TINKERING WITH VALUATION ESTIMATES: IS THERE A FUTURE FOR WILLINGNESS TO ACCEPT MEASURES?

This paper examines various methods proposed in the literature to calibrate welfare measures, especially willingness to accept and willingness to pay, derived from contingent valuation surveys. Through simulation and a case study, we hope to provide guidance for empirical welfare measurement in response to the theoretical dispute regarding WTA/WTP disparities.Resource /Energy Economics and Policy,

Sigma and omega meson propagation in a dense nuclear medium

The propagation of the scalar ($\sigma$) and vector ($\omega$) mesons in nuclear matter is studied in detail using the Walecka model over a wide range of densities and including the effects of a finite $\sigma$ width through the inclusion of a two-pion loop. We calculate the dispersion relation and spectral functions of the $\sigma$ and (transverse and longitudinal) $\omega$ mesons, including the effect of $\sigma$-$\omega$ mixing in matter. It is shown that the mixing effect is quite important in the propagation of the (longitudinal) $\omega$ and $\sigma$ mesons above normal nuclear matter density. We find that there is a two-peak structure in the spectral function of the $\sigma$ channel, caused by $\sigma$-$\omega$ mixing.Comment: 17 pages including 6 ps files, submitted to Phys. Lett. B. Acknowledgement is revise

Phase Distribution and Phase Correlation of Financial Time Series

Scaling, phase distribution and phase correlation of financial time series are investigated based on the Dow Jones Industry Average (DJIA) and NASDAQ 10-minute intraday data for a period from Aug. 1 1997 to Dec. 31 2003. The returns of the two indices are shown to have nice scaling behaviors and belong to stable distributions according to the criterion of Levy's alpha stable distribution condition. A novel approach catching characteristic features of financial time series based on the concept of instantaneous phase is further proposed to study phase distribution and correlation. The analysis of phase distribution concludes return time series fall into a class which is different from other non-stationary time series. The correlation between returns of the two indices probed by the distribution of phase difference indicates there was a remarkable change of trading activities after the event of 911 attack, and this change persisted in later trading activities.Phase Distribution, High Frequency Data, Scaling Analysis, Levy Distribution, Stock Market, Frequency Variant

Use of graphics in decision aids for telerobotic control: (Parts 5-8 of an 8-part MIT progress report)

Four separate projects recently completed or in progress at the MIT Man-Machine Systems Laboratory are summarized. They are: a decision aid for retrieving a tumbling satellite in space; kinematic control and graphic display of redundant teleoperators; real time terrain/object generation: a quad-tree approach; and two dimensional control for three dimensional obstacle avoidance

Stoichiometry and Change of the mRNA Closed-Loop Factors as Translating Ribosomes Transit from Initiation to Elongation

Protein synthesis is a highly efficient process and is under exacting control. Yet, the actual abundance of translation factors present in translating complexes and how these abundances change during the transit of a ribosome across an mRNA remains unknown. Using analytical ultracentrifugation with fluorescent detection we have determined the stoichiometry of the closed-loop translation factors for translating ribosomes. A variety of pools of translating polysomes and monosomes were identified, each containing different abundances of the closed-loop factors eIF4E, eIF4G, and PAB1 and that of the translational repressor, SBP1. We establish that closed-loop factors eIF4E/eIF4G dissociated both as ribosomes transited polyadenylated mRNA from initiation to elongation and as translation changed from the polysomal to monosomal state prior to cessation of translation. eIF4G was found to particularly dissociate from polyadenylated mRNA as polysomes moved to the monosomal state, suggesting an active role for translational repressors in this process. Consistent with this suggestion, translating complexes generally did not simultaneously contain eIF4E/eIF4G and SBP1, implying mutual exclusivity in such complexes. For substantially deadenylated mRNA, however, a second type of closed-loop structure was identified that contained just eIF4E and eIF4G. More than one eIF4G molecule per polysome appeared to be present in these complexes, supporting the importance of eIF4G interactions with the mRNA independent of PAB1. These latter closed-loop structures, which were particularly stable in polysomes, may be playing specific roles in both normal and disease states for specific mRNA that are deadenylated and/or lacking PAB1. These analyses establish a dynamic snapshot of molecular abundance changes during ribosomal transit across an mRNA in what are likely to be critical targets of regulation

Gated communities

Includes bibliographical references (p. 172-177).Thesis (B.Sc)--University of Hong Kong, 2009.published_or_final_versio

Fock terms in the quark-meson coupling model

The mean field description of nuclear matter in the quark-meson coupling model is improved by the inclusion of exchange contributions (Fock terms). The inclusion of Fock terms allows us to explore the momentum dependence of meson-nucleon vertices and the role of pionic degrees of freedom in matter. It is found that the Fock terms maintain the previous predictions of the model for the in-medium properties of the nucleon and for the nuclear incompressibility. The Fock terms significantly increase the absolute values of the single-particle, four-component scalar and vector potentials, a feature that is relevant for the spin-orbit splitting in finite nuclei.Comment: RevTex, 17 pages, 4 Postscript figures, version to appear in Nucl. Phys.

Renin-Angiotensin-Aldosterone System Antagonism and Polycystic Kidney Disease Progression.

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a systemic disease characterised by the formation of multiple renal cysts that adversely affect renal function. ADPKD shows significant progression with age when complications due to hypertension are most significant. The activation of the renin-angiotensin-aldosterone system (RAAS) occurs in progressive kidney disease leading to hypertension. The RAAS system may also contribute to ADPKD progression by stimulating signalling pathways in the renal cyst cells to promote growth and deregulate epithelial transport. This mini review focuses on the contribution of the RAAS system to renal cyst enlargement and the potential for antagonists of the RAAS system to suppress cyst enlargement as well as control ADPKD-associated hypertension

Generation of Differentially Private Heterogeneous Electronic Health Records

Electronic Health Records (EHRs) are commonly used by the machine learning community for research on problems specifically related to health care and medicine. EHRs have the advantages that they can be easily distributed and contain many features useful for e.g. classification problems. What makes EHR data sets different from typical machine learning data sets is that they are often very sparse, due to their high dimensionality, and often contain heterogeneous (mixed) data types. Furthermore, the data sets deal with sensitive information, which limits the distribution of any models learned using them, due to privacy concerns. For these reasons, using EHR data in practice presents a real challenge. In this work, we explore using Generative Adversarial Networks to generate synthetic, heterogeneous EHRs with the goal of using these synthetic records in place of existing data sets for downstream classification tasks. We will further explore applying differential privacy (DP) preserving optimization in order to produce DP synthetic EHR data sets, which provide rigorous privacy guarantees, and are therefore shareable and usable in the real world. The performance (measured by AUROC, AUPRC and accuracy) of our model's synthetic, heterogeneous data is very close to the original data set (within 3 - 5% of the baseline) for the non-DP model when tested in a binary classification task. Using strong $(1, 10^{-5})$ DP, our model still produces data useful for machine learning tasks, albeit incurring a roughly 17% performance penalty in our tested classification task. We additionally perform a sub-population analysis and find that our model does not introduce any bias into the synthetic EHR data compared to the baseline in either male/female populations, or the 0-18, 19-50 and 51+ age groups in terms of classification performance for either the non-DP or DP variant