Glass-forming ability of butanediol isomers

In this study, the thermal behavior of butanediol isomers is investigated for temperatures ranging from 103 to 303 K using differential scanning calorimetry, complemented, when necessary, by polarized light thermal microscopy. The butanediol isomers display quite different thermal behaviors: for 1,2- and 1,3-isomers, glass transition is the only thermal event observed; for 1,4-butanediol, crystallization occurs on cooling even at a high scanning rate and no glass formation was detected; and for the 2,3-isomer, glass or crystal formation is dependent on the experimental conditions employed. The glass-forming ability of the isomers is correlated with data available on their molecular symmetry.     

Dark matter results from 100 live days of XENON100 data

We present results from the direct search for dark matter with the XENON100 detector, installed underground at the Laboratori Nazionali del Gran Sasso of INFN, Italy. XENON100 is a two-phase time-projection chamber with a 62 kg liquid xenon target. Interaction vertex reconstruction in three dimensions with millimeter precision allows the selection of only the innermost 48 kg as the ultralow background fiducial target. In 100.9 live days of data, acquired between January and June 2010, no evidence for dark matter is found. Three candidate events were observed in the signal region with an expected background of (1.8 ± 0.6) events. This leads to the most stringent limit on dark matter interactions today, excluding spin-independent elastic weakly interacting massive particle (WIMP) nucleon scattering cross sections above 7.0 × 10(-45) cm(2) for a WIMP mass of 50 GeV/c(2) at 90% confidence level.     

3D elemental distribution images in biological samples by XRFµCT

An X‐ray transmission microtomography (CT) system combined with an X‐ray fluorescence microtomography (XRFµCT) system was implemented in the Brazilian Synchrotron Light Laboratory (LNLS), Campinas, Brazil. The aim of this work was to determine the elemental distribution in biological samples (breast, prostate and lung samples) in order to verify the concentration of some elements correlated with characteristics and pathology of each tissue observed by the transmission CT. The experiments were performed at the X‐ray fluorescence beamline (D09B‐XRF) of the Brazilian Synchrotron Light Laboratory, Campinas, Brazil. A quasi‐monochromatic beam produced by a multilayer monochromator was used as an incident beam. The sample was placed on a high‐precision goniometer and translation stages that allow rotating as well as translating it perpendicularly to the beam. The fluorescence photons were collected with an energy dispersive HPGe detector placed at 90° to the incident beam, while transmitted photons were detected with a fast Na(Tl) scintillation counter placed behind the sample on the beam path. The CT images were reconstructed using a filtered‐back projection algorithm and the XRFµCT images were reconstructed using a filtered‐back projection algorithm with absorption corrections. The 3D images were reconstructed using the 3D‐DOCTOR software. Results from the 3D visualization showed that the distribution of iron, copper and zinc is different and heterogeneous from the analyzed samples. Copyright © 2011 John Wiley & Sons, Ltd.     

Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company

Due to an increased awareness and significant environmental pressures from various stakeholders, companies have begun to realize the significance of incorporating green practices into their daily activities. This paper proposes a framework using Fuzzy TOPSIS to select green suppliers for a Brazilian electronics company; our framework is built on the criteria of green supply chain management (GSCM) practices. An empirical analysis is made, and the data are collected from a set of 12 available suppliers. We use a fuzzy TOPSIS approach to rank the suppliers, and the results of the proposed framework are compared with the ranks obtained by both the geometric mean and the graded mean methods of fuzzy TOPSIS methodology. Then a Spearman rank correlation coefficient is used to find the statistical difference between the ranks obtained by the three methods. Finally, a sensitivity analysis has been performed to examine the influence of the preferences given by the decision makers for the chosen GSCM practices on the selection of green suppliers. Results indicate that the four dominant criteria are Commitment of senior management to GSCM; Product designs that reduce, reuse, recycle, or reclaim materials, components, or energy; Compliance with legal environmental requirements and auditing programs; and Product designs that avoid or reduce toxic or hazardous material use.     

