Floral anatomy of Paepalanthoideae (Eriocaulaceae, Poales) and their nectariferous structures

• Background and Aims: Eriocaulaceae (Poales) is currently divided in two subfamilies: Eriocauloideae, which comprises two genera and Paepalanthoideae, with nine genera. The floral anatomy of Actinocephalus polyanthus, Leiothrix fluitans, Paepalanthus chlorocephalus, P. flaccidus and Rondonanthus roraimae was studied here. The flowers of these species of Paepalanthoideae are unisexual, and form capitulum-type inflorescences. Staminate and pistillate flowers are randomly distributed in the capitulum and develop centripetally. This work aims to establish a floral nomenclature for the Eriocaulaceae to provide more information about the taxonomy and phylogeny of the family. • Methods: Light microscopy, scanning electron microscopy and chemical tests were used to investigate the floral structures. • Key Results: Staminate and pistillate flowers are trimerous (except in P. flaccidus, which presents dimerous flowers), and the perianth of all species is differentiated into sepals and petals. Staminate flowers present an androecium with scale-like staminodes (not in R. roraimae) and fertile stamens, and nectariferous pistillodes. Pistillate flowers present scale-like staminodes (except for R. roraimae, which presents elongated and vascularized staminodes), and a gynoecium with a hollow style, ramified in stigmatic and nectariferous portions. • Conclusions: The scale-like staminodes present in the species of Paepalanthoideae indicate a probable reduction of the outer whorl of stamens present in species of Eriocauloideae. Among the Paepalanthoideae genera, Rondonanthus, which is probably basal, shows vascularized staminodes in their pistillate flowers. The occurrence of nectariferous pistillodes in staminate flowers and that of nectariferous portions of the style in pistillate flowers of Paepalanthoideae are emphasized as nectariferous structures in Eriocaulaceae. © The Author 2006. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

Classification of lumber of Eucalyptus using non-destructive tests

Classification and standardization of the sawn wood is a usual activity, developed by countries that come as great consumers of this material. Brazil does not practice the classification of sawn wood. This work had the main objective of evaluating the sensibility of most common non-destructive tests in the classification of dimension lumber from fast grown Eucalyptus plantation. Wood was obtained from genetic material cultivated at Minas Gerais State, Brazil. 296 beams of structural dimensions (6 cm × 12 cm × 280 cm) from 10 different clones of Eucalyptus were sampled. Beams were non-destructively (stress wave, ultrasound and transverse vibration) and destructively (static bending and compression parallel to grain) tested. Non-destructive results showed sensibility in the classification of structural dimension lumber, being possible to establish wave velocity intervals that attend to the main strength classes reported by Wooden Structures Brazilian Code.

The role of hierarchical morphologies in the superior gas sensing performance of CuO-based chemiresistors

The development of gas sensors with innovative designs and advanced functional materials has attracted considerable scientific interest given their potential for addressing important technological challenges. This work presents new insight towards the development of high-performance p-type semiconductor gas sensors. Gas sensor test devices, based on copper (II) oxide (CuO) with innovative and unique designs (urchin-like, fiber-like, and nanorods), are prepared by a microwave-assisted synthesis method. The crystalline composition, surface area, porosity, and morphological characteristics are studied by X-ray powder diffraction, nitrogen adsorption isotherms, field-emission scanning electron microscopy and high-resolution transmission electron microscopy. Gas sensor measurements, performed simultaneously on multiple samples, show that morphology can have a substantial influence on gas sensor performance. An assembly of urchin-like structures is found to be most effective for hydrogen detection in the range of parts-per-million at 200 °C with 300-fold larger response than the previously best reported values for semiconducting CuO hydrogen gas sensors. These results show that morphology plays an important role in the gas sensing performance of CuO and can be effectively applied in the further development of gas sensors based on p-type semiconductors. High-performance gas sensors based on CuO hierarchical morphologies with in situ gas sensor comparison are reported. Urchin-like morphologies with high hydrogen sensitivity and selectivity that show chemical and thermal stability and low temperature operation are analyzed. The role of morphological influences in p-type gas sensor materials is discussed. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Classification of honeys from Pará State (Amazon region, Brazil) produced by three different species of bees

