Examining the ‘Cosmetics Placebo Effect’

Previous studies have found a positive effect of cosmetics on certain behavioral measures, such as the tip given to waitresses by male patrons. These studies have employed confederates who usually wear cosmetics. We therefore sought to examine whether the positive effect found in these studies could, in part, be explained by a change in behavior. In order to test the possibility of a ‘cosmetics placebo effect’, we employed a confederate to solicit donations from passersby. On some days our confederate would not have any cosmetics applied to her face (i.e., no cosmetics condition), on some days cosmetics were pretended to be applied to her face (i.e., placebo cosmetics condition), and on other days cosmetics were actually applied to her face (i.e., cosmetics condition). In line with previous research, we found that across conditions men donated significantly more than women to our female solicitor, providing support for the ‘showoff hypothesis’, in which male generosity serves as a mating tactic. When investigating men’s donations in more detail, we found that the highest percentage of donations came in the cosmetics condition, followed by the placebo cosmetics condition, and then by no cosmetics condition. The effect of condition on donation rates, however, was not statistically significant. Our study was limited to one solicitor and one dependent variable (i.e., percentage of people approached who donated) and therefore future research would benefit from using more confederates as well as examining other behavioral measures. Given the influence of cosmetics use on so many real-world outcomes, we believe that further exploration into a possible ‘cosmetics placebo effect’ would be valuable

Decision-Making in Agent-Based Modeling: A Current Review and Future Prospectus

All basic processes of ecological populations involve decisions; when and where to move, when and what to eat, and whether to fight or flee. Yet decisions and the underlying principles of decision-making have been difficult to integrate into the classical population-level models of ecology. Certainly, there is a long history of modeling individuals' searching behavior, diet selection, or conflict dynamics within social interactions. When all the individuals are given certain simple rules to govern their decision-making processes, the resultant population–level models have yielded important generalizations and theory. But it is also recognized that such models do not represent the way real individuals decide on actions. Factors that influence a decision include the organism's environment with its dynamic rewards and risks, the complex internal state of the organism, and its imperfect knowledge of the environment. In the case of animals, it may also involve complex social factors, and experience and learning, which vary among individuals. The way that all factors are weighed and processed to lead to decisions is a major area of behavioral theory.While classic population-level modeling is limited in its ability to integrate decision-making in its actual complexity, the development of individual- or agent-based models (IBM/ABMs) (we use ABM throughout to designate both “agent-based modeling” and an “agent-based model”) has opened the possibility of describing the way that decisions are made, and their effects, in minute detail. Over the years, these models have increased in size and complexity. Current ABMs can simulate thousands of individuals in realistic environments, and with highly detailed internal physiology, perception and ability to process the perceptions and make decisions based on those and their internal states. The implementation of decision-making in ABMs ranges from fairly simple to highly complex; the process of an individual deciding on an action can occur through the use of logical and simple (if-then) rules to more sophisticated neural networks and genetic algorithms. The purpose of this paper is to give an overview of the ways in which decisions are integrated into a variety of ABMs and to give a prospectus on the future of modeling of decisions in ABMs

Bio-Assisted Tailored Synthesis of Plasmonic Silver Nanorings and Site-Selective Deposition on Graphene Arrays

The spontaneous interaction between noble metals and biological scaffolds enables simple and cost-effective synthesis of nanomaterials with unique features. Here, plasmonic silver nanorings are synthesized on a ring-like protein, i.e., a peroxiredoxin (PRX), and used to assemble large arrays of functional nanostructures. The PRX drives the seeding growth of metal silver under wet reducing conditions, yielding nanorings with outer and inner diameters down to 28 and 3 nm, respectively. The obtained hybrid nanostructures are selectively deposited onto a solid-state 2D membrane made of graphene in order to prepare plasmonic nanopores. In particular, the interaction between the graphene and the PRX allows for the simple preparation of ordered arrays of plasmonic nanorings on a 2D-material membrane. This fabrication process can be finalized by drilling a nanometer scale pore in the middle of the ring. Fluorescence spectroscopic measurements in combination with numerical simulations demonstrate the plasmonic effects induced in the metallic nanoring cavity. The prepared nanopores represent one of the first examples of hybrid plasmonic nanopore structures integrated on a 2D-material membrane. The diameter of the nanopore and the atomically thick substrate make this proof-of-concept approach particularly interesting for nanopore-based technologies and applications such as next-generation sequencing and single-molecule detection

Heated nuclear matter, condensation phenomena and the hadronic equation of state

The thermodynamic properties of heated nuclear matter are explored using an exactly solvable canonical ensemble model. This model reduces to the results of an ideal Fermi gas at low temperatures. At higher temperatures, the fragmentation of the nuclear matter into clusters of nucleons leads to features that resemble a Bose gas. Some parallels of this model with the phenomena of Bose condensation and with percolation phenomena are discussed. A simple expression for the hadronic equation of state is obtained from the model.Comment: 12 pages, revtex, 1 ps file appended (figure 1

