Cluster persistence in one-dimensional diffusion--limited cluster--cluster aggregation

The persistence probability, $P_C(t)$, of a cluster to remain unaggregated is studied in cluster-cluster aggregation, when the diffusion coefficient of a cluster depends on its size $s$ as $D(s) \sim s^\gamma$. In the mean-field the problem maps to the survival of three annihilating random walkers with time-dependent noise correlations. For $\gamma \ge 0$ the motion of persistent clusters becomes asymptotically irrelevant and the mean-field theory provides a correct description. For $\gamma < 0$ the spatial fluctuations remain relevant and the persistence probability is overestimated by the random walk theory. The decay of persistence determines the small size tail of the cluster size distribution. For $0 < \gamma < 2$ the distribution is flat and, surprisingly, independent of $\gamma$.Comment: 11 pages, 6 figures, RevTeX4, submitted to Phys. Rev.

Designing for dynamic task allocation

Future platforms are envisioned in which human-machine teams are able to share and trade tasks as demands in situations change. It seems that human-machine coordination has not received the attention it deserves by past and present approaches to task allocation. In this paper a simple way to make coordination requirements explicit is proposed and for dynamic task allocation a dual-route approach is suggested. Advantages of adaptable automation, in which the human adjusts the way tasks are divided and shared, are complemented with those of adaptive automation, in which the machine allocates tasks. To be able to support design for dynamic task allocation, a theory about task allocation decision making by means of modeling of trust is proposed. It is suggested that dynamic task allocation is improved when information about situational abilities of agents is provided and the cost of observing and re-directing agents is reduced

Towards Task Allocation Decision Support by means of Cognitive Modeling of Trust

An important issue in research on human-machine cooperation concerns how tasks should be dynamically allocated within a human-machine team in order to improve team performance. The ability to support humans in task allocation decision making requires a thorough understanding of its underlying cognitive processes, and that of relative trust more specifically. This paper presents a computational agent-based model of these cognitive processes and proposes an experiment design that can be used to validate theoretical aspects of this model

Moderate contrast in the evaluation of paintings is liked more but remembered less than high contrast

Many visual aspects of paintings, as well as exposure to art and cultural norms, contribute to the aesthetic evaluation of paintings. The current study looked at heightened visual contrast as an important factor in the appreciation of paintings. Participants evaluated abstract digitized paintings that were manipulated in contrast for an appreciation task and were later presented with these paintings in a memory task. The results indicated that for art appreciation, a moderate increase in contrast resulted in the highest appreciation for paintings whereas recognition memory was better for paintings with a higher increase in contrast. These results replicate earlier findings with regard to the role of contrast in aesthetic perception and extend these findings by demonstrating a surprising different effect of contrast manipulation for recognition memory. Confidence with which memory decisions were made was in line with art appreciation decisions not memory performance

Charge-density-wave order parameter of the Falicov-Kimball model in infinite dimensions

In the large-U limit, the Falicov-Kimball model maps onto an effective Ising model, with an order parameter described by a BCS-like mean-field theory in infinite dimensions. In the small-U limit, van Dongen and Vollhardt showed that the order parameter assumes a strange non-BCS-like shape with a sharp reduction near T approx T_c/2. Here we numerically investigate the crossover between these two regimes and qualitatively determine the order parameter for a variety of different values of U. We find the overall behavior of the order parameter as a function of temperature to be quite anomalous.Comment: (5 pages, 3 figures, typeset with ReVTeX4

Phase separation and the segregation principle in the infinite-U spinless Falicov-Kimball model

The simplest statistical-mechanical model of crystalline formation (or alloy formation) that includes electronic degrees of freedom is solved exactly in the limit of large spatial dimensions and infinite interaction strength. The solutions contain both second-order phase transitions and first-order phase transitions (that involve phase-separation or segregation) which are likely to illustrate the basic physics behind the static charge-stripe ordering in cuprate systems. In addition, we find the spinodal-decomposition temperature satisfies an approximate scaling law.Comment: 19 pages and 10 figure