Horizontal and vertical tree community structure in a lowland atlantic rain forest, southeastern Brazil

A estrutura horizontal e vertical do componente arbóreo foi investigada em um trecho de Floresta Atlântica baixo-montana através de um levantamento fitossociológico em dois blocos amostrais de 0,99 ha cada no Parque Estadual Intervales. Todos os indivíduos com DAP > 5 cm foram registrados. Foram amostrados 3.078 indivíduos distribuídos em 172 espécies. O índice de diversidade de Shannon foi de H' = 3,85 nat.ind.-1. A família Myrtaceae se destacou tanto em número de espécies (38) quanto em número de indivíduos (745) no levantamento. Euterpe edulis Mart. teve o maior valor de importância (33,98%), abrangendo 21,8% do total de indivíduos registrados. O índice de similaridade quantitativo foi maior do que o qualitativo, mostrando pouca variação estrutural entre os blocos amostrais, mas a grande quantidade de espécies pouco abundantes, resultou em pronunciadas diferenças florísticas entre eles. Uma análise de correspondência retificada (DCA) gerou três estratos verticais arbitrários. O estrato A (> 26 m) teve a menor densidade e foi bem representado pelas espécies Sloanea guianensis (Aubl.) Benth. e Virola bicuhyba (Schott. ex A.DC.) Warb. O estrato B (8 m < h < 26 m) mostrou a maior riqueza e diversidade florística, e o estrato C (< 8 m) a maior densidade. Euterpe edulis, Guapira opposita (Vell.) Reitz, Garcinia gardneriana (Planch. & Triana) Zappi e Eugenia mosenii (Kausel) Sobral foram bem representadas nos estratos B e C da floresta. A existência de estratos verticais em florestas tropicais é discutida, recomendando-se o uso da DCA para estudos da estratificação vertical em outras florestas tropicais.

Structural and functional characterization of neuwiedase, a nonhemorrhagic fibrin(ogen)olytic metalloprotease from Bothrops neuwiedi snake venom

A fibrino(geno)lytic nonhemorrhagic metalloprotease (neuwiedase) was purified from Bothrops neuwiedi snake venom by a single chromatographic step procedure on a CM-Sepharose column, Neuwiedase represented 4.5% (w/w) of the crude desiccated venom, with an approximate Mr of 20,000 and pI 5.9, As regards the amino acid composition, neuwiedase showed similarities with other metalloproteases, with high proportions of Asx, Glx, Leu, and Ser, Atomic absorption spectroscopy showed that one mole of Zn2+ and one mole of Ca2+ were present per mole olf protein. The cDNA encoding neuwiedase was isolated by RT-PCR from venom gland RNA, using oligonucleotides based on the partially determined amino-acid sequences of this metalloprotease. The fall sequence contained approximately 594 bp, which codified the 198 amino acid residues with an estimated molecular weight of 22,375. Comparison of the nucleotide and amino acid sequences of neuwiedase with those of other snake venom metalloproteases showed a high level of sequential similarity, Neuwiedase has two highly conserved characteristics sequences H(142)E(143)XXH(146)XXG(140)XXH(152) and C164I165M166. The three-dimensional structure of neuwiedase was modeled based on the crystal structure of Crotalus adamanteus Adamalysin II. This model revealed that the zinc binding site region showed a I high structural similarity with other metalloproteases,, the proteolyitc specificity, using the B beta-chain of oxidized insulin as substrate, was shown to be directed to the Ala(14)-Leu(15) and Tyr(16)-Leu(17) peptide bonds which were preferentially hydrolyzed. Neuwiedase is a A alpha,B beta fibrinogenase, Its activity upon the A alpha chain of fibrinogen was detected within 15 min of incubation. The optimal temperature and pH for the degradation of both A alpha and B beta chains were 37 degrees C and 7.4-8.0, respectively. This activity was inhibited by EDTA and 1,10-phenantroline, Neuwiedase also showed proteolytic activity upon fibrin and some components of the extracellular matrix. However, it did not show TAME esterase activity and was not able to inhibit platelet aggregation. (C) 2000 Academic Press.

