Effects of the target spin on the reaction mechanism of the (16)O+(63)Cu system

Precise quasielastic and alpha-transfer excitation functions, at theta(lab) = 161 degrees, have been measured at energies near the Coulomb barrier for the (16)O + (63)Cu system. This is the first time reported quasielastic barrier distribution for a medium odd-A nucleus target deduced from the data. Additional elastic scattering angular distributions data available in the literature for this system were also used in the investigation of the role of several individual channels in the reaction dynamics, by comparing the data with free-parameter coupled-channels calculations. In order to do so, the nucleus-nucleus bare potential has a double-folding potential as the real component and only a very short-range imaginary potential. The quasielastic barrier distribution has been shown to be a powerful tool in this analysis at the barrier region. A high collectivity of the (63)Cu was observed, mainly due to the strong influence of its 5/2-and 7/2-states on all reaction channels investigated. A striking influence of the reorientation of the ground-state target-spin on the elastic cross sections, taken at backward angles, was also observed.

Near-barrier quasielastic scattering as a sensitive tool to derive nuclear matter diffuseness

Quasielastic excitation functions for the (16,18)O + (60)Ni systems were measured at energies near and below the Coulomb barrier, at the backward angle theta(LAB) = 161 degrees. The corresponding quasielastic barrier distributions were derived. The data were compared with predictions from coupled channel calculations using a double-folding potential as a bare potential. For the (16)O-induced scattering, good agreement was obtained for the barrier distribution by using the projectile default nuclear matter diffuseness obtained from the Sao Paulo potential systematic, that is, 0.56 fm. However, for the (18)O-induced scattering, good agreement was obtained only when the projectile nuclear matter diffuseness was changed to 0.62 fm. Therefore, in this paper we show how near-barrier quasielastic scattering can be used as a sensitive tool to derive nuclear matter diffuseness.

Elastic scattering and total reaction cross sections for the (8)B, (7)Be, and (6)Li+(12)C systems

Angular distributions for the elastic scattering of (8)B, (7)Be, and (6)Li on a (12)C target have been measured at E(lab) = 25.8, 18.8, and 12.3 MeV, respectively. The analyses of these angular distributions have been performed in terms of the optical model using Woods-Saxon and double-folding type potentials. The effect of breakup in the elastic scattering of (8)B + (12)C is investigated by performing coupled-channels calculations with the continuum discretized coupled-channel method and cluster-model folding potentials. Total reaction cross sections were deduced from the elastic-scattering analysis and compared with published data on elastic scattering of other weakly and tightly bound projectiles on (12)C, as a function of energy. With the exception of (4)He and (16)O, the data can be described using a universal function for the reduced cross sections.

Sensitivity to noise and ergodicity of an assembly line of cellular automata that classifies density

We investigate the sensitivity of the composite cellular automaton of H. Fuks [Phys. Rev. E 55, R2081 (1997)] to noise and assess the density classification performance of the resulting probabilistic cellular automaton (PCA) numerically. We conclude that the composite PCA performs the density classification task reliably only up to very small levels of noise. In particular, it cannot outperform the noisy Gacs-Kurdyumov-Levin automaton, an imperfect classifier, for any level of noise. While the original composite CA is nonergodic, analyses of relaxation times indicate that its noisy version is an ergodic automaton, with the relaxation times decaying algebraically over an extended range of parameters with an exponent very close (possibly equal) to the mean-field value.

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.

Protein preparation, crystallization and preliminary X-ray analysis of Trypanosoma cruzi nucleoside diphosphate kinase 1

The flagellated protozoan parasite Trypanosoma cruzi is the aetiological agent of Chagas disease. Nucleoside diphosphate kinases (NDPKs) are enzymes that are involved in energy management and nucleoside balance in the cell. T. cruzi TcNDPK1, a canonical isoform, was overexpressed in Escherichia coli as an N-terminally poly-His-tagged fusion protein and crystallized. Crystals grew after 72 h in 0.2 M MgCl(2), 20% PEG 3350. Data were collected to 3.5 angstrom resolution using synchrotron X-ray radiation at the National Synchrotron Light Laboratory (Campinas, Brazil). The crystals belonged to the trigonal space group P3, with unit-cell parameters a = b = 127.84, c = 275.49 angstrom. Structure determination is under way and will provide relevant information that may lead to the first step in rational drug design for the treatment of Chagas disease.

