Construction of weakly CUD sequences for MCMC sampling

In Markov chain Monte Carlo (MCMC) sampling considerable thought goes into constructing random transitions. But those transitions are almost always driven by a simulated IID sequence. Recently it has been shown that replacing an IID sequence by a weakly completely uniformly distributed (WCUD) sequence leads to consistent estimation in finite state spaces. Unfortunately, few WCUD sequences are known. This paper gives general methods for proving that a sequence is WCUD, shows that some specific sequences are WCUD, and shows that certain operations on WCUD sequences yield new WCUD sequences. A numerical example on a 42 dimensional continuous Gibbs sampler found that some WCUD inputs sequences produced variance reductions ranging from tens to hundreds for posterior means of the parameters, compared to IID inputs.Comment: Published in at http://dx.doi.org/10.1214/07-EJS162 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

Systemic inflammation: Cancer's long-distance reach to maximize metastasis

While major improvements have been made in targeting primary tumor growth, metastasis and combating cancer spread remain an enigma. We recently identified a systemic inflammatory cascade involving IL17-producing γδ T cells and neutrophils that advance breast cancer metastasis. These data provide insights into how immune cells promote cancer spread

Exploring strong-field deviations from general relativity via gravitational waves

Two new observational windows have been opened to strong gravitational physics: gravitational waves, and very long baseline interferometry. This suggests observational searches for new phenomena in this regime, and in particular for those necessary to make black hole evolution consistent with quantum mechanics. We describe possible features of "compact quantum objects" that replace classical black holes in a consistent quantum theory, and approaches to observational tests for these using gravitational waves. This is an example of a more general problem of finding consistent descriptions of deviations from general relativity, which can be tested via gravitational wave detection. Simple models for compact modifications to classical black holes are described via an effective stress tensor, possibly with an effective equation of state. A general discussion is given of possible observational signatures, and of their dependence on properties of the colliding objects. The possibility that departures from classical behavior are restricted to the near-horizon regime raises the question of whether these will be obscured in gravitational wave signals, due to their mutual interaction in a binary coalescence being deep in the mutual gravitational well. Numerical simulation with such simple models will be useful to clarify the sensitivity of gravitational wave observation to such highly compact departures from classical black holes.Comment: 20 pages, 9 figures. v2: references and CERN preprint number adde

Revving up dendritic cells while braking PD-L1 to jump-start the cancer-immunity cycle motor

Although it is successful for some, most melanoma patients are refractory to T cell checkpoint inhibition. In this issue of Immunity, Merad and colleagues (2016) describe a dendritic-cell-based strategy to heighten the efficacy of therapeutic anti-PD-L1 and BRAF inhibitors in mouse melanoma models

Volatility, Money Market Rates, and the Transmission of Monetary Policy

We explore the effect of volatility in the federal funds market on the expectations hypothesis in money markets. We find that lower volatility in the bank funding markets market, all else equal, leads to a lower term premium and thus longer-term rates for a given setting of the overnight rate. The results appear to hold for the US as well as the Euro Area and the UK. The results have implications for the design of operational frameworks for the implementation of monetary policy and for the interpretation of the changes in the Libor-OIS spread during the financial crisisMonetary transmission mechanism, expectations hypothesis, term premium

Measures of metacognition on signal-detection theoretic models

Analysing metacognition, specifically knowledge of accuracy of internal perceptual, memorial or other knowledge states, is vital for many strands of psychology, including determining the accuracy of feelings of knowing, and discriminating conscious from unconscious cognition. Quantifying metacognitive sensitivity is however more challenging than quantifying basic stimulus sensitivity. Under popular signal detection theory (SDT) models for stimulus classification tasks, approaches based on type II receiver-operator characteristic (ROC) curves or type II d-prime risk confounding metacognition with response biases in either the type I (classification) or type II (metacognitive) tasks. A new approach introduces meta-d′: the type I d-prime that would have led to the observed type II data had the subject used all the type I information. Here we (i) further establish the inconsistency of the type II d-prime and ROC approaches with new explicit analyses of the standard SDT model, and (ii) analyse, for the first time, the behaviour of meta-d′ under non-trivial scenarios, such as when metacognitive judgments utilize enhanced or degraded versions of the type I evidence. Analytically, meta-d′ values typically reflect the underlying model well, and are stable under changes in decision criteria; however, in relatively extreme cases meta-d′ can become unstable. We explore bias and variance of in-sample measurements of meta-d′ and supply MATLAB code for estimation in general cases. Our results support meta-d′ as a useful measure of metacognition, and provide rigorous methodology for its application. Our recommendations are useful for any researchers interested in assessing metacognitive accuracy