A genetic algorithm with neural network fitness function evaluation for IMRT beam angle optimization

Intensity Modulated Radiotherapy Treatment (IMRT) is a technique used in the treatment of cancer, where the radiation beams are modulated by a multileaf collimator allowing the irradiation of the patient using non-uniform radiation fields from selected angles. Beam angle optimization consists in trying to find the best set of angles that should be used in IMRT planning. The choice of this set of angles is patient and pathology dependent and, in clinical practice, most of the times it is made using a trial and error procedure or simply using equidistantly distributed angles. In this paper we propose a genetic algorithm that aims at calculating good sets of angles in an automated way, given a predetermined number of angles. We consider the discretization of all possible angles in the interval [0 \(^{\circ }\) , 360 \(^{\circ }\) ], and each individual is represented by a chromosome with 360 binary genes. As the calculation of a given individual’s fitness is very expensive in terms of computational time, the genetic algorithm uses a neural network as a surrogate model to calculate the fitness of most of the individuals in the population. To explicitly consider the estimation error that can result from the use of this surrogate model, the fitness of each individual is represented by an interval of values and not by a single crisp value. The genetic algorithm is capable of finding improved solutions, when compared to the usual equidistant solution applied in clinical practice. The genetic algorithm will be described and computational results will be shown.     

Viscoelastic flow analysis using the software OpenFOAM and differential constitutive equations

Viscoelastic fluids are of great importance in many industrial sectors, such as in food and synthetic polymers industries. The rheological response of viscoelastic fluids is quite complex, including combination of viscous and elastic effects and non-linear phenomena. This work presents a numerical methodology based on the split-stress tensor approach and the concept of equilibrium stress tensor to treat high Weissenberg number problems using any differential constitutive equations. The proposed methodology was implemented in a new computational fluid dynamics (CFD) tool and consists of a viscoelastic fluid module included in the OpenFOAM, a flexible open source CFD package. Oldroyd-B/UCM, Giesekus, Phan-Thien–Tanner (PTT), Finitely Extensible Nonlinear Elastic (FENE-P and FENE-CR), and Pom–Pom based constitutive equations were implemented, in single and multimode forms. The proposed methodology was evaluated by comparing its predictions with experimental and numerical data from the literature for the analysis of a planar 4:1 contraction flow, showing to be stable and efficient.     

A newton approach for long term stability studies in power systems

This paper deals with the problem of transient and long term stability of power systems. The issue of assessing both horizons of analysis is particularly focused. This is because the long term stability may be studied by a simplified algebraic model which also captures some dynamic characteristics. Such an approach is called quasi-dynamic model. The idea of analyzing the transient period and migrating to the quasi-dynamic model is addressed in this paper. The theoretical foundation is presented and some tests are carried out in order to validate the approach.     

Moran's genetics model via electric networks

Using the electric approach, we derive exact and asymptotic closed form formulas for hitting times in symmetric cases of the Moran's genetics model.     

Orbital Stability of Double Solitons for the Benjamin-Ono Equation

In this paper we prove the orbital stability of double solitons for the Benjamin-Ono equation. In the case of the KdV equation, this stability has been proved in [17]. Parts of the proof given there rely on the fact that the Euler-Lagrange equations for the conserved quantities of the KdV equation are ordinary differential equations. Since this is not the case for the Benjamin-Ono equation, new methods are required. Our approach consists in using a new invariant for multi-solitons, and certain new identities motivated by the Sylvester Law of Inertia.     

A branch-and-price algorithm for scheduling parallel machines with sequence dependent setup times

We consider the problem of scheduling n independent jobs on m unrelated parallel machines with sequence-dependent setup times and availability dates for the machines and release dates for the jobs to minimize a regular additive cost function. In this work, we develop a new branch-and-price optimization algorithm for the solution of this general class of parallel machines scheduling problems. A new column generation accelerating method, termed “primal box”, and a specific branching variable selection rule that significantly reduces the number of explored nodes are proposed. The computational results show that the approach solves problems of large size to optimality within reasonable computational time.