Indian population (18.8%) than the urban groups (12.5%). Its possible that the host genetic background could influence and modulate the replication of the virus in order to generate HB carrier state.

Giardia survey in live-trapped small domestic and wild mammals in four regions in the southwest region of the State of São Paulo, Brazil

For the first time, a survey on Giardia in the live-trapped small domestic and wild mammals was perfomed in four regions of state of the São Paulo, Brazil, with special attention to the parasitism of Rattus rattus rattus by Giardia. This species was found infected in all studied sites: Botucatu (15.4%), Conchas (28.5%), Itaporanga (38.7%) and São Roque (100 %). Two new hosts and their frequency of infection were described for Giardia in Nectomys squamipes, an aquatic rodent and in Bolomys lasiurus, a forest rodent (100 % and 14.3 %, respectively). Both G. muris and G. duodenalis groups were found in scrapings of intestinal mucosa of those rodents. Mixed infection was observed in some animals. It is important to emphasize the infection by G. duodenalis in the black rat as this species lives as a comensal with man and in N. squamipes as it may contaminate small streams used for domestic consumption. Therefore, further investigation will be necessary to elucidate the potential of these rodents to act as reservoirs of Giardia for man.

Generic optimality conditions for semi-algebraic convex programs

We consider linear optimization over a nonempty convex semi-algebraic feasible region F. Semidefinite programming is an example. If F is compact, then for almost every linear objective there is a unique optimal solution, lying on a unique \active" manifold, around which F is \partly smooth", and the second-order sufficient conditions hold. Perturbing the objective results in smooth variation of the optimal solution. The active manifold consists, locally, of these perturbed optimal solutions; it is independent of the representation of F, and is eventually identified by a variety of iterative algorithms such as proximal and projected gradient schemes. These results extend to unbounded sets F.

Comparison of Some Molecular-genetic Techniques for Identification of Leishmania Circulating in Natural Foci of Zoonotic Cutaneous Leishmaniasis in the Central Asia Region

Different molecular-genetic methods were used to identify a cohort of Leishmania strains from natural foci of zoonotic cutaneous leishmaniasis located in Central Asia, on the former USSR territory. The results obtained using isoenzymes, PCR, restriction fragment length polymorphisms of kDNA and molecular hybridization techniques are discussed in terms of their applicability, discrimination power and feasibility for answering questions related to molecular epidemiological research and for detecting mixed Leishmania infections

Treg-therapy allows mixed chimerism and transplantation tolerance without cytoreductive conditioning.

Establishment of mixed chimerism through transplantation of allogeneic donor bone marrow (BM) into sufficiently conditioned recipients is an effective experimental approach for the induction of transplantation tolerance. Clinical translation, however, is impeded by the lack of feasible protocols devoid of cytoreductive conditioning (i.e. irradiation and cytotoxic drugs/mAbs). The therapeutic application of regulatory T cells (Tregs) prolongs allograft survival in experimental models, but appears insufficient to induce robust tolerance on its own. We thus investigated whether mixed chimerism and tolerance could be realized without the need for cytoreductive treatment by combining Treg therapy with BM transplantation (BMT). Polyclonal recipient Tregs were cotransplanted with a moderate dose of fully mismatched allogeneic donor BM into recipients conditioned solely with short-course costimulation blockade and rapamycin. This combination treatment led to long-term multilineage chimerism and donor-specific skin graft tolerance. Chimeras also developed humoral and in vitro tolerance. Both deletional and nondeletional mechanisms contributed to maintenance of tolerance. All tested populations of polyclonal Tregs (FoxP3-transduced Tregs, natural Tregs and TGF-beta induced Tregs) were effective in this setting. Thus, Treg therapy achieves mixed chimerism and tolerance without cytoreductive recipient treatment, thereby eliminating a major toxic element impeding clinical translation of this approach.