To Help or Not to Help? Assessing the Impact of Envy and Gratitude on Prosocial Behaviors

Envy is an other-oriented but negative emotion; no research has examined the influence of envy on prosocial behavior. Study 1 examined whether envy and gratitude would promote or inhibit prosocial behavior. I hypothesized that envy would result in less helping behavior than a neutral condition, whereas gratitude would increase helping behavior. Results supported the hypothesis that envy inhibits prosocial behavior. There was not enough evidence to suggest that gratitude promoted helping. Study 2 examined how envy and gratitude affected prosocial behavior when participants were given the choice to help or harm others. I hypothesized that experiencing envy would result in greater likelihood of engaging in harmful behavior, but that gratitude would promote more helpful behavior, even when it meant a less positive outcome for participants. The hypothesis that envy increases harming behavior was supported, while there was not enough evidence to suggest that gratitude promoted helping behavior in this scenario

When Empathy Only Goes So Far: Development of a Trait Parochial Empathy Scale

Empathy, the ability to feel and/or understand another’s emotional state, plays a significant role in interpersonal interactions, mitigating hostility and enhancing affiliation and helping. However, empathy also biases interpersonal reactions. For example, at the group level empathy can become amplified towards members of their ingroup and blunted towards individuals in outgroups, a term called parochial empathy. Currently, no validated measures of parochial empathy at the dispositional level exist, and development of such a scale would be important to understanding the role of group-based emotions in prejudice and discrimination against outgroups. I conducted five studies to develop and validate a self-report Trait Parochial Empathy Scale (TPES) that could measure tendencies to respond with parochial empathy across any set of group membership categories. Study 1 assessed the factor structure of the TPES through exploratory and confirmatory factor analyses while Study 2 attempted to replicate the Study 1 factor structure and assess concurrent and divergent validity of the TPES using attitudinal measures. Study 3 assessed the temporal consistency of the TPES. Study 4 examined whether the TPES could be flexibly used across a variety of groups by assessing its relation to various outcomes across different ingroup and outgroup combinations. Finally, Study 5 assessed the ability of the TPES to predict in vivo behavior

A New Type of distributed Enamel based Clearing Electrode

Clearing electrodes can be used for electron cloud (EC) suppression in high intensity particle accelerators. In this paper the use of low and highly resistive layers on a dielectric substrate are examined. The beam coupling impedance of such a structure is evaluated. Furthermore the clearing efficiency as well as technological issues are discussed

Coulomb Gap and Correlated Vortex Pinning in Superconductors

The positions of columnar pins and magnetic flux lines determined from a decoration experiment on BSCCO were used to calculate the single--particle density of states at low temperatures in the Bose glass phase. A wide Coulomb gap is found, with gap exponent $s \approx 1.2$, as a result of the long--range interaction between the vortices. As a consequence, the variable--range hopping transport of flux lines is considerably reduced with respect to the non--interacting case, the effective Mott exponent being enhanced from $p_0 = 1/3$ to $p_{\rm eff} \approx 0.5$ for this specific experiment.Comment: 10 pages, Revtex, 4 figures appended as uu-encoded postscript files, also available as hardcopies from [email protected]

Nucleation mechanism for the direct graphite-to-diamond phase transition

Graphite and diamond have comparable free energies, yet forming diamond from graphite is far from easy. In the absence of a catalyst, pressures that are significantly higher than the equilibrium coexistence pressures are required to induce the graphite-to-diamond transition. Furthermore, the formation of the metastable hexagonal polymorph of diamond instead of the more stable cubic diamond is favored at lower temperatures. The concerted mechanism suggested in previous theoretical studies cannot explain these phenomena. Using an ab initio quality neural-network potential we performed a large-scale study of the graphite-to-diamond transition assuming that it occurs via nucleation. The nucleation mechanism accounts for the observed phenomenology and reveals its microscopic origins. We demonstrated that the large lattice distortions that accompany the formation of the diamond nuclei inhibit the phase transition at low pressure and direct it towards the hexagonal diamond phase at higher pressure. The nucleation mechanism proposed in this work is an important step towards a better understanding of structural transformations in a wide range of complex systems such as amorphous carbon and carbon nanomaterials

Interactions, Distribution of Pinning Energies, and Transport in the Bose Glass Phase of Vortices in Superconductors

We study the ground state and low energy excitations of vortices pinned to columnar defects in superconductors, taking into account the long--range interaction between the fluxons. We consider the ``underfilled'' situation in the Bose glass phase, where each flux line is attached to one of the defects, while some pins remain unoccupied. By exploiting an analogy with disordered semiconductors, we calculate the spatial configurations in the ground state, as well as the distribution of pinning energies, using a zero--temperature Monte Carlo algorithm minimizing the total energy with respect to all possible one--vortex transfers. Intervortex repulsion leads to strong correlations whenever the London penetration depth exceeds the fluxon spacing. A pronounced peak appears in the static structure factor $S(q)$ for low filling fractions $f \leq 0.3$. Interactions lead to a broad Coulomb gap in the distribution of pinning energies $g(\epsilon)$ near the chemical potential $\mu$, separating the occupied and empty pins. The vanishing of $g(\epsilon)$ at $\mu$ leads to a considerable reduction of variable--range hopping vortex transport by correlated flux line pinning.Comment: 16 pages (twocolumn), revtex, 16 figures not appended, please contact [email protected]

Performance and Cost Assessment of Machine Learning Interatomic Potentials.

Machine learning of the quantitative relationship between local environment descriptors and the potential energy surface of a system of atoms has emerged as a new frontier in the development of interatomic potentials (IAPs). Here, we present a comprehensive evaluation of machine learning IAPs (ML-IAPs) based on four local environment descriptors-atom-centered symmetry functions (ACSF), smooth overlap of atomic positions (SOAP), the spectral neighbor analysis potential (SNAP) bispectrum components, and moment tensors-using a diverse data set generated using high-throughput density functional theory (DFT) calculations. The data set comprising bcc (Li, Mo) and fcc (Cu, Ni) metals and diamond group IV semiconductors (Si, Ge) is chosen to span a range of crystal structures and bonding. All descriptors studied show excellent performance in predicting energies and forces far surpassing that of classical IAPs, as well as predicting properties such as elastic constants and phonon dispersion curves. We observe a general trade-off between accuracy and the degrees of freedom of each model and, consequently, computational cost. We will discuss these trade-offs in the context of model selection for molecular dynamics and other applications