Chemical abundance analysis of the Be star HD 171054

In this work the results of a spectroscopic study of the southern field narrow-line Be star HD 171054 are presented. High dispersion and signal-to-noise ratio spectra allowed the estimation of the fundamental photospheric parameters such as the projected rotational velocity, effective temperature and superficial gravity from non-LTE stellar atmosphere models. From these parameters and microturbulence, the abundances of He, C, N, O, Mg, Al and Si for this object are estimated. Results show that C is depleted whereas N is overabundant compared with the sun and OB stars in the solar vicinity. Oxygen and helium are close to the solar value. Magnesium is down by 0.43 dex and aluminium and silicon are overabundant. (C) 2010 Elsevier B.V. All rights reserved.

Star products made (somewhat) easier

We develop an approach to the deformation quantization on the real plane with an arbitrary Poisson structure which is based on Weyl symmetrically ordered operator products. By using a polydifferential representation for the deformed coordinates, xj we are able to formulate a simple and effective iterative procedure which allowed us to calculate the fourth-order star product (and may be extended to the fifth order at the expense of tedious but otherwise straightforward calculations). Modulo some cohomology issues which we do not consider here, the method gives an explicit and physics-friendly description of the star products.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

Timing and structure of the 8.2 kyr BP event inferred from delta(18)O records of stalagmites from China, Oman, and Brazil

Oxygen isotope records of stalagmites from China and Oman reveal a weak summer monsoon event, with a double-plunging structure, that started 8.21 +/- 0.02 kyr B. P. An identical but antiphased pattern is also evident in two stalagmite records from eastern Brazil, indicating that the South American Summer Monsoon was intensified during the 8.2 kyr B. P. event. These records demonstrate that the event was of global extent and synchronous within dating errors of <50 years. In comparison with recent model simulations, it is plausible that the 8.2 kyr B. P. event can be tied in changes of the Atlantic Meridional Overturning Circulation triggered by a glacial lake draining event. This, in turn, affected North Atlantic climate and latitudinal position of the Intertropical Convergence Zone, resulting in the observed low-latitude monsoonal precipitation patterns.

Second-order negative-curvature methods for box-constrained and general constrained optimization

A Nonlinear Programming algorithm that converges to second-order stationary points is introduced in this paper. The main tool is a second-order negative-curvature method for box-constrained minimization of a certain class of functions that do not possess continuous second derivatives. This method is used to define an Augmented Lagrangian algorithm of PHR (Powell-Hestenes-Rockafellar) type. Convergence proofs under weak constraint qualifications are given. Numerical examples showing that the new method converges to second-order stationary points in situations in which first-order methods fail are exhibited.

Weak hypergraph regularity and linear hypergraphs

We consider conditions which allow the embedding of linear hypergraphs of fixed size. In particular, we prove that any k-uniform hypergraph H of positive uniform density contains all linear k-uniform hypergraphs of a given size. More precisely, we show that for all integers l >= k >= 2 and every d > 0 there exists Q > 0 for which the following holds: if His a sufficiently large k-uniform hypergraph with the property that the density of H induced on every vertex subset of size on is at least d, then H contains every linear k-uniform hypergraph F with l vertices. The main ingredient in the proof of this result is a counting lemma for linear hypergraphs, which establishes that the straightforward extension of graph epsilon-regularity to hypergraphs suffices for counting linear hypergraphs. We also consider some related problems. (C) 2009 Elsevier Inc. All rights reserved.

Improving ultimate convergence of an augmented Lagrangian method

Optimization methods that employ the classical Powell-Hestenes-Rockafellar augmented Lagrangian are useful tools for solving nonlinear programming problems. Their reputation decreased in the last 10 years due to the comparative success of interior-point Newtonian algorithms, which are asymptotically faster. In this research, a combination of both approaches is evaluated. The idea is to produce a competitive method, being more robust and efficient than its `pure` counterparts for critical problems. Moreover, an additional hybrid algorithm is defined, in which the interior-point method is replaced by the Newtonian resolution of a Karush-Kuhn-Tucker (KKT) system identified by the augmented Lagrangian algorithm. The software used in this work is freely available through the Tango Project web page:http://www.ime.usp.br/similar to egbirgin/tango/.

