Large time behaviour for functional differential equations with dominant eigenvalues of arbitrary order

The spectral theory for linear autonomous neutral functional differential equations (FDE) yields explicit formulas for the large time behaviour of solutions. Our results are based on resolvent computations and Dunford calculus, applied to establish explicit formulas for the large time behaviour of solutions of FDE. We investigate in detail a class of two-dimensional systems of FDE. (C) 2009 Elsevier Inc. All rights reserved.

A compound class of Weibull and power series distributions

In this paper we introduce the Weibull power series (WPS) class of distributions which is obtained by compounding Weibull and power series distributions where the compounding procedure follows same way that was previously carried out by Adamidis and Loukas (1998) This new class of distributions has as a particular case the two-parameter exponential power series (EPS) class of distributions (Chahkandi and Gawk 2009) which contains several lifetime models such as exponential geometric (Adamidis and Loukas 1998) exponential Poisson (Kus 2007) and exponential logarithmic (Tahmasbi and Rezaei 2008) distributions The hazard function of our class can be increasing decreasing and upside down bathtub shaped among others while the hazard function of an EPS distribution is only decreasing We obtain several properties of the WPS distributions such as moments order statistics estimation by maximum likelihood and inference for a large sample Furthermore the EM algorithm is also used to determine the maximum likelihood estimates of the parameters and we discuss maximum entropy characterizations under suitable constraints Special distributions are studied in some detail Applications to two real data sets are given to show the flexibility and potentiality of the new class of distributions (C) 2010 Elsevier B V All rights reserved

Efficient supervised optimum-path forest classification for large datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Molecular characterization and phylogenetic analysis of JussuMP-I: A RGD-P-III class hemorrhagic metalloprotease from Bothrops jararacussu snake venom

Snake venom metalloproteases (SVMPs) embody zinc-dependent multidomain enzymes responsible for a relevant pathophysiology in envenomation. including local and systemic hemorrhage. The molecular features responsible for hemorrhagic potency of SVMPs have been associated with their multidomains structures which can target these proteins them to several receptors of different tissues and cellular types. BjussuMP-I. a SVMP isolated from the Bothrops jararacussu venom, has been characterized as a P-III hemorrhagic metalloprotease. The complete cDNA sequence of BjussuMP-I with 1641bp encodes open reading frames of 547 amino acid residues, which conserve the common domains of P-III high molecular weight hemorrhagic metalloproteases: (i) pre-pro-peptide, (ii) metalloprotease, (iii) disintegrin-like and (iv) rich cysteine domain. BjussuMP-I induced lyses in fibrin clots and inhibited collagen- and ADP-induced platelet aggregation. We are reporting, for the first time, the primary structure of an RGD-P-III class snake venom metalloprotease. A phylogenetic analysis of the BjussuMP-1 metalloprotease/catalytic domain was performed to get new insights into the molecular evolution of the metalloproteases. A theoretical molecular model of this domain was built through folding recognition (threading) techniques and refined by molecular dynamics simulation. Then, the final BjussuMP-I catalytic domain model was compared to other SVMPs and Reprolysin family proteins in order to identify eventual structural differences, which could help to understand the biochemical activities of these enzymes. The presence of large hydrophobic areas and some conserved surface charge-positive residues were identified as important features of the SVMPs and other metalloproteases. (C) 2006 Elsevier B.V. All rights reserved.

Influence of atypical pluviosity on phytoplankton assemblages in a stretch of a large sub-tropical river (Brazil)