Characterization of Yeast Extracellular Vesicles: Evidence for the Participation of Different Pathways of Cellular Traffic in Vesicle Biogenesis

Background: Extracellular vesicles in yeast cells are involved in the molecular traffic across the cell wall. In yeast pathogens, these vesicles have been implicated in the transport of proteins, lipids, polysaccharide and pigments to the extracellular space. Cellular pathways required for the biogenesis of yeast extracellular vesicles are largely unknown. Methodology/Principal Findings: We characterized extracellular vesicle production in wild type (WT) and mutant strains of the model yeast Saccharomyces cerevisiae using transmission electron microscopy in combination with light scattering analysis, lipid extraction and proteomics. WT cells and mutants with defective expression of Sec4p, a secretory vesicle-associated Rab GTPase essential for Golgi-derived exocytosis, or Snf7p, which is involved in multivesicular body (MVB) formation, were analyzed in parallel. Bilayered vesicles with diameters at the 100-300 nm range were found in extracellular fractions from yeast cultures. Proteomic analysis of vesicular fractions from the cells aforementioned and additional mutants with defects in conventional secretion pathways (sec1-1, fusion of Golgi-derived exocytic vesicles with the plasma membrane; bos1-1, vesicle targeting to the Golgi complex) or MVB functionality (vps23, late endosomal trafficking) revealed a complex and interrelated protein collection. Semi-quantitative analysis of protein abundance revealed that mutations in both MVB- and Golgi-derived pathways affected the composition of yeast extracellular vesicles, but none abrogated vesicle production. Lipid analysis revealed that mutants with defects in Golgi-related components of the secretory pathway had slower vesicle release kinetics, as inferred from intracellular accumulation of sterols and reduced detection of these lipids in vesicle fractions in comparison with WT cells. Conclusions/Significance: Our results suggest that both conventional and unconventional pathways of secretion are required for biogenesis of extracellular vesicles, which demonstrate the complexity of this process in the biology of yeast cells.

Use of Medical Subject Headings (MeSH) in Portuguese for categorizing web-based healthcare content

Introduction: Internet users are increasingly using the worldwide web to search for information relating to their health. This situation makes it necessary to create specialized tools capable of supporting users in their searches. Objective: To apply and compare strategies that were developed to investigate the use of the Portuguese version of Medical Subject Headings (MeSH) for constructing an automated classifier for Brazilian Portuguese-language web-based content within or outside of the field of healthcare, focusing on the lay public. Methods: 3658 Brazilian web pages were used to train the classifier and 606 Brazilian web pages were used to validate it. The strategies proposed were constructed using content-based vector methods for text classification, such that Naive Bayes was used for the task of classifying vector patterns with characteristics obtained through the proposed strategies. Results: A strategy named InDeCS was developed specifically to adapt MeSH for the problem that was put forward. This approach achieved better accuracy for this pattern classification task (0.94 sensitivity, specificity and area under the ROC curve). Conclusions: Because of the significant results achieved by InDeCS, this tool has been successfully applied to the Brazilian healthcare search portal known as Busca Saude. Furthermore, it could be shown that MeSH presents important results when used for the task of classifying web-based content focusing on the lay public. It was also possible to show from this study that MeSH was able to map out mutable non-deterministic characteristics of the web. (c) 2010 Elsevier Inc. All rights reserved.