Estrutura de comunidades e influência da heterogeneidade ambiente na diversidade de anuros em área de pastagem no sudeste do Brasil

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

Uma abordagem híbrida e semiautomática para estimativa de regiões cobertas por nuvens e sombras em imagens de satélite: análise e avaliação

Os principais objetivos deste trabalho são propor um algoritmo eficiente e o mais automático possível para estimar o que está coberto por regiões de nuvens e sombras em imagens de satélite; e um índice de confiabilidade, que seja aplicado previamente à imagem, visando medir a viabilidade da estimação das regiões cobertas pelos componentes atmosféricos usando tal algoritmo. A motivação vem dos problemas causados por esses elementos, entre eles: dificultam a identificação de objetos de imagem, prejudicam o monitoramento urbano e ambiental, e desfavorecem etapas cruciais do processamento digital de imagens para extrair informações ao usuário, como segmentação e classificação. Através de uma abordagem híbrida, é proposto um método para decompor regiões usando um filtro passa-baixas não-linear de mediana, a fim de mapear as regiões de estrutura (homogêneas), como vegetação, e de textura (heterogêneas), como áreas urbanas, na imagem. Nessas áreas, foram aplicados os métodos de restauração Inpainting por suavização baseado em Transformada Cosseno Discreta (DCT), e Síntese de Textura baseada em modelos, respectivamente. É importante salientar que as técnicas foram modificadas para serem capazes de trabalhar com imagens de características peculiares que são obtidas por meio de sensores de satélite, como por exemplo, as grandes dimensões e a alta variação espectral. Já o índice de confiabilidade, tem como objetivo analisar a imagem que contém as interferências atmosféricas e daí estimar o quão confiável será a redefinição com base no percentual de cobertura de nuvens sobre as regiões de textura e estrutura. Tal índice é composto pela combinação do resultado de algoritmos supervisionados e não-supervisionados envolvendo 3 métricas: Exatidão Global Média (EGM), Medida De Similaridade Estrutural (SSIM) e Confiança Média Dos Pixels (CM). Finalmente, verificou-se a eficácia destas metodologias através de uma avaliação quantitativa (proporcionada pelo índice) e qualitativa (pelas imagens resultantes do processamento), mostrando ser possível a aplicação das técnicas para solucionar os problemas que motivaram a realização deste trabalho.

Function inferences from a molecular structural model of bacterial ParE toxin

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

Definição de framework para a padronização de processos em um periódico científico com base em revisão da literatura e nos objetivos de desempenho

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts

The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.

(Table 2) Similarity Indexes (Pearson's correlation coefficient) of the silicoflagellate assemblages of IODP Exp302

The silicoflagellate and ebridian assemblages in early middle Eocene Arctic cores obtained by IODP Expedition 302 (ACEX) were studied in order to decipher the paleoceanography of the upper water column. The assemblages in Lithologic Unit 2 (49.7-45.1 Ma), one of the biosiliceous intervals, were usually endemic as compared to the assemblages that occurred outside of the Arctic Ocean. The presence of these endemic assemblages is probably due to a unique environmental setting, controlled by the degree of mixing between the low-salinity Arctic waters and relatively high salinity waters supplied from outside the Arctic Ocean, such as the Atlantic and possibly the Western Siberian Sea. Using the basin-to-basin fractionation model, the early middle Eocene Arctic Ocean corresponds to an estuarine circulation type, which includes the modern-day Black Sea. The abundant down-core occurrence of ebridians strongly suggests the past presence of low-salinity waters, and may indicate that low oxygen concentrations prevailed in the euphotic layer, on the basis of the ecology of the modern ebridian Hermesinum adriaticum.

Probability sampling protocol of classification maps from spaceborne/airborne image