This study aimed to evaluate the influence of alterations in pluviosity and ecological variables on microphytoplankton (> 20 mu m) structure (composition, richness, diversity, and abundance) and its biomass (chlorophyll-a), comparing different regions in a stretch of the low Igua double dagger u River and in some tributaries. Phytoplankton was sampled in 10 stations (5 in Igua double dagger u River and 5 in tributaries) during a dry period (April/2004) and an atypical rainy period (June/2004). The conductivity showed significant difference among the sampling points. Temperature, dissolved oxygen, pH, silicate, and nitrate showed significant differences between the dry and wet periods. Phytoplankton was composed of 149 taxa, and the most representative class was Chlorophyceae (71 taxa), followed by Bacillariophyceae (35 taxa), and Cyanophyceae (25 taxa). During the rainy period, stations of Igua double dagger u River showed higher taxa number and total density compared to the tributaries, but the values were similar in the dry period. Tributaries presented higher diversity and equitability in both periods. Except by two stations in Igua double dagger u River, the higher taxa number, densities and biomass occurred in the dry period, associated to low levels of suspended matter. The canonical correspondence analysis indicated the dominance of Bacillariophyceae and Chrysophyceae in the rainy period related to nitrate and suspended matter. Two other groups were observed in the dry period: one formed by Cyanophyceae, Dinophyceae, and Rhodophyceae, related to temperature and nitrite and other by Euglenophyceae and Chlorophyceae related to total phosphorus and silicate. The groups suggest adequate conditions of the physical, chemical and climatic factors to the establishment of the algae classes. Phytoplanktonic assemblages responded quickly to the environmental regional variations under strong influence of pluviosity, while in the dry period, homogeneity among stations and environmental variables was observed. The importance of climatic events is relevant in ecological studies in a temporal scale.

On the worldsheet derivation of large N dualities for the superstring

Large N topological string dualities have led to a class of proposed open/ closed dualities for superstrings. In the topological string context, the worldsheet derivation of these dualities has already been given. In this paper we take the first step in deriving the full ten-dimensional superstring dualities by showing how the dualities arise on the superstring worldsheet at the level of F terms. As part of this derivation, we show for F-term computations that the hybrid formalism for the superstring is equivalent to a (c) over cap = 5 topological string in ten-dimensional spacetime. Using the (c) over cap = 5 description, we then show that the D brane boundary state for the ten-dimensional open superstring naturally emerges on the worldsheet of the closed superstring dual.

Conservative prosthetic-periodontal treatment for molar class iii furcation involvement: Case report

Purpose: The treatment for furcation involvement is a great challenge to the general dentists. Tunneling may be a treatment alternative for class II and III furcation involvements in mandibular molars with large angle separation and great divergence between the mesial and distal roots. This alternative is a conservative treatment that allows a great condition to oral hygiene maintenance by the patient. Thus, the aim of this case report was to describe a conservative and therapeutic treatment modality for the horizontal defect of periodontal tissues in the furcal area with buccal-lingual extension (class III furcation involvement). Case Report: A patient with class III furcation involvement in the first mandibular molar was submitted to root resection and periodontal surgery to expose the clinical crown for the full-coverage restoration with tunnel preparation. Results: The final result of the treatment with tunneled crown was favorable and predictable due to adequate hygiene condition to avoid plaque accumulation and occurrence of root caries. Clinical Significance: A multidisciplinary approach is essential to achieve a correct treatment plan including surgical-periodontal procedures integrated to the prosthetic rehabilitation. Besides, the recommendation for oral hygiene maintenance is essential for the treatment longevity with tunneled crown. © 2011 Nova Science Publishers, Inc.

P-I class metalloproteinase from Bothrops moojeni venom is a post-proline cleaving peptidase with kininogenase activity: Insights into substrate selectivity and kinetic behavior