Historical Neighborhood Redlining

The source data used to construct this contextual file for the National Longitudinal Study of Adolescent to Adult Health (Add Health) come from Mapping Inequality: Redlining in New Deal America, compiled by Robert K. Nelson and the Digital Scholarship Lab at the University of Richmond. This file augments the current Add Health contextual data collection by providing information about whether a respondent’s place of residence falls inside or within varying proximities to historically redlined neighborhood boundaries at the time of their Wave I, III, IV, and V survey interviews. This contextual database allows researchers to identify potential long-term consequences of redlining for contemporary inequities in neighborhood environments, and individual health and socioeconomic attainment over the life course. Before analyzing these data, however, we urge users to review the following background section and cited references

Fragment size correlations in finite systems - application to nuclear multifragmentation

We present a new method for the calculation of fragment size correlations in a discrete finite system in which correlations explicitly due to the finite extent of the system are suppressed. To this end, we introduce a combinatorial model, which describes the fragmentation of a finite system as a sequence of independent random emissions of fragments. The sequence is accepted when the sum of the sizes is equal to the total size. The parameters of the model, which may be used to calculate all partition probabilities, are the intrinsic probabilities associated with the fragments. Any fragment size correlation function can be built by calculating the ratio between the partition probabilities in the data sample (resulting from an experiment or from a Monte Carlo simulation) and the 'independent emission' model partition probabilities. This technique is applied to charge correlations introduced by Moretto and collaborators. It is shown that the percolation and the nuclear statistical multifragmentaion model ({\sc smm}) are almost independent emission models whereas the nuclear spinodal decomposition model ({\sc bob}) shows strong correlations corresponding to the break-up of the hot dilute nucleus into nearly equal size fragments

Persistence, extinction and spatio-temporal synchronization of SIRS cellular automata models

Spatially explicit models have been widely used in today's mathematical ecology and epidemiology to study persistence and extinction of populations as well as their spatial patterns. Here we extend the earlier work--static dispersal between neighbouring individuals to mobility of individuals as well as multi-patches environment. As is commonly found, the basic reproductive ratio is maximized for the evolutionary stable strategy (ESS) on diseases' persistence in mean-field theory. This has important implications, as it implies that for a wide range of parameters that infection rate will tend maximum. This is opposite with present results obtained in spatial explicit models that infection rate is limited by upper bound. We observe the emergence of trade-offs of extinction and persistence on the parameters of the infection period and infection rate and show the extinction time having a linear relationship with respect to system size. We further find that the higher mobility can pronouncedly promote the persistence of spread of epidemics, i.e., the phase transition occurs from extinction domain to persistence domain, and the spirals' wavelength increases as the mobility increasing and ultimately, it will saturate at a certain value. Furthermore, for multi-patches case, we find that the lower coupling strength leads to anti-phase oscillation of infected fraction, while higher coupling strength corresponds to in-phase oscillation.Comment: 12page

Classification of the Nuclear Multifragmentation Phase Transition

Using a recently proposed classification scheme for phase transitions in finite systems [Phys.Rev.Lett.{\bf 84},3511 (2000)] we show that within the statistical standard model of nuclear multifragmentation the predicted phase transition is of first order.Comment: 5 pages, 4 eps figures, accepted for publication in Phys.Rev.C (in press

Reanalysis and Simulation Suggest a Phylogenetic Microarray Does Not Accurately Profile Microbial Communities

The second generation (G2) PhyloChip is designed to detect over 8700 bacteria and archaeal and has been used over 50 publications and conference presentations. Many of those publications reveal that the PhyloChip measures of species richness greatly exceed statistical estimates of richness based on other methods. An examination of probes downloaded from Greengenes suggested that the system may have the potential to distort the observed community structure. This may be due to the sharing of probes by taxa; more than 21% of the taxa in that downloaded data have no unique probes. In-silico simulations using these data showed that a population of 64 taxa representing a typical anaerobic subterranean community returned 96 different taxa, including 15 families incorrectly called present and 19 families incorrectly called absent. A study of nasal and oropharyngeal microbial communities by Lemon et al (2010) found some 1325 taxa using the G2 PhyloChip, however, about 950 of these taxa have, in the downloaded data, no unique probes and cannot be definitively called present. Finally, data from Brodie et al (2007), when re-examined, indicate that the abundance of the majority of detected taxa, are highly correlated with one another, suggesting that many probe sets do not act independently. Based on our analyses of downloaded data, we conclude that outputs from the G2 PhyloChip should be treated with some caution, and that the presence of taxa represented solely by non-unique probes be independently verified