USHER: an algorithm for particle insertion in dense fluids

The insertion of solvent particles in molecular dynamics simulations of complex fluids is required in many situations involving open systems, but this challenging task has been scarcely explored in the literature. We propose a simple and fast algorithm (USHER) that inserts the new solvent particles at locations where the potential energy has the desired prespecified value. For instance, this value may be set equal to the system's excess energy per particle, in such way that the inserted particles are energetically indistinguishable from the other particles present. During the search for the insertion site, the USHER algorithm uses a steepest descent iterator with a displacement whose magnitude is adapted to the local features of the energy landscape. The only adjustable parameter in the algorithm is the maximum displacement and we show that its optimal value can be extracted from an analysis of the structure of the potential energy landscape. We present insertion tests in periodic and non-periodic systems filled with a Lennard-Jones fluid whose density ranges from moderate values to high values.Comment: 10 pages (Latex), 8 figures (postscript); J. Chem. Phys. (in press) 200

A minimal model for acoustic forces on Brownian particles

We present a generalization of the inertial coupling (IC) [Usabiaga et al. J. Comp. Phys. 2013] which permits the resolution of radiation forces on small particles with arbitrary acoustic contrast factor. The IC method is based on a Eulerian-Lagrangian approach: particles move in continuum space while the fluid equations are solved in a regular mesh (here we use the finite volume method). Thermal fluctuations in the fluid stress, important below the micron scale, are also taken into account following the Landau-Lifshitz fluid description. Each particle is described by a minimal cost resolution which consists on a single small kernel (bell-shaped function) concomitant to the particle. The main role of the particle kernel is to interpolate fluid properties and spread particle forces. Here, we extend the kernel functionality to allow for an arbitrary particle compressibility. The particle-fluid force is obtained from an imposed no-slip constraint which enforces similar particle and kernel fluid velocities. This coupling is instantaneous and permits to capture the fast, non-linear effects underlying the radiation forces on particles. Acoustic forces arise either because an excess in particle compressibility (monopolar term) or in mass (dipolar contribution) over the fluid values. Comparison with theoretical expressions show that the present generalization of the IC method correctly reproduces both contributions. Due to its low computational cost, the present method allows for simulations with many particles using a standard Graphical Processor Unit (GPU)

Stress and Decision Making: Effects on Valuation, Learning, and Risk-taking

A wide range of stressful experiences can influence human decision making in complex ways beyond the simple predictions of a fight-or-flight model. Recent advances may provide insight into this complicated interaction, potentially in directions that could result in translational applications. Early research suggests that stress exposure influences basic neural circuits involved in reward processing and learning, while also biasing decisions toward habit and modulating our propensity to engage in risk-taking. That said, a substantial array of theoretical and methodological considerations in research on the topic challenge strong cross study comparisons necessary for the field to move forward. In this review we examine the multifaceted stress construct in the context of human decision making, emphasizing stress’ effect on valuation, learning, and risk-taking

Constructing three emotion knowledge tests from the invariant measurement approach

Background. Psychological constructionist models like the Conceptual Act Theory (CAT) postulate that complex states such as emotions are composed of basic psychological ingredients that are more clearly respected by the brain than basic emotions. The objective of this study was the construction and initial validation of Emotion Knowledge measures from the CAT frame by means of an invariant measurement approach, the Rasch Model (RM). Psychological distance theory was used to inform item generation. Methods. Three EK testsemotion vocabulary (EV), close emotional situations (CES) and far emotional situations (FES)were constructed and tested with the RM in a community sample of 100 females and 100 males (age range: 18-65), both separately and conjointly. Results. It was corroborated that data-RM fit was sufficient. Then, the effect of type of test and emotion on Rasch-modelled item difficulty was tested. Significant effects of emotion on EK item difficulty were found, but the only statistically significant difference was that between "happiness" and the remaining emotions; neither type of test, nor interaction effects on EK item difficulty were statistically significant. The testing of gender differences was carried out after corroborating that differential item functioning (DIF) would not be a plausible alternative hypothesis for the results. No statistically significant sex-related differences were found out in EV, CES, FES, or total EK. However, the sign of d indicate that female participants were consistently better than male ones, a result that will be of interest for future meta-analyses. Discussion. The three EK tests are ready to be used as components of a higher-level measurement process.Fil: Delgado, Ana R.. Universidad de Salamanca; EspañaFil: Prieto, Gerardo. Universidad de Salamanca; EspañaFil: Burin, Debora Ines. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Psicología; Argentin