Simultaneous removal of CO2, SO2, and NOx from flue gas by liquid phase dehumidification at cryogenic temperatures and low pressure

Published versio

Scaling of the distribution of fluctuations of financial market indices

We study the distribution of fluctuations over a time scale $\Delta t$ (i.e., the returns) of the S&P 500 index by analyzing three distinct databases. Database (i) contains approximately 1 million records sampled at 1 min intervals for the 13-year period 1984-1996, database (ii) contains 8686 daily records for the 35-year period 1962-1996, and database (iii) contains 852 monthly records for the 71-year period 1926-1996. We compute the probability distributions of returns over a time scale $\Delta t$, where $\Delta t$ varies approximately over a factor of 10^4 - from 1 min up to more than 1 month. We find that the distributions for $\Delta t \leq$ 4 days (1560 mins) are consistent with a power-law asymptotic behavior, characterized by an exponent $\alpha \approx 3$, well outside the stable L\'evy regime $0 < \alpha < 2$. To test the robustness of the S&P result, we perform a parallel analysis on two other financial market indices. Database (iv) contains 3560 daily records of the NIKKEI index for the 14-year period 1984-97, and database (v) contains 4649 daily records of the Hang-Seng index for the 18-year period 1980-97. We find estimates of $\alpha$ consistent with those describing the distribution of S&P 500 daily-returns. One possible reason for the scaling of these distributions is the long persistence of the autocorrelation function of the volatility. For time scales longer than $(\Delta t)_{\times} \approx 4$ days, our results are consistent with slow convergence to Gaussian behavior.Comment: 12 pages in multicol LaTeX format with 27 postscript figures (Submitted to PRE May 20, 1999). See http://polymer.bu.edu/~amaral/Professional.html for more of our work on this are

When we should worry more: Using cognitive bias modification to drive adaptive health behaviour

A lack of behavioural engagement in health promotion or disease prevention is a problem across many health domains. In these cases where people face a genuine danger, a reduced focus on threat and low levels of anxiety or worry are maladaptive in terms of promoting protection or prevention behaviour. Therefore, it is possible that increasing the processing of threat will increase worry and thereby enhance engagement in adaptive behaviour. Laboratory studies have shown that cognitive bias modification (CBM) can increase or decrease anxiety and worry when increased versus decreased processing of threat is encouraged. In the current study, CBM for interpretation (CBM-I) is used to target engagement in sun protection behaviour. The goal was to investigate whether inducing a negative rather than a positive interpretation bias for physical threat information can enhance worry elicited when viewing a health campaign video (warning against melanoma skin cancer), and consequently lead to more adaptive behaviour (sun protection). Participants were successfully trained to either adopt a positive or negative interpretation bias using physical threat scenarios. However, contrary to expectations results showed that participants in the positive training condition reported higher levels of worry elicited by the melanoma video than participants in the negative training condition. Video elicited worry was, however, positively correlated with a measure of engagement in sun protection behaviour, suggesting that higher levels of worry do promote adaptive behaviour. These findings imply that more research is needed to determine under which conditions increased versus decreased processing of threat can drive adaptive worry. Various potential explanations for the current findings and suggestions for future research are discussed

Islet Formation during the Neonatal Development in Mice

The islet of Langerhans is a unique micro-organ within the exocrine pancreas, which is composed of insulin-secreting beta-cells, glucagon-secreting alpha-cells, somatostatin-secreting delta-cells, pancreatic polypeptide-secreting PP cells and ghrelin-secreting epsilon-cells. Islets also contain non-endocrine cell types such as endothelial cells. However, the mechanism(s) of islet formation is poorly understood due to technical difficulties in capturing this dynamic event in situ. We have developed a method to monitor beta-cell proliferation and islet formation in the intact pancreas using transgenic mice in which the beta-cells are specifically tagged with a fluorescent protein. Endocrine cells proliferate contiguously, forming branched cord-like structures in both embryos and neonates. Our study has revealed long stretches of interconnected islets located along large blood vessels in the neonatal pancreas. Alpha-cells span the elongated islet-like structures, which we hypothesize represent sites of fission and facilitate the eventual formation of discrete islets. We propose that islet formation occurs by a process of fission following contiguous endocrine cell proliferation, rather than by local aggregation or fusion of isolated beta-cells and islets. Mathematical modeling of the fission process in the neonatal islet formation is also presented