Dark matter in the Kim-Nilles mechanism

The Kim-Nilles mechanism relates the $\mu$ term with the axion scale $f_a$, leading to the axino-Higgsino-Higgs Yukawa coupling of order $\mu/f_a$. This can bring a dangerous thermal production of axinos. If the axino is stable, its mass has to be as small as ${\cal O}$(0.1keV), or the reheat temperature should be lower than ${\cal O}$(10GeV) taking the lower axion scale $10^{10}$ GeV in order not to overclose the Universe. If the axino decays to a neutralino, the overproduced neutralinos can re-annihilate appropriately to saturate the observed dark matter density if the annihilation rate is of order $10^{-8}{GeV}^{-2}$ for the axion scale larger than about $10^{11}$ GeV. Thus, a light Higgsino-like lightest supersymmetric particle with a sizable bino mixture becomes a good dark matter candidate whose nucleonic cross-section is of order $10^{-45}$cm$^2$.Comment: 10 pages, 1 figure; Corrected errors in Eq.(7) and in the direct detection cross-section of the Higgsino-like dark matter; Revised Fig.1; Added a discussion on the saxion; Added references; to appear in PR

Improving Credit Card Operations with Data Mining Techniques

Consumer credit is ubiquitous and lending poses credit risk – the risk of economic loss due to the failure of a borrower to repay according to the terms of his or her contract with the lender. And so, managing credit risk entails estimating the potential ability of borrowers to repay their debts. Researchers have sought to identify factors that contribute to consumer risk, by using quantitative models. However, the presence of data mining techniques to identify credit risk cannot be ignored. There is a paucity of research to demonstrate the use of data mining techniques in this context, and such studies could be instructive to practitioners and academicians. This study fills that void. Using a data mining tool, this study shows that consumers can be segmented by their characteristics such as education, income, years on the job, and payment habits. The study showed that the rich were highly educated and always paid in full. Delinquency experiences were more frequent in the lower income segments. Knowledge about the risk of delinquency can be useful for lenders to price for credit risk and therefore to expand the reach of credit to consumers without having to compromise on profitability

ADsafety: Type-Based Verification of JavaScript Sandboxing

Web sites routinely incorporate JavaScript programs from several sources into a single page. These sources must be protected from one another, which requires robust sandboxing. The many entry-points of sandboxes and the subtleties of JavaScript demand robust verification of the actual sandbox source. We use a novel type system for JavaScript to encode and verify sandboxing properties. The resulting verifier is lightweight and efficient, and operates on actual source. We demonstrate the effectiveness of our technique by applying it to ADsafe, which revealed several bugs and other weaknesses.Comment: in Proceedings of the USENIX Security Symposium (2011

A Search for Radio Emission at the Bottom of the Main Sequence and Beyond

We have used the VLA to conduct a deep search for 3.6 cm radio emission from nearby very low mass stars and brown dwarfs. The Gudel-Benz relation is used to predict radio luminosities for some very low mass stars and candidate brown dwarfs with measured X-ray fluxes. The predicted radio fluxes are quite small, whereas the measured radio flux from the brown dwarf candidate Rho Oph GY 31 is relatively strong. In light of our new observations, this object remains an anomaly. We present upper limits for our measured radio fluxes at 3.6 cm for our targets.Comment: 10 pages, no figures. Accepted for publication in A