Interpretation of MINOS data in terms of nonstandard neutrino interactions

The MINOS experiment at Fermilab has recently reported a tension between the oscillation results for neutrinos and antineutrinos. We show that this tension, if it persists, can be understood in the framework of nonstandard neutrino interactions (NSI). While neutral current NSI (nonstandard matter effects) are disfavored by atmospheric neutrinos, a new charged current coupling between tau neutrinos and nucleons can fit the MINOS data without violating other constraints. In particular, we show that loop-level contributions to flavor-violating tau decays are sufficiently suppressed. However, conflicts with existing bounds could arise once the effective theory considered here is embedded into a complete renormalizable model. We predict the future sensitivity of the T2K and NOvA experiments to the NSI parameter region favored by the MINOS fit, and show that both experiments are excellent tools to test the NSI interpretation of the MINOS data.

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Crystallization and preliminary X-ray diffraction analysis of recombinant chlorocatechol 1,2-dioxygenase from Pseudomonas putida

Chlorocatechol 1,2-dioxygenase from the Gram-negative bacterium Pseudomonas putida (Pp 1,2-CCD) is considered to be an important biotechnological tool owing to its ability to process a broad spectrum of organic pollutants. In the current work, the crystallization, crystallographic characterization and phasing of the recombinant Pp 1,2-CCD enzyme are described. Reddish-brown crystals were obtained in the presence of polyethylene glycol and magnesium acetate by utilizing the vapour-diffusion technique in sitting drops. Crystal dehydration was the key step in obtaining data sets, which were collected on the D03B-MX2 beamline at the CNPEM/MCT - LNLS using a MAR CCD detector. Pp 1,2-CCD crystals belonged to space group P6(1)22 and the crystallographic structure of Pp 1,2-CCD has been solved by the MR-SAD technique using Fe atoms as scattering centres and the coordinates of 3-chlorocatechol 1,2-dioxygenase from Rhodococcus opacus (PDB entry 2boy) as the search model. The initial model, which contains three molecules in the asymmetric unit, has been refined to 3.4 A resolution.

Geodynamic evolution of the SW Variscides: Orogenic collapse shown by new tectonometamorphic and isotopic data from western Ossa-Morena Zone, SW Iberia

The pre-Mesozoic geodynamic evolution of SW Iberia has been investigated on the basis of detailed structural analysis, isotope dating, and petrologic study of high-pressure (HP) rocks, revealing the superposition of several tectonometamorphic events: (1) An HP event older than circa 358 Ma is recorded in basic rocks preserved inside marbles, which suggests subduction of a continental margin. The deformation associated with this stage is recorded by a refractory graphite fabric and noncoaxial mesoscopic structures found within the host metasediments. The sense of shear is top to south, revealing thrusting synthetic with subduction (underthrusting) to the north. (2) Recrystallization before circa 358 Ma is due to a regional-scale thermal episode and magmatism. (3) Noncoaxial deformation with top to north sense of shear in northward dipping large-scale shear zones is associated with pervasive hydration and metamorphic retrogression under mostly greenschist facies. This indicates exhumation by normal faulting in a detachment zone confined to the top to north and north dipping shear zones during postorogenic collapse soon after 358 Ma ago (inversion of earlier top to south thrusts). (4) Static recrystallization at circa 318 Ma is due to regional-scale granitic intrusions. Citation: Rosas, F. M., F. O. Marques, M. Ballevre, and C. Tassinari (2008), Geodynamic evolution of the SW Variscides: Orogenic collapse shown by new tectonometamorphic and isotopic data from western Ossa-Morena Zone, SW Iberia, Tectonics, 27, TC6008, doi:10.1029/2008TC002333.

X-ray diffraction data of tibolone Delta(4) isomer (isotibolone)

Tibolone is used for hormone reposition of postmenopause women and isotibolone is considered the major degradation product of tibolone. Isotibolone can also be present in tibolone API raw materials due to some inadequate synthesis. Its presence is then necessary to be identified and quantified in the quality control of both API and drug products. In this work we present the indexing of an isotibolone X-ray diffraction pattern measured with synchrotron light (lambda=1.2407 angstrom) in the transmission mode. The characterization of the isotibolone sample by IR spectroscopy, elemental analysis, and thermal analysis are also presented. The isotibolone crystallographic data are a=6.8066 angstrom, b=20.7350 angstrom, c=6.4489 angstrom, beta=76.428 degrees, V=884.75 angstrom(3), and space group P2(1), rho(o)= 1.187 g cm(-3), Z=2. (C) 2009 International Centre for Diffraction Data. [DOI: 10.1154/1.3257612]

Intracellular Ca(2+) Regulation During Neuronal Differentiation of Murine Embryonal Carcinoma and Mesenchymal Stem Cells