Vinte e sete amostras de mel, produzidas em dez cidades do Estado do Pará (Região Amazônica, norte do Brasil) por três espécies diferentes de abelhas (Apis mellifera, Melipona fasciculata e Melipona flavoneata), foram analisadas em seus teores de elementos minerais (Al, As, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sr e Zn) e alguns parâmetros fisicoquímicos (cor, umidade, densidade, pH, sólidos insolúveis e solúveis totais, cinzas, condutividade elétrica, índice de formol, acidez livre, hidroximetilfurfural, açúcares redutores e totais e sacarose). Os teores minerais foram determinados via espectrometria de emissão atômica por plasma acoplado indutivamente (ICP OES) e as análises dos parâmetros físico-químicos seguiram metodologias oficiais. Os resultados das análises físico-químicas apresentaram-se de acordo com a legislação nacional e internacional, bem como com outros trabalhos similares ao redor do mundo. A análise estatística multivariada (análise por agrupamento hierárquico (HCA) e por componentes principais (PCA)) foi aplicada aos resultados dos teores metálicos e aos parâmetros físico-químicos, sendo possível a separação das amostras de mel conforme a espécie produtora.

Mapeando o conhecimento em sistemas de classificação de bibliotecas

This study explores, in 3 steps, how the 3 main library classification systems, the Library of Congress Classification, the Dewey Decimal Classification, and the Universal Decimal Classification, cover human knowledge. First, we mapped the knowledge covered by the 3 systems. We used the “10 Pillars of Knowledge: Map of Human Knowledge”, which comprises 10 pillars, as an evaluative model. We mapped all the subject-based classes and subclasses that are part of the first 2 levels of the 3 hierarchical structures. Then, we zoomed into each of the 10 pillars and analyzed how the three systems cover the 10 knowledge domains. Finally, we focused on the 3 library systems. Based on the way each one of them covers the 10 knowledge domains, it is evident that they failed to adequately and systematically present contemporary human knowledge. They are unsystematic and biased, and, at the top 2 levels of the hierarchical structures, they are incomplete.

Long-range and short-range structures of cube-like shape SrTiO3 powders: microwave-assisted hydrothermal synthesis and photocatalytic activity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Self-Organizing Maps of Molecular Descriptors for Sesquiterpene Lactones and Their Application to the Chemotaxonomy of the Asteraceae Family

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Homogeneous structures and rigidity of isoparametric submanifolds in Hilbert space

We study isoparametric submanifolds of rank at least two in a separable Hilbert space, which are known to be homogeneous by the main result in [E. Heintze and X. Liu, Ann. of Math. (2), 149 (1999), 149-181], and with such a submanifold M and a point x in M we associate a canonical homogeneous structure I" (x) (a certain bilinear map defined on a subspace of T (x) M x T (x) M). We prove that I" (x) , together with the second fundamental form alpha (x) , encodes all the information about M, and we deduce from this the rigidity result that M is completely determined by alpha (x) and (Delta alpha) (x) , thereby making such submanifolds accessible to classification. As an essential step, we show that the one-parameter groups of isometries constructed in [E. Heintze and X. Liu, Ann. of Math. (2), 149 (1999), 149-181] to prove their homogeneity induce smooth and hence everywhere defined Killing fields, implying the continuity of I" (this result also seems to close a gap in [U. Christ, J. Differential Geom., 62 (2002), 1-15]). Here an important tool is the introduction of affine root systems of isoparametric submanifolds.

The Ecological Basis for Biogeographic Classification: an Example in Orchid Bees (Apidae: Euglossini)

Biogeography has been difficult to apply as a methodological approach because organismic biology is incomplete at levels where the process of formulating comparisons and analogies is complex. The study of insect biogeography became necessary because insects possess numerous evolutionary traits and play an important role as pollinators. Among insects, the euglossine bees, or orchid bees, attract interest because the study of their biology allows us to explain important steps in the evolution of social behavior and many other adaptive tradeoffs. We analyzed the distribution of morphological characteristics in Colombian orchid bees from an ecological perspective. The aim of this study was to observe the distribution of these attributes on a regional basis. Data corresponding to Colombian euglossine species were ordered with a correspondence analysis and with subsequent hierarchical clustering. Later, and based on community proprieties, we compared the resulting hierarchical model with the collection localities to seek to identify a biogeographic classification pattern. From this analysis, we derived a model that classifies the territory of Colombia into 11 biogeographic units or natural clusters. Ecological assumptions in concordance with the derived classification levels suggest that species characteristics associated with flight performance, nectar uptake, and social behavior are the factors that served to produce the current geographical structure.

