Integrated visual vocabulary in latent Dirichlet allocation-based scene classification for IKONOS image

Scene classification based on latent Dirichlet allocation (LDA) is a more general modeling method known as a bag of visual words, in which the construction of a visual vocabulary is a crucial quantization process to ensure success of the classification. A framework is developed using the following new aspects: Gaussian mixture clustering for the quantization process, the use of an integrated visual vocabulary (IVV), which is built as the union of all centroids obtained from the separate quantization process of each class, and the usage of some features, including edge orientation histogram, CIELab color moments, and gray-level co-occurrence matrix (GLCM). The experiments are conducted on IKONOS images with six semantic classes (tree, grassland, residential, commercial/industrial, road, and water). The results show that the use of an IVV increases the overall accuracy (OA) by 11 to 12% and 6% when it is implemented on the selected and all features, respectively. The selected features of CIELab color moments and GLCM provide a better OA than the implementation over CIELab color moment or GLCM as individuals. The latter increases the OA by only ∼2 to 3%. Moreover, the results show that the OA of LDA outperforms the OA of C4.5 and naive Bayes tree by ∼20%. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.JRS.8.083690]

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

Molecular and phenotypic characterization of the alternative seasonal growth habit and flowering time in barley (Hordeum vulgare ssp. vulgare L.)

Barley can be classified into three major agronomic types, based on its seasonal growth habit (SGH): spring, winter and alternative. Winter varieties require exposure to vernalization to promote subsequent flowering and are autumn-sown. Spring varieties proceed to flowering in the absence of vernalization and are sown in the spring. The ‘alternative’ (also known as ‘facultative’) SGH is only loosely defined and can be sown in autumn or spring. Here, we investigate the molecular genetic basis of alternative barley. Analysis of the major barley vernalization (VRN-H1, VRN-H2) and photoperiod (PPD-H1, PPD-H2) response genes in a collection of 386 varieties found alternative SGH to be characterized by specific allelic combinations. Spring varieties possessed spring loci at one or both of the vernalization response loci, combined with long-day non-responsive ppd-H1 alleles and wild-type alleles at the short-day photoperiod response locus, PPD-H2. Winter varieties possessed winter alleles at both vernalization loci, in combination with the mutant ppd-H2 allele conferring delayed flowering under short-day photoperiods. In contrast, all alternative varieties investigated possessed a single spring allele (either at VRN-H1 or at VRN-H2) combined with mutant ppd-H2 alleles. This allelic combination is found only in alternative types and is diagnostic for alternative SGH in the collection studied. Analysis of flowering time under controlled environment found alternative varieties flowered later than spring control lines, with the difference most pronounced under short-day photoperiods. This work provides genetic characterization of the alternative SGH phenotype, allowing precise manipulation of SGH and flowering time within breeding programmes, and provides the molecular tools for classification of all three SGH categories within national variety registration processes.

GEMINI near-infrared spectroscopic observations of young massive stars embedded in molecular clouds

K-band spectra of young stellar candidates in four Southern hemisphere clusters have been obtained with the Gemini Near-Infrared Spectrograph in Gemini South. The clusters are associated with IRAS sources that have colours characteristic of ultracompact H II regions. Spectral types were obtained by comparison of the observed spectra with those of a near-infrared (NIR) library; the results include the spectral classification of nine massive stars and seven objects confirmed as background late-type stars. Two of the studied sources have K-band spectra compatible with those characteristic of very hot stars, as inferred from the presence of C IV, N III and N V emission lines at 2.078, 2.116 and 2.100 mu m, respectively. One of them, I16177_IRS1, has a K-band spectrum similar to that of Cyg OB2 7, an O3If* supergiant star. The nebular K-band spectrum of the associated Ultra-Compact (UC) H II region shows the s-process [Kr III] and [Se IV] high excitation emission lines, previously identified only in planetary nebula. One young stellar object was found in each cluster, associated with either the main IRAS source or a nearby resolved Midecourse Space eXperiment (MSX) component, confirming the results obtained from previous NIR photometric surveys. The distances to the stars were derived from their spectral types and previously determined JHK magnitudes; they agree well with the values obtained from the kinematic method, except in the case of IRAS 15408-5356, for which the spectroscopic distance is about a factor of 2 smaller than the kinematic value.

