Study of Pt/MCM-22 based catalysts in the transformation of n-hexane: effect of rare earth elements and mode of platinum introduction

The bifunctional transformation of n-hexane was carried out over Pt/MCM-22 based catalysts. MCM-22 was synthesized and submitted to ion exchange with rare earth nitrate solutions of La, Nd and Yb, followed by Pt introduction. Three different methods were used to introduce about 1 wt% of Pt in the zeolite: ion exchange, incipient wetness impregnation and mechanical mixture with Pt/Al(2)O(3). The bifunctional catalysts were characterized by transmission electron microscopy and by the model reaction of toluene hydrogenation. These experiments showed that, in the ion exchanged sample, Pt is located both within the inner micropores and on the outer surface, whereas in the impregnated one, the metal is essentially located on the outer surface under the form of large particles. The presence of RE elements increases the hydrogenating activity of Pt/MCM-22 since the location of these species at the vicinity of metal particles causes modification on its electronic properties. Whatever the mode of Pt introduction, a fast initial decrease in conversion is observed for n-hexane transformation, followed by a plateau related to the occurrence of the catalytic transformations at the hemicages located at the outer surface of the crystals. The effect of rare earth elements on the hydrogenating function leads to a lower selectivity in dibranched isomers and increased amounts of light products.

A new strategy for the synthesis of 3-cinnamoyl-2-styrylchromones and their transformation into new xanthenodiones derivatives

23rd ISHC Congress will be held in Glasgow, Scotland from July 31 August 4, 2011.

The First WORKS Conference on Transformation of Work in a Global Knowledge Economy

The relationship between the changes of the global economy and individual working conditions formed the background of the first WORKS conference “The transformation of work in a global knowledge economy: towards a conceptual framework”, held in Chania, Greece from 21st – 22nd September, 2006 and attended by around 50 European researchers. Experts from academia and trade unions from all over the world were invited to give insights into their field of research, contributing to one of the main topics of the conference: (i) globalisation and organisational restructuring, (ii) workers’ organisation, the quality of working life and the gender dimension and (iii) global experiences and recommendations.

The transformation of work? A quantitative evaluation of changes in work in Portugal

This report is made for the Work Package 15 of WORKS project and tries to develop more information on the Portuguese situation in the work structures changes in the recent years. It starts with an analysis of socio- economical indicators (Macro economical indicators, Employment indicators, Consumption, Technology at the workplace, Productivity), and then approaches the situation in terms of work flexibility in its dimensions of time use and New forms of work organisation. It traces employment in business functions with a sectoral and occupational approach, and analyses the occupational change in South Europe with particular relevance to Portugal (skill utilisation and job satisfaction, occupational and industrial mobility, quantitative evaluation of the shape of employment in Europe. Finaly are analysed the globalisation indicators.

Development of an interface for ontology‐based transformation between features of different types

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

On divisors of pseudovarieties generated by some classes of full transformation semigroups

Algebra Colloquium, 15 (2008), p. 581–588

Schistosoma mansoni: the effect of dexamethasone on the cercaria-schistosomulum transformation, in vivo

Treatment with dexamethasone (DMS) in the early phases of the experimental Schistosoma mansoni infection causes an indirect effect on the cercaria-schistosomulum transformation process. This is observed when naive albino mice are treated with that drug (50 mg/Kg, subcutaneously) and infected intraperitonealy 01 hour later with about 500 S. mansoni cercariae (LE strain). An inhibition in the host cell adhesion to the larvae, with a simultaneous delay in the cercaria-schistosomulum transformation, is observed. This effect is probably due to a blockade of the neutrophil migration to the peritoneal cavity of mice, by an impairment of the release of chemotactic substances. Such delay probably favors the killing of S. mansoni larvae, still in the transformation process, by the vertebrate host defenses, as the complement system.

Transformation of Medicago truncatula with the arginine decarboxylase gene to modify polyamine metabolism toward water deficit resistance

Dissertation submitted to obtain a Ph.D. (Doutoramento) degree in Biology at the Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa

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.

Relative abelian kernels of some classes of transformation monoids

Bulletin of the Australian Mathematical Society, nº 73 (2006), p. 375-404

Environmental pressures and impacts of public sector organizations: the case of the Portuguese Military

Progress in Industrial Ecology, An International Journal, nº 4(5), p. 363-381

Developing and implementing an environmental performance index for the Portuguese military

Business Strategy and the Environment nº 15, p. 71–86

Adenoviruses isolated from civilian and military personnel in the city of Rio de Janeiro, Brazil

Adenovirus are important pathogen primarily associated to respiratory infections of children and military personnel, even though it is also associated to cases of conjunctivitis and keratoconjunctivitis. We analyzed respiratory secretion collected from subjects with and without respiratory infection symptoms, being 181 civilians and 221 military subjects. The samples were inoculated in HEp-2 and/or A549 tissue cultures for viral isolation. Samples presenting cytopathogenic effect (CPE) in any tissue culture were tested by a polymerase chain reaction (PCR) assay to confirm adenovirus isolation. The isolates confirmed as adenovirus were further analyzed by restriction endonuclease assay for determination of viral species. Three isolates were identified as specie A (two from civilian and one from military), one isolate from military was identified as specie C, and one isolate from civilian was identified as specie D. For two isolates the specie could not be identified.

Transformation of a Cutaneous Follicle Center Lymphoma to a Diffuse Large B-Cell Lymphoma - An Unusual Presentation

Primary cutaneous follicle center lymphoma (PCFCL) is characterized by a proliferation of follicle center cells in the skin. A definitive diagnosis is frequently delayed because of difficulties in interpretation of the histopathologic findings. It has an excellent prognosis with a 5-year survival over 95% and its risk of transformation has not been established. We describe a case report of man with a gastric diffuse large B-cell lymphoma (DLBCL) referred to our clinic because of nodules in the back that had gradually developed over a period of 10 years. A biopsy performed 3 years before was interpreted as reactive follicular hyperplasia. A new skin biopsy revealed a diffuse large B-cell lymphoma and immunoglobulin heavy chain gene rearrangements from the initial skin biopsy (PCBCL) and the DLBCL gastric biopsy were studied by polymerase chain reaction and an identical clonal rearrangement was detected which was highly suggestive of a transformation lymphoma.