Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Two formation channels of ultra-compact dwarf galaxies in Hickson compact groups

Context. The formation of ultra-compact dwarf galaxies (UCDs) is believed to be driven by interaction, and UCDs are abundant in the cores of galaxy clusters, environments that mark the end-point of galaxy evolution. Nothing is known about the properties of UCDs in compact groups of galaxies, environments where most of galaxy evolution and interaction is believed to occur and where UCDs in an intermediate stage in their evolution may be expected. Aims. The main goal of this study is to detect and characterize, for the first time, the UCD population of compact groups of galaxies. For that, two nearby groups in different evolutionary stages, HCG22 and HCG90, were targeted. Methods. We selected about 40 UCD candidates from pre-existing photometry of both groups, and obtained spectra of these candidates using the VLT FORS2 instrument in MXU mode. Archival HST/ACS imaging was used to measure their structural parameters. Results. We detect 16 and 5 objects belonging to HCG22 and HCG90, respectively, covering the magnitude range -10.0 > M(R) > -11.5 mag. Their integrated colours are consistent with old ages covering a broad range in metallicities (metallicities confirmed by the spectroscopic measurements). Photometric mass estimates put 4 objects in HCG90 and 9 in HCG22 in the mass range of UCDs (> 2 x 10(6) M(circle dot)) for an assumed age of 12Gyr. These UCDs are on average 2-3 times larger than the typical size of Galactic GCs, covering a range of 2 less than or similar to r(h) less than or similar to 21 pc. The UCDs in HCG22 are more concentrated around the central galaxy than in HCG90, at the 99% confidence level. They cover a broad range in [alpha/Fe] abundances from sub-to super-solar. The spectra of 3 UCDs (2 in HCG22, 1 in HCG90) show tentative evidence of intermediate age stellar populations. The clearest example is the largest and most massive UCD (similar to 10(7) M(circle dot)) in our sample, which is detected in HCG22. Its properties are most consistent with a stripped dwarf galaxy nucleus. We calculate the specific frequency (S(N)) of UCDs for both groups, finding that HCG22 has about three times higher S(N) than HCG90. Conclusions. The ensemble properties of the detected UCDs supports two co-existing formation channels: a star cluster origin (low-luminosity, compact sizes, old ages, super-solar alpha/Fe), and an origin as tidally stripped dwarf nuclei (more extended and younger stellar populations). Our results imply that the UCDs detected in both groups do not, in their majority, originate from relatively recent galaxy interactions. Most of the detected UCDs have likely been brought into the group along with their host galaxies.

DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 <= r <= 21 (85.2%) and r >= 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 <= r <= 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (> 80%) while simultaneously achieving low contamination (similar to 2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 <= r <= 21.

Disordered ensembles of random matrices

It is shown that the families of generalized matrix ensembles recently considered which give rise to an orthogonal invariant stable Levy ensemble can be generated by the simple procedure of dividing Gaussian matrices by a random variable. The nonergodicity of this kind of disordered ensembles is investigated. It is shown that the same procedure applied to random graphs gives rise to a family that interpolates between the Erdos-Renyi and the scale free models.

Musical genres: beating to the rhythms of different drums

Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.

Observation of a Cooperative Radiation Force in the Presence of Disorder

Cooperative scattering of light by an extended object such as an atomic ensemble or a dielectric sphere is fundamentally different from scattering from many pointlike scatterers such as single atoms. Homogeneous distributions tend to scatter cooperatively, whereas fluctuations of the density distribution increase the disorder and suppress cooperativity. In an atomic cloud, the amount of disorder can be tuned via the optical thickness, and its role can be studied via the radiation force exerted by the light on the atomic cloud. Monitoring cold (87)Rb atoms released from a magneto-optical trap, we present the first experimental signatures of radiation force reduction due to cooperative scattering. The results are in agreement with an analytical expression interpolating between the disorder and the cooperativity-dominated regimes.