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

MCAO for Extremely Large Telescopes: the cases of LBT and E-ELT

Several MCAO systems are under study to improve the angular resolution of the current and of the future generation large ground-based telescopes (diameters in the 8-40 m range). The subject of this PhD Thesis is embedded in this context. Two MCAO systems, in dierent realization phases, are addressed in this Thesis: NIRVANA, the 'double' MCAO system designed for one of the interferometric instruments of LBT, is in the integration and testing phase; MAORY, the future E-ELT MCAO module, is under preliminary study. These two systems takle the sky coverage problem in two dierent ways. The layer oriented approach of NIRVANA, coupled with multi-pyramids wavefront sensors, takes advantage of the optical co-addition of the signal coming from up to 12 NGS in a annular 2' to 6' technical FoV and up to 8 in the central 2' FoV. Summing the light coming from many natural sources permits to increase the limiting magnitude of the single NGS and to improve considerably the sky coverage. One of the two Wavefront Sensors for the mid- high altitude atmosphere analysis has been integrated and tested as a stand- alone unit in the laboratory at INAF-Osservatorio Astronomico di Bologna and afterwards delivered to the MPIA laboratories in Heidelberg, where was integrated and aligned to the post-focal optical relay of one LINC-NIRVANA arm. A number of tests were performed in order to characterize and optimize the system functionalities and performance. A report about this work is presented in Chapter 2. In the MAORY case, to ensure correction uniformity and sky coverage, the LGS-based approach is the current baseline. However, since the Sodium layer is approximately 10 km thick, the articial reference source looks elongated, especially when observed from the edge of a large aperture. On a 30-40 m class telescope, for instance, the maximum elongation varies between few arcsec and 10 arcsec, depending on the actual telescope diameter, on the Sodium layer properties and on the laser launcher position. The centroiding error in a Shack-Hartmann WFS increases proportionally to the elongation (in a photon noise dominated regime), strongly limiting the performance. To compensate for this effect a straightforward solution is to increase the laser power, i.e. to increase the number of detected photons per subaperture. The scope of Chapter 3 is twofold: an analysis of the performance of three dierent algorithms (Weighted Center of Gravity, Correlation and Quad-cell) for the instantaneous LGS image position measurement in presence of elongated spots and the determination of the required number of photons to achieve a certain average wavefront error over the telescope aperture. An alternative optical solution to the spot elongation problem is proposed in Section 3.4. Starting from the considerations presented in Chapter 3, a first order analysis of the LGS WFS for MAORY (number of subapertures, number of detected photons per subaperture, RON, focal plane sampling, subaperture FoV) is the subject of Chapter 4. An LGS WFS laboratory prototype was designed to reproduce the relevant aspects of an LGS SH WFS for the E-ELT and to evaluate the performance of different centroid algorithms in presence of elongated spots as investigated numerically and analytically in Chapter 3. This prototype permits to simulate realistic Sodium proles. A full testing plan for the prototype is set in Chapter 4.

Quality of Service in Distributed Stream Processing for large scale Smart Pervasive Environments

The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs.

From large polycyclic aromatic hydrocarbons to extended aromate-rich networks

The common ground of this study is the development of novel synthetic strategies to extended one-, two- and three-dimensional aromate-rich systems for which a number of applications are envisaged. rnThe point of departure is the synthesis and characterization of highly symmetric macrocyclic PAHs (polycyclic aromatic hydrocarbons) for which various aspects of supramolecular chemistry will be investigated. The versatility of the Yamamoto macrocyclization will be demonstrated on the basis of a set of cyclic trimers that exhibit a rich supramolecular chemistry. 1,10-phenanthroline, triphenylene and ortho-terphenyl building blocks have been successfully assembled to the corresponding macrocycles following the newly developed synthetic route. Scanning-tunneling microscopy (STM) and two-dimensional wide-angle X-ray scattering (2D-WAXS) were used to study the two- and three-dimensional self-assembly, respectively.rnSecondly, the development of chemical approaches to highly shape-anisotropic graphene nanoribbons (GNRs) and related nanographene molecules shall be discussed. Aryl-aryl coupling was used for the bottom-up fabrication of dendronized monomers, polymers and model compounds. Subsequently, these structures were converted into the final graphene material using oxidative (Scholl-type) cyclodehydrogenation. The GNRs thus obtained are characterized by an unprecedented length and lateral extension. The relevance of structural tailoring in the field of well-defined graphene materials is discussed in detail as only the chemical approach provides full geometry control. rnLastly, novel pathways towards the synthesis of extended three-dimensional networks that are dominated by nitrogen-rich motifs will be presented. If porous, these materials hold a great potential in the fields of gas and energy storage as well as for applications in catalysis. Hence, poly(aminal) networks based on melamine as crosslinking unit were synthesized and characterized with respect to the applications mentioned above. As set of conjugated poly(azomethine) networks was investigated regarding their use as a novel class of organic semiconductors for photocatalytic water splitting. The network structures described in this chapter can also be subjected to a controlled pyrolysis yielding mesoporous, nitrogen-rich carbon materials that were evaluated as active component for supercapacitors.rn