Molecular phylogeny of tribe Rhipsalideae (Cactaceae) and taxonomic implications for Schlumbergera and Hatiora

Tribe Rhipsalideae is composed of unusual epiphytic or lithophytic cacti that inhabit humid tropical and subtropical forests. Members of this tribe present a reduced vegetative body, a specialized adventitious root system, usually spineless areoles and flowers and fruits reduced in size. Despite the debate surrounding the classification of Rhipsalideae, no studies have ever attempted to reconstruct phylogenetic relationships among its members or to test the monophyly of its genera using DNA sequence data; all classifications formerly proposed for this tribe have only employed morphological data. In this study, we reconstruct the phylogeny of Rhipsalideae using plastid (trnQ-rps16, rpl32-trnL, psbA-trnH) and nuclear (ITS) markers to evaluate the classifications previously proposed for the group. We also examine morphological features traditionally used to delimit genera within Rhipsalideae in light of the resulting phylogenetic trees. In total new sequences for 35 species of Rhipsalideae were produced (out of 55: 63%). The molecular phylogeny obtained comprises four main clades supporting the recognition of genera Lepismium, Rhipsalis, Hatiora and Schlumbergera. The evidence gathered indicate that a broader genus Schlumbergera, including Hatiora subg. Rhipsalidopsis, should be recognized. Consistent morphological characters rather than homoplastic features are used in order to establish a more coherent and practical classification for the group. Nomenclatural changes and a key for the identification of the genera currently included in Rhipsalideae are provided. (C) 2011 Elsevier Inc. All rights reserved.

A molecular phylogeny of the stingless bee genus Melipona (Hymenoptera: Apidae)

Stingless bees (Meliponini) constitute a diverse group of highly eusocial insects that occur throughout tropical regions around the world. The meliponine genus Melipona is restricted to the New World tropics and has over 50 described species. Melipona, like Apis, possesses the remarkable ability to use representational communication to indicate the location of foraging patches. Although Melipona has been the subject of numerous behavioral, ecological, and genetic studies, the evolutionary history of this genus remains largely unexplored. Here, we implement a multigene phylogenetic approach based on nuclear, mitochondrial, and ribosomal loci, coupled with molecular clock methods, to elucidate the phylogenetic relationships and antiquity of subgenera and species of Melipona. Our phylogenetic analysis resolves the relationship among subgenera and tends to agree with morphology-based classification hypotheses. Our molecular clock analysis indicates that the genus Melipona shared a most recent common ancestor at least similar to 14-17 million years (My) ago. These results provide the groundwork for future comparative analyses aimed at understanding the evolution of complex communication mechanisms in eusocial Apidae. (C) 2010 Elsevier Inc. All rights reserved.

Structural Aspects of the Distinct Biochemical Properties of Glutaredoxin 1 and Glutaredoxin 2 from Saccharomyces cerevisiae

Glutaredoxins (Grxs) are small (9-12 kDa) heat-stable proteins that are ubiquitously distributed. In Saccharomyces cerevisiae, seven Grx enzymes have been identified. Two of them (yGrx1 and yGrx2) are dithiolic, possessing a conserved Cys-Pro-Tyr-Cys motif. Here, we show that yGrx2 has a specific activity 15 times higher than that of yGrx1, although these two oxidoreductases share 64% identity and 85% similarity with respect to their amino acid sequences. Further characterization of the enzymatic activities through two-substrate kinetics analysis revealed that yGrx2 possesses a lower Km for glutathione and a higher turnover than yGrx1. To better comprehend these biochemical differences, the pK(a) of the N-terminal active-site cysteines (Cys27) of these two proteins and of the yGrx2-C30S mutant were determined. Since the pK(a) values of the yGrx1 and yGix2 Cys27 residues are very similar, these parameters cannot account for the difference observed between their specific activities. Therefore, crystal structures of yGrx2 in the oxidized form and with a glutathionyl mixed disulfide were determined at resolutions of 2.05 and 1.91 angstrom, respectively. Comparisons of yGrx2 structures with the recently determined structures of yGrx1 provided insights into their remarkable functional divergence. We hypothesize that the substitutions of Ser23 and Gln52 in yGrx1 by Ala23 and Glu52 in yGrx2 modify the capability of the active-site C-terminal cysteine to attack the mixed disulfide between the N-terminal active-site cysteine and the glutathione molecule. Mutagenesis studies supported this hypothesis. The observed structural and functional differences between yGrx1 and yGrx2 may reflect variations in substrate specificity. (C) 2008 Elsevier Ltd. All rights reserved.

Molecular characterization and fumonisin production by Fusarium verticillioides isolated from corn grains of different geographic origins in Brazil