Density-Profile Processes Describing Biological Signaling Networks: Almost Sure Convergence to Deterministic Trajectories

We introduce jump processes in R(k), called density-profile processes, to model biological signaling networks. Our modeling setup describes the macroscopic evolution of a finite-size spin-flip model with k types of spins with arbitrary number of internal states interacting through a non-reversible stochastic dynamics. We are mostly interested on the multi-dimensional empirical-magnetization vector in the thermodynamic limit, and prove that, within arbitrary finite time-intervals, its path converges almost surely to a deterministic trajectory determined by a first-order (non-linear) differential equation with explicit bounds on the distance between the stochastic and deterministic trajectories. As parameters of the spin-flip dynamics change, the associated dynamical system may go through bifurcations, associated to phase transitions in the statistical mechanical setting. We present a simple example of spin-flip stochastic model, associated to a synthetic biology model known as repressilator, which leads to a dynamical system with Hopf and pitchfork bifurcations. Depending on the parameter values, the magnetization random path can either converge to a unique stable fixed point, converge to one of a pair of stable fixed points, or asymptotically evolve close to a deterministic orbit in Rk. We also discuss a simple signaling pathway related to cancer research, called p53 module.

Countability and star covering properties

Whenever P is a topological property, we say that a topological space is star P if whenever U is an open cover of X, there is a subspace A subset of X with property P such that X = St(A, U). We study the relationships of star P properties for P is an element of {Lindelof, sigma-compact, countable} with other Lindelof type properties. (C) 2010 Elsevier B.V. All rights reserved.

Star-group identities and groups of units

Analogous to *-identities in rings with involution we define *-identities in groups. Suppose that G is a torsion group with involution * and that F is an infinite field with char F not equal 2. Extend * linearly to FG. We prove that the unit group U of FG satisfies a *-identity if and only if the symmetric elements U(+) satisfy a group identity.

Intrachain Energy Migration to Weak Charge-Transfer State in Polyfluorene End-Capped with Naphthalimide Derivative

Polyfluorene end-capped with N-(2-benzothiazole)-1 8-naphthalimide (PF-BNI) is a highly fluorescent material with fluorescence emission modulated by solvent polarity Its low energy excited state is assigned as a mixed configuration state between the singlet S(1) of the fluorene backbone (F) with the charge transfer (CI) of the end group BNI The triexponential fluorescence decays of PF-BNI were associated with fast energy migration to form an intrachain charge-transfer (ICCT) state polyfluorene backbone decay and ICCT deactivation Time-resolved fluorescence anisotropy exhibited biexponential relaxation with a fast component of 12-16 ps in addition to a slow one in the range 0 8-1 4 ns depending on the solvent showing that depolarization occurs from two different processes energy migration to form the ICCT state and slow rotational diffusion motion of end segments at a longer time Results from femtosecond transient absorption measurements agreed with anisotropy decay and showed a decay component of about 16 ps at 605 nm in PF BNI ascribed to the conversion of S(1) to the ICCT excited state From the ratio of asymptotic and initial amplitudes of the transient absorption measurement the efficiency of intrachain ICCT formation is estimated in 0 5 which means that on average, half of the excited state formed in a BNI-(F)(n)-BNI chain with n = 32 is converted to its low energy intrachain charge-transfer (ICCT) state

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Performance Evaluation of Different PV-Array Configurations under Weak Light Conditions and Partial Shadings

The paper analyses empirical performance data of five commercial PV-plants in Germany. The purpose was on one side to investigate the weak light performance of the different PV-modules used. On the other hand it was to quantify and compare the shading losses of different PV-array configurations. The importance of this study relies on the fact that even if the behavior under weak light conditions or the shading losses might seem to be a relatively small percentage of the total yearly output; in projects where a performance guarantee is given, these variation can make the difference between meeting or not the conditions.When analyzing the data, a high dispersion was found. To reduce the optical losses and spectral effects, a series of data filters were applied based on the angle of incidence and absolute Air Mass. To compensate for the temperature effects and translate the values to STC (25°C), five different methods were assessed. At the end, the Procedure 2 of IEC 60891 was selected due to its relative simplicity, usage of mostly standard parameters found in datasheets, good accuracy even with missing values, and its potential to improve the results when the complete set of inputs is available.After analyzing the data, the weak light performance of the modules did not show a clear superiority of a certain technology or technology group over the others. Moreover, the uncertainties in the measurements restrictive the conclusiveness of the results.In the partial shading analysis, the landscape mounting of mc-Si PV-modules in free-field showed a significantly better performance than the portrait one. The cross-table string using CIGS modules did not proved the benefits expected and performed actually poorer than a regular one-string-per-table layout. Parallel substrings with CdTe showed a proper functioning and relatively low losses. Among the two product generations of CdTe analyzed, none showed a significantly better performance under partial shadings.

Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups

This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.