Human multipotent adipose-derived stem cells restore dystrophin expression of Duchenne skeletal-muscle cells in vitro

Background information. DMD (Duchenne muscular dystrophy) is a devastating X-linked disorder characterized by progressive muscle degeneration and weakness. The use of cell therapy for the repair of defective muscle is being pursued as a possible treatment for DMD. Mesenchymal stem cells have the potential to differentiate and display a myogenic phenotype in vitro. Since liposuctioned human fat is available in large quantities, it may be an ideal source of stem cells for therapeutic applications. ASCs (adipose-derived stem cells) are able to restore dystrophin expression in the muscles of mdx (X-linked muscular dystrophy) mice. However, the outcome when these cells interact with human dystrophic muscle is still unknown. Results. We show here that ASCs participate in myotube formation when cultured together with differentiating human DMD myoblasts, resulting in the restoration of dystrophin expression. Similarly, dystrophin was induced when ASCs were co-cultivated with DMD myotubes. Experiments with GFP (green fluorescent protein)-positive ASCs and DAPI (4,6-diamidino-2-phenylindole)-stained DMD myoblasts indicated that ASCs participate in human myogenesis through cellular fusion. Conclusions. These results show that ASCs have the potential to interact with dystrophic muscle cells, restoring dystrophin expression of DMD cells in vitro. The possibility of using adipose tissue as a source of stem cell therapies for muscular diseases is extremely exciting.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Annealing effects on microstructure and coercive field of ferritic-martensitic ODS Eurofer steel

Oxide dispersion strengthened reduced-activation ferritic-martensitic steels are promising candidates for applications in future fusion power plants. Samples of a reduced activation ferritic-martensitic 9 wt.%Cr-oxide dispersion strengthened Eurofer steel were cold rolled to 80% reduction in thickness and annealed in vacuum for 1 h from 200 to 1350 degrees C to evaluate its thermal stability. Vickers microhardness testing and electron backscatter diffraction (EBSD) were used to characterize the microstructure. The microstructural changes were also followed by magnetic measurements, in particular the corresponding variation of the coercive field (H(c)), as a function of the annealing treatment. Results show that magnetic measurements were sensitive to detect the changes, in particular the martensitic transformation, in samples annealed above 850 degrees C (austenitic regime). (C) 2010 Elsevier B.V. All rights reserved.

Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

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.

Microstructure and mechanical properties of laser-welded joints of TWIP and TRIP steels

With the aim of investigating a laser-welded dissimilar joint of TWIP and TRIP steel sheets, the microstructure was characterized by means of OM, SEM, and EBSD to differentiate the fusion zone, heat-affected zone, and the base material. OIM was used to differentiate between ferritic, bainitic, and martensitic structures. Compositions were measured by means of optical emission spectrometry and EDX to evaluate the effect of manganese segregation. Microhardness measurements and tensile tests were performed to evaluate the mechanical properties of the joint. Residual stresses and XRD phase quantification were used to characterize the weld. Grain coarsening and martensitic areas were found in the fusion zone, and they had significant effects on the mechanical properties of the weld. The heat-affected zone of the TRIP steel and the corresponding base material showed considerable differences in the microstructure and properties. (C) 2009 Elsevier B.V. All rights reserved.

Characterization of mixed waste of granite and LD slag

This study focuses on the technical feasibility of the utilization of waste from the cutting of granite to adjust the chemical composition of slag from steelworks LD, targeting the addition of clinker Portland cement. For this, chemical characterization of the waste, its mixture and fusion was performed, obtaining a CaO/SiO(2) relationship of around 0.9 to 1.2 for the steelworks slag. We selected samples of the waste, mixed, melted and cooled in water and in the oven. Samples cooled in water, after examining with X-ray difractrograms, had been predominantly amorphous. For samples cooled in the furnace, which had vitreous, there was the presence of mineralogical phases Akermanita and Gehlenita, which is considered as the ideal stage for the mineral water activity of the slag. The adjustment of the chemical composition of the slag from steel works by the addition of waste granite was efficient, transforming the waste into a product that is the same as blast furnace slag and can be used in the manufacture of cement.