A new class of bragg stacks and its principle application

This work is focused on the development of high quality nanoporous 1D photonic crystals –so called Bragg stacks – made by spin-coating of approximately 25 nm large SiO2 and TiO2 nanoparticles bearing interparticle voids large enough to infiltrate reactive species. Therefore, the first part of this work describes the synthesis of well-dispersed TiO2 nanoparticles in this size range (the corresponding SiO2 nanoparticles are commercially available). In the second part, a protocol was developed to prepare nanoporous Bragg stacks of up to 12 bilayers with high quality and precision. Tailor-made Bragg stacks were prepared for different applications such as (i) a surface emitting feedback laser with a FWHM of only 6 nm and (ii) an electrochromic device with absorption reversibly switchable by an external electrical bias independently of the Bragg reflection. In the last chapter, the approach to 1D photonic crystals is transferred to 1D phononic crystals. Contrast in the modulus is achieved by spin-coating SiO2 and PMMA as high and low moduli material. This system showed a band gap of fg = 12.6 GHz with a width of Dfg/fg = 4.5 GHz.

Mining for Class-Specific Motifs in Protein Sequence Classification

Background: In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results: We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion: The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms.

Structural basis for the regulation of cysteine-protease activity by a new class of protease inhibitors in Plasmodium

Plasmodium cysteine proteases are essential for host-cell invasion and egress, hemoglobin degradation, and intracellular development of the parasite. The temporal, site-specific regulation of cysteine-protease activity is a prerequisite for survival and propagation of Plasmodium. Recently, a new family of inhibitors of cysteine proteases (ICPs) with homologs in at least eight Plasmodium species has been identified. Here, we report the 2.6 A X-ray crystal structure of the C-terminal, inhibitory domain of ICP from P. berghei (PbICP-C) in a 1:1 complex with falcipain-2, an important hemoglobinase of Plasmodium. The structure establishes Plasmodium ICP as a member of the I42 class of chagasin-like protease inhibitors but with large insertions and differences in the binding mode relative to other family members. Furthermore, the PbICP-C structure explains why host-cell cathepsin B-like proteases and, most likely, also the protease-like domain of Plasmodium SERA5 (serine-repeat antigen 5) are no targets for ICP.

Squared Extrapolation Methods (SQUAREM): A New Class of Simple and Efficient Numerical Schemes for Accelerating the Convergence of the EM Algorithm

We derive a new class of iterative schemes for accelerating the convergence of the EM algorithm, by exploiting the connection between fixed point iterations and extrapolation methods. First, we present a general formulation of one-step iterative schemes, which are obtained by cycling with the extrapolation methods. We, then square the one-step schemes to obtain the new class of methods, which we call SQUAREM. Squaring a one-step iterative scheme is simply applying it twice within each cycle of the extrapolation method. Here we focus on the first order or rank-one extrapolation methods for two reasons, (1) simplicity, and (2) computational efficiency. In particular, we study two first order extrapolation methods, the reduced rank extrapolation (RRE1) and minimal polynomial extrapolation (MPE1). The convergence of the new schemes, both one-step and squared, is non-monotonic with respect to the residual norm. The first order one-step and SQUAREM schemes are linearly convergent, like the EM algorithm but they have a faster rate of convergence. We demonstrate, through five different examples, the effectiveness of the first order SQUAREM schemes, SqRRE1 and SqMPE1, in accelerating the EM algorithm. The SQUAREM schemes are also shown to be vastly superior to their one-step counterparts, RRE1 and MPE1, in terms of computational efficiency. The proposed extrapolation schemes can fail due to the numerical problems of stagnation and near breakdown. We have developed a new hybrid iterative scheme that combines the RRE1 and MPE1 schemes in such a manner that it overcomes both stagnation and near breakdown. The squared first order hybrid scheme, SqHyb1, emerges as the iterative scheme of choice based on our numerical experiments. It combines the fast convergence of the SqMPE1, while avoiding near breakdowns, with the stability of SqRRE1, while avoiding stagnations. The SQUAREM methods can be incorporated very easily into an existing EM algorithm. They only require the basic EM step for their implementation and do not require any other auxiliary quantities such as the complete data log likelihood, and its gradient or hessian. They are an attractive option in problems with a very large number of parameters, and in problems where the statistical model is complex, the EM algorithm is slow and each EM step is computationally demanding.