Social Support Shopping: Evidence from a Regression Discontinuity in Disability Insurance Reform

This paper examines how a change in the generosity of one social assistance program generates spillovers onto other social assistance programs. We exploit an age discontinuity in the stringency of the 1993 Dutch disability reforms to estimate the causal effect of exit from disability insurance (DI) on participation in other social assistance programs. We find strong evidence of "social support shopping": 43 percent of those induced to leave DI due to the reform receive an alternative form of social assistance two years after the implementation of the reform. As a result, for each Euro saved in DI benefits, the government has to spend an extra 60 cents in other social assistance programs. This crowd-out rate grows from 60% to 69% if we also take into account the response of the partners’ of those affected by the DI reform. The crowd-out effect declines over time, but is still 25% eight years after the reform.crowd-out, spillover effects, social insurance, income assistance, welfare, regression discontinuity, administrative data

Edge-disjoint homotopic paths in a planar graph with one hole

AbstractWe prove the following theorem, conjectured by K. Mehlhorn: Let G = (V, E) be a planar graph, embedded in the plane C. Let O denote the interior of the unbounded face, and let I be the interior of some fixed bounded face. Let C1, …, Ck be curves in Cß(I⌣O), with end points in V⌢bd(I⌣O), so that for each vertex v of G the degree of v in G has the same parity as the number of curves Ci beginning or ending in v (counting a curve beginning and ending in v for two). Then there exist pairwise edge-disjoint paths P1, …, Pk in G so that Pi is homotopic to Ci in the space Cß(I⌣O) for i = 1, …, k, if and only if for each dual walk Q from {I, O} to {I, O} the number of edges in Q is not smaller than the number of times Q necessarily intersects the curves Ci. The theorem generalizes a theorem of Okamura and Seymour. We demonstrate how a polynomial-time algorithm finding the paths can be derived

Manned maneuvering unit applications for automated rendezvous and capture

Automated Rendezvous and Capture (AR&C) is an important technology to multiple National Aeronautics and Space Administration (NASA) programs and centers. The recent Johnson Spacecraft Center (JSC) AR&C Quality Function Deployment (QFD) has listed on-orbit demonstration of related technologies as a near term priority. Martin Marietta has been evaluating use of the Manned Maneuvering Unit (MMU) for a low cost near term on-orbit demonstration of AR&C technologies such as control algorithms, sensors, and processors as well as system level performance. The MMU Program began in 1979 as the method of repairing the Space Shuttle (STS) Thermal Protection System (the tiles). The units were not needed for this task, but were successfully employed during three Shuttle flights in 1984: a test flight was flown in in February as proof of concept, in April the MMU participated in the Solar Max Repair Mission, and in November the MMU's returned to space to successfully rescue the two errant satellites, Westar and Palapa. In the intervening years, the MMU simulator and MMU Qualification Test Unit (QTU) have been used for Astronaut training and experimental evaluations. The Extra-Vehicular Activities (EVA) Retriever has used the QTU, in an unmanned form, as a free-flyer on the Johnson Space Center (JSC) Precision Air Bearing Floor (PABF). Currently, the MMU is undergoing recertification for flight. The two flight units were removed from storage in September, 1991 and evaluation tests were performed. The tests demonstrated that the units are in good shape with no discrepancies that would preclude further use. The Return to Flight effort is currently clearing up recertification issues and evaluating the design against the present Shuttle environments

Recurrent critical points and typical limit sets for conformal measures☆☆Portions of the paper were presented at the AMS Special Session on Low-Dimensional Dynamics in Milwaukee, Wisconsin, October 1997.

AbstractFor a rational f:Ĉ→Ĉ with a conformal measure μ we show that if there is a subset of the Julia set J(f) of positive μ-measure whose points are not eventual preimages of critical or parabolic points and have limit sets not contained in the union of the limit sets of recurrent critical points, then μ is non-atomic, μ(J(f))=1, ω(x)=J(f) for μ-a.e. point x∈J(f) and f is conservative, ergodic and exact. The proof uses a version of the Lebesgue Density Theorem valid for Borel measures and conformal balls

Characterizing Cancer Subtypes Using Dual Analysis in Caleydo StratomeX

Dual analysis uses statistics to describe both the dimensions and rows of a high-dimensional dataset. Researchers have integrated it into StratomeX, a Caleydo view for cancer subtype analysis. In addition, significant-difference plots show the elements of a candidate subtype that differ significantly from other subtypes, thus letting analysts characterize subtypes. Analysts can also investigate how data samples relate to their assigned subtype and other groups. This approach lets them create well-defined subtypes based on statistical properties. Three case studies demonstrate the approach's utility, showing how it reproduced findings from a published subtype characterization

Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’21)

Recommender systems were originally developed as interactive intelligent systems that can proactively guide users to items that match their preferences. Despite its origin on the crossroads of HCI and AI, the majority of research on recommender systems gradually focused on objective accuracy criteria paying less and less attention to how users interact with the system as well as the efficacy of interface designs from users’ perspectives. This trend is reversing with the increased volume of research that looks beyond algorithms, into users’ interactions, decision making processes, and overall experience. The series of workshops on Interfaces and Human Decision Making for Recommender Systems focuses on the "human side" of recommender systems. The goal of the research stream featured at the workshop is to improve users’ overall experience with recommender systems by integrating different theories of human decision making into the construction of recommender systems and exploring better interfaces for recommender systems. In this summary,we introduce the JointWorkshop on Interfaces and Human Decision Making for Recommender Systems at RecSys’21, review its history, and discuss most important topics considered at the workshop