Large pseudoscalar Yukawa couplings in the complex 2HDM

We start by presenting the current status of a complex flavour conserving two-Higgs doublet model. We will focus on some very interesting scenarios where unexpectedly the light Higgs couplings to leptons and to b-quarks can have a large pseudoscalar component with a vanishing scalar component. Predictions for the allowed parameter space at end of the next run with a total collected luminosity of 300 fb(-1) and 3000 fb(-1) are also discussed. These scenarios are not excluded by present data and most probably will survive the next LHC run. However, a measurement of the mixing angle phi(tau), between the scalar and pseudoscalar component of the 125 GeV Higgs, in the decay h -> tau(+)tau(-) will be able to probe many of these scenarios, even with low luminosity. Similarly, a measurement of phi(t) in the vertex (t) over bar th could help to constrain the low tan beta region in the Type I model.

Juggling time concepts: complex metanarrative in Alejandro González Iñárritu’s 21 Grams

ABSTRACT - Starting with the explanation of metanarrative as a sort of self-reflexive storytelling (as defended by Kenneth Weaver Hope in his unpublished PhD. thesis), I propose to talk about enunciative practices that stress the telling more than the told. In line with some metaficcional practices applied to cinema, such as the ‘mindfuck’ film (Jonathan Eig, 2003), the ‘psychological puzzle film’ (Elliot Panek, 2003) and the ‘mind-game film’ (Thomas Elsaesser, 2009), I will address the manipulations that a narrative film endures in order to produce a more fruitful and complex experience for the viewer. I will particularly concentrate on the misrepresentation of time as a way to produce a labyrinthine work of fiction where the linear description of events is replaced by a game of time disclosure. The viewer is thus called upon to reconstruct the order of the various situations portrayed in a process that I call ‘temporal mapping’. However, as the viewer attempts to do this, the film, ironically, because of the intricate nature of the plot and the uncertain status of the characters, resists the attempt. There is a sort of teasing taking place between the film and its spectator: an invitation of decoding that is half-denied until the end, where the puzzle is finally solved. I will use three of Alejandro Iñárritu’s films to better convey my point: Amores perros (2000), 21 Grams (2003) and Babel (2006). I will consider Iñárritu’s methods to produce a non-linear storytelling as a way to stress the importance of time and its validity as one of the elements that make up for a metanarrative experience in films. I will focus especially on 21 Grams, which I consider to be a paragon of the labyrinth.

How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

On similarities in infrared spectra of complex drugs

A chromatographic separation of active ingredients of Combivir, Epivir, Kaletra, Norvir, Prezista, Retrovir, Trivizir, Valcyte, and Viramune is performed on thin layer chromatography. The spectra of these nine drugs were recorded using the Fourier transform infrared spectroscopy. This information is then analyzed by means of the cosine correlation. The comparison of the infrared spectra in the perspective of the adopted similarity measure is possible to visualize with present day computer tools, and the emerging clusters provide additional information about the similarities of the investigated set of complex drugs.

Two-loop stability of a complex singlet extended Standard Model

Motivated by the dark matter and the baryon asymmetry problems, we analyze a complex singlet extension of the Standard Model with a Z(2) symmetry (which provides a dark matter candidate). After a detailed two-loop calculation of the renormalization group equations for the new scalar sector, we study the radiative stability of the model up to a high energy scale (with the constraint that the 126 GeV Higgs boson found at the LHC is in the spectrum) and find it requires the existence of a new scalar state mixing with the Higgs with a mass larger than 140 GeV. This bound is not very sensitive to the cutoff scale as long as the latter is larger than 10(10) GeV. We then include all experimental and observational constraints/measurements from collider data, from dark matter direct detection experiments, and from the Planck satellite and in addition force stability at least up to the grand unified theory scale, to find that the lower bound is raised to about 170 GeV, while the dark matter particle must be heavier than about 50 GeV.

The Sinemurian ammonites of the Lusitanian Basin (Portugal): an example of complex endemic evolutioin

Palaeodiversity 3: 59–87; Stuttgart 30 December 2010

The alternative complex III from Rhodothermus marinus - a prototype of a new family of quinol: electron acceptor oxidoreductase

Dissertation presented to obtain a PhD degree in Biochemistry at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Energy transduction by respiratory complex I

Dissertation presented to obtain a PhD degree in Biochemistry at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

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.

Mycobacterium avium complex (MAC): an unusual potential pathogen in cerebrospinal fluid of AIDS patients

Mycobacterium avium complex (MAC) is frequently isolated from patients with late complications of Acquired Immunodeficiency Syndrome (AIDS), especially in North America and Europe. However, its isolation from the central nervous system (CNS) has been seldom reported in these countries. MAC infections in AIDS patients in African and Latin American countries are believed to be uncommon. We report the isolation of MAC from cerebrospinal fluid (CSF) of 11 AIDS patients out of 1723 (0.63%) seen at "Centro de Referência e Treinamento - AIDS", São Paulo and discuss the significance of its isolation.

