Shared intentions and the advance of cumulative culture in hunter-gatherers

It has been hypothesized that the evolution of modern human cognition was catalyzed by the development of jointly intentional modes of behaviour. From an early age (1-2 years), human infants outperform apes at tasks that involve collaborative activity. Specifically, human infants excel at joint action motivated by reasoning of the form "we will do X" (shared intentions), as opposed to reasoning of the form "I will do X [because he is doing X]" (individual intentions). The mechanism behind the evolution of shared intentionality is unknown. Here we formally model the evolution of jointly intentional action and show under what conditions it is likely to have emerged in humans. Modelling the interaction of hunter-gatherers as a coordination game, we find that when the benefits from adopting new technologies or norms are low but positive, the sharing of intentions does not evolve, despite being a mutualistic behaviour that directly benefits all participants. When the benefits from adopting new technologies or norms are high, such as may be the case during a period of rapid environmental change, shared intentionality evolves and rapidly becomes dominant in the population. Our results shed new light on the evolution of collaborative behaviours.Comment: 6 pages, 4 figures, 1 table, Supplementary Information not include

2004 Presidential Election: Who Won The Popular Vote? An Examination of the Comparative Validity of Exit Poll and Vote Count Data

* There is a substantial discrepancy -- well outside the margin of error and outcomedeterminative -- between the national exit poll and the popular vote count.* The possible causes of the discrepancy would be random error, a skewed exit poll, or breakdown in the fairness of the voting process and accuracy of the vote count.* Analysis shows that the discrepancy cannot reasonably be accounted for by chance or random error.* Evidence does not support hypotheses that the discrepancy was produced by problems with the exit poll.* Widespread breakdown in the fairness of the voting process and accuracy of the vote count are the most likely explanations for the discrepancy.* In an accurate count of a free and fair election, the strong likelihood is that Kerry would have been the winner of the popular vote.This document was originally published by Verified Vote 2004, and is authored by Jonathan Simon, currently with Election Defense Alliance

The Prospects for Sustained Growth in Africa: Benchmarking the Constraints

A dozen countries had weak institutions in 1960 and yet sustained high rates of growth subsequently. We use data on their characteristics early in the growth process to create benchmarks with which to evaluate potential constraints on sustained growth for sub-Saharan Africa. This analysis suggests that what are usually regarded as first-order problems -- broad institutions, macroeconomic stability, trade openness, education, and inequality -- may not nowbe binding constraints in Africa, although the extent of ill-health, internal conflict, and societal fractionalization do stand out as problems in contemporary Africa. A key question is to what extent Africa can rely on manufactured exports as a mode of "escape from underdevelopment," a strategy successfully deployed by almost all the benchmark countries. The benchmarking comparison specifically raises two key concerns as far as a development strategy based on expanding exports of manufactures is concerned: micro-level institutions that affect the costs of exporting, and the level of the real exchange rate -- especially the need to avoid overvaluation.

Reflection Positivity and Monotonicity

We prove general reflection positivity results for both scalar fields and Dirac fields on a Riemannian manifold, and comment on applications to quantum field theory. As another application, we prove the inequality $C_D \leq C_N$ between Dirichlet and Neumann covariance operators on a manifold with a reflection.Comment: 11 page

Modeling and Analysing Respondent Driven Sampling as a Counting Process

Respondent-driven sampling (RDS) is an approach to sampling design and analysis which utilizes the networks of social relationships that connect members of the target population, using chain-referral methods to facilitate sampling. RDS typically leads to biased sampling, favoring participants with many acquaintances. Naive estimates, such as the sample average, which are uncorrected for the sampling bias, will themselves be biased. To compensate for this bias, current methodology suggests inverse-degree weighting, where the "degree" is the number of acquaintances. This stems from the fundamental RDS assumption that the probability of sampling an individual is proportional to their degree. Since this assumption is tenuous at best, we propose to harness the additional information encapsulated in the time of recruitment, into a model-based inference framework for RDS. This information is typically collected by researchers, but ignored. We adapt methods developed for inference in epidemic processes to estimate the population size, degree counts and frequencies. While providing valuable information in themselves, these quantities ultimately serve to debias other estimators, such a disease's prevalence. A fundamental advantage of our approach is that, being model-based, it makes all assumptions of the data-generating process explicit. This enables verification of the assumptions, maximum likelihood estimation, extension with covariates, and model selection. We develop asymptotic theory, proving consistency and asymptotic normality properties. We further compare these estimators to the standard inverse-degree weighting through simulations, and using real-world data. In both cases we find our estimators to outperform current methods. The likelihood problem in the model we present is convex, and thus efficiently solvable. We implement these estimators in an R package, chords, available on CRAN.Comment: 16 page