The impact of the subtropical South Atlantic SST on South American precipitation

The Community Climate Model (CCM3) from the National Center for Atmospheric Research (NCAR) is used to investigate the effect of the South Atlantic sea surface temperature (SST) anomalies on interannual to decadal variability of South American precipitation. Two ensembles composed of multidecadal simulations forced with monthly SST data from the Hadley Centre for the period 1949 to 2001 are analysed. A statistical treatment based on signal-to-noise ratio and Empirical Orthogonal Functions (EOF) is applied to the ensembles in order to reduce the internal variability among the integrations. The ensemble treatment shows a spatial and temporal dependence of reproducibility. High degree of reproducibility is found in the tropics while the extratropics is apparently less reproducible. Austral autumn (MAM) and spring (SON) precipitation appears to be more reproducible over the South America-South Atlantic region than the summer (DJF) and winter (JJA) rainfall. While the Inter-tropical Convergence Zone (ITCZ) region is dominated by external variance, the South Atlantic Convergence Zone (SACZ) over South America is predominantly determined by internal variance, which makes it a difficult phenomenon to predict. Alternatively, the SACZ over western South Atlantic appears to be more sensitive to the subtropical SST anomalies than over the continent. An attempt is made to separate the atmospheric response forced by the South Atlantic SST anomalies from that associated with the El Nino - Southern Oscillation (ENSO). Results show that both the South Atlantic and Pacific SSTs modulate the intensity and position of the SACZ during DJF. Particularly, the subtropical South Atlantic SSTs are more important than ENSO in determining the position of the SACZ over the southeast Brazilian coast during DJF. On the other hand, the ENSO signal seems to influence the intensity of the SACZ not only in DJF but especially its oceanic branch during MAM. Both local and remote influences, however, are confounded by the large internal variance in the region. During MAM and JJA, the South Atlantic SST anomalies affect the magnitude and the meridional displacement of the ITCZ. In JJA, the ENSO has relatively little influence on the interannual variability of the simulated rainfall. During SON, however, the ENSO seems to counteract the effect of the subtropical South Atlantic SST variations on convection over South America.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Experimental study of a Tollmien-Schlichting wave interacting with a shallow 3D roughness element

The paper is devoted to an experimental study of the effect of a shallow 3D roughness element on the evolution of a 2D Tollmien-Schlichting wave in a Blasius boundary layer. The experiments were carried out under controlled disturbance conditions on an airfoil section which could provide a long run with zero pressure gradient flow. A pneumatically driven slit source was used to introduce the Tollmien-Schilichting wave upstream of the lower branch of the neutral stability curve. A few wavelengths downstream, the T-S wave interacts with a cylindrical roughness element. The height of the roughness was slowly oscillating in time, which allows a continuous measurement of the T-S wave response downstream the roughness. The oscillation frequency was approximately 1500 times lower than the frequency of the studied Tollmien-Schlichting wave and therefore, behaved as a steady roughness with respect to the T-S wave. Hot wire anemometry was used to measure wall normal profiles and spanwise scans close to the maximum of the eigenfunction of the T-S wave. The oscillation of the roughness and the synchronization of all-equipments permitted the use of ensemble average techniques. Two different amplitudes of T-S waves with a non-dimensional frequency of F120E-06 were studied. They show a strong amplification of the disturbances in a small spanwise wave number range. The analysis of the wall normal T-S profiles suggests the growth of oblique modes.

Influence of chemical interesterification on thermal behavior, microstructure, polymorphism and crystallization properties of canola oil and fully hydrogenated cottonseed oil blends

This work evaluated chemical interesterification of canola oil (CaO) and fully hydrogenated cottonseed oil (FHCSO) blends, with 20%, 25%, 30%, 35% and 40%(w/w) FHCSO content. Interesterification produced reduction of trisaturated and increase in monounsaturated and diunsaturated triacylglycerols contents, which caused important changes in temperatures and enthalpies associated with the crystallization and melting thermograms. It was verified reduction in medium crystal diameter in all blends, in addition crystal morphology modification. Crystallization kinetics revealed that crystal formation induction period and maximum solid fat content were altered according to FHCSO content in original blends and as a result of random rearrangement. Changes in Avrami constant (k) and exponent (n) indicated, respectively, that interesterification decreased crystallization rates and altered crystalline morphology. However, X-ray diffraction analyses showed randomization did not change the original crystalline polymorphism. The original and interesterified blends had significant predominance of beta` polymorph, which is interesting for several food applications. (C) 2009 Elsevier Ltd. All rights reserved.