População e Enriquecimento de Ontologias através de Web Scraping

O surgir da World Wide Web providenciou aos utilizadores uma série de oportunidades no que diz respeito ao acesso a dados e informação. Este acesso tornou-se um ato banal para qualquer utilizador da Web, tanto pelo utilizador comum como por outros mais experientes, tanto para obter informações básicas, como outras informações mais complexas. Todo este avanço tecnológico permitiu que os utilizadores tivessem acesso a uma vasta quantidade de informação, dispersa pelo globo, não tendo, na maior parte das vezes, a informação qualquer tipo de ligação entre si. A necessidade de se obter informação de interesse relativamente a determinado tema, mas tendo que recorrer a diversas fontes para obter toda a informação que pretende obter e comparar, torna-se um processo moroso para o utilizador. Pretende-se que este processo de recolha de informação de páginas web seja o mais automatizado possível, dando ao utilizador a possibilidade de utilizar algoritmos e ferramentas de análise e processamento automáticas, reduzindo desta forma o tempo e esforço de realização de tarefas sobre páginas web. Este processo é denominado Web Scraping. Neste trabalho é descrita uma arquitetura de sistema de web scraping automático e configurável baseado em tecnologias existentes, nomeadamente no contexto da web semântica. Para tal o trabalho desenvolvido analisa os efeitos da aplicação do Web Scraping percorrendo os seguintes pontos: • Identificação e análise de diversas ferramentas de web scraping; • Identificação do processo desenvolvido pelo ser humano complementar às atuais ferramentas de web scraping; • Design duma arquitetura complementar às ferramentas de web scraping que dê apoio ao processo de web scraping do utilizador; • Desenvolvimento dum protótipo baseado em ferramentas e tecnologias existentes; • Realização de experiências no domínio de aplicação de páginas de super-mercados portugueses; • Analisar resultados obtidos a partir destas.

Digital storytelling: an integrated approach to language for the 21st century student

Societal changes have, throughout history, pushed the long-established boundaries of education across all grade levels. Technology and media merge with education in a continuous complex social process with human consequences and effects. We, teachers, can aspire to understand and interpret this volatile context that is being redesigned at the same time society itself is being reshaped as a result of the technological evolution. The language- learning classroom is not impenetrable to these transformations. Rather, it can perhaps be seen as a playground where teachers and students gather to combine the past and the present in an integrated approach. We draw on the results from a previous study and argue that Digital Storytelling as a Process is capable of aggregating and fostering positive student development in general, as well as enhancing interpersonal relationships and self-knowledge while improving digital literacy. Additionally, we establish a link between the four basic language-learning skills and the Digital Storytelling process and demonstrate how these converge into what can be labeled as an integrated language learning approach.

RESEARCH OF ANTIGEN AND ANTIBODIES FROM RETROVIRUSES, CMV AND HBV AMONG PRISONERS OF THE PENITENTIARY COMPLEX OF THE REGION OF CAMPINAS, SP, BRAZIL

Some viruses of the families Retroviridae, such as Human T Lymphotropic Virus (HTLV); Herpesviridae as the Cytomegalovirus (CMV) and Hepadnaviridae such as the Hepatitis B Virus (HBV) are liable to be co-transmitted with the Human Immunodeficiency Virus (HIV). Since prisoners are exposed to several and important risk factors involved in the transmission of HIV and the above mentioned viruses, male inmates from the penitentiary complex of Campinas, SP, Brazil, including HIV + and HIV - ones, were examined for the presence of HTLV-I and/or II antibodies; IgG and IgM anti-CMV antibodies, and the research of the superficial hepatitis B antigen (HBsAg). The presence of anti-HTLV-I and/or II was determined by the Western Blot (WB) technique, whereas IgG and IgM anti-CMV and the search of HBsAg were carried out by the Microparticle Enzyme Immunoassay (MEIA-Abbott Lab).With regard to anti-HTLV-I and/or II, 58.3% (14/24-Number of positive reactions/number of sera examined) were reactive among the anti-HIV positive sera. Conversely, only 12.5% (3/24) among the HIV- negative sera showed positive reactions to HTLV-I and/or II antibodies. When looking for IgG anti-CMV percentages of 97.7% (43/44) and 95% (38/40) were obtained for anti-HIV positive and negative sera, respectively. As to IgM anti-CMV antibodies 11.36% (5/44) and 2.5% (1/40) of reactive sera were found for anti-HIV positive and negative, respectively. The HBsAg was found in 12.8% (5/39) of the sera which were anti-HIV positive.

Computational design with flexible backbone sampling for protein remodeling and scaffolding of complex binding sites

Dissertation presented to obtain the Doutoramento (Ph.D.) degree in Biochemistry at the Instituto de Tecnologia Qu mica e Biol ogica da Universidade Nova de Lisboa

Clinical and laboratory findings of disseminated Mycobacterium avium complex infection (DMAC) in a pair matched case-control study

A pair matched case/control study was conducted from January 1991 to 30 June 1992 in order to define clinical and laboratory findings associated with DMAC infection in AIDS patients. Since DMAC infection is usually associated with advanced immunodeficiency, and therefore also with other opportunistic illnesses, in addition to the number of CD4+ lymphocytes, cases and controls were matched using the following criteria: date of AIDS diagnosis and antiretroviral therapy, number and severity of associated opportunistic infections and, whenever possible, type of Pneumocystis carinii prophylaxis, age and gender, in this order of relevance. Cases (defined as patients presenting at least one positive culture for MAC at a normally sterile site) and controls presented CD4+ lymphocyte counts below 50 cel/mm3. A significantly higher prevalence of general, digestive and respiratory signs, increased LDH levels, low hemoglobin levels and CD4+ cell counts were recorded for cases when compared to controls. Increases in gGT and alkaline phosphatase levels seen in cases were also recorded for controls. In conclusion, the strategy we used for selecting controls allowed us to detect laboratory findings associated to DMAC infection not found in other advanced immunossupressed AIDS patients without DMAC.