Fast oxidation of sulfur dioxide by hydrogen peroxide in deliquesced aerosol particles

Atmospheric sulfate aerosols have important impacts on air quality, climate, and human and ecosystem health. However, current air-quality models generally underestimate the rate of conversion of sulfur dioxide (SO2) to sulfate during severe haze pollution events, indicating that our understanding of sulfate formation chemistry is incomplete. This may arise because the air-quality models rely upon kinetics studies of SO2 oxidation conducted in dilute aqueous solutions, and not at the high solute strengths of atmospheric aerosol particles. Here, we utilize an aerosol flow reactor to perform direct investigation on the kinetics of aqueous oxidation of dissolved SO2 by hydrogen peroxide (H2O2) using pH-buffered, submicrometer, deliquesced aerosol particles at relative humidity of 73 to 90%. We find that the high solute strength of the aerosol particles significantly enhances the sulfate formation rate for the H2O2 oxidation pathway compared to the dilute solution. By taking these effects into account, our results indicate that the oxidation of SO2 by H2O2 in the liquid water present in atmospheric aerosol particles can contribute to the missing sulfate source during severe haze episodes

The relationship between oxidised LDL, endothelial progenitor cells and coronary endothelial function in patients with CHD

Objective The balance between coronary endothelial dysfunction and repair is influenced by many protective and deleterious factors circulating in the blood. We studied the relationship between oxidised low-density lipoprotein (oxLDL), circulating endothelial progenitor cells (EPCs) and coronary endothelial function in patients with stable coronary heart disease (CHD). Methods 33 patients with stable CHD were studied. Plasma oxLDL was measured using ELISA, coronary endothelial function was assessed using intracoronary acetylcholine infusion and EPCs were quantified using flow cytometry for CD34+/KDR+ cells. Results Plasma oxLDL correlated positively with the number of EPCs in the blood (r=0.46, p=0.02). There was a positive correlation between the number of circulating EPCs and coronary endothelial function (r=0.42, p=0.04). There was no significant correlation between oxLDL and coronary endothelial function. Conclusions Plasma levels of oxLDL are associated with increased circulating EPCs in the blood of patients with CHD, which may reflect a host-repair response to endothelial injury. Patients with stable CHD had a high prevalence of coronary endothelial dysfunction, which was associated with lower numbers of circulating EPCs, suggesting a mechanistic link between endothelial dysfunction and the pathogenesis of atherosclerosis

Overcoming the critical slowing down of flat-histogram Monte Carlo simulations: Cluster updates and optimized broad-histogram ensembles

We study the performance of Monte Carlo simulations that sample a broad histogram in energy by determining the mean first-passage time to span the entire energy space of d-dimensional ferromagnetic Ising/Potts models. We first show that flat-histogram Monte Carlo methods with single-spin flip updates such as the Wang-Landau algorithm or the multicanonical method perform sub-optimally in comparison to an unbiased Markovian random walk in energy space. For the d=1,2,3 Ising model, the mean first-passage time \tau scales with the number of spins N=L^d as \tau \propto N^2L^z. The critical exponent z is found to decrease as the dimensionality d is increased. In the mean-field limit of infinite dimensions we find that z vanishes up to logarithmic corrections. We then demonstrate how the slowdown characterized by z>0 for finite d can be overcome by two complementary approaches - cluster dynamics in connection with Wang-Landau sampling and the recently developed ensemble optimization technique. Both approaches are found to improve the random walk in energy space so that \tau \propto N^2 up to logarithmic corrections for the d=1 and d=2 Ising model