Thermal Behavior, Microstructure, Polymorphism, and Crystallization Properties of Zero Trans Fats from Soybean Oil and Fully Hydrogenated Soybean Oil

Blends of soybean oil (SO) and fully hydrogenated soybean oil (FHSBO), with 10, 20, 30, 40, and 50% (w/w) FHSBO content were interesterified under the following conditions: 20 min reaction time, 0.4% sodium methoxide catalyst, and 500 rpm stirring speed, at 100 A degrees C. The original and interesterified blends were examined for triacylglycerol composition, thermal behavior, microstructure, crystallization kinetics, and polymorphism. Interesterification produced substantial rearrangement of the triacylglycerol species in all the blends, reduction of trisaturated triacylglycerol content and increase in monounsaturated-disaturated and diunsaturated-monosaturated triacylglycerols. Evaluation of thermal behavior parameters showed linear relations with FHSBO content in the original blends. Blend melting and crystallization thermograms were significantly modified by the randomization. Interesterification caused significant reductions in maximum crystal diameter in all blends, in addition to modifying crystal morphology. Characterization of crystallization kinetics revealed that crystal formation induction period (tau (SFC)) and maximum solid fat content (SFC(max)) were altered according to FHSBO content in the original blends and as a result of the random rearrangement. Changes in Avrami constant (k) and exponent (n) indicated, respectively, that-as compared with the original blends-interesterification decreased crystallization velocities and modified crystallization processes, altering crystalline morphology and nucleation mechanism. X-ray diffraction analyses revealed that interesterification altered crystalline polymorphism. The interesterified blends showed a predominance of the beta` polymorph, which is of more interest for food applications.

Acquisition of the English article system in SLA and the Missing Surface Inflection Hypothesis

This paper examines the article system in interlanguage grammar focusing on Japanese learners of English, whose native language lacks articles. It will be demonstrated that for the acquisition of the English article system, count/mass distinctions and definiteness are the crucial factors. Although Japanese does not employ the article system to encode these aspects, it will be argued that they are nevertheless syntactically encoded through its classifier system. Hence, the problem for these learners must be to map these features onto the appropriate surface forms as the Missing Surface Inflection Hypothesis predicts (Prévost & White 2000). This suggestion will further be supported empirically by a fill-in-the article task. It will be concluded that these Japanese learners understand the English article system fairly well, possibly due to their native language, yet have problems with realizing the relevant features (i.e. count/mass distinctions and definiteness) in the target language.

Role of phosphorylation in the conformation of tau peptides implicated in Alzheimer's disease

A series of peptides corresponding to isolated regions of Tau (tau) protein have been synthesized and their conformations determined by H-1 NMR spectroscopy. Immunodominant peptides corresponding to tau(224-240) and a bisphosphorylated derivative in which a single Thr and a single Ser are phosphorylated at positions 231 and 235 respectively, and which are recognized by an Alzheimer's disease-specific monoclonal antibody, were the main focus of the study. The nonphosphorylated peptide adopts essentially a random coil conformation in aqueous solution, but becomes slightly more ordered into P-type structure as the hydrophobicity of the solvent is increased by adding up to 50% trifluoroethanol (TFE). Similar trends are observed for the bisphosphorylated peptide, with a somewhat stronger tendency to form an extended structure, There is tentative NMR evidence for a small population of species containing a turn at residues 229-231 in the phosphorylated peptide, and this is strongly supported by CD spectroscopy. A proposal that the selection of a bioactive conformation from a disordered solution ensemble may be an important step (in either tubulin binding or in the formation of PHF) is supported by kinetic data on Pro isomerization. A recent study showed that Thr231 phosphorylation affected the rate of prolyl isomerization and abolished tubulin binding. This binding was restored by the action of the prolyl isomerase Pin1. In the current study, we find evidence for the existence of both trans and cis forms of tau peptides in solution but no difference in the equilibrium distribution of cis-trans isomers upon phosphorylation. Increasing hydrophobicity decreases the prevalence of cis forms and increases the major trans conformation of each of the prolines present in these molecules. We also synthesized mutant peptides containing Tyr substitutions preceding the Pro residues and found that phosphorylation of Tyr appears to have an effect on the equilibrium ratio of cis-trans isomerization and decreases the cis content.

Quantum nonlinear dynamics of continuously measured systems

Classical dynamics is formulated as a Hamiltonian flow in phase space, while quantum mechanics is formulated as unitary dynamics in Hilbert space. These different formulations have made it difficult to directly compare quantum and classical nonlinear dynamics. Previous solutions have focused on computing quantities associated with a statistical ensemble such as variance or entropy. However a more diner comparison would compare classical predictions to the quantum predictions for continuous simultaneous measurement of position and momentum of a single system, in this paper we give a theory of such measurement and show that chaotic behavior in classical systems fan be reproduced by continuously measured quantum systems.