How Important Are Wages to the Elderly? Evidence from the New Beneficiary Data System and the Social Security Earnings Test

More than 40 percent of Social Security beneficiaries continue to work after age 65. This research investigates the extent to which these individuals substitute labor across periods in response to anticipated wage changes induced by the Social Security earnings test. While we find that a disproportionate number of individuals choose earnings within a few percentage points of the earnings limit, we find no evidence that these individuals substitute labor supply between

Recent status of the understanding of neutrino-nucleus cross section

In this work we have presented current understanding of neutrino-nucleon/nucleus cross sections in the few GeV energy region relevant for a precise determination of neutrino oscillation parameters and CP violation in the leptonic sector. In this energy region various processes like quasielastic and inelastic production of single and multipion production, coherent pion production, kaon, eta, hyperon production, associated particle production as well as deep inelastic scattering processes contribute to the neutrino event rates.Comment: 9-Pages, 4-figures, Talk given at DAE-HEP Symposium held at Delhi University, 12-16 December, 201

Vergleichende Untersuchungen zu GPCR-induzierten dynamischen Konformationsänderung in β-arrestin1 und 2

G protein-coupled receptors (GPCRs) constitute the largest family of membrane receptors in human physiology, comprising more than 800 different genes. They sense diverse extracellular signals and initiate intracellular signaling responses via the activation of specific G proteins. The downregulation of GPCR signaling is mediated by four ubiquitously expressed GPCR kinases (GRK2, 3, 5, and 6) and two β-arrestin isoforms (β-arrestin1 and 2). GRKs phosphorylate intracellular domains of active receptors to facilitate high-affinity β-arrestin-binding. Depending on the specific GPCR–β-arrestin interaction, β-arrestins undergo different conformational changes to mediate receptor desensitization, internalization, and mitogen-activated protein kinase (MAPK) signal-amplification. However, the impact of individual GRK isoforms on these processes has not been comprehensively assessed until now. Moreover, whether β-arrestin1 and 2 undergo different conformational changes upon binding to the same GPCR is still unknown. The first part of this thesis focusses on the elaboration of GRK isoform-specific aspects of GPCR signaling. For this, a panel of elven in-house created combinatorial HEK293 knockout cell clones, lacking GRK2/3/5/6 (including four single, two double, four triple, and a quadruple GRK knockout cell line), was extensively used. To investigate GRK isoform-specific β-arrestin recruitment, a NanoLuc–HaloTag-based BRET system was established and combined with the unique possibility to vary individual GRK expression levels using different ΔGRK knockout cell lines. Hence, the GRK-specificity of β-arrestin-binding was assessed with two different strategies: first, utilizing the triple GRK knockout cell lines, featuring the endogenous expression of only one GRK isoform (ΔGRK3/5/6, ΔGRK2/5/6, ΔGRK2/3/6, ΔGRK2/3/5), and additionally by re-introduction of a single GRK isoform in the quadruple GRK knockout cell line (ΔQ-GRK)

Identifying Twitter Spam by Utilizing Random Forests

The use of Twitter has rapidly grown since the first tweet in 2006. The number of spammers on Twitter shows a similar increase. Classifying users into spammers and non-spammers has been heavily researched, and new methods for spam detection are developing rapidly. One of these classification techniques is known as random forests. We examine three studies that employ random forests using user based features, geo-tagged features, and time dependent features. Each study showed high accuracy rates and F-measures with the exception of one model that had a test set with a more realistic proportion of spam relative to typical testing procedures. These studies suggest that random forests, in combination with unique feature selection can be used to identify spam and spammers with high accuracy but may have short- comings when applied to real world situations

Complexity reduction of influence nets using arc removal

© 2015 - IOS Press and the authors. The model building of Influence Nets, a special instance of Bayesian belief networks, is a time-consuming and labor-intensive task. No formal process exists that decision makers/system analyst, who are typically not familiar with the underlying theory and assumptions of belief networks, can use to build concise and easy-to-interpret models. In many cases, the developed model is extremely dense, that is, it has a very high link-to-node ratio. The complexity of a network makes the already intractable task of belief updating more difficult. The problem is further intensified in dynamic domains where the structure of the built model is repeated for multiple time-slices. It is, therefore, desirable to do a post-processing of the developed models and to remove arcs having a negligible influence on the variable(s) of interests. The paper applies sensitivity of arc analysis to identify arcs that can be removed from an Influence Net without having a significant impact on its inferencing capability. A metric is suggested to gauge changes in the joint distribution of variables before and after the arc removal process. The results are benchmarked against the KL divergence metric. An empirical study based on several real Influence Nets is conducted to test the performance of the sensitivity of arc analysis in reducing the model complexity of an Influence Net without causing a significant change in its joint probability distribution