Gibberella moniliformis is most commonly associated with maize worldwide and produces high levels of fumonisins, some of the most agriculturally important mycotoxins. Studies demonstrate that molecular methods can be helpful for a rapid identification of Fusarium species and their levels of toxin production. The purpose of this research was to apply molecular methods (AFLP, TEF-1 alpha partial gene sequencing and PCR based on MAT alleles) for the identification of Fusarium species isolated from Brazilian corn and to verify if real time RT-PCR technique based on FUM1 and FUM19 genes is appropriated to estimate fumonisins B(1) and B(2) production levels. Among the isolated strains, 96 were identified as Fusarium verricillioides, and four as other Fusarium species. Concordant phylogenies were obtained by AFLP and TEF-1 alpha sequencing, permitting the classification of the different species into distinct clades. Concerning MAT alleles, 70% of the F. verricillioides isolates carried the MAT-1 and 30% MAT-2. A significant correlation was observed between the expression of the genes and toxin production r=0.95 and r=0.79 (correlation of FUM1 with FB(1) and FB(2), respectively, P < 0.0001): r=0.93 and r =0.78 (correlation of FUM19 with FB(1) and FB(2). respectively, P < 0.0001). Molecular methods used in this study were found to be useful for the rapid identification of Fusarium species. The high and significant correlation between FUM1 and FUM19 expression and fumonisins production suggests that real time RT-PCR is suitable for studies considering the influence of abiotic and biotic factors on expression of these genes. This is the first report concerning the expression of fumonisin biosynthetic genes in Fusarium strains isolated from Brazilian agricultural commodity. (c) 2010 Elsevier B.V. All rights reserved.

A Survey on Graphical Methods for Classification Predictive Performance Evaluation

Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.

Crystal Engineering of an Anti-HIV Drug Based on the Recognition of Assembling Molecular Frameworks

A rational strategy was employed for design of an orthorhombic structure of lamivudine with maleic acid. On the basis of the lamivudine saccharinate structure reported in the literature, maleic acid was chosen to synthesize a salt with the anti-HIV drug because of the structural similarities between the salt formers. Maleic acid has an acid-ionization constant of the anti first proton and an arrangement of their hydrogen bonding functionalities similar to those of saccharin. Likewise, there is a saccharin-like conformational rigidity in maleic acid because of the hydrogen-bonded ring formation and the Z-configuration around the C=C double bond. As was conceivably predicted, lamivudine maleate assembles into a structure whose intermolecular architecture is related to that of saccharinate salt of the drug. Therefore, a molecular framework responsible for crystal assembly into a lamivudine saccharinate-like structure could be recognized in the salt formers. Furthermore, structural correlations and structure-solubility relationships were established for lamivudine maleate and saccharinate. Although there is a same molecular framework in maleic acid and saccharin, these salt formers are Structurally different in some aspects. When compared to saccharin, neither out-of-plane SO(2) oxygens nor a benzene group occur in maleic acid. Both features could be related to higher solubility of lamivudine maleate. Here, we also anticipate that multicomponent molecular crystals of lamivudine with other salt formers possessing the molecular framework responsible for crystal assembly can be engineered successfully.

The CATH classification revisited-architectures reviewed and new ways to characterize structural divergence in superfamilies

The latest version of CATH (class, architecture, topology, homology) (version 3.2), released in July 2008 (http://www.cathdb.info), contains 1 14215 domains, 2178 Homologous superfamilies and 1110 fold groups. We have assigned 20 330 new domains, 87 new homologous superfamilies and 26 new folds since CATH release version 3.1. A total of 28 064 new domains have been assigned since our NAR 2007 database publication (CATH version 3.0). The CATH website has been completely redesigned and includes more comprehensive documentation. We have revisited the CATH architecture level as part of the development of a `Protein Chart` and present information on the population of each architecture. The CATHEDRAL structure comparison algorithm has been improved and used to characterize structural diversity in CATH superfamilies and structural overlaps between superfamilies. Although the majority of superfamilies in CATH are not structurally diverse and do not overlap significantly with other superfamilies, similar to 4% of superfamilies are very diverse and these are the superfamilies that are most highly populated in both the PDB and in the genomes. Information on the degree of structural diversity in each superfamily and structural overlaps between superfamilies can now be downloaded from the CATH website.

An illustration of variable precision rough set theory : The gender classification of the European barn swallow (Hirundo rustica)

This paper introduces a new technique in the investigation of object classification and illustrates the potential use of this technique for the analysis of a range of biological data, using avian morphometric data as an example. The nascent variable precision rough sets (VPRS) model is introduced and compared with the decision tree method ID3 (through a ‘leave n out’ approach), using the same dataset of morphometric measures of European barn swallows (Hirundo rustica) and assessing the accuracy of gender classification based on these measures. The results demonstrate that the VPRS model, allied with the use of a modern method of discretization of data, is comparable with the more traditional non-parametric ID3 decision tree method. We show that, particularly in small samples, the VPRS model can improve classification and to a lesser extent prediction aspects over ID3. Furthermore, through the ‘leave n out’ approach, some indication can be produced of the relative importance of the different morphometric measures used in this problem. In this case we suggest that VPRS has advantages over ID3, as it intelligently uses more of the morphometric data available for the data classification, whilst placing less emphasis on variables with low reliability. In biological terms, the results suggest that the gender of swallows can be determined with reasonable accuracy from morphometric data and highlight the most important variables in this process. We suggest that both analysis techniques are potentially useful for the analysis of a range of different types of biological datasets, and that VPRS in particular has potential for application to a range of biological circumstances.