Changes in intracellular Ca(2+) concentration ([Ca(2+)](i)) play a central role in neuronal differentiation. However, Ca(2+) signaling in this process remains poorly understood and it is unknown whether embryonic and adult stem cells share the same signaling pathways. To clarify this issue, neuronal differentiation was analyzed in two cell lines: embryonic P19 carcinoma stem cells (CSCs) and adult murine bone-marrow mesenchymal stem cells (MSC). We studied Ca(2+) release from the endoplasmic reticulum via intracellular ryanodine-sensitive (RyR) and IP(3)-sensitive (IP(3)R) receptors. We observed that caffeine, a RyR agonist, induced a [Ca(2+)](i) response that increased throughout neuronal differentiation. We also demonstrated a functional coupling between RyRs and L-but not with N-, P-, or Q-type Ca(v)1 Ca(2+) channels, both in embryonal CSC and adult MSC. We also found that agonists of L-type channels and of RyRs increase neurogenesis and neuronal differentiation, while antagonists of these channels have the opposite effect. Thus, our data demonstrate that in both cell lines RyRs control internal Ca(2+) release following voltage-dependent Ca(2+) entry via L-type Ca(2+) channels. This study shows that both in embryonal CSC and adult MSC [Ca(2+)](i) is controlled by a common pathway, indicating that coupling of L-type Ca(2+) channels and RyRs may be a conserved mechanism necessary for neuronal differentiation.

Effect of sugarcane harvesting systems on soil carbon stocks in Brazil: an examination of existing data

Agricultural management practices that promote net carbon (C) accumulation in the soil have been considered as an important potential mitigation option to combat global warming. The change in the sugarcane harvesting system, to one which incorporates C into the soil from crop residues, is the focus of this work. The main objective was to assess and discuss the changes in soil organic C stocks caused by the conversion of burnt to unburnt sugarcane harvesting systems in Brazil, when considering the main soils and climates associated with this crop. For this purpose, a dataset was obtained from a literature review of soils under sugarcane in Brazil. Although not necessarily from experimental studies, only paired comparisons were examined, and for each site the dominant soil type, topography and climate were similar. The results show a mean annual C accumulation rate of 1.5 Mg ha-1 year-1 for the surface to 30-cm depth (0.73 and 2.04 Mg ha-1 year-1 for sandy and clay soils, respectively) caused by the conversion from a burnt to an unburnt sugarcane harvesting system. The findings suggest that soil should be included in future studies related to life cycle assessment and C footprint of Brazilian sugarcane ethanol.

Use of blanks to determine in vitro net gas and methane production when using rumen fermentation modifiers

Blanks (flasks without substrate containing only inoculum and medium) are used in vitro to correct for gas. CH(4) and residual organic matter (OM) fermented in inoculum. However inclusion of rumen fermentation modifiers may affect fermentation of OM in the substrate and inoculum. Thus, data correction using blanks that lack additives may result in inaccurate adjustment for background fermentation. Our objective was to evaluate impacts of using blanks containing additive (i.e., specific blanks) or blanks without additive on estimation of in vitro net gas and CH(4) production. We used the semi-automatic in vitro gas production technique including monensin sodium at 2.08 mg/l of buffered rumen fluid (Experiment 1) or carvacrol, eugenol and 1,8-cineol at 667 mg/l (Experiment 2) in flasks with substrate and in blank flasks. At 16h of incubation, monensin reduced (P <= 0.02) total gas production in flasks containing substrate (162.0 ml versus 146.3 ml) and in blanks (84.4 ml versus 79.2 ml). Total methane production was also decreased (P <= 0.05) by adding monensin to flasks containing substrate (15.7 ml versus 11.9 ml) as well as in blanks (6.4 ml versus 5.0 ml). Inclusion of carvacrol or eugenol reduced (P <= 0.05) total gas and CH(4) production in flasks with substrate and in blanks, but in a more pronounced manner than monensin. For these three additives, correction for blank without additive resulted in lower net gas and CH(4) production than correction for a treatment specific blank. For instance, correcting carvacrol data using a blank without the additive resulted in negative net gas and CH(4) production (-6.5 and -1.5 ml. respectively). These biologically impossible results occurred because total gas and CH(4) production in blanks without carvacrol (46.1 and 2.1 ml, respectively) were higher than in flasks containing substrate plus carvacrol (39.7 and 0.6 ml, respectively). Results demonstrated that inclusion of rumen additives affected fermentation of OM in the substrate and the inoculum. Thus, correction of gas and CH(4) production using blanks without additives resulted in overestimation of these variables. Blanks containing the additive of interest should be included when rumen fermentation modifiers are evaluated in vitro. This paper is part of the special issue entitled: Greenhouse Gases in Animal Agriculture Finding a Balance between Food and Emissions, Guest Edited by T.A. McAllister, Section Guest Editors: K.A. Beauchemin, X. Hao, S. McGinn and Editor for Animal Feed Science and Technology, P.H. Robinson. (C) 2011 Elsevier B.V. All rights reserved.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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.

SAB(IO): A BIOLOGICALLY PLAUSIBLE CONNECTIONIST APPROACH TO AUTOMATIC TEXT SUMMARIZATION

An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the sa-called biologically implausible algorithms.

Equivalence between hot tensile and creep testing data for Kanthal A1 alloy

Hot tensile and creep tests were carried out on Kanthal A1 alloy in the temperature range from 600 to 800 degrees C. Each of these sets of data were analyzed separately according to their own methodologies, but an attempt was made to find a correlation between them. A new criterion proposed for converting hot tensile data to creep data, makes possible the analysis of the two kinds of results according to usual creep relations like: Norton, Monkman-Grant, Larson-Miller and others. The remarkable compatibility verified between both sets of data by this procedure strongly suggests that hot tensile data can be converted to creep data and vice-versa for Kanthal A1 alloy, as verified previously for other metallic materials.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.