To deliver sample estimates provided with the necessary probability foundation to permit generalization from the sample data subset to the whole target population being sampled, probability sampling strategies are required to satisfy three necessary not sufficient conditions: (i) All inclusion probabilities be greater than zero in the target population to be sampled. If some sampling units have an inclusion probability of zero, then a map accuracy assessment does not represent the entire target region depicted in the map to be assessed. (ii) The inclusion probabilities must be: (a) knowable for nonsampled units and (b) known for those units selected in the sample: since the inclusion probability determines the weight attached to each sampling unit in the accuracy estimation formulas, if the inclusion probabilities are unknown, so are the estimation weights. This original work presents a novel (to the best of these authors' knowledge, the first) probability sampling protocol for quality assessment and comparison of thematic maps generated from spaceborne/airborne Very High Resolution (VHR) images, where: (I) an original Categorical Variable Pair Similarity Index (CVPSI, proposed in two different formulations) is estimated as a fuzzy degree of match between a reference and a test semantic vocabulary, which may not coincide, and (II) both symbolic pixel-based thematic quality indicators (TQIs) and sub-symbolic object-based spatial quality indicators (SQIs) are estimated with a degree of uncertainty in measurement in compliance with the well-known Quality Assurance Framework for Earth Observation (QA4EO) guidelines. Like a decision-tree, any protocol (guidelines for best practice) comprises a set of rules, equivalent to structural knowledge, and an order of presentation of the rule set, known as procedural knowledge. The combination of these two levels of knowledge makes an original protocol worth more than the sum of its parts. The several degrees of novelty of the proposed probability sampling protocol are highlighted in this paper, at the levels of understanding of both structural and procedural knowledge, in comparison with related multi-disciplinary works selected from the existing literature. In the experimental session the proposed protocol is tested for accuracy validation of preliminary classification maps automatically generated by the Satellite Image Automatic MapperT (SIAMT) software product from two WorldView-2 images and one QuickBird-2 image provided by DigitalGlobe for testing purposes. In these experiments, collected TQIs and SQIs are statistically valid, statistically significant, consistent across maps and in agreement with theoretical expectations, visual (qualitative) evidence and quantitative quality indexes of operativeness (OQIs) claimed for SIAMT by related papers. As a subsidiary conclusion, the statistically consistent and statistically significant accuracy validation of the SIAMT pre-classification maps proposed in this contribution, together with OQIs claimed for SIAMT by related works, make the operational (automatic, accurate, near real-time, robust, scalable) SIAMT software product eligible for opening up new inter-disciplinary research and market opportunities in accordance with the visionary goal of the Global Earth Observation System of Systems (GEOSS) initiative and the QA4EO international guidelines.

The bacterial helicase-primase interaction: a common structural/functional module

The lack of a high-resolution structure for the bacterial helicase-primase complex and the fragmented structural information for the individual proteins have been hindering our detailed understanding of this crucial binary protein interaction. Two new structures for the helicase-interacting domain of the bacterial primases from Escherichia coli and Bacillus stearothermophilus have recently been solved and both revealed a unique and surprising structural similarity to the amino-terminal domain of the helicase itself. In this minireview, the current data are discussed and important new structural and functional aspects of the helicase-primase interaction are highlighted. An attractive structural model with direct biological significance for the function of this complex and also for the development of new antibacterial compounds is examined.

Prediction of peptide and protein propensity for amyloid formation

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

HCX : an efficient hybrid clustering approach for XML documents

This paper proposes a novel Hybrid Clustering approach for XML documents (HCX) that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The empirical analysis reveals that the proposed method is scalable and accurate.

XCFS - a novel approach for clustering XML documents using both the structure and the content

XML document clustering is essential for many document handling applications such as information storage, retrieval, integration and transformation. An XML clustering algorithm should process both the structural and the content information of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. This paper introduces a novel approach that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The proposed method reduces the high dimensionality of input data by using only the structure-constrained content. The empirical analysis reveals that the proposed method can effectively cluster even very large XML datasets and outperform other existing methods.

The synthesis of novel nitroxides and their application as small-molecule antioxidants and profluorescent probes for oxidative stress