Complex network classification using partially self-avoiding deterministic walks

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

Abstract Background Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.

Elementi postmoderni nell'horror americano contemporaneo. Forme testuali e culturali della mutazione 1968-1998

This research argues for an analysis of textual and cultural forms in the American horror film (1968- 1998), by defining the so-called postmodern characters. The “postmodern” term will not mean a period of the history of cinema, but a series of forms and strategies recognizable in many American films. From a bipolar re-mediation and cognitive point of view, the postmodern phenomenon is been considered as a formal and epistemological re-configuration of the cultural “modern” system. The first section of the work examines theoretical problems about the “postmodern phenomenon” by defining its cultural and formal constants in different areas (epistemology, economy, mass-media): the character of convergence, fragmentation, manipulation and immersion represent the first ones, while the “excess” is the morphology of the change, by realizing the “fluctuation” of the previous consolidated system. The second section classifies the textual and cultural forms of American postmodern film, generally non-horror. The “classic narrative” structure – coherent and consequent chain of causal cues toward a conclusion – is scattered by the postmodern constant of “fragmentation”. New textual models arise, fragmenting the narrative ones into the aggregations of data without causal-temporal logics. Considering the process of “transcoding”1 and “remediation”2 between media, and the principle of “convergence” in the phenomenon, the essay aims to define these structures in postmodern film as “database forms” and “navigable space forms.” The third section applies this classification to American horror film (1968-1998). The formal constant of “excess” in the horror genre works on the paradigm of “vision”: if postmodern film shows a crisis of the “truth” in the vision, in horror movies the excess of vision becomes “hyper-vision” – that is “multiplication” of the death/blood/torture visions – and “intra-vision”, that shows the impossibility of recognizing the “real” vision from the virtual/imaginary. In this perspective, the textual and cultural forms and strategies of postmodern horror film are predominantly: the “database-accumulation” forms, where the events result from a very simple “remote cause” serving as a pretext (like in Night of the Living Dead); the “database-catalogue” forms, where the events follow one another displaying a “central” character or theme. In the first case, the catalogue syntagms are connected by “consecutive” elements, building stories linked by the actions of a single character (usually the killer), or connected by non-consecutive episodes about a general theme: examples of the first kind are built on the model of The Wizard of Gore; the second ones, on the films such as Mario Bava’s I tre volti della paura. The “navigable space” forms are defined: hyperlink a, where one universe is fluctuating between reality and dream, as in Rosemary’s Baby; hyperlink b (where two non-hierarchical universes are convergent, the first one real and the other one fictional, as in the Nightmare series); hyperlink c (where more worlds are separated but contiguous in the last sequence, as in Targets); the last form, navigable-loop, includes a textual line which suddenly stops and starts again, reflecting the pattern of a “loop” (as in Lost Highway). This essay analyses in detail the organization of “visual space” into the postmodern horror film by tracing representative patterns. It concludes by examining the “convergence”3 of technologies and cognitive structures of cinema and new media.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.

Classification algorithms for Intelligent Transport Systems

Intelligent Transport Systems (ITS) consists in the application of ICT to transport to offer new and improved services to the mobility of people and freights. While using ITS, travellers produce large quantities of data that can be collected and analysed to study their behaviour and to provide information to decision makers and planners. The thesis proposes innovative deployments of classification algorithms for Intelligent Transport System with the aim to support the decisions on traffic rerouting, bus transport demand and behaviour of two wheelers vehicles. The first part of this work provides an overview and a classification of a selection of clustering algorithms that can be implemented for the analysis of ITS data. The first contribution of this thesis is an innovative use of the agglomerative hierarchical clustering algorithm to classify similar travels in terms of their origin and destination, together with the proposal for a methodology to analyse drivers’ route choice behaviour using GPS coordinates and optimal alternatives. The clusters of repetitive travels made by a sample of drivers are then analysed to compare observed route choices to the modelled alternatives. The results of the analysis show that drivers select routes that are more reliable but that are more expensive in terms of travel time. Successively, different types of users of a service that provides information on the real time arrivals of bus at stop are classified using Support Vector Machines. The results shows that the results of the classification of different types of bus transport users can be used to update or complement the census on bus transport flows. Finally, the problem of the classification of accidents made by two wheelers vehicles is presented together with possible future application of clustering methodologies aimed at identifying and classifying the different types of accidents.