Aspects of the interaction between Xanthorrhoea australis and Phytophthora cinnamomi in south-western Victoria, Australia

Diseases in natural ecosystems are often assumed to be less severe than those observed in domestic cropping systems due to the extensive biodiversity exhibited in wild vegetation communities. In Australia, it is this natural biodiversity that is now under threat from Phytophthora cinnamomi. The soilborne Oomycete causes severe decline of native vegetation communities in south-western Victoria, Australia, disrupting the ecological balance of native forest and heathland communities. While the effect of disease caused by P. cinnamomi on native vegetation communities in Victoria has been extensively investigated, little work has focused on the Anglesea healthlands in south-western Victoria. Nothing is known about the population structure of P. cinnamomi at Anglesea. This project was divided into two main components to investigate fundamental issues affecting the management of P. cinnamomi in the Anglesea heathlands. The first component examined the phenotypic characteristics of P. cinnamomi isolates sampled from the population at Anglesea, and compared these with isolates from other regions in Victoria, and also from Western Australia. The second component of the project investigated the effect of the fungicide phosphonate on the host response following infection by P. cinnamomi. Following soil sampling in the Anglesea heathlands, a collection of P, cinnamomi isolates was established. Morphological and physiological traits of each isolate were examined. All isolates were found to be of the A2 mating type. Variation was demonstrated among isolates in the following characteristics: radial growth rate on various nutrient media, sporangial production, and sporangial dimensions. Oogonial dimensions did not differ significantly between isolates. Morphological and physiological variation was rarely dependant on isolate origin. To examine the genetic diversity among isolates and to determine whether phenotypic variation observed was genetically based, Random Amplified Polymorphic DNA (RAPD) analyses were conducted. No significant variation was observed among isolates based on an analysis of molecular variance (AMQVA). The results are discussed in relation to population biology, and the effect of genetic variation on population structure and population dynamics. X australis, an arborescent monocotyledon indigenous to Australia, is highly susceptible to infection by P. cinnamomi. It forms an important component of the heathland vegetation community, providing habitat for native flora and fauna, A cell suspension culture system was developed to investigate the effect of the fungicide phosphonate on the host-pathogen interaction between X. australis and P. cinnamomi. This allowed the interaction between the host and the pathogen to be examined at a cellular level. Subsequently, histological studies using X. australis seedlings were undertaken to support the cellular study. Observations in the cell culture system correlated well with those in the plant. The anatomical structure of X australis roots was examined to assist in the interpretation of results of histopathological studies. The infection of single cells and roots of X. australis, and the effect of phosphonate on the interaction are described. Phosphonate application prior to inoculation with P. cinnamomi reduced the infection of cells in culture and of cells in planta. In particular, phosphonate was found to stimulate the production of phenolic material in roots of X australis seedlings and in cells in suspension cultures. In phosphonate-treated roots of X australis seedlings, the deposition of electron dense material, possibly lignin or cellulose, was observed following infection with P. cinnamomi. It is proposed that this is a significant consequence of the stimulation of plant defence pathways by the fungicide. Results of the study are discussed in terms of the implications of the findings on management of the Anglesea heathlands in Victoria, taking into account variation in pathogen morphology, pathogenicity and genotype. The mode of action of phosphonate in the plant is discussed in relation to plant physiology and biochemistry.

Automated classification of human daily activities in ambulatory environment

This paper presents a human daily activity classification approach based on the sensory data collected from a single tri-axial accelerometer worn on waist belt. The classification algorithm was realized to distinguish 6 different activities including standing, jumping, sitting-down, walking, running and falling through three major steps: wavelet transformation, Principle Component Analysis (PCA)-based dimensionality reduction and followed by implementing a radial basis function (RBF) kernel Support Vector Machine (SVM) classifier. Two trials were conducted to evaluate different aspects of the classification scheme. In the first trial, the classifier was trained and evaluated by using a dataset of 420 samples collected from seven subjects by using a k-fold cross-validation method. The parameters σ and c of the RBF kernel were optimized through automatic searching in terms of yielding the highest recognition accuracy and robustness. In the second trial, the generation capability of the classifier was also validated by using the dataset collected from six new subjects. The average classification rates of 95% and 93% are obtained in trials 1 and 2, respectively. The results in trial 2 show the system is also good at classifying activity signals of new subjects. It can be concluded that the collective effects of the usage of single accelerometer sensing, the setting of the accelerometer placement and efficient classifier would make this wearable sensing system more realistic and more comfortable to be implemented for long-term human activity monitoring and classification in ambulatory environment, therefore, more acceptable by users.