The detection and potential treatment of oxidative stress in biological systems has been explored using isoindoline-based nitroxide radicals. A novel tetraethyl-fluorescein nitroxide was synthesised for its use as a profluorescent probe for redox processes in biological systems. This tetraethyl system, as well as a tetramethyl-fluorescein nitroxide, were shown to be sensitive and selective probes for superoxide in vitro. The redox environment of cellular systems was also explored using the tetramethylfluorescein species based on its reduction to the hydroxylamine. Flow cytometry was employed to assess the extent of nitroxide reduction, reflecting the overall cellular redox environment. Treatment of normal fibroblasts with rotenone and 2-deoxyglucose resulted in an oxidising cellular environment as shown by the lack of reduction of the fluorescein-nitroxide system. Assessment of the tetraethyl-fluorescein nitroxide system in the same way demonstrated its enhanced resistance to reduction and offers the potential to detect and image biologically relevant reactive oxygen species directly. Importantly, these profluorescent nitroxide compounds were shown to be more effective than the more widely used and commercially available probes for reactive oxygen species such as 2’,7’-dichlorodihydrofluorescein diacetate. Fluorescence imaging of the tetramethyl-fluorescein nitroxide and a number of other rhodamine-nitroxide derivatives was undertaken, revealing the differential cellular localisation of these systems and thus their potential for the detection of redox changes in specific cellular compartments. As well as developing novel methods for the detection of oxidative stress, a number of novel isoindoline nitroxides were synthesised for their potential application as small-molecule antioxidants. These compounds incorporated known pharmacophores into the isoindoline-nitroxide structure in an attempt to increase their efficacy in biological systems. A primary and a secondary amine nitroxide were synthesised which incorporated the phenethylamine backbone of the sympathomimetic amine class of drugs. Initial assessment of the novel primary amine derivative indicated a protective effect comparable to that of 5-carboxy-1,1,3,3- tetramethylisoindolin-2-yloxyl. Methoxy-substituted nitroxides were also synthesised as potential antioxidants for their structural similarity to some amphetamine type stimulants. A copper-catalysed methodology provided access to both the mono- and di-substituted methoxy-nitroxides. Deprotection of the ethers in these compounds using boron tribromide successfully produced a phenolnitroxide, however the catechol moiety in the disubstituted derivative appeared to undergo reaction with the nitroxide to produce quinone-like degradation products. A novel fluoran-nitroxide was also synthesised from the methoxy-substituted nitroxide, providing a pH-sensitive spin probe. An amino-acid precursor containing a nitroxide moiety was also synthesised for its application as a dual-action antioxidant. N-Acetyl protection of the nitroxide radical was necessary prior to the Erlenmeyer reaction with N-acetyl glycine. Hydrolysis and reduction of the azlactone intermediate produced a novel amino acid precursor with significant potential as an effective antioxidant.

Enriching XML documents clustering by using concise structure and content

With the growing number of XML documents on theWeb it becomes essential to effectively organise these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. However, many issues arise in discovering knowledge from these types of semi-structured documents due to their heterogeneity and structural irregularity. Most of the existing research on clustering techniques focuses only on one feature of the XML documents, this being either their structure or their content due to scalability and complexity problems. The knowledge gained in the form of clusters based on the structure or the content is not suitable for reallife datasets. It therefore becomes essential to include both the structure and content of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both these kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. The overall objective of this thesis is to address these issues by: (1) proposing methods to utilise frequent pattern mining techniques to reduce the dimension; (2) developing models to effectively combine the structure and content of XML documents; and (3) utilising the proposed models in clustering. This research first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. A clustering framework with two types of models, implicit and explicit, is developed. The implicit model uses a Vector Space Model (VSM) to combine the structure and the content information. The explicit model uses a higher order model, namely a 3- order Tensor Space Model (TSM), to explicitly combine the structure and the content information. This thesis also proposes a novel incremental technique to decompose largesized tensor models to utilise the decomposed solution for clustering the XML documents. The proposed framework and its components were extensively evaluated on several real-life datasets exhibiting extreme characteristics to understand the usefulness of the proposed framework in real-life situations. Additionally, this research evaluates the outcome of the clustering process on the collection selection problem in the information retrieval on the Wikipedia dataset. The experimental results demonstrate that the proposed frequent pattern mining and clustering methods outperform the related state-of-the-art approaches. In particular, the proposed framework of utilising frequent structures for constraining the content shows an improvement in accuracy over content-only and structure-only clustering results. The scalability evaluation experiments conducted on large scaled datasets clearly show the strengths of the proposed methods over state-of-the-art methods. In particular, this thesis work contributes to effectively combining the structure and the content of XML documents for clustering, in order to improve the accuracy of the clustering solution. In addition, it also contributes by addressing the research gaps in frequent pattern mining to generate efficient and concise frequent subtrees with various node relationships